TBD Meeting (2976-20)

Precision medicine is driven by technologies such as rapid genome sequencing and artificial intelligence (AI), according to a presentation at the AACR virtual meeting II.

AI can be applied to the sequencing information derived from advanced cancers to make highly personalized treatment recommendations for patients, said Olivier Elemento, PhD, of Weill Cornell Medicine, New York.

Dr. Elemento described such work during the opening plenary session of the meeting.

Dr. Elemento advocated for whole-genome sequencing (WGS) of metastatic sites, as it can reveal “branched evolution” as tumors progress from localized to metastatic (Nat Genet. 2016 Dec;48[12]:1490-9).

The metastases share common mutations with the primaries from which they arise but also develop their own mutational profiles, which facilitate site-of-origin-agnostic, predictive treatment choices.

As examples, Dr. Elemento mentioned HER2 amplification found in a patient with urothelial cancer (J Natl Compr Canc Netw. 2019 Mar 1;17[3]:194-200) and a patient with uterine serous carcinoma (Gynecol Oncol Rep. 2019 Feb 21;28:54-7), both of whom experienced long-lasting remissions to HER2-targeted therapy.

Dr. Elemento also noted that WGS can reveal complex structural variants in lung adenocarcinomas that lack alterations in the RTK/RAS/RAF pathway (unpublished data).
 

Application of machine learning

One study suggested that microRNA expression and machine learning can be used to identify malignant thyroid lesions (Clin Cancer Res. 2012 Apr 1;18[7]:2032-8). The approach diagnosed malignant lesions with 90% accuracy, 100% sensitivity, and 86% specificity.

Dr. Elemento and colleagues used a similar approach to predict response to immunotherapy in melanoma (unpublished data).

The idea was to mine the cancer genome and transcriptome, allowing for identification of signals from neoantigens, immune gene expression, immune cell composition, and T-cell receptor repertoires, Dr. Elemento said. Integrating these signals with clinical outcome data via machine learning technology enabled the researchers to predict immunotherapy response in malignant melanoma with nearly 90% accuracy.

AI and image analysis

Studies have indicated that AI can be applied to medical images to improve diagnosis and treatment. The approach has been shown to:

• Facilitate correct diagnoses of malignant skin lesions (Nature. 2017 Feb 2;542[7639]:115-8).
• Distinguish lung adenocarcinoma from squamous cell cancer with 100% accuracy (EBioMedicine. 2018 Jan;27:317-28).
• Recognize distinct breast cancer subtypes (ductal, lobular, mucinous, papillary) and biomarkers (bioRxiv 242818. doi: 10.1101/242818; EBioMedicine. 2018 Jan;27:317-28)
• Predict mesothelioma prognosis (Nat Med. 2019 Oct;25[10]:1519-25).
• Predict prostate biopsy results (unpublished data) and calculate Gleason scores that can predict survival in prostate cancer patients (AACR 2020, Abstract 867).

Drug development through applied AI

In another study, Dr. Elemento and colleagues used a Bayesian machine learning approach to predict targets of molecules without a known mechanism of action (Nat Commun. 2019 Nov 19;10[1]:5221).

The method involved using data on gene expression profiles, cell line viability, side effects in animals, and structures of the molecules. The researchers applied this method to a large library of orphan small molecules and found it could predict targets in about 40% of cases.

Of 24 AI-predicted microtubule-targeting molecules, 14 depolymerized microtubules in the lab. Five of these molecules were effective in cell lines that were resistant to other microtubule-targeted drugs.

Dr. Elemento went on to describe how Oncoceutics was developing an antineoplastic agent called ONC201, but the company lacked information about the agent’s target. Using AI, the target was identified as dopamine receptor 2 (DRD2; Clin Cancer Res. 2019 Apr 1;25[7]:2305-13).

With that information, Oncoceutics initiated trials of ONC201 in tumors expressing high levels of DRD2, including a highly resistant glioma (J Neurooncol. 2019 Oct;145[1]:97-105). Responses were seen, and ONC201 is now being tested against other DRD2-expressing cancers.
 

Challenges to acknowledge

Potential benefits of AI in the clinic are exciting, but there are many bench-to-bedside challenges.

A clinically obvious example of AI’s applications is radiographic image analysis. There is no biologic rationale for our RECIST “cut values” for partial response, minimal response, and stable disease.

If AI can measure subtle changes on imaging that correlate with tumor biology (i.e., radiomics), we stand a better chance of predicting treatment outcomes than we can with conventional measurements of shrinkage of arbitrarily selected “target lesions.”

A tremendous amount of work is needed to build the required large image banks. During that time, AI will only improve – and without the human risks of fatigue, inconsistency, or burnout.

Those human frailties notwithstanding, AI cannot substitute for the key discussions between patient and clinician regarding goals of care, trade-offs of risks and benefits, and shared decision-making regarding management options.

At least initially (but painfully), complex technologies like WGS and digital image analysis via AI may further disadvantage patients who are medically disadvantaged by geography or socioeconomic circumstances.

In the discussion period, AACR President Antoni Ribas, MD, of University of California, Los Angeles, asked whether AI can simulate crosstalk between gene pathways so that unique treatment combinations can be identified. Dr. Elemento said those simulations are the subject of ongoing investigation.

The theme of the opening plenary session at the AACR virtual meeting II was “Turning Science into Life-Saving Care.” Applications of AI to optimize personalized use of genomics, digital image analysis, and drug development show great promise for being among the technologies that can help to realize AACR’s thematic vision.

Dr. Elemento disclosed relationships with Volastra Therapeutics, OneThree Biotech, Owkin, Freenome, Genetic Intelligence, Acuamark Diagnostics, Eli Lilly, Janssen, and Sanofi.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

Precision medicine is driven by technologies such as rapid genome sequencing and artificial intelligence (AI), according to a presentation at the AACR virtual meeting II.

AI can be applied to the sequencing information derived from advanced cancers to make highly personalized treatment recommendations for patients, said Olivier Elemento, PhD, of Weill Cornell Medicine, New York.

Dr. Elemento described such work during the opening plenary session of the meeting.

Dr. Elemento advocated for whole-genome sequencing (WGS) of metastatic sites, as it can reveal “branched evolution” as tumors progress from localized to metastatic (Nat Genet. 2016 Dec;48[12]:1490-9).

The metastases share common mutations with the primaries from which they arise but also develop their own mutational profiles, which facilitate site-of-origin-agnostic, predictive treatment choices.

As examples, Dr. Elemento mentioned HER2 amplification found in a patient with urothelial cancer (J Natl Compr Canc Netw. 2019 Mar 1;17[3]:194-200) and a patient with uterine serous carcinoma (Gynecol Oncol Rep. 2019 Feb 21;28:54-7), both of whom experienced long-lasting remissions to HER2-targeted therapy.

Dr. Elemento also noted that WGS can reveal complex structural variants in lung adenocarcinomas that lack alterations in the RTK/RAS/RAF pathway (unpublished data).
 

Application of machine learning

One study suggested that microRNA expression and machine learning can be used to identify malignant thyroid lesions (Clin Cancer Res. 2012 Apr 1;18[7]:2032-8). The approach diagnosed malignant lesions with 90% accuracy, 100% sensitivity, and 86% specificity.

Dr. Elemento and colleagues used a similar approach to predict response to immunotherapy in melanoma (unpublished data).

The idea was to mine the cancer genome and transcriptome, allowing for identification of signals from neoantigens, immune gene expression, immune cell composition, and T-cell receptor repertoires, Dr. Elemento said. Integrating these signals with clinical outcome data via machine learning technology enabled the researchers to predict immunotherapy response in malignant melanoma with nearly 90% accuracy.

AI and image analysis

Studies have indicated that AI can be applied to medical images to improve diagnosis and treatment. The approach has been shown to:

• Facilitate correct diagnoses of malignant skin lesions (Nature. 2017 Feb 2;542[7639]:115-8).
• Distinguish lung adenocarcinoma from squamous cell cancer with 100% accuracy (EBioMedicine. 2018 Jan;27:317-28).
• Recognize distinct breast cancer subtypes (ductal, lobular, mucinous, papillary) and biomarkers (bioRxiv 242818. doi: 10.1101/242818; EBioMedicine. 2018 Jan;27:317-28)
• Predict mesothelioma prognosis (Nat Med. 2019 Oct;25[10]:1519-25).
• Predict prostate biopsy results (unpublished data) and calculate Gleason scores that can predict survival in prostate cancer patients (AACR 2020, Abstract 867).

Drug development through applied AI

In another study, Dr. Elemento and colleagues used a Bayesian machine learning approach to predict targets of molecules without a known mechanism of action (Nat Commun. 2019 Nov 19;10[1]:5221).

The method involved using data on gene expression profiles, cell line viability, side effects in animals, and structures of the molecules. The researchers applied this method to a large library of orphan small molecules and found it could predict targets in about 40% of cases.

Of 24 AI-predicted microtubule-targeting molecules, 14 depolymerized microtubules in the lab. Five of these molecules were effective in cell lines that were resistant to other microtubule-targeted drugs.

Dr. Elemento went on to describe how Oncoceutics was developing an antineoplastic agent called ONC201, but the company lacked information about the agent’s target. Using AI, the target was identified as dopamine receptor 2 (DRD2; Clin Cancer Res. 2019 Apr 1;25[7]:2305-13).

With that information, Oncoceutics initiated trials of ONC201 in tumors expressing high levels of DRD2, including a highly resistant glioma (J Neurooncol. 2019 Oct;145[1]:97-105). Responses were seen, and ONC201 is now being tested against other DRD2-expressing cancers.
 

Challenges to acknowledge

Potential benefits of AI in the clinic are exciting, but there are many bench-to-bedside challenges.

A clinically obvious example of AI’s applications is radiographic image analysis. There is no biologic rationale for our RECIST “cut values” for partial response, minimal response, and stable disease.

If AI can measure subtle changes on imaging that correlate with tumor biology (i.e., radiomics), we stand a better chance of predicting treatment outcomes than we can with conventional measurements of shrinkage of arbitrarily selected “target lesions.”

A tremendous amount of work is needed to build the required large image banks. During that time, AI will only improve – and without the human risks of fatigue, inconsistency, or burnout.

Those human frailties notwithstanding, AI cannot substitute for the key discussions between patient and clinician regarding goals of care, trade-offs of risks and benefits, and shared decision-making regarding management options.

At least initially (but painfully), complex technologies like WGS and digital image analysis via AI may further disadvantage patients who are medically disadvantaged by geography or socioeconomic circumstances.

In the discussion period, AACR President Antoni Ribas, MD, of University of California, Los Angeles, asked whether AI can simulate crosstalk between gene pathways so that unique treatment combinations can be identified. Dr. Elemento said those simulations are the subject of ongoing investigation.

The theme of the opening plenary session at the AACR virtual meeting II was “Turning Science into Life-Saving Care.” Applications of AI to optimize personalized use of genomics, digital image analysis, and drug development show great promise for being among the technologies that can help to realize AACR’s thematic vision.

Dr. Elemento disclosed relationships with Volastra Therapeutics, OneThree Biotech, Owkin, Freenome, Genetic Intelligence, Acuamark Diagnostics, Eli Lilly, Janssen, and Sanofi.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

Precision medicine is driven by technologies such as rapid genome sequencing and artificial intelligence (AI), according to a presentation at the AACR virtual meeting II.

AI can be applied to the sequencing information derived from advanced cancers to make highly personalized treatment recommendations for patients, said Olivier Elemento, PhD, of Weill Cornell Medicine, New York.

Dr. Elemento described such work during the opening plenary session of the meeting.

Dr. Elemento advocated for whole-genome sequencing (WGS) of metastatic sites, as it can reveal “branched evolution” as tumors progress from localized to metastatic (Nat Genet. 2016 Dec;48[12]:1490-9).

The metastases share common mutations with the primaries from which they arise but also develop their own mutational profiles, which facilitate site-of-origin-agnostic, predictive treatment choices.

As examples, Dr. Elemento mentioned HER2 amplification found in a patient with urothelial cancer (J Natl Compr Canc Netw. 2019 Mar 1;17[3]:194-200) and a patient with uterine serous carcinoma (Gynecol Oncol Rep. 2019 Feb 21;28:54-7), both of whom experienced long-lasting remissions to HER2-targeted therapy.

Dr. Elemento also noted that WGS can reveal complex structural variants in lung adenocarcinomas that lack alterations in the RTK/RAS/RAF pathway (unpublished data).
 

Application of machine learning

One study suggested that microRNA expression and machine learning can be used to identify malignant thyroid lesions (Clin Cancer Res. 2012 Apr 1;18[7]:2032-8). The approach diagnosed malignant lesions with 90% accuracy, 100% sensitivity, and 86% specificity.

Dr. Elemento and colleagues used a similar approach to predict response to immunotherapy in melanoma (unpublished data).

The idea was to mine the cancer genome and transcriptome, allowing for identification of signals from neoantigens, immune gene expression, immune cell composition, and T-cell receptor repertoires, Dr. Elemento said. Integrating these signals with clinical outcome data via machine learning technology enabled the researchers to predict immunotherapy response in malignant melanoma with nearly 90% accuracy.

AI and image analysis

Studies have indicated that AI can be applied to medical images to improve diagnosis and treatment. The approach has been shown to:

• Facilitate correct diagnoses of malignant skin lesions (Nature. 2017 Feb 2;542[7639]:115-8).
• Distinguish lung adenocarcinoma from squamous cell cancer with 100% accuracy (EBioMedicine. 2018 Jan;27:317-28).
• Recognize distinct breast cancer subtypes (ductal, lobular, mucinous, papillary) and biomarkers (bioRxiv 242818. doi: 10.1101/242818; EBioMedicine. 2018 Jan;27:317-28)
• Predict mesothelioma prognosis (Nat Med. 2019 Oct;25[10]:1519-25).
• Predict prostate biopsy results (unpublished data) and calculate Gleason scores that can predict survival in prostate cancer patients (AACR 2020, Abstract 867).

Drug development through applied AI

In another study, Dr. Elemento and colleagues used a Bayesian machine learning approach to predict targets of molecules without a known mechanism of action (Nat Commun. 2019 Nov 19;10[1]:5221).

The method involved using data on gene expression profiles, cell line viability, side effects in animals, and structures of the molecules. The researchers applied this method to a large library of orphan small molecules and found it could predict targets in about 40% of cases.

Of 24 AI-predicted microtubule-targeting molecules, 14 depolymerized microtubules in the lab. Five of these molecules were effective in cell lines that were resistant to other microtubule-targeted drugs.

Dr. Elemento went on to describe how Oncoceutics was developing an antineoplastic agent called ONC201, but the company lacked information about the agent’s target. Using AI, the target was identified as dopamine receptor 2 (DRD2; Clin Cancer Res. 2019 Apr 1;25[7]:2305-13).

With that information, Oncoceutics initiated trials of ONC201 in tumors expressing high levels of DRD2, including a highly resistant glioma (J Neurooncol. 2019 Oct;145[1]:97-105). Responses were seen, and ONC201 is now being tested against other DRD2-expressing cancers.
 

Challenges to acknowledge

Potential benefits of AI in the clinic are exciting, but there are many bench-to-bedside challenges.

A clinically obvious example of AI’s applications is radiographic image analysis. There is no biologic rationale for our RECIST “cut values” for partial response, minimal response, and stable disease.

If AI can measure subtle changes on imaging that correlate with tumor biology (i.e., radiomics), we stand a better chance of predicting treatment outcomes than we can with conventional measurements of shrinkage of arbitrarily selected “target lesions.”

A tremendous amount of work is needed to build the required large image banks. During that time, AI will only improve – and without the human risks of fatigue, inconsistency, or burnout.

Those human frailties notwithstanding, AI cannot substitute for the key discussions between patient and clinician regarding goals of care, trade-offs of risks and benefits, and shared decision-making regarding management options.

At least initially (but painfully), complex technologies like WGS and digital image analysis via AI may further disadvantage patients who are medically disadvantaged by geography or socioeconomic circumstances.

In the discussion period, AACR President Antoni Ribas, MD, of University of California, Los Angeles, asked whether AI can simulate crosstalk between gene pathways so that unique treatment combinations can be identified. Dr. Elemento said those simulations are the subject of ongoing investigation.

The theme of the opening plenary session at the AACR virtual meeting II was “Turning Science into Life-Saving Care.” Applications of AI to optimize personalized use of genomics, digital image analysis, and drug development show great promise for being among the technologies that can help to realize AACR’s thematic vision.

Dr. Elemento disclosed relationships with Volastra Therapeutics, OneThree Biotech, Owkin, Freenome, Genetic Intelligence, Acuamark Diagnostics, Eli Lilly, Janssen, and Sanofi.

Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.

Patients with early onset cancers have an increased prevalence of germline pathogenic variants, suggesting that genetic testing would be worthwhile in this population, according to a presentation at the AACR virtual meeting II.

Investigators analyzed blood samples from 1,201 patients who were aged 18-39 years when diagnosed with a solid tumor malignancy.

In this group, there were 877 patients with early onset cancers, defined as cancers for which 39 years of age is greater than 1 standard deviation below the mean age of diagnosis for the cancer type.

The remaining 324 patients had young adult cancers, defined as cancers for which 39 years of age is less than 1 standard deviation below the mean age of diagnosis.

The most common early onset cancers were breast, colorectal, kidney, pancreas, and ovarian cancer.

The most common young adult cancers were sarcoma, brain cancer, and testicular cancer, as expected, said investigator Zsofia K. Stadler, MD, of Memorial Sloan Kettering Cancer Center in New York.

Dr. Stadler and colleagues performed next-generation sequencing of the patient samples using a panel of up to 88 genes previously implicated in cancer predisposition. This revealed a significantly higher prevalence of germline mutations in patients with early onset cancers than in those with young adult cancers – 21% and 13%, respectively (P = .002).

In patients with only high- and moderate-risk cancer susceptibility genes, the prevalence was 15% in the early onset group and 10% in the young adult group (P = .01). “Among the early onset cancer group, pancreas, breast, and kidney cancer patients harbored the highest rates of germline mutations,” Dr. Stadler said, noting that the spectrum of mutated genes differed in early onset and young adult cancer patients.

“In early onset patients, the most commonly mutated genes were BRCA1 and BRCA2 [4.9%], Lynch syndrome genes [2.2%], ATM [1.6%], and CHECK2 [1.7%],” Dr. Stadler said. “On the other hand, in young adults, TP53 mutations [2.2%], and SDHA and SDHB mutations dominated [1.9%], with the majority of mutations occurring in sarcoma patients.”

These findings suggest the prevalence of inherited cancer susceptibility syndromes in young adults with cancer is not uniform.

“We found a very high prevalence of germline mutations in young patients with cancer types that typically present at later ages,” Dr. Stadler said, referring to the early onset patients.

Conversely, the young adult cancer patients had a prevalence and spectrum of mutations more similar to what is seen in pediatric cancer populations, she noted.

The findings are surprising, according to AACR past president Elaine R. Mardis, PhD, of The Ohio State University in Columbus.

Dr. Mardis said the results show that, in young adults with early onset cancers, “the germline prevalence of these mutations is significantly higher than we had previously thought.”

“Although representing only about 4% of all cancers, young adults with cancer ... face unique challenges,” Dr. Stadler said. “Identifying whether a young patient’s cancer occurred in the setting of an inherited cancer predisposition syndrome is especially important in this patient population.”

Such knowledge “can significantly impact the risk of second primary cancers and the need for increased surveillance measures or even risk-reducing surgeries,” Dr. Stadler explained. She added that it can also have implications for identifying at-risk family members, such as younger siblings or children who should pursue genetic testing and appropriate prevention measures.

“Our results suggest that, among patients with early onset cancer, the increased prevalence of germline mutations supports a role for genetic testing, irrespective of tumor type,” Dr. Stadler said.

This study was partially funded by the Precision, Interception and Prevention Program, the Robert and Katie Niehaus Center for Inherited Cancer Genomics, the Marie-Josee and Henry R. Kravis Center for Molecular Oncology, and a National Cancer Institute Cancer Center Core Grant. Dr. Stadler reported that an immediate family member serves as a consultant in ophthalmology for Allergan, Adverum Biotechnologies, Alimera Sciences, BioMarin, Fortress Biotech, Genentech/Roche, Novartis, Optos, Regeneron, Regenxbio, and Spark Therapeutics. Dr. Mardis disclosed relationships with Qiagen NV, Pact Pharma LLC, Moderna Inc., and Interpreta LLC.

sworcester@mdedge.com

SOURCE: Stadler Z et al. AACR 2020, Abstract 1122.

Patients with early onset cancers have an increased prevalence of germline pathogenic variants, suggesting that genetic testing would be worthwhile in this population, according to a presentation at the AACR virtual meeting II.

Investigators analyzed blood samples from 1,201 patients who were aged 18-39 years when diagnosed with a solid tumor malignancy.

In this group, there were 877 patients with early onset cancers, defined as cancers for which 39 years of age is greater than 1 standard deviation below the mean age of diagnosis for the cancer type.

The remaining 324 patients had young adult cancers, defined as cancers for which 39 years of age is less than 1 standard deviation below the mean age of diagnosis.

The most common early onset cancers were breast, colorectal, kidney, pancreas, and ovarian cancer.

The most common young adult cancers were sarcoma, brain cancer, and testicular cancer, as expected, said investigator Zsofia K. Stadler, MD, of Memorial Sloan Kettering Cancer Center in New York.

Dr. Stadler and colleagues performed next-generation sequencing of the patient samples using a panel of up to 88 genes previously implicated in cancer predisposition. This revealed a significantly higher prevalence of germline mutations in patients with early onset cancers than in those with young adult cancers – 21% and 13%, respectively (P = .002).

In patients with only high- and moderate-risk cancer susceptibility genes, the prevalence was 15% in the early onset group and 10% in the young adult group (P = .01). “Among the early onset cancer group, pancreas, breast, and kidney cancer patients harbored the highest rates of germline mutations,” Dr. Stadler said, noting that the spectrum of mutated genes differed in early onset and young adult cancer patients.

“In early onset patients, the most commonly mutated genes were BRCA1 and BRCA2 [4.9%], Lynch syndrome genes [2.2%], ATM [1.6%], and CHECK2 [1.7%],” Dr. Stadler said. “On the other hand, in young adults, TP53 mutations [2.2%], and SDHA and SDHB mutations dominated [1.9%], with the majority of mutations occurring in sarcoma patients.”

These findings suggest the prevalence of inherited cancer susceptibility syndromes in young adults with cancer is not uniform.

“We found a very high prevalence of germline mutations in young patients with cancer types that typically present at later ages,” Dr. Stadler said, referring to the early onset patients.

Conversely, the young adult cancer patients had a prevalence and spectrum of mutations more similar to what is seen in pediatric cancer populations, she noted.

The findings are surprising, according to AACR past president Elaine R. Mardis, PhD, of The Ohio State University in Columbus.

Dr. Mardis said the results show that, in young adults with early onset cancers, “the germline prevalence of these mutations is significantly higher than we had previously thought.”

“Although representing only about 4% of all cancers, young adults with cancer ... face unique challenges,” Dr. Stadler said. “Identifying whether a young patient’s cancer occurred in the setting of an inherited cancer predisposition syndrome is especially important in this patient population.”

Such knowledge “can significantly impact the risk of second primary cancers and the need for increased surveillance measures or even risk-reducing surgeries,” Dr. Stadler explained. She added that it can also have implications for identifying at-risk family members, such as younger siblings or children who should pursue genetic testing and appropriate prevention measures.

“Our results suggest that, among patients with early onset cancer, the increased prevalence of germline mutations supports a role for genetic testing, irrespective of tumor type,” Dr. Stadler said.

This study was partially funded by the Precision, Interception and Prevention Program, the Robert and Katie Niehaus Center for Inherited Cancer Genomics, the Marie-Josee and Henry R. Kravis Center for Molecular Oncology, and a National Cancer Institute Cancer Center Core Grant. Dr. Stadler reported that an immediate family member serves as a consultant in ophthalmology for Allergan, Adverum Biotechnologies, Alimera Sciences, BioMarin, Fortress Biotech, Genentech/Roche, Novartis, Optos, Regeneron, Regenxbio, and Spark Therapeutics. Dr. Mardis disclosed relationships with Qiagen NV, Pact Pharma LLC, Moderna Inc., and Interpreta LLC.

sworcester@mdedge.com

SOURCE: Stadler Z et al. AACR 2020, Abstract 1122.

Patients with early onset cancers have an increased prevalence of germline pathogenic variants, suggesting that genetic testing would be worthwhile in this population, according to a presentation at the AACR virtual meeting II.

Investigators analyzed blood samples from 1,201 patients who were aged 18-39 years when diagnosed with a solid tumor malignancy.

In this group, there were 877 patients with early onset cancers, defined as cancers for which 39 years of age is greater than 1 standard deviation below the mean age of diagnosis for the cancer type.

The remaining 324 patients had young adult cancers, defined as cancers for which 39 years of age is less than 1 standard deviation below the mean age of diagnosis.

The most common early onset cancers were breast, colorectal, kidney, pancreas, and ovarian cancer.

The most common young adult cancers were sarcoma, brain cancer, and testicular cancer, as expected, said investigator Zsofia K. Stadler, MD, of Memorial Sloan Kettering Cancer Center in New York.

Dr. Stadler and colleagues performed next-generation sequencing of the patient samples using a panel of up to 88 genes previously implicated in cancer predisposition. This revealed a significantly higher prevalence of germline mutations in patients with early onset cancers than in those with young adult cancers – 21% and 13%, respectively (P = .002).

In patients with only high- and moderate-risk cancer susceptibility genes, the prevalence was 15% in the early onset group and 10% in the young adult group (P = .01). “Among the early onset cancer group, pancreas, breast, and kidney cancer patients harbored the highest rates of germline mutations,” Dr. Stadler said, noting that the spectrum of mutated genes differed in early onset and young adult cancer patients.

“In early onset patients, the most commonly mutated genes were BRCA1 and BRCA2 [4.9%], Lynch syndrome genes [2.2%], ATM [1.6%], and CHECK2 [1.7%],” Dr. Stadler said. “On the other hand, in young adults, TP53 mutations [2.2%], and SDHA and SDHB mutations dominated [1.9%], with the majority of mutations occurring in sarcoma patients.”

These findings suggest the prevalence of inherited cancer susceptibility syndromes in young adults with cancer is not uniform.

“We found a very high prevalence of germline mutations in young patients with cancer types that typically present at later ages,” Dr. Stadler said, referring to the early onset patients.

Conversely, the young adult cancer patients had a prevalence and spectrum of mutations more similar to what is seen in pediatric cancer populations, she noted.

The findings are surprising, according to AACR past president Elaine R. Mardis, PhD, of The Ohio State University in Columbus.

Dr. Mardis said the results show that, in young adults with early onset cancers, “the germline prevalence of these mutations is significantly higher than we had previously thought.”

“Although representing only about 4% of all cancers, young adults with cancer ... face unique challenges,” Dr. Stadler said. “Identifying whether a young patient’s cancer occurred in the setting of an inherited cancer predisposition syndrome is especially important in this patient population.”

Such knowledge “can significantly impact the risk of second primary cancers and the need for increased surveillance measures or even risk-reducing surgeries,” Dr. Stadler explained. She added that it can also have implications for identifying at-risk family members, such as younger siblings or children who should pursue genetic testing and appropriate prevention measures.

“Our results suggest that, among patients with early onset cancer, the increased prevalence of germline mutations supports a role for genetic testing, irrespective of tumor type,” Dr. Stadler said.

This study was partially funded by the Precision, Interception and Prevention Program, the Robert and Katie Niehaus Center for Inherited Cancer Genomics, the Marie-Josee and Henry R. Kravis Center for Molecular Oncology, and a National Cancer Institute Cancer Center Core Grant. Dr. Stadler reported that an immediate family member serves as a consultant in ophthalmology for Allergan, Adverum Biotechnologies, Alimera Sciences, BioMarin, Fortress Biotech, Genentech/Roche, Novartis, Optos, Regeneron, Regenxbio, and Spark Therapeutics. Dr. Mardis disclosed relationships with Qiagen NV, Pact Pharma LLC, Moderna Inc., and Interpreta LLC.

sworcester@mdedge.com

SOURCE: Stadler Z et al. AACR 2020, Abstract 1122.

Clearance of circulating tumor DNA (ctDNA) correlates with longer progression-free survival (PFS) in patients with EGFR-mutant, MET-amplified non–small cell lung cancer (NSCLC) treated with EGFR- and MET-targeted therapies, according to an analysis of data from the phase 1b TATTON study.

The median PFS was 9.1 months for patients with ctDNA clearance and 3.9 months for those without ctDNA clearance three to four cycles after starting treatment with osimertinib, an EGFR tyrosine kinase inhibitor (TKI), and savolitinib, a MET TKI (P = 0.0146).

“[O]ur findings indicate that EGFR-mutant ctDNA clearance may be predictive of longer PFS for patients with EGFR-mutant, MET-amplified non–small cell lung cancer and detectable ctDNA at baseline,” said investigator Ryan Hartmaier, PhD, of AstraZeneca in Boston, Mass.

Dr. Hartmaier presented these findings at the AACR virtual meeting II.
 

Prior results of TATTON

Interim results of the TATTON study were published earlier this year (Lancet Oncol. 2020 Mar;21[3]:373-386). The trial enrolled patients with locally advanced or metastatic EGFR-mutant, MET-amplified NSCLC who had progressed on a prior EGFR TKI. Results included patients enrolled in parts B and D.

Part B consisted of patients who had previously received a third-generation EGFR TKI and patients who had not received a third-generation EGFR TKI and were either Thr790Met negative or Thr790Met positive. There were 144 patients in part B. All received oral osimertinib at 80 mg, 138 received savolitinib at 600 mg, and 8 received savolitinib at 300 mg daily. Part D included 42 patients who had not received a third-generation EGFR TKI and were Thr790Met negative. In this cohort, patients received osimertinib at 80 mg and savolitinib at 300 mg daily.

The objective response rate (all partial responses) was 48% in part B and 64% in part D. The median PFS was 7.6 months and 9.1 months, respectively.

Alexander E. Drilon, MD, of Memorial Sloan Kettering Cancer Center in New York said results of the TATTON study demonstrate that MET dependence is an actionable EGFR TKI resistance mechanism in EGFR-mutant lung cancers.

“We all would welcome the approval of an EGFR and MET TKI combination in the future,” Dr. Drilon said in a discussion of the study at the AACR meeting.

According to Dr. Hartmaier, MET-based resistance mechanisms are seen in up to 10% of patients with EGFR-mutated NSCLC following progression on first- and second-generation EGFR TKIs, and up to 25% of those progressing on osimertinib, a third-generation EGFR TKI.

“Nonclinical and clinical evidence suggests that combined treatment of a MET inhibitor and an EGFR TKI could overcome acquired MET-mediated resistance,” he said.
 

ctDNA analysis

Patients in the TATTON study had ctDNA samples collected at various time points from baseline through cycle five of treatment and until disease progression or treatment discontinuation.

Dr. Hartmaier’s analysis focused on ctDNA changes from baseline to day 1 of the third or fourth treatment cycle, time points at which the bulk of ctDNA could be observed, he said.

Among 34 evaluable patients in part B who received savolitinib at 600 mg, 22 had ctDNA clearance, and 12 had not. Among 16 evaluable patients in part D who received savolitinib at 300 mg, 13 had ctDNA clearance, and 3 had not.

Rates of ctDNA clearance were “remarkably similar” among the dosing groups, Dr. Hartmaier said.

In part B, the median PFS was 9.1 months for patients with ctDNA clearance and 3.9 months for patients without clearance (hazard ratio, 0.34; 95% confidence interval, 0.14-0.81; P = 0.0146).

Dr. Hartmaier did not present PFS results according to ctDNA clearance for patients in part D.

Dr. Drilon said serial ctDNA analyses can provide information on mechanisms of primary or acquired resistance, intra- and inter-tumoral heterogeneity, and the potential durability of benefit that can be achieved with combination targeted therapy. He acknowledged, however, that more work needs to be done in the field of MET-targeted therapy development.

“We need to work on standardizing diagnostic definitions of MET dependence, recognizing that loose definitions and poly-assay use make data challenging to interpret,” he said.

The TATTON study was supported by AstraZeneca. Dr. Hartmaier is an AstraZeneca employee and shareholder. Dr. Drilon disclosed relationships with AstraZeneca, Pfizer, Helsinn, Beigene, and other companies.

SOURCE: Hartmaier R, et al. AACR 2020, Abstract CT303.

Clearance of circulating tumor DNA (ctDNA) correlates with longer progression-free survival (PFS) in patients with EGFR-mutant, MET-amplified non–small cell lung cancer (NSCLC) treated with EGFR- and MET-targeted therapies, according to an analysis of data from the phase 1b TATTON study.

The median PFS was 9.1 months for patients with ctDNA clearance and 3.9 months for those without ctDNA clearance three to four cycles after starting treatment with osimertinib, an EGFR tyrosine kinase inhibitor (TKI), and savolitinib, a MET TKI (P = 0.0146).

“[O]ur findings indicate that EGFR-mutant ctDNA clearance may be predictive of longer PFS for patients with EGFR-mutant, MET-amplified non–small cell lung cancer and detectable ctDNA at baseline,” said investigator Ryan Hartmaier, PhD, of AstraZeneca in Boston, Mass.

Dr. Hartmaier presented these findings at the AACR virtual meeting II.
 

Prior results of TATTON

Interim results of the TATTON study were published earlier this year (Lancet Oncol. 2020 Mar;21[3]:373-386). The trial enrolled patients with locally advanced or metastatic EGFR-mutant, MET-amplified NSCLC who had progressed on a prior EGFR TKI. Results included patients enrolled in parts B and D.

Part B consisted of patients who had previously received a third-generation EGFR TKI and patients who had not received a third-generation EGFR TKI and were either Thr790Met negative or Thr790Met positive. There were 144 patients in part B. All received oral osimertinib at 80 mg, 138 received savolitinib at 600 mg, and 8 received savolitinib at 300 mg daily. Part D included 42 patients who had not received a third-generation EGFR TKI and were Thr790Met negative. In this cohort, patients received osimertinib at 80 mg and savolitinib at 300 mg daily.

The objective response rate (all partial responses) was 48% in part B and 64% in part D. The median PFS was 7.6 months and 9.1 months, respectively.

Alexander E. Drilon, MD, of Memorial Sloan Kettering Cancer Center in New York said results of the TATTON study demonstrate that MET dependence is an actionable EGFR TKI resistance mechanism in EGFR-mutant lung cancers.

“We all would welcome the approval of an EGFR and MET TKI combination in the future,” Dr. Drilon said in a discussion of the study at the AACR meeting.

According to Dr. Hartmaier, MET-based resistance mechanisms are seen in up to 10% of patients with EGFR-mutated NSCLC following progression on first- and second-generation EGFR TKIs, and up to 25% of those progressing on osimertinib, a third-generation EGFR TKI.

“Nonclinical and clinical evidence suggests that combined treatment of a MET inhibitor and an EGFR TKI could overcome acquired MET-mediated resistance,” he said.
 

ctDNA analysis

Patients in the TATTON study had ctDNA samples collected at various time points from baseline through cycle five of treatment and until disease progression or treatment discontinuation.

Dr. Hartmaier’s analysis focused on ctDNA changes from baseline to day 1 of the third or fourth treatment cycle, time points at which the bulk of ctDNA could be observed, he said.

Among 34 evaluable patients in part B who received savolitinib at 600 mg, 22 had ctDNA clearance, and 12 had not. Among 16 evaluable patients in part D who received savolitinib at 300 mg, 13 had ctDNA clearance, and 3 had not.

Rates of ctDNA clearance were “remarkably similar” among the dosing groups, Dr. Hartmaier said.

In part B, the median PFS was 9.1 months for patients with ctDNA clearance and 3.9 months for patients without clearance (hazard ratio, 0.34; 95% confidence interval, 0.14-0.81; P = 0.0146).

Dr. Hartmaier did not present PFS results according to ctDNA clearance for patients in part D.

Dr. Drilon said serial ctDNA analyses can provide information on mechanisms of primary or acquired resistance, intra- and inter-tumoral heterogeneity, and the potential durability of benefit that can be achieved with combination targeted therapy. He acknowledged, however, that more work needs to be done in the field of MET-targeted therapy development.

“We need to work on standardizing diagnostic definitions of MET dependence, recognizing that loose definitions and poly-assay use make data challenging to interpret,” he said.

The TATTON study was supported by AstraZeneca. Dr. Hartmaier is an AstraZeneca employee and shareholder. Dr. Drilon disclosed relationships with AstraZeneca, Pfizer, Helsinn, Beigene, and other companies.

SOURCE: Hartmaier R, et al. AACR 2020, Abstract CT303.

Clearance of circulating tumor DNA (ctDNA) correlates with longer progression-free survival (PFS) in patients with EGFR-mutant, MET-amplified non–small cell lung cancer (NSCLC) treated with EGFR- and MET-targeted therapies, according to an analysis of data from the phase 1b TATTON study.

The median PFS was 9.1 months for patients with ctDNA clearance and 3.9 months for those without ctDNA clearance three to four cycles after starting treatment with osimertinib, an EGFR tyrosine kinase inhibitor (TKI), and savolitinib, a MET TKI (P = 0.0146).

“[O]ur findings indicate that EGFR-mutant ctDNA clearance may be predictive of longer PFS for patients with EGFR-mutant, MET-amplified non–small cell lung cancer and detectable ctDNA at baseline,” said investigator Ryan Hartmaier, PhD, of AstraZeneca in Boston, Mass.

Dr. Hartmaier presented these findings at the AACR virtual meeting II.
 

Prior results of TATTON

Interim results of the TATTON study were published earlier this year (Lancet Oncol. 2020 Mar;21[3]:373-386). The trial enrolled patients with locally advanced or metastatic EGFR-mutant, MET-amplified NSCLC who had progressed on a prior EGFR TKI. Results included patients enrolled in parts B and D.

Part B consisted of patients who had previously received a third-generation EGFR TKI and patients who had not received a third-generation EGFR TKI and were either Thr790Met negative or Thr790Met positive. There were 144 patients in part B. All received oral osimertinib at 80 mg, 138 received savolitinib at 600 mg, and 8 received savolitinib at 300 mg daily. Part D included 42 patients who had not received a third-generation EGFR TKI and were Thr790Met negative. In this cohort, patients received osimertinib at 80 mg and savolitinib at 300 mg daily.

The objective response rate (all partial responses) was 48% in part B and 64% in part D. The median PFS was 7.6 months and 9.1 months, respectively.

Alexander E. Drilon, MD, of Memorial Sloan Kettering Cancer Center in New York said results of the TATTON study demonstrate that MET dependence is an actionable EGFR TKI resistance mechanism in EGFR-mutant lung cancers.

“We all would welcome the approval of an EGFR and MET TKI combination in the future,” Dr. Drilon said in a discussion of the study at the AACR meeting.

According to Dr. Hartmaier, MET-based resistance mechanisms are seen in up to 10% of patients with EGFR-mutated NSCLC following progression on first- and second-generation EGFR TKIs, and up to 25% of those progressing on osimertinib, a third-generation EGFR TKI.

“Nonclinical and clinical evidence suggests that combined treatment of a MET inhibitor and an EGFR TKI could overcome acquired MET-mediated resistance,” he said.
 

ctDNA analysis

Patients in the TATTON study had ctDNA samples collected at various time points from baseline through cycle five of treatment and until disease progression or treatment discontinuation.

Dr. Hartmaier’s analysis focused on ctDNA changes from baseline to day 1 of the third or fourth treatment cycle, time points at which the bulk of ctDNA could be observed, he said.

Among 34 evaluable patients in part B who received savolitinib at 600 mg, 22 had ctDNA clearance, and 12 had not. Among 16 evaluable patients in part D who received savolitinib at 300 mg, 13 had ctDNA clearance, and 3 had not.

Rates of ctDNA clearance were “remarkably similar” among the dosing groups, Dr. Hartmaier said.

In part B, the median PFS was 9.1 months for patients with ctDNA clearance and 3.9 months for patients without clearance (hazard ratio, 0.34; 95% confidence interval, 0.14-0.81; P = 0.0146).

Dr. Hartmaier did not present PFS results according to ctDNA clearance for patients in part D.

Dr. Drilon said serial ctDNA analyses can provide information on mechanisms of primary or acquired resistance, intra- and inter-tumoral heterogeneity, and the potential durability of benefit that can be achieved with combination targeted therapy. He acknowledged, however, that more work needs to be done in the field of MET-targeted therapy development.

“We need to work on standardizing diagnostic definitions of MET dependence, recognizing that loose definitions and poly-assay use make data challenging to interpret,” he said.

The TATTON study was supported by AstraZeneca. Dr. Hartmaier is an AstraZeneca employee and shareholder. Dr. Drilon disclosed relationships with AstraZeneca, Pfizer, Helsinn, Beigene, and other companies.

SOURCE: Hartmaier R, et al. AACR 2020, Abstract CT303.

Artificial intelligence (AI)–based Gleason scores correlated with pathologists’ Gleason scores for predicting survival in patients with prostate cancer, according to a cohort-based analysis.

An AI-based Gleason score – derived from 7,267 digitized biopsy slides, pathology reports, and clinical data from patient electronic medical records – was calculated for each of 599 prostate cancer patients.

The AI scores were compared with pathologists’ Gleason scores, which were obtained from pathology reports for each of the patients.

The two scores were “highly correlated,” according to investigators. The area under the curve (AUC) for the 7-year mortality rate was 0.667 for the AI-based scores and 0.659 for the pathologists’ scores.

The investigators also found that markers extracted using AI-based algorithms could predict disease progression in patients with low- and higher-grade disease.

Daphna Laifenfeld, PhD, chief scientific officer of Ibex Medical Analytics in Tel Aviv, reported these results in a poster at the AACR virtual meeting II. Ibex Medical Analytics is the company that developed the AI-based algorithms and Gleason score (the Ibex score).

In addition to comparing the Ibex Gleason scores with pathologists’ scores, Dr. Laifenfeld and colleagues sought to “develop AI markers – computational features extracted from slides using AI-based algorithms – that can predict disease progression in low-, and separately, higher-grade patients.”

Information extracted using the algorithms included Gleason scores; perineural invasion; and other characteristics such as inflammation, high-grade prostatic intraepithelial neoplasia, and atrophy.

“We used data ... to address each aim, analyzing hundreds of patients in each comparison, and employed logistic regression to develop the predictive models,” Dr. Laifenfeld said.

Of the 357 patients evaluated, 180 had low-grade disease, defined by a prebiopsy prostate-specific antigen (PSA) level less than 10 ng/mL (Gleason group 1), and 177 patients had higher-grade disease (Gleason group 2 or higher).

Gleason group 1 patients were considered to have progressed if they developed higher-grade cancer, underwent prostatectomy, or if their cancer had metastasized. Gleason group 2 and above patients were considered to have progressed if their cancer metastasized or if they had a postprostatectomy PSA level greater than 4 ng/ml.

In Gleason group 1 patients, combining multiple features from the pathology report with prebiopsy PSA levels was shown to predict disease progression better than prebiopsy PSA levels alone (AUC, 0.687).

“Importantly, AI markers that combine features automatically extracted by Ibex with prebiopsy PSA levels are even better associated with progression (AUC, 0.748),” Dr. Laifenfeld said.

Similarly, in the Gleason group 2 and above patients, the AI markers that combine Ibex-extracted features with prebiopsy PSA levels were also highly associated with progression (AUC, 0.862 vs. AUC, 0.77 for the non–Ibex-based approach) and can be used for patient stratification, Dr. Laifenfeld said.

“For each patient, we can predict whether or not their disease will progress,” she said. “[T]his type of stratification can then be used to support clinical disease management decisions, and [it can be used] in the course of drug development for patient stratification and trial enrichment strategies.”

Dr. Laifenfeld and some coinvestigators are employed by Ibex Medical Analytics.

sworcester@mdedge.com

SOURCE: Laifenfeld D et al. AACR 2020, Abstract 867.

Artificial intelligence (AI)–based Gleason scores correlated with pathologists’ Gleason scores for predicting survival in patients with prostate cancer, according to a cohort-based analysis.

An AI-based Gleason score – derived from 7,267 digitized biopsy slides, pathology reports, and clinical data from patient electronic medical records – was calculated for each of 599 prostate cancer patients.

The AI scores were compared with pathologists’ Gleason scores, which were obtained from pathology reports for each of the patients.

The two scores were “highly correlated,” according to investigators. The area under the curve (AUC) for the 7-year mortality rate was 0.667 for the AI-based scores and 0.659 for the pathologists’ scores.

The investigators also found that markers extracted using AI-based algorithms could predict disease progression in patients with low- and higher-grade disease.

Daphna Laifenfeld, PhD, chief scientific officer of Ibex Medical Analytics in Tel Aviv, reported these results in a poster at the AACR virtual meeting II. Ibex Medical Analytics is the company that developed the AI-based algorithms and Gleason score (the Ibex score).

In addition to comparing the Ibex Gleason scores with pathologists’ scores, Dr. Laifenfeld and colleagues sought to “develop AI markers – computational features extracted from slides using AI-based algorithms – that can predict disease progression in low-, and separately, higher-grade patients.”

Information extracted using the algorithms included Gleason scores; perineural invasion; and other characteristics such as inflammation, high-grade prostatic intraepithelial neoplasia, and atrophy.

“We used data ... to address each aim, analyzing hundreds of patients in each comparison, and employed logistic regression to develop the predictive models,” Dr. Laifenfeld said.

Of the 357 patients evaluated, 180 had low-grade disease, defined by a prebiopsy prostate-specific antigen (PSA) level less than 10 ng/mL (Gleason group 1), and 177 patients had higher-grade disease (Gleason group 2 or higher).

Gleason group 1 patients were considered to have progressed if they developed higher-grade cancer, underwent prostatectomy, or if their cancer had metastasized. Gleason group 2 and above patients were considered to have progressed if their cancer metastasized or if they had a postprostatectomy PSA level greater than 4 ng/ml.

In Gleason group 1 patients, combining multiple features from the pathology report with prebiopsy PSA levels was shown to predict disease progression better than prebiopsy PSA levels alone (AUC, 0.687).

“Importantly, AI markers that combine features automatically extracted by Ibex with prebiopsy PSA levels are even better associated with progression (AUC, 0.748),” Dr. Laifenfeld said.

Similarly, in the Gleason group 2 and above patients, the AI markers that combine Ibex-extracted features with prebiopsy PSA levels were also highly associated with progression (AUC, 0.862 vs. AUC, 0.77 for the non–Ibex-based approach) and can be used for patient stratification, Dr. Laifenfeld said.

“For each patient, we can predict whether or not their disease will progress,” she said. “[T]his type of stratification can then be used to support clinical disease management decisions, and [it can be used] in the course of drug development for patient stratification and trial enrichment strategies.”

Dr. Laifenfeld and some coinvestigators are employed by Ibex Medical Analytics.

sworcester@mdedge.com

SOURCE: Laifenfeld D et al. AACR 2020, Abstract 867.

Artificial intelligence (AI)–based Gleason scores correlated with pathologists’ Gleason scores for predicting survival in patients with prostate cancer, according to a cohort-based analysis.

An AI-based Gleason score – derived from 7,267 digitized biopsy slides, pathology reports, and clinical data from patient electronic medical records – was calculated for each of 599 prostate cancer patients.

The AI scores were compared with pathologists’ Gleason scores, which were obtained from pathology reports for each of the patients.

The two scores were “highly correlated,” according to investigators. The area under the curve (AUC) for the 7-year mortality rate was 0.667 for the AI-based scores and 0.659 for the pathologists’ scores.

The investigators also found that markers extracted using AI-based algorithms could predict disease progression in patients with low- and higher-grade disease.

Daphna Laifenfeld, PhD, chief scientific officer of Ibex Medical Analytics in Tel Aviv, reported these results in a poster at the AACR virtual meeting II. Ibex Medical Analytics is the company that developed the AI-based algorithms and Gleason score (the Ibex score).

In addition to comparing the Ibex Gleason scores with pathologists’ scores, Dr. Laifenfeld and colleagues sought to “develop AI markers – computational features extracted from slides using AI-based algorithms – that can predict disease progression in low-, and separately, higher-grade patients.”

Information extracted using the algorithms included Gleason scores; perineural invasion; and other characteristics such as inflammation, high-grade prostatic intraepithelial neoplasia, and atrophy.

“We used data ... to address each aim, analyzing hundreds of patients in each comparison, and employed logistic regression to develop the predictive models,” Dr. Laifenfeld said.

Of the 357 patients evaluated, 180 had low-grade disease, defined by a prebiopsy prostate-specific antigen (PSA) level less than 10 ng/mL (Gleason group 1), and 177 patients had higher-grade disease (Gleason group 2 or higher).

Gleason group 1 patients were considered to have progressed if they developed higher-grade cancer, underwent prostatectomy, or if their cancer had metastasized. Gleason group 2 and above patients were considered to have progressed if their cancer metastasized or if they had a postprostatectomy PSA level greater than 4 ng/ml.

In Gleason group 1 patients, combining multiple features from the pathology report with prebiopsy PSA levels was shown to predict disease progression better than prebiopsy PSA levels alone (AUC, 0.687).

“Importantly, AI markers that combine features automatically extracted by Ibex with prebiopsy PSA levels are even better associated with progression (AUC, 0.748),” Dr. Laifenfeld said.

Similarly, in the Gleason group 2 and above patients, the AI markers that combine Ibex-extracted features with prebiopsy PSA levels were also highly associated with progression (AUC, 0.862 vs. AUC, 0.77 for the non–Ibex-based approach) and can be used for patient stratification, Dr. Laifenfeld said.

“For each patient, we can predict whether or not their disease will progress,” she said. “[T]his type of stratification can then be used to support clinical disease management decisions, and [it can be used] in the course of drug development for patient stratification and trial enrichment strategies.”

Dr. Laifenfeld and some coinvestigators are employed by Ibex Medical Analytics.

sworcester@mdedge.com

SOURCE: Laifenfeld D et al. AACR 2020, Abstract 867.

There are several mechanisms by which the aging microenvironment can drive cancer and influence response to therapy, according to a plenary presentation at the AACR virtual meeting II.

Ashani T. Weeraratna, PhD, highlighted research showing how the aging microenvironment affects tumor cell metabolism, angiogenesis, and treatment resistance in melanoma.

Dr. Weeraratna, of Johns Hopkins Bloomberg School of Public Health in Baltimore, first described a study showing how fibroblasts in the aged microenvironment contribute to tumor progression in models of melanoma (Nature. 2016 Apr 14;532[7598]:250-4).

Dr. Weeraratna and colleagues isolated dermal fibroblasts from young human donors (aged 25-35 years) and older donors (55-65 years) and used these cells to produce artificial skin.

Melanoma cells placed in the artificial skin created with young fibroblasts remained “very tightly nested at the surface,” Dr. Weeraratna said. On the other hand, melanoma cells migrated “very rapidly” through the artificial dermis created from aged fibroblasts.

In mouse models of melanoma, tumors grew much faster in young mice (6-8 weeks) than in old mice (12-18 months). However, tumors metastasized to the lung at a “much greater rate in the aged mice than in the young mice,” Dr. Weeraratna said.
 

Angiogenesis, SFRP2, and VEGF

Dr. Weeraratna went on to explain how a member of her lab conducted proteomic analyses of young and aged lung fibroblasts. The results were compared with results from prior analyses of young and aged skin fibroblasts.

The results showed that aged skin fibroblasts promote noncanonical WNT signaling via expression of SFRP2, SERPINE2, DKK1, Wnt5A, and ROR2. On the other hand, aged lung fibroblasts promote canonical WNT signaling via some of the same family members, including SFRP1, DKK3, and ROR1.

Research by another group showed that SFRP2 stimulates angiogenesis via a calcineurin/NFAT signaling pathway (Cancer Res. 2009 Jun 1;69[11]:4621-8).

Research in Dr. Weeraratna’s lab showed that SFRP2 and VEGF are inversely correlated with aging. Tumors in aged mice had an abundance of SFRP2 but little VEGF. Tumors in young mice had an abundance of VEGF but little SFRP2.

Dr. Weeraratna’s team wanted to determine if results would be similar in melanoma patients, so the researchers analyzed data from the TCGA database. They found that VEGF and two of its key receptors are decreased in older melanoma patients, in comparison with younger melanoma patients.

The clinical relevancy of this finding is reflected in an analysis of data from the AVAST-M study (Ann Oncol. 2019;30[12]:2013-4). When compared with observation, bevacizumab did not improve survival overall or for older patients, but the EGFR inhibitor was associated with longer survival in patients younger than 45 years.

Dr. Weeraratna said this finding and her group’s prior findings suggest younger melanoma patients have more VEGF but less angiogenesis than older patients. The older patients have less VEGF and more SFRP2, which drives angiogenesis.

Dr. Weeraratna’s lab then conducted experiments in young mice, which suggested that an anti-VEGF antibody can reduce angiogenesis, but not in the presence of SFRP2.

Lipid metabolism and treatment resistance

A recently published study by Dr. Weeraratna and colleagues tied changes in aged fibroblast lipid metabolism to treatment resistance in melanoma (Cancer Discov. 2020 Jun 4;CD-20-0329).

The research showed that melanoma cells accumulate lipids when incubated with aged, rather than young, fibroblasts in vitro.

Lipid uptake is mediated by fatty acid transporters (FATPs), and the researchers found that most FATPs were unchanged by age. However, FATP2 was elevated in melanoma cells exposed to aged media, aged mice, and melanoma patients older than 50 years of age.

When melanoma cells were incubated with conditioned media from aged fibroblasts and a FATP2 inhibitor, they no longer took up lipids.

When FATP2 was knocked down in aged mice with melanoma, BRAF and MEK inhibitors (which are not very effective ordinarily) caused dramatic and prolonged tumor regression. These effects were not seen with FATP2 inhibition in young mice.

These results suggest FATP2 is a key transporter of lipids in the aged microenvironment, and inhibiting FATP2 can delay the onset of treatment resistance.

Striving to understand a complex system

For many years, the dogma was that cancer cells behaved like unwelcome invaders, co-opting the metabolic machinery of the sites of spread, with crowding of the normal structures within those organs.

To say that concept was primitive is an understatement. Clearly, the relationship between tumor cells and the surrounding stroma is complex. Changes that occur in an aging microenvironment can influence cancer outcomes in older adults.

Dr. Weeraratna’s presentation adds further impetus to efforts to broaden eligibility criteria for clinical trials so the median age and the metabolic milieu of trial participants more closely parallels the general population.

She highlighted the importance of data analysis by age cohorts and the need to design preclinical studies so that investigators can study the microenvironment of cancer cells in in vitro models and in young and older laboratory animals.

As management expert W. Edwards Deming is believed to have said, “Every system is perfectly designed to get the results it gets.” Cancer is likely not an independent, hostile invader, overtaking the failing machinery of aging cells. To understand the intersection of cancer and aging, we need a more perfect understanding of the system in which tumors develop and are treated.

Dr. Weeraratna reported having no disclosures.


Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.
 

SOURCE: Weeraratna A. AACR 2020. Age against the machine: How the aging microenvironment governs response to therapy.

There are several mechanisms by which the aging microenvironment can drive cancer and influence response to therapy, according to a plenary presentation at the AACR virtual meeting II.

Ashani T. Weeraratna, PhD, highlighted research showing how the aging microenvironment affects tumor cell metabolism, angiogenesis, and treatment resistance in melanoma.

Dr. Weeraratna, of Johns Hopkins Bloomberg School of Public Health in Baltimore, first described a study showing how fibroblasts in the aged microenvironment contribute to tumor progression in models of melanoma (Nature. 2016 Apr 14;532[7598]:250-4).

Dr. Weeraratna and colleagues isolated dermal fibroblasts from young human donors (aged 25-35 years) and older donors (55-65 years) and used these cells to produce artificial skin.

Melanoma cells placed in the artificial skin created with young fibroblasts remained “very tightly nested at the surface,” Dr. Weeraratna said. On the other hand, melanoma cells migrated “very rapidly” through the artificial dermis created from aged fibroblasts.

In mouse models of melanoma, tumors grew much faster in young mice (6-8 weeks) than in old mice (12-18 months). However, tumors metastasized to the lung at a “much greater rate in the aged mice than in the young mice,” Dr. Weeraratna said.
 

Angiogenesis, SFRP2, and VEGF

Dr. Weeraratna went on to explain how a member of her lab conducted proteomic analyses of young and aged lung fibroblasts. The results were compared with results from prior analyses of young and aged skin fibroblasts.

The results showed that aged skin fibroblasts promote noncanonical WNT signaling via expression of SFRP2, SERPINE2, DKK1, Wnt5A, and ROR2. On the other hand, aged lung fibroblasts promote canonical WNT signaling via some of the same family members, including SFRP1, DKK3, and ROR1.

Research by another group showed that SFRP2 stimulates angiogenesis via a calcineurin/NFAT signaling pathway (Cancer Res. 2009 Jun 1;69[11]:4621-8).

Research in Dr. Weeraratna’s lab showed that SFRP2 and VEGF are inversely correlated with aging. Tumors in aged mice had an abundance of SFRP2 but little VEGF. Tumors in young mice had an abundance of VEGF but little SFRP2.

Dr. Weeraratna’s team wanted to determine if results would be similar in melanoma patients, so the researchers analyzed data from the TCGA database. They found that VEGF and two of its key receptors are decreased in older melanoma patients, in comparison with younger melanoma patients.

The clinical relevancy of this finding is reflected in an analysis of data from the AVAST-M study (Ann Oncol. 2019;30[12]:2013-4). When compared with observation, bevacizumab did not improve survival overall or for older patients, but the EGFR inhibitor was associated with longer survival in patients younger than 45 years.

Dr. Weeraratna said this finding and her group’s prior findings suggest younger melanoma patients have more VEGF but less angiogenesis than older patients. The older patients have less VEGF and more SFRP2, which drives angiogenesis.

Dr. Weeraratna’s lab then conducted experiments in young mice, which suggested that an anti-VEGF antibody can reduce angiogenesis, but not in the presence of SFRP2.

Lipid metabolism and treatment resistance

A recently published study by Dr. Weeraratna and colleagues tied changes in aged fibroblast lipid metabolism to treatment resistance in melanoma (Cancer Discov. 2020 Jun 4;CD-20-0329).

The research showed that melanoma cells accumulate lipids when incubated with aged, rather than young, fibroblasts in vitro.

Lipid uptake is mediated by fatty acid transporters (FATPs), and the researchers found that most FATPs were unchanged by age. However, FATP2 was elevated in melanoma cells exposed to aged media, aged mice, and melanoma patients older than 50 years of age.

When melanoma cells were incubated with conditioned media from aged fibroblasts and a FATP2 inhibitor, they no longer took up lipids.

When FATP2 was knocked down in aged mice with melanoma, BRAF and MEK inhibitors (which are not very effective ordinarily) caused dramatic and prolonged tumor regression. These effects were not seen with FATP2 inhibition in young mice.

These results suggest FATP2 is a key transporter of lipids in the aged microenvironment, and inhibiting FATP2 can delay the onset of treatment resistance.

Striving to understand a complex system

For many years, the dogma was that cancer cells behaved like unwelcome invaders, co-opting the metabolic machinery of the sites of spread, with crowding of the normal structures within those organs.

To say that concept was primitive is an understatement. Clearly, the relationship between tumor cells and the surrounding stroma is complex. Changes that occur in an aging microenvironment can influence cancer outcomes in older adults.

Dr. Weeraratna’s presentation adds further impetus to efforts to broaden eligibility criteria for clinical trials so the median age and the metabolic milieu of trial participants more closely parallels the general population.

She highlighted the importance of data analysis by age cohorts and the need to design preclinical studies so that investigators can study the microenvironment of cancer cells in in vitro models and in young and older laboratory animals.

As management expert W. Edwards Deming is believed to have said, “Every system is perfectly designed to get the results it gets.” Cancer is likely not an independent, hostile invader, overtaking the failing machinery of aging cells. To understand the intersection of cancer and aging, we need a more perfect understanding of the system in which tumors develop and are treated.

Dr. Weeraratna reported having no disclosures.


Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.
 

SOURCE: Weeraratna A. AACR 2020. Age against the machine: How the aging microenvironment governs response to therapy.

There are several mechanisms by which the aging microenvironment can drive cancer and influence response to therapy, according to a plenary presentation at the AACR virtual meeting II.

Ashani T. Weeraratna, PhD, highlighted research showing how the aging microenvironment affects tumor cell metabolism, angiogenesis, and treatment resistance in melanoma.

Dr. Weeraratna, of Johns Hopkins Bloomberg School of Public Health in Baltimore, first described a study showing how fibroblasts in the aged microenvironment contribute to tumor progression in models of melanoma (Nature. 2016 Apr 14;532[7598]:250-4).

Dr. Weeraratna and colleagues isolated dermal fibroblasts from young human donors (aged 25-35 years) and older donors (55-65 years) and used these cells to produce artificial skin.

Melanoma cells placed in the artificial skin created with young fibroblasts remained “very tightly nested at the surface,” Dr. Weeraratna said. On the other hand, melanoma cells migrated “very rapidly” through the artificial dermis created from aged fibroblasts.

In mouse models of melanoma, tumors grew much faster in young mice (6-8 weeks) than in old mice (12-18 months). However, tumors metastasized to the lung at a “much greater rate in the aged mice than in the young mice,” Dr. Weeraratna said.
 

Angiogenesis, SFRP2, and VEGF

Dr. Weeraratna went on to explain how a member of her lab conducted proteomic analyses of young and aged lung fibroblasts. The results were compared with results from prior analyses of young and aged skin fibroblasts.

The results showed that aged skin fibroblasts promote noncanonical WNT signaling via expression of SFRP2, SERPINE2, DKK1, Wnt5A, and ROR2. On the other hand, aged lung fibroblasts promote canonical WNT signaling via some of the same family members, including SFRP1, DKK3, and ROR1.

Research by another group showed that SFRP2 stimulates angiogenesis via a calcineurin/NFAT signaling pathway (Cancer Res. 2009 Jun 1;69[11]:4621-8).

Research in Dr. Weeraratna’s lab showed that SFRP2 and VEGF are inversely correlated with aging. Tumors in aged mice had an abundance of SFRP2 but little VEGF. Tumors in young mice had an abundance of VEGF but little SFRP2.

Dr. Weeraratna’s team wanted to determine if results would be similar in melanoma patients, so the researchers analyzed data from the TCGA database. They found that VEGF and two of its key receptors are decreased in older melanoma patients, in comparison with younger melanoma patients.

The clinical relevancy of this finding is reflected in an analysis of data from the AVAST-M study (Ann Oncol. 2019;30[12]:2013-4). When compared with observation, bevacizumab did not improve survival overall or for older patients, but the EGFR inhibitor was associated with longer survival in patients younger than 45 years.

Dr. Weeraratna said this finding and her group’s prior findings suggest younger melanoma patients have more VEGF but less angiogenesis than older patients. The older patients have less VEGF and more SFRP2, which drives angiogenesis.

Dr. Weeraratna’s lab then conducted experiments in young mice, which suggested that an anti-VEGF antibody can reduce angiogenesis, but not in the presence of SFRP2.

Lipid metabolism and treatment resistance

A recently published study by Dr. Weeraratna and colleagues tied changes in aged fibroblast lipid metabolism to treatment resistance in melanoma (Cancer Discov. 2020 Jun 4;CD-20-0329).

The research showed that melanoma cells accumulate lipids when incubated with aged, rather than young, fibroblasts in vitro.

Lipid uptake is mediated by fatty acid transporters (FATPs), and the researchers found that most FATPs were unchanged by age. However, FATP2 was elevated in melanoma cells exposed to aged media, aged mice, and melanoma patients older than 50 years of age.

When melanoma cells were incubated with conditioned media from aged fibroblasts and a FATP2 inhibitor, they no longer took up lipids.

When FATP2 was knocked down in aged mice with melanoma, BRAF and MEK inhibitors (which are not very effective ordinarily) caused dramatic and prolonged tumor regression. These effects were not seen with FATP2 inhibition in young mice.

These results suggest FATP2 is a key transporter of lipids in the aged microenvironment, and inhibiting FATP2 can delay the onset of treatment resistance.

Striving to understand a complex system

For many years, the dogma was that cancer cells behaved like unwelcome invaders, co-opting the metabolic machinery of the sites of spread, with crowding of the normal structures within those organs.

To say that concept was primitive is an understatement. Clearly, the relationship between tumor cells and the surrounding stroma is complex. Changes that occur in an aging microenvironment can influence cancer outcomes in older adults.

Dr. Weeraratna’s presentation adds further impetus to efforts to broaden eligibility criteria for clinical trials so the median age and the metabolic milieu of trial participants more closely parallels the general population.

She highlighted the importance of data analysis by age cohorts and the need to design preclinical studies so that investigators can study the microenvironment of cancer cells in in vitro models and in young and older laboratory animals.

As management expert W. Edwards Deming is believed to have said, “Every system is perfectly designed to get the results it gets.” Cancer is likely not an independent, hostile invader, overtaking the failing machinery of aging cells. To understand the intersection of cancer and aging, we need a more perfect understanding of the system in which tumors develop and are treated.

Dr. Weeraratna reported having no disclosures.


Dr. Lyss was a community-based medical oncologist and clinical researcher for more than 35 years before his recent retirement. His clinical and research interests were focused on breast and lung cancers as well as expanding clinical trial access to medically underserved populations. He is based in St. Louis. He has no conflicts of interest.
 

SOURCE: Weeraratna A. AACR 2020. Age against the machine: How the aging microenvironment governs response to therapy.

There was a trend toward a greater risk of breast cancer with higher degrees of breast density asymmetry among women undergoing image-guided breast biopsies in a study presented at the AACR virtual meeting II.

The 854 women in the study had been referred for biopsy after an abnormal mammogram.

Researchers used the mammograms to assess global bilateral asymmetry, which was the overall absolute difference in percent fibroglandular tissue volume (%FGV) between the ipsilateral (biopsied) breast and the contralateral (unaffected) breast.

The researchers also assessed local bilateral asymmetry, which was the perilesional %FGV difference in an area twice the size of, but excluding, the biopsy target, and the corresponding area in the unaffected breast.

The women were then divided into quartiles based on breast density asymmetry.

Most of the women had benign breast disease, including proliferative (43%) and nonproliferative (33%) disease, but 23% had carcinoma in situ or invasive breast cancer.

The trend for higher risk of in situ or invasive cancer with increasing breast density asymmetry was observed only in the local analysis. The odds ratio was 1.59 (95% confidence interval, 0.94-2.69) for women in the highest quartile of breast density asymmetry (absolute difference, > 8.23) versus those in the lowest quartile (absolute difference, ≤ –5.55; P = .067).

When compared with women who had proliferative benign disease, women with carcinoma in situ or invasive breast cancer “were more likely to be in the higher than lower quartiles,” said lead investigator Maeve Mullooly, PhD, a research fellow at the Royal College of Surgeons in Dublin.

There was no association between breast density asymmetry and traditional breast cancer risk factors such as age, body mass index, race, and hormone therapy. However, among women diagnosed with benign nonproliferative disease, women with a breast cancer family history were more likely to have higher overall breast density asymmetry.
 

Study rationale and details

Higher breast density is a known risk factor for breast cancer. Breast asymmetry also has been reported as a possible risk factor (Breast Cancer Res. 2006;8[2]:R14), and incorporation of breast density asymmetry into traditional risk factors in one study improved risk prediction (Breast Cancer Res. 2017 Mar 14;19[1]:29).

Building on that work, the goal of Dr. Mullooly’s study was to “learn how to better use breast density to inform breast cancer risk prediction,” she said.

To that end, her team turned to 854 women enrolled from 2007-2010 in the National Cancer Institute’s Breast Radiology Evaluation and Study of Tissues Project, a cross-sectional molecular epidemiologic study designed to understand how breast density measures are related to breast cancer etiology.

Most of the women were non-Hispanic white. The mean age was 51 years (range, 40-65), and the median body mass index was ²⁵ kg/m².

About three-quarters of the women (76%) had a breast density asymmetry of at least 2% on the global analysis, with 43% having higher %FGV in the biopsied breast and 33% having higher %FGV in the unaffected breast. In all, 89% of women had local breast density asymmetry, with higher density in the biopsied breast in 61% of women and higher density in the contralateral breast in 28%.
 

Next steps

This research is ongoing, and additional follow-up is planned, according to Dr. Mullooly. She said the researchers hope to apply more recent analytical techniques to the mammograms and to study the histologic differences in their breast biopsy specimens, among other steps, to see if stronger relationships with greater clinical utility emerge.

It was a “very well done study” with “very provocative data,” said presentation moderator Jennifer Wargo, MD, professor of genomic medicine and surgical oncology at the University of Texas MD Anderson Cancer Center in Houston.

She was interested in the planned next steps, particularly the histologic analysis of dense versus less dense breast tissue. There could be “differences in stroma or hormonal levels even at the microenvironmental level” that “represent a potential field defect, which later puts someone at risk,” she said, adding that it’s “great” that the work is continuing.

The National Cancer Institute funded the research. Dr. Mullooly reported no relevant disclosures. Dr. Wargo disclosed relationships with Bristol-Myers Squibb, Roche/Genentech, Novartis, GlaxoSmithKline, AstraZeneca, Imedex, Dava Oncology, Omniprex, Illumina, Gilead, PeerView, Physician Education Resource, MedImmune, Merck, Biothera Pharmaceuticals, and Microbiome DX.

aotto@mdedge.com

SOURCE: Mullooly M et al. AACR 2020, Abstract NG15.

There was a trend toward a greater risk of breast cancer with higher degrees of breast density asymmetry among women undergoing image-guided breast biopsies in a study presented at the AACR virtual meeting II.

The 854 women in the study had been referred for biopsy after an abnormal mammogram.

Researchers used the mammograms to assess global bilateral asymmetry, which was the overall absolute difference in percent fibroglandular tissue volume (%FGV) between the ipsilateral (biopsied) breast and the contralateral (unaffected) breast.

The researchers also assessed local bilateral asymmetry, which was the perilesional %FGV difference in an area twice the size of, but excluding, the biopsy target, and the corresponding area in the unaffected breast.

The women were then divided into quartiles based on breast density asymmetry.

Most of the women had benign breast disease, including proliferative (43%) and nonproliferative (33%) disease, but 23% had carcinoma in situ or invasive breast cancer.

The trend for higher risk of in situ or invasive cancer with increasing breast density asymmetry was observed only in the local analysis. The odds ratio was 1.59 (95% confidence interval, 0.94-2.69) for women in the highest quartile of breast density asymmetry (absolute difference, > 8.23) versus those in the lowest quartile (absolute difference, ≤ –5.55; P = .067).

When compared with women who had proliferative benign disease, women with carcinoma in situ or invasive breast cancer “were more likely to be in the higher than lower quartiles,” said lead investigator Maeve Mullooly, PhD, a research fellow at the Royal College of Surgeons in Dublin.

There was no association between breast density asymmetry and traditional breast cancer risk factors such as age, body mass index, race, and hormone therapy. However, among women diagnosed with benign nonproliferative disease, women with a breast cancer family history were more likely to have higher overall breast density asymmetry.
 

Study rationale and details

Higher breast density is a known risk factor for breast cancer. Breast asymmetry also has been reported as a possible risk factor (Breast Cancer Res. 2006;8[2]:R14), and incorporation of breast density asymmetry into traditional risk factors in one study improved risk prediction (Breast Cancer Res. 2017 Mar 14;19[1]:29).

Building on that work, the goal of Dr. Mullooly’s study was to “learn how to better use breast density to inform breast cancer risk prediction,” she said.

To that end, her team turned to 854 women enrolled from 2007-2010 in the National Cancer Institute’s Breast Radiology Evaluation and Study of Tissues Project, a cross-sectional molecular epidemiologic study designed to understand how breast density measures are related to breast cancer etiology.

Most of the women were non-Hispanic white. The mean age was 51 years (range, 40-65), and the median body mass index was ²⁵ kg/m².

About three-quarters of the women (76%) had a breast density asymmetry of at least 2% on the global analysis, with 43% having higher %FGV in the biopsied breast and 33% having higher %FGV in the unaffected breast. In all, 89% of women had local breast density asymmetry, with higher density in the biopsied breast in 61% of women and higher density in the contralateral breast in 28%.
 

Next steps

This research is ongoing, and additional follow-up is planned, according to Dr. Mullooly. She said the researchers hope to apply more recent analytical techniques to the mammograms and to study the histologic differences in their breast biopsy specimens, among other steps, to see if stronger relationships with greater clinical utility emerge.

It was a “very well done study” with “very provocative data,” said presentation moderator Jennifer Wargo, MD, professor of genomic medicine and surgical oncology at the University of Texas MD Anderson Cancer Center in Houston.

She was interested in the planned next steps, particularly the histologic analysis of dense versus less dense breast tissue. There could be “differences in stroma or hormonal levels even at the microenvironmental level” that “represent a potential field defect, which later puts someone at risk,” she said, adding that it’s “great” that the work is continuing.

The National Cancer Institute funded the research. Dr. Mullooly reported no relevant disclosures. Dr. Wargo disclosed relationships with Bristol-Myers Squibb, Roche/Genentech, Novartis, GlaxoSmithKline, AstraZeneca, Imedex, Dava Oncology, Omniprex, Illumina, Gilead, PeerView, Physician Education Resource, MedImmune, Merck, Biothera Pharmaceuticals, and Microbiome DX.

aotto@mdedge.com

SOURCE: Mullooly M et al. AACR 2020, Abstract NG15.

There was a trend toward a greater risk of breast cancer with higher degrees of breast density asymmetry among women undergoing image-guided breast biopsies in a study presented at the AACR virtual meeting II.

The 854 women in the study had been referred for biopsy after an abnormal mammogram.

Researchers used the mammograms to assess global bilateral asymmetry, which was the overall absolute difference in percent fibroglandular tissue volume (%FGV) between the ipsilateral (biopsied) breast and the contralateral (unaffected) breast.

The researchers also assessed local bilateral asymmetry, which was the perilesional %FGV difference in an area twice the size of, but excluding, the biopsy target, and the corresponding area in the unaffected breast.

The women were then divided into quartiles based on breast density asymmetry.

Most of the women had benign breast disease, including proliferative (43%) and nonproliferative (33%) disease, but 23% had carcinoma in situ or invasive breast cancer.

The trend for higher risk of in situ or invasive cancer with increasing breast density asymmetry was observed only in the local analysis. The odds ratio was 1.59 (95% confidence interval, 0.94-2.69) for women in the highest quartile of breast density asymmetry (absolute difference, > 8.23) versus those in the lowest quartile (absolute difference, ≤ –5.55; P = .067).

When compared with women who had proliferative benign disease, women with carcinoma in situ or invasive breast cancer “were more likely to be in the higher than lower quartiles,” said lead investigator Maeve Mullooly, PhD, a research fellow at the Royal College of Surgeons in Dublin.

There was no association between breast density asymmetry and traditional breast cancer risk factors such as age, body mass index, race, and hormone therapy. However, among women diagnosed with benign nonproliferative disease, women with a breast cancer family history were more likely to have higher overall breast density asymmetry.
 

Study rationale and details

Higher breast density is a known risk factor for breast cancer. Breast asymmetry also has been reported as a possible risk factor (Breast Cancer Res. 2006;8[2]:R14), and incorporation of breast density asymmetry into traditional risk factors in one study improved risk prediction (Breast Cancer Res. 2017 Mar 14;19[1]:29).

Building on that work, the goal of Dr. Mullooly’s study was to “learn how to better use breast density to inform breast cancer risk prediction,” she said.

To that end, her team turned to 854 women enrolled from 2007-2010 in the National Cancer Institute’s Breast Radiology Evaluation and Study of Tissues Project, a cross-sectional molecular epidemiologic study designed to understand how breast density measures are related to breast cancer etiology.

Most of the women were non-Hispanic white. The mean age was 51 years (range, 40-65), and the median body mass index was ²⁵ kg/m².

About three-quarters of the women (76%) had a breast density asymmetry of at least 2% on the global analysis, with 43% having higher %FGV in the biopsied breast and 33% having higher %FGV in the unaffected breast. In all, 89% of women had local breast density asymmetry, with higher density in the biopsied breast in 61% of women and higher density in the contralateral breast in 28%.
 

Next steps

This research is ongoing, and additional follow-up is planned, according to Dr. Mullooly. She said the researchers hope to apply more recent analytical techniques to the mammograms and to study the histologic differences in their breast biopsy specimens, among other steps, to see if stronger relationships with greater clinical utility emerge.

It was a “very well done study” with “very provocative data,” said presentation moderator Jennifer Wargo, MD, professor of genomic medicine and surgical oncology at the University of Texas MD Anderson Cancer Center in Houston.

She was interested in the planned next steps, particularly the histologic analysis of dense versus less dense breast tissue. There could be “differences in stroma or hormonal levels even at the microenvironmental level” that “represent a potential field defect, which later puts someone at risk,” she said, adding that it’s “great” that the work is continuing.

The National Cancer Institute funded the research. Dr. Mullooly reported no relevant disclosures. Dr. Wargo disclosed relationships with Bristol-Myers Squibb, Roche/Genentech, Novartis, GlaxoSmithKline, AstraZeneca, Imedex, Dava Oncology, Omniprex, Illumina, Gilead, PeerView, Physician Education Resource, MedImmune, Merck, Biothera Pharmaceuticals, and Microbiome DX.

aotto@mdedge.com

SOURCE: Mullooly M et al. AACR 2020, Abstract NG15.

Lipophilic statin use is associated with reduced mortality risk in women with ovarian cancer, findings from a large observational study suggest.

The study included 10,062 patients with epithelial ovarian cancer enrolled in the Finnish national cancer registry. There were 2,621 patients who were prescribed statins between 1995 and 2015, and 80% of them used lipophilic statins.

When compared with no statin use, any statin use was associated with a 40% reduction in ovarian cancer mortality (weighted hazard ratio, 0.60), and any use of lipophilic statins was associated with a 43% reduction in ovarian cancer mortality (wHR, 0.57).

Kala Visvanathan, MD, of Johns Hopkins University in Baltimore, and colleagues reported these findings in a poster at the AACR virtual meeting II.

Reductions in ovarian cancer mortality were observed in women who took simvastatin or atorvastatin (wHRs 0.24 and 0.20, respectively), the researchers found.

Lipophilic statin use also was associated with a reduction in ovarian cancer mortality across disease subtypes, although the magnitude of reduction varied. The hazard ratios were 0.60 for high-grade serous ovarian cancer, 0.50 for endometrioid ovarian cancer, 0.20 for clear cell ovarian cancer, 0.30 for mucinous ovarian cancer, and 0.27 for borderline disease.

Survival benefits were evident both in patients who started statins prior to their ovarian cancer diagnosis and in those who started statins after diagnosis.

Never-statin users had a median age of 62 years at baseline, and ever-statin users had a median age of 67 years. The median follow-up was 3.6 years and 5.5 years, respectively.

Data from the registry were linked to prescription claims, and a series of analyses were conducted to examine the association between pre- and postdiagnostic statin use and mortality. The findings were adjusted for age at diagnosis, stage, ovarian cancer subtype, treatments, year of diagnosis, and chronic disease medications. Adherence to statins was greater than 90%.
 

Implications and next steps

The idea of using statins for the treatment of ovarian cancer is appealing because of the promising survival data as well as the broad access, low cost, and tolerability of statins, Dr. Visvanathan said in a statement. About 28% of U.S. adults over age 40 routinely take statins for cholesterol control, and statins are widely used in other countries, she said.

“Our results support research to evaluate the repurposing of therapies that are well tolerated and inexpensive in order to help reduce the global cancer burden,” Dr. Visvanathan and colleagues wrote in their poster.

“Our results provide evidence in support of the evaluation of lipophilic statins, particularly atorvastatin and/or simvastatin, for the treatment of [epithelial ovarian cancer] in conjunction with existing therapies,” the researchers wrote. They added that these statins should be “evaluated in randomized clinical trials that include correlative endpoints.”

Further, the researchers argued that “the results are biologically plausible based on known mechanisms associated with statin use and highlight the fact that statins may be effective to treat more than one disease/outcome (i.e., high cholesterol, EOC [epithelial ovarian cancer], breast cancer).”

The results of this study are intriguing, according to James Yarmolinsky, MSc, of the University of Bristol, England. Mr. Yarmolinsky is the lead author of a case-control study that showed an association between genetically proxied 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibition and lower odds of developing epithelial ovarian cancer (JAMA. 2020;323[7]:646-655).

Mr. Yarmolinsky and colleagues found that HMG-CoA reductase inhibition equivalent to a 38.7-mg/dL reduction in low-density lipoprotein cholesterol was significantly associated with lower odds of epithelial ovarian cancer in the general population (odds ratio, 0.60) and among BRCA1/2 mutation carriers (hazard ratio, 0.69). The findings raised questions about whether a similar association would be seen with medications such as statins that inhibit HMG-CoA reductase.

“These findings linking statin use to lower ovarian cancer mortality are really interesting given our own research suggesting that these drugs may also lower women’s risk of developing this disease in the first place,” Mr. Yarmolinsky said.

“The survival rate for ovarian cancer remains the lowest among all gynecological cancers in the United States, so use of these medications in either a preventive or therapeutic context could offer an important approach for reducing disease burden,” he added. “If the findings reported by Visvanathan and colleagues can be shown to replicate in other large population-based studies, testing the efficacy of statins in a randomized clinical trial could provide definitive evidence of whether these medications lower ovarian cancer mortality.”

The Department of Defense and the Breast Cancer Research Foundation funded the current study. Dr. Visvanathan and Mr. Yarmolinsky reported no disclosures.

sworcester@mdedge.com

SOURCE: Visvanathan K et al. AACR 2020, Abstract 5782.

Lipophilic statin use is associated with reduced mortality risk in women with ovarian cancer, findings from a large observational study suggest.

The study included 10,062 patients with epithelial ovarian cancer enrolled in the Finnish national cancer registry. There were 2,621 patients who were prescribed statins between 1995 and 2015, and 80% of them used lipophilic statins.

When compared with no statin use, any statin use was associated with a 40% reduction in ovarian cancer mortality (weighted hazard ratio, 0.60), and any use of lipophilic statins was associated with a 43% reduction in ovarian cancer mortality (wHR, 0.57).

Kala Visvanathan, MD, of Johns Hopkins University in Baltimore, and colleagues reported these findings in a poster at the AACR virtual meeting II.

Reductions in ovarian cancer mortality were observed in women who took simvastatin or atorvastatin (wHRs 0.24 and 0.20, respectively), the researchers found.

Lipophilic statin use also was associated with a reduction in ovarian cancer mortality across disease subtypes, although the magnitude of reduction varied. The hazard ratios were 0.60 for high-grade serous ovarian cancer, 0.50 for endometrioid ovarian cancer, 0.20 for clear cell ovarian cancer, 0.30 for mucinous ovarian cancer, and 0.27 for borderline disease.

Survival benefits were evident both in patients who started statins prior to their ovarian cancer diagnosis and in those who started statins after diagnosis.

Never-statin users had a median age of 62 years at baseline, and ever-statin users had a median age of 67 years. The median follow-up was 3.6 years and 5.5 years, respectively.

Data from the registry were linked to prescription claims, and a series of analyses were conducted to examine the association between pre- and postdiagnostic statin use and mortality. The findings were adjusted for age at diagnosis, stage, ovarian cancer subtype, treatments, year of diagnosis, and chronic disease medications. Adherence to statins was greater than 90%.
 

Implications and next steps

The idea of using statins for the treatment of ovarian cancer is appealing because of the promising survival data as well as the broad access, low cost, and tolerability of statins, Dr. Visvanathan said in a statement. About 28% of U.S. adults over age 40 routinely take statins for cholesterol control, and statins are widely used in other countries, she said.

“Our results support research to evaluate the repurposing of therapies that are well tolerated and inexpensive in order to help reduce the global cancer burden,” Dr. Visvanathan and colleagues wrote in their poster.

“Our results provide evidence in support of the evaluation of lipophilic statins, particularly atorvastatin and/or simvastatin, for the treatment of [epithelial ovarian cancer] in conjunction with existing therapies,” the researchers wrote. They added that these statins should be “evaluated in randomized clinical trials that include correlative endpoints.”

Further, the researchers argued that “the results are biologically plausible based on known mechanisms associated with statin use and highlight the fact that statins may be effective to treat more than one disease/outcome (i.e., high cholesterol, EOC [epithelial ovarian cancer], breast cancer).”

The results of this study are intriguing, according to James Yarmolinsky, MSc, of the University of Bristol, England. Mr. Yarmolinsky is the lead author of a case-control study that showed an association between genetically proxied 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibition and lower odds of developing epithelial ovarian cancer (JAMA. 2020;323[7]:646-655).

Mr. Yarmolinsky and colleagues found that HMG-CoA reductase inhibition equivalent to a 38.7-mg/dL reduction in low-density lipoprotein cholesterol was significantly associated with lower odds of epithelial ovarian cancer in the general population (odds ratio, 0.60) and among BRCA1/2 mutation carriers (hazard ratio, 0.69). The findings raised questions about whether a similar association would be seen with medications such as statins that inhibit HMG-CoA reductase.

“These findings linking statin use to lower ovarian cancer mortality are really interesting given our own research suggesting that these drugs may also lower women’s risk of developing this disease in the first place,” Mr. Yarmolinsky said.

“The survival rate for ovarian cancer remains the lowest among all gynecological cancers in the United States, so use of these medications in either a preventive or therapeutic context could offer an important approach for reducing disease burden,” he added. “If the findings reported by Visvanathan and colleagues can be shown to replicate in other large population-based studies, testing the efficacy of statins in a randomized clinical trial could provide definitive evidence of whether these medications lower ovarian cancer mortality.”

The Department of Defense and the Breast Cancer Research Foundation funded the current study. Dr. Visvanathan and Mr. Yarmolinsky reported no disclosures.

sworcester@mdedge.com

SOURCE: Visvanathan K et al. AACR 2020, Abstract 5782.

Lipophilic statin use is associated with reduced mortality risk in women with ovarian cancer, findings from a large observational study suggest.

The study included 10,062 patients with epithelial ovarian cancer enrolled in the Finnish national cancer registry. There were 2,621 patients who were prescribed statins between 1995 and 2015, and 80% of them used lipophilic statins.

When compared with no statin use, any statin use was associated with a 40% reduction in ovarian cancer mortality (weighted hazard ratio, 0.60), and any use of lipophilic statins was associated with a 43% reduction in ovarian cancer mortality (wHR, 0.57).

Kala Visvanathan, MD, of Johns Hopkins University in Baltimore, and colleagues reported these findings in a poster at the AACR virtual meeting II.

Reductions in ovarian cancer mortality were observed in women who took simvastatin or atorvastatin (wHRs 0.24 and 0.20, respectively), the researchers found.

Lipophilic statin use also was associated with a reduction in ovarian cancer mortality across disease subtypes, although the magnitude of reduction varied. The hazard ratios were 0.60 for high-grade serous ovarian cancer, 0.50 for endometrioid ovarian cancer, 0.20 for clear cell ovarian cancer, 0.30 for mucinous ovarian cancer, and 0.27 for borderline disease.

Survival benefits were evident both in patients who started statins prior to their ovarian cancer diagnosis and in those who started statins after diagnosis.

Never-statin users had a median age of 62 years at baseline, and ever-statin users had a median age of 67 years. The median follow-up was 3.6 years and 5.5 years, respectively.

Data from the registry were linked to prescription claims, and a series of analyses were conducted to examine the association between pre- and postdiagnostic statin use and mortality. The findings were adjusted for age at diagnosis, stage, ovarian cancer subtype, treatments, year of diagnosis, and chronic disease medications. Adherence to statins was greater than 90%.
 

Implications and next steps

The idea of using statins for the treatment of ovarian cancer is appealing because of the promising survival data as well as the broad access, low cost, and tolerability of statins, Dr. Visvanathan said in a statement. About 28% of U.S. adults over age 40 routinely take statins for cholesterol control, and statins are widely used in other countries, she said.

“Our results support research to evaluate the repurposing of therapies that are well tolerated and inexpensive in order to help reduce the global cancer burden,” Dr. Visvanathan and colleagues wrote in their poster.

“Our results provide evidence in support of the evaluation of lipophilic statins, particularly atorvastatin and/or simvastatin, for the treatment of [epithelial ovarian cancer] in conjunction with existing therapies,” the researchers wrote. They added that these statins should be “evaluated in randomized clinical trials that include correlative endpoints.”

Further, the researchers argued that “the results are biologically plausible based on known mechanisms associated with statin use and highlight the fact that statins may be effective to treat more than one disease/outcome (i.e., high cholesterol, EOC [epithelial ovarian cancer], breast cancer).”

The results of this study are intriguing, according to James Yarmolinsky, MSc, of the University of Bristol, England. Mr. Yarmolinsky is the lead author of a case-control study that showed an association between genetically proxied 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibition and lower odds of developing epithelial ovarian cancer (JAMA. 2020;323[7]:646-655).

Mr. Yarmolinsky and colleagues found that HMG-CoA reductase inhibition equivalent to a 38.7-mg/dL reduction in low-density lipoprotein cholesterol was significantly associated with lower odds of epithelial ovarian cancer in the general population (odds ratio, 0.60) and among BRCA1/2 mutation carriers (hazard ratio, 0.69). The findings raised questions about whether a similar association would be seen with medications such as statins that inhibit HMG-CoA reductase.

“These findings linking statin use to lower ovarian cancer mortality are really interesting given our own research suggesting that these drugs may also lower women’s risk of developing this disease in the first place,” Mr. Yarmolinsky said.

“The survival rate for ovarian cancer remains the lowest among all gynecological cancers in the United States, so use of these medications in either a preventive or therapeutic context could offer an important approach for reducing disease burden,” he added. “If the findings reported by Visvanathan and colleagues can be shown to replicate in other large population-based studies, testing the efficacy of statins in a randomized clinical trial could provide definitive evidence of whether these medications lower ovarian cancer mortality.”

The Department of Defense and the Breast Cancer Research Foundation funded the current study. Dr. Visvanathan and Mr. Yarmolinsky reported no disclosures.

sworcester@mdedge.com

SOURCE: Visvanathan K et al. AACR 2020, Abstract 5782.

Immunotherapy after resection of the primary tumor improved survival in some patients with stage III melanoma in an analysis presented at the AACR virtual meeting II.

Among patients with stage IIIC disease, the 2-year survival rate was 70% in those who received immunotherapy and 59% in those who did not (P < .01). The median overall survival in this group was 32.8 months with immunotherapy and 28 months without it (P < .01).

Among patients with stage IIIA disease, the 2-year survival rate was 94% with immunotherapy and 91% without it (P = .03).

There was a trend toward a 2-year survival benefit with immunotherapy in patients with stage IIIB disease and in all 4,094 stage III patients, but the differences were not significant. The 2-year survival rate was 84% with immunotherapy and 81% without it among patients with stage IIIB disease (P = .35). The survival rates were 83% and 80%, respectively, in all stage III patients (P = .051).

This was an early analysis, noted investigator Justin Moyers, MD, of Loma Linda (Calif.) University. Ipilimumab was approved as adjuvant therapy for stage III melanoma patients in 2015, the year patients from this analysis were diagnosed.

“There’s really only 2 full years of survival data,” Dr. Moyers said. “I think given time, we will see a benefit amongst all the substages.”

In the meantime, “I would definitely not use this data to say whether or not [immunotherapy] should be given,” Dr. Moyers said.

The researchers were just using the database – which captures 52% of U.S. melanoma cases – to see if “real-world data mimics the clinical trial data,” Dr. Moyers said.

Overall, the findings support “adjuvant immunotherapy in the real-world setting,” he said.

The researchers also looked at treatment patterns in 2015-2016 across 8,160 patients with stage III melanoma, 4,094 of whom were included in the aforementioned survival analysis. There were 2,260 patients (27.7%) who received immunotherapy after surgery during that time period.

Uptake of adjuvant immunotherapy “was low to start, but those patients did better than ones who did not get” it, said AACR president Antoni Ribas, MD, PhD, of the University of California, Los Angeles, who was not involved in the study.

Immunotherapy recipients were younger, on average (54.8 years vs. 62.4 years). Patients with Charlson comorbidity scores above zero and those on Medicare were less likely to receive immunotherapy (18.4% Medicare vs. over 30% with other payers). There also were trends of decreased use with lower income and lower high school graduation rates.

The finding “highlights the negative impact of socioeconomic [factors] on access to proven therapy,” Dr. Ribas said.

As for low use among Medicare patients, uptake of new treatments, in general, “seems to be faster with private insurance,” he noted.

The study excluded patients who received systemic therapies other than immunotherapy, as well as those who received immunotherapy before surgery. Among study limitations, the specific immunotherapies patients received was unknown.

There was no external funding for this study. Dr. Moyers reported travel compensation from Astellas Pharmaceuticals in 2018. Dr. Ribas disclosed relationships with Amgen, Chugai, Merck, Sanofi, Tango, Arcus, Bioncotech, Compugen, CytomX, FLX Bio, ImaginAb, Isoplexis, Merus, Rgenix, and PACT.

aotto@mdedge.com

SOURCE: Moyers J et al. AACR 2020, Abstract 4338.

Immunotherapy after resection of the primary tumor improved survival in some patients with stage III melanoma in an analysis presented at the AACR virtual meeting II.

Among patients with stage IIIC disease, the 2-year survival rate was 70% in those who received immunotherapy and 59% in those who did not (P < .01). The median overall survival in this group was 32.8 months with immunotherapy and 28 months without it (P < .01).

Among patients with stage IIIA disease, the 2-year survival rate was 94% with immunotherapy and 91% without it (P = .03).

There was a trend toward a 2-year survival benefit with immunotherapy in patients with stage IIIB disease and in all 4,094 stage III patients, but the differences were not significant. The 2-year survival rate was 84% with immunotherapy and 81% without it among patients with stage IIIB disease (P = .35). The survival rates were 83% and 80%, respectively, in all stage III patients (P = .051).

This was an early analysis, noted investigator Justin Moyers, MD, of Loma Linda (Calif.) University. Ipilimumab was approved as adjuvant therapy for stage III melanoma patients in 2015, the year patients from this analysis were diagnosed.

“There’s really only 2 full years of survival data,” Dr. Moyers said. “I think given time, we will see a benefit amongst all the substages.”

In the meantime, “I would definitely not use this data to say whether or not [immunotherapy] should be given,” Dr. Moyers said.

The researchers were just using the database – which captures 52% of U.S. melanoma cases – to see if “real-world data mimics the clinical trial data,” Dr. Moyers said.

Overall, the findings support “adjuvant immunotherapy in the real-world setting,” he said.

The researchers also looked at treatment patterns in 2015-2016 across 8,160 patients with stage III melanoma, 4,094 of whom were included in the aforementioned survival analysis. There were 2,260 patients (27.7%) who received immunotherapy after surgery during that time period.

Uptake of adjuvant immunotherapy “was low to start, but those patients did better than ones who did not get” it, said AACR president Antoni Ribas, MD, PhD, of the University of California, Los Angeles, who was not involved in the study.

Immunotherapy recipients were younger, on average (54.8 years vs. 62.4 years). Patients with Charlson comorbidity scores above zero and those on Medicare were less likely to receive immunotherapy (18.4% Medicare vs. over 30% with other payers). There also were trends of decreased use with lower income and lower high school graduation rates.

The finding “highlights the negative impact of socioeconomic [factors] on access to proven therapy,” Dr. Ribas said.

As for low use among Medicare patients, uptake of new treatments, in general, “seems to be faster with private insurance,” he noted.

The study excluded patients who received systemic therapies other than immunotherapy, as well as those who received immunotherapy before surgery. Among study limitations, the specific immunotherapies patients received was unknown.

There was no external funding for this study. Dr. Moyers reported travel compensation from Astellas Pharmaceuticals in 2018. Dr. Ribas disclosed relationships with Amgen, Chugai, Merck, Sanofi, Tango, Arcus, Bioncotech, Compugen, CytomX, FLX Bio, ImaginAb, Isoplexis, Merus, Rgenix, and PACT.

aotto@mdedge.com

SOURCE: Moyers J et al. AACR 2020, Abstract 4338.

Immunotherapy after resection of the primary tumor improved survival in some patients with stage III melanoma in an analysis presented at the AACR virtual meeting II.

Among patients with stage IIIC disease, the 2-year survival rate was 70% in those who received immunotherapy and 59% in those who did not (P < .01). The median overall survival in this group was 32.8 months with immunotherapy and 28 months without it (P < .01).

Among patients with stage IIIA disease, the 2-year survival rate was 94% with immunotherapy and 91% without it (P = .03).

There was a trend toward a 2-year survival benefit with immunotherapy in patients with stage IIIB disease and in all 4,094 stage III patients, but the differences were not significant. The 2-year survival rate was 84% with immunotherapy and 81% without it among patients with stage IIIB disease (P = .35). The survival rates were 83% and 80%, respectively, in all stage III patients (P = .051).

This was an early analysis, noted investigator Justin Moyers, MD, of Loma Linda (Calif.) University. Ipilimumab was approved as adjuvant therapy for stage III melanoma patients in 2015, the year patients from this analysis were diagnosed.

“There’s really only 2 full years of survival data,” Dr. Moyers said. “I think given time, we will see a benefit amongst all the substages.”

In the meantime, “I would definitely not use this data to say whether or not [immunotherapy] should be given,” Dr. Moyers said.

The researchers were just using the database – which captures 52% of U.S. melanoma cases – to see if “real-world data mimics the clinical trial data,” Dr. Moyers said.

Overall, the findings support “adjuvant immunotherapy in the real-world setting,” he said.

The researchers also looked at treatment patterns in 2015-2016 across 8,160 patients with stage III melanoma, 4,094 of whom were included in the aforementioned survival analysis. There were 2,260 patients (27.7%) who received immunotherapy after surgery during that time period.

Uptake of adjuvant immunotherapy “was low to start, but those patients did better than ones who did not get” it, said AACR president Antoni Ribas, MD, PhD, of the University of California, Los Angeles, who was not involved in the study.

Immunotherapy recipients were younger, on average (54.8 years vs. 62.4 years). Patients with Charlson comorbidity scores above zero and those on Medicare were less likely to receive immunotherapy (18.4% Medicare vs. over 30% with other payers). There also were trends of decreased use with lower income and lower high school graduation rates.

The finding “highlights the negative impact of socioeconomic [factors] on access to proven therapy,” Dr. Ribas said.

As for low use among Medicare patients, uptake of new treatments, in general, “seems to be faster with private insurance,” he noted.

The study excluded patients who received systemic therapies other than immunotherapy, as well as those who received immunotherapy before surgery. Among study limitations, the specific immunotherapies patients received was unknown.

There was no external funding for this study. Dr. Moyers reported travel compensation from Astellas Pharmaceuticals in 2018. Dr. Ribas disclosed relationships with Amgen, Chugai, Merck, Sanofi, Tango, Arcus, Bioncotech, Compugen, CytomX, FLX Bio, ImaginAb, Isoplexis, Merus, Rgenix, and PACT.

aotto@mdedge.com

SOURCE: Moyers J et al. AACR 2020, Abstract 4338.

Targeting TIGIT, an inhibitory receptor expressed on immune cells, could complement activity of anti–programmed death–ligand 1/PD-1 antibodies in patients with solid tumors, results of a phase 1 study suggest.

The combination of the anti-TIGIT antibody tiragolumab with the PD-L1 inhibitor atezolizumab was well tolerated and showed preliminary activity in the phase 1b portion of the study, according to investigator Johanna C. Bendell, MD, of Sarah Cannon Research Institute/Tennessee Oncology in Nashville, Tenn.

Objective responses occurred mainly in chemoimmunotherapy-naive, PD-L1-positive tumors. In an expansion cohort of 13 patients with PD-L1-positive non–small cell lung cancer (NSCLC), the confirmed overall response rate was 46%, with several responses demonstrating durability.

Dr. Bendell reported these results at the AACR virtual meeting II.

While several important research questions remain, the results in the lung cancer expansion cohort were encouraging, particularly in patients who were smokers and previous smokers, said invited discussant Michele Teng, PhD, of QIMR Berghofer Medical Research Institute in Brisbane, Australia.

“Although it was [a] small cohort, the data suggest promising duration of response in some of the patients [n = 4] who have been under study for more than 700 days,” Dr. Teng said.

Based on the preliminary safety and activity seen in this study, the combination of tiragolumab and atezolizumab is being evaluated in a randomized, placebo-controlled phase 2 study, and a phase 3 study is recruiting.
 

Rationale, design, and safety

TIGIT is a novel inhibitory receptor expressed on multiple immune cells, especially CD8-positive T cells and natural killer cells, Dr. Bendell explained. She added that TIGIT is coexpressed with PD-1 on immune cells.

“Using anti-TIGIT antibodies to prevent TIGIT from binding, and cotargeting TIGIT and PD-L1, may restore antitumor response and enhance anti-PD-L1 effect,” Dr. Bendell said.

The phase 1 study Dr. Bendell presented, known as GO30103, was designed to evaluate tiragolumab as a single agent and in combination with atezolizumab in advanced solid tumors.

There were 24 patients in the phase 1a portion of GO30103, which was intended to determine the preliminary safety, tolerability, and recommended phase 2 dose of tiragolumab. There were 49 patients treated with tiragolumab plus atezolizumab in the phase 1b portion, which was intended to provide data on pharmacokinetics as well as preliminary antitumor activity of the combination.

No dose-limiting toxicities were seen in either cohort. The recommended phase 2 dose of tiragolumab was 600 mg every 3 weeks.

Tiragolumab was well tolerated in the phase 1a and 1b portions of the trial, according to Dr. Bendell.

“Immune-related adverse events were seen, but their incidence was not out of proportion to events seen with atezolizumab alone,” she said.

Treatment-related grade 3-4 adverse events occurred in one patient (4%) in the phase 1a portion of the trial and two patients (4%) in the phase 1b portion. There were no grade 5 adverse events related to treatment.

Efficacy and next steps

No objective responses were seen with tiragolumab monotherapy, although several patients did exhibit tumor reduction.

“We were not really expecting much single-agent activity of the anti-TIGIT drug,” Dr. Bendell said. “There’s some preclinical data that suggests that TIGIT may be more important as a single agent in earlier stages of cancer.”

In contrast, the combination of tiragolumab and atezolizumab resulted in several responses, including one in a patient with PD-L1-positive NSCLC who was previously treated with immunotherapy, according to Dr. Bendell.

The 13-patient expansion cohort of patients with PD-L1-positive NSCLC were treated at the recommended phase 2 dose of tiragolumab and atezolizumab. In these chemoimmunotherapy-naive patients, the overall response rate was 46%. Responses occurred in 6 of 13 patients and included 2 complete responses. Four patients had stable disease, so the disease control rate was 85% (11/13).

Based on that expansion cohort, a randomized, phase 2 study called CITYSCAPE was initiated. Results of CITYSCAPE were recently presented as part of the American Society of Clinical Oncology virtual scientific program.

In that study, tiragolumab plus atezolizumab improved the overall response rate and progression-free survival when compared with placebo plus atezolizumab. More substantial improvement was seen in the subgroup of patients with PD-L1 tumor proportion scores of 50% or greater.

The activity and safety of tiragolumab plus atezolizumab will be confirmed in the ongoing SKYSCRAPER-01 trial (NCT04294810), a phase 3 study of first-line treatment in patients with NSCLC and a PD-L1 tumor proportion score of 50% or greater, according to investigators.

The phase 1 study presented by Dr. Bendell was sponsored by Genentech. Dr. Bendell disclosed relationships with Genentech/Roche, Gilead, Five Prime, Lilly, and other companies.
 

SOURCE: Bendell JC et al. AACR 2020, Abstract CT302.

Targeting TIGIT, an inhibitory receptor expressed on immune cells, could complement activity of anti–programmed death–ligand 1/PD-1 antibodies in patients with solid tumors, results of a phase 1 study suggest.

The combination of the anti-TIGIT antibody tiragolumab with the PD-L1 inhibitor atezolizumab was well tolerated and showed preliminary activity in the phase 1b portion of the study, according to investigator Johanna C. Bendell, MD, of Sarah Cannon Research Institute/Tennessee Oncology in Nashville, Tenn.

Objective responses occurred mainly in chemoimmunotherapy-naive, PD-L1-positive tumors. In an expansion cohort of 13 patients with PD-L1-positive non–small cell lung cancer (NSCLC), the confirmed overall response rate was 46%, with several responses demonstrating durability.

Dr. Bendell reported these results at the AACR virtual meeting II.

While several important research questions remain, the results in the lung cancer expansion cohort were encouraging, particularly in patients who were smokers and previous smokers, said invited discussant Michele Teng, PhD, of QIMR Berghofer Medical Research Institute in Brisbane, Australia.

“Although it was [a] small cohort, the data suggest promising duration of response in some of the patients [n = 4] who have been under study for more than 700 days,” Dr. Teng said.

Based on the preliminary safety and activity seen in this study, the combination of tiragolumab and atezolizumab is being evaluated in a randomized, placebo-controlled phase 2 study, and a phase 3 study is recruiting.
 

Rationale, design, and safety

TIGIT is a novel inhibitory receptor expressed on multiple immune cells, especially CD8-positive T cells and natural killer cells, Dr. Bendell explained. She added that TIGIT is coexpressed with PD-1 on immune cells.

“Using anti-TIGIT antibodies to prevent TIGIT from binding, and cotargeting TIGIT and PD-L1, may restore antitumor response and enhance anti-PD-L1 effect,” Dr. Bendell said.

The phase 1 study Dr. Bendell presented, known as GO30103, was designed to evaluate tiragolumab as a single agent and in combination with atezolizumab in advanced solid tumors.

There were 24 patients in the phase 1a portion of GO30103, which was intended to determine the preliminary safety, tolerability, and recommended phase 2 dose of tiragolumab. There were 49 patients treated with tiragolumab plus atezolizumab in the phase 1b portion, which was intended to provide data on pharmacokinetics as well as preliminary antitumor activity of the combination.

No dose-limiting toxicities were seen in either cohort. The recommended phase 2 dose of tiragolumab was 600 mg every 3 weeks.

Tiragolumab was well tolerated in the phase 1a and 1b portions of the trial, according to Dr. Bendell.

“Immune-related adverse events were seen, but their incidence was not out of proportion to events seen with atezolizumab alone,” she said.

Treatment-related grade 3-4 adverse events occurred in one patient (4%) in the phase 1a portion of the trial and two patients (4%) in the phase 1b portion. There were no grade 5 adverse events related to treatment.

Efficacy and next steps

No objective responses were seen with tiragolumab monotherapy, although several patients did exhibit tumor reduction.

“We were not really expecting much single-agent activity of the anti-TIGIT drug,” Dr. Bendell said. “There’s some preclinical data that suggests that TIGIT may be more important as a single agent in earlier stages of cancer.”

In contrast, the combination of tiragolumab and atezolizumab resulted in several responses, including one in a patient with PD-L1-positive NSCLC who was previously treated with immunotherapy, according to Dr. Bendell.

The 13-patient expansion cohort of patients with PD-L1-positive NSCLC were treated at the recommended phase 2 dose of tiragolumab and atezolizumab. In these chemoimmunotherapy-naive patients, the overall response rate was 46%. Responses occurred in 6 of 13 patients and included 2 complete responses. Four patients had stable disease, so the disease control rate was 85% (11/13).

Based on that expansion cohort, a randomized, phase 2 study called CITYSCAPE was initiated. Results of CITYSCAPE were recently presented as part of the American Society of Clinical Oncology virtual scientific program.

In that study, tiragolumab plus atezolizumab improved the overall response rate and progression-free survival when compared with placebo plus atezolizumab. More substantial improvement was seen in the subgroup of patients with PD-L1 tumor proportion scores of 50% or greater.

The activity and safety of tiragolumab plus atezolizumab will be confirmed in the ongoing SKYSCRAPER-01 trial (NCT04294810), a phase 3 study of first-line treatment in patients with NSCLC and a PD-L1 tumor proportion score of 50% or greater, according to investigators.

The phase 1 study presented by Dr. Bendell was sponsored by Genentech. Dr. Bendell disclosed relationships with Genentech/Roche, Gilead, Five Prime, Lilly, and other companies.
 

SOURCE: Bendell JC et al. AACR 2020, Abstract CT302.

Targeting TIGIT, an inhibitory receptor expressed on immune cells, could complement activity of anti–programmed death–ligand 1/PD-1 antibodies in patients with solid tumors, results of a phase 1 study suggest.

The combination of the anti-TIGIT antibody tiragolumab with the PD-L1 inhibitor atezolizumab was well tolerated and showed preliminary activity in the phase 1b portion of the study, according to investigator Johanna C. Bendell, MD, of Sarah Cannon Research Institute/Tennessee Oncology in Nashville, Tenn.

Objective responses occurred mainly in chemoimmunotherapy-naive, PD-L1-positive tumors. In an expansion cohort of 13 patients with PD-L1-positive non–small cell lung cancer (NSCLC), the confirmed overall response rate was 46%, with several responses demonstrating durability.

Dr. Bendell reported these results at the AACR virtual meeting II.

While several important research questions remain, the results in the lung cancer expansion cohort were encouraging, particularly in patients who were smokers and previous smokers, said invited discussant Michele Teng, PhD, of QIMR Berghofer Medical Research Institute in Brisbane, Australia.

“Although it was [a] small cohort, the data suggest promising duration of response in some of the patients [n = 4] who have been under study for more than 700 days,” Dr. Teng said.

Based on the preliminary safety and activity seen in this study, the combination of tiragolumab and atezolizumab is being evaluated in a randomized, placebo-controlled phase 2 study, and a phase 3 study is recruiting.
 

Rationale, design, and safety

TIGIT is a novel inhibitory receptor expressed on multiple immune cells, especially CD8-positive T cells and natural killer cells, Dr. Bendell explained. She added that TIGIT is coexpressed with PD-1 on immune cells.

“Using anti-TIGIT antibodies to prevent TIGIT from binding, and cotargeting TIGIT and PD-L1, may restore antitumor response and enhance anti-PD-L1 effect,” Dr. Bendell said.

The phase 1 study Dr. Bendell presented, known as GO30103, was designed to evaluate tiragolumab as a single agent and in combination with atezolizumab in advanced solid tumors.

There were 24 patients in the phase 1a portion of GO30103, which was intended to determine the preliminary safety, tolerability, and recommended phase 2 dose of tiragolumab. There were 49 patients treated with tiragolumab plus atezolizumab in the phase 1b portion, which was intended to provide data on pharmacokinetics as well as preliminary antitumor activity of the combination.

No dose-limiting toxicities were seen in either cohort. The recommended phase 2 dose of tiragolumab was 600 mg every 3 weeks.

Tiragolumab was well tolerated in the phase 1a and 1b portions of the trial, according to Dr. Bendell.

“Immune-related adverse events were seen, but their incidence was not out of proportion to events seen with atezolizumab alone,” she said.

Treatment-related grade 3-4 adverse events occurred in one patient (4%) in the phase 1a portion of the trial and two patients (4%) in the phase 1b portion. There were no grade 5 adverse events related to treatment.

Efficacy and next steps

No objective responses were seen with tiragolumab monotherapy, although several patients did exhibit tumor reduction.

“We were not really expecting much single-agent activity of the anti-TIGIT drug,” Dr. Bendell said. “There’s some preclinical data that suggests that TIGIT may be more important as a single agent in earlier stages of cancer.”

In contrast, the combination of tiragolumab and atezolizumab resulted in several responses, including one in a patient with PD-L1-positive NSCLC who was previously treated with immunotherapy, according to Dr. Bendell.

The 13-patient expansion cohort of patients with PD-L1-positive NSCLC were treated at the recommended phase 2 dose of tiragolumab and atezolizumab. In these chemoimmunotherapy-naive patients, the overall response rate was 46%. Responses occurred in 6 of 13 patients and included 2 complete responses. Four patients had stable disease, so the disease control rate was 85% (11/13).

Based on that expansion cohort, a randomized, phase 2 study called CITYSCAPE was initiated. Results of CITYSCAPE were recently presented as part of the American Society of Clinical Oncology virtual scientific program.

In that study, tiragolumab plus atezolizumab improved the overall response rate and progression-free survival when compared with placebo plus atezolizumab. More substantial improvement was seen in the subgroup of patients with PD-L1 tumor proportion scores of 50% or greater.

The activity and safety of tiragolumab plus atezolizumab will be confirmed in the ongoing SKYSCRAPER-01 trial (NCT04294810), a phase 3 study of first-line treatment in patients with NSCLC and a PD-L1 tumor proportion score of 50% or greater, according to investigators.

The phase 1 study presented by Dr. Bendell was sponsored by Genentech. Dr. Bendell disclosed relationships with Genentech/Roche, Gilead, Five Prime, Lilly, and other companies.
 

SOURCE: Bendell JC et al. AACR 2020, Abstract CT302.

Use of statins or other lipid-lowering drugs was associated with a lower risk of dying from colorectal cancer in a large study, investigators reported.

Use of lipid-lowering medication was linked to a 56% lower risk of colorectal cancer death among individuals with no cancer at baseline who were enrolled in the Atherosclerosis Risk in Communities (ARIC) study. The reduction in mortality risk was evident regardless of sex, race, age, or how long patients had been on lipid-lowering drugs.

Michael T. Marrone, PhD, of Johns Hopkins University, Baltimore, and colleagues detailed these findings in a poster presented at the AACR virtual meeting II.

“Definitely for those individuals at average risk for colorectal cancer, if their primary care doctor recommends a lipid-lowering medication for cardiovascular disease prevention, they should follow their doctor’s advice,” Dr. Marrone said in an interview.

“We really can’t say that they should take this specifically for colon cancer prevention, but they should just follow the recommendation for cardiovascular disease prevention,” he added.

While previous studies have linked lipid-lowering drugs, and statins in particular, to a modestly reduced risk of developing colorectal cancer, the impact on risk by factors such as sex, race, and duration of use have not been well characterized, according to Dr. Marrone.

Another motivation for this study was to determine, in participants free of cancer at baseline, the risk of actually dying from this cancer. “That endpoint has not been well studied in the literature at all,” Dr. Marrone said.

To address those gaps, Dr. Marrone and colleagues analyzed data on 14,428 patients from the ARIC study who were cancer free at study visits between 1990 and 1992. Follow-up continued through the end of 2015 or until death, whichever came first.

A total of 384 incident colorectal cancer cases and 144 deaths were seen over 290,249 person-years at risk. The patients’ mean age was 57 years, 54.9% were women, and 27.9% were black. At scheduled follow-up visits from 1996 to 1998, 22% of patients were taking lipid-lowering drugs, mostly statins.

Compared with patients who never used lipid-lowering medications, patients who had ever used a lipid-lowering drug had a lower risk of colorectal cancer incidence (hazard ratio, 0.72). The incidence of colorectal cancer was lower among all lipid-lowering drug users, including men (HR, 0.69), women (HR, 0.76), black patients (HR, 0.60), and white patients (HR, 0.77).

Similarly, colorectal cancer–related death was lower among patients who had ever used a lipid-lowering drug (HR, 0.44). That association was apparent in men (HR, 0.58), women (HR, 0.33), black patients (HR, 0.63), and white patients (HR, 0.40).

In addition, the mortality risk was lower among lipid-lowering drug users regardless of duration of use or age at first use. The HR was 0.50 for patients taking lipid-lowering drugs for less than 15 years and 0.44 for patients taking the drugs for 15 years or more. HRs by age were 0.69 for patients aged 50-59 years, 0.45 for patients aged 60-69 years, and 0.57 for patients aged 70 and older.

While results of this particular study do help “move the needle forward” in terms of characterizing the relationship between lipid-lowering drugs and colorectal cancer risk, further studies are needed to better characterize the effects of long-term statin use, said Jennifer M. Weiss, MD, of the University of Wisconsin–Madison.

Clinical studies of the impact of statins on colorectal neoplasias have produced inconsistent results, Dr. Weiss and coauthor Bryson W. Katona, MD, PhD, wrote in a review article on chemoprevention in colorectal cancer.

“I definitely think there have been some studies that showed a modestly reduced risk,” Dr. Weiss said in an interview. “Unfortunately, there are also are some studies that show an increased risk of adenomas, and then there’s some studies that show no significant change. So we just can’t unequivocally confirm that there’s a significant association between statin use and decreased risk of developing colorectal cancer or adenomas.”

This research was funded by grants from the National Cancer Institute; the National Heart, Lung, and Blood Institute; the National Program of Cancer Registries; and the American Association for Cancer Research. Dr. Marrone disclosed no conflicts of interest. Dr. Weiss was an investigator for the CPP FAP-310 trial (NCT01483144) and received no salary support for her participation in the trial.

SOURCE: Marrone MT et al. AACR 2020, Abstract 2357.

Use of statins or other lipid-lowering drugs was associated with a lower risk of dying from colorectal cancer in a large study, investigators reported.

Use of lipid-lowering medication was linked to a 56% lower risk of colorectal cancer death among individuals with no cancer at baseline who were enrolled in the Atherosclerosis Risk in Communities (ARIC) study. The reduction in mortality risk was evident regardless of sex, race, age, or how long patients had been on lipid-lowering drugs.

Michael T. Marrone, PhD, of Johns Hopkins University, Baltimore, and colleagues detailed these findings in a poster presented at the AACR virtual meeting II.

“Definitely for those individuals at average risk for colorectal cancer, if their primary care doctor recommends a lipid-lowering medication for cardiovascular disease prevention, they should follow their doctor’s advice,” Dr. Marrone said in an interview.

“We really can’t say that they should take this specifically for colon cancer prevention, but they should just follow the recommendation for cardiovascular disease prevention,” he added.

While previous studies have linked lipid-lowering drugs, and statins in particular, to a modestly reduced risk of developing colorectal cancer, the impact on risk by factors such as sex, race, and duration of use have not been well characterized, according to Dr. Marrone.

Another motivation for this study was to determine, in participants free of cancer at baseline, the risk of actually dying from this cancer. “That endpoint has not been well studied in the literature at all,” Dr. Marrone said.

To address those gaps, Dr. Marrone and colleagues analyzed data on 14,428 patients from the ARIC study who were cancer free at study visits between 1990 and 1992. Follow-up continued through the end of 2015 or until death, whichever came first.

A total of 384 incident colorectal cancer cases and 144 deaths were seen over 290,249 person-years at risk. The patients’ mean age was 57 years, 54.9% were women, and 27.9% were black. At scheduled follow-up visits from 1996 to 1998, 22% of patients were taking lipid-lowering drugs, mostly statins.

Compared with patients who never used lipid-lowering medications, patients who had ever used a lipid-lowering drug had a lower risk of colorectal cancer incidence (hazard ratio, 0.72). The incidence of colorectal cancer was lower among all lipid-lowering drug users, including men (HR, 0.69), women (HR, 0.76), black patients (HR, 0.60), and white patients (HR, 0.77).

Similarly, colorectal cancer–related death was lower among patients who had ever used a lipid-lowering drug (HR, 0.44). That association was apparent in men (HR, 0.58), women (HR, 0.33), black patients (HR, 0.63), and white patients (HR, 0.40).

In addition, the mortality risk was lower among lipid-lowering drug users regardless of duration of use or age at first use. The HR was 0.50 for patients taking lipid-lowering drugs for less than 15 years and 0.44 for patients taking the drugs for 15 years or more. HRs by age were 0.69 for patients aged 50-59 years, 0.45 for patients aged 60-69 years, and 0.57 for patients aged 70 and older.

While results of this particular study do help “move the needle forward” in terms of characterizing the relationship between lipid-lowering drugs and colorectal cancer risk, further studies are needed to better characterize the effects of long-term statin use, said Jennifer M. Weiss, MD, of the University of Wisconsin–Madison.

Clinical studies of the impact of statins on colorectal neoplasias have produced inconsistent results, Dr. Weiss and coauthor Bryson W. Katona, MD, PhD, wrote in a review article on chemoprevention in colorectal cancer.

“I definitely think there have been some studies that showed a modestly reduced risk,” Dr. Weiss said in an interview. “Unfortunately, there are also are some studies that show an increased risk of adenomas, and then there’s some studies that show no significant change. So we just can’t unequivocally confirm that there’s a significant association between statin use and decreased risk of developing colorectal cancer or adenomas.”

This research was funded by grants from the National Cancer Institute; the National Heart, Lung, and Blood Institute; the National Program of Cancer Registries; and the American Association for Cancer Research. Dr. Marrone disclosed no conflicts of interest. Dr. Weiss was an investigator for the CPP FAP-310 trial (NCT01483144) and received no salary support for her participation in the trial.

SOURCE: Marrone MT et al. AACR 2020, Abstract 2357.

Use of statins or other lipid-lowering drugs was associated with a lower risk of dying from colorectal cancer in a large study, investigators reported.

Use of lipid-lowering medication was linked to a 56% lower risk of colorectal cancer death among individuals with no cancer at baseline who were enrolled in the Atherosclerosis Risk in Communities (ARIC) study. The reduction in mortality risk was evident regardless of sex, race, age, or how long patients had been on lipid-lowering drugs.

Michael T. Marrone, PhD, of Johns Hopkins University, Baltimore, and colleagues detailed these findings in a poster presented at the AACR virtual meeting II.

“Definitely for those individuals at average risk for colorectal cancer, if their primary care doctor recommends a lipid-lowering medication for cardiovascular disease prevention, they should follow their doctor’s advice,” Dr. Marrone said in an interview.

“We really can’t say that they should take this specifically for colon cancer prevention, but they should just follow the recommendation for cardiovascular disease prevention,” he added.

While previous studies have linked lipid-lowering drugs, and statins in particular, to a modestly reduced risk of developing colorectal cancer, the impact on risk by factors such as sex, race, and duration of use have not been well characterized, according to Dr. Marrone.

Another motivation for this study was to determine, in participants free of cancer at baseline, the risk of actually dying from this cancer. “That endpoint has not been well studied in the literature at all,” Dr. Marrone said.

To address those gaps, Dr. Marrone and colleagues analyzed data on 14,428 patients from the ARIC study who were cancer free at study visits between 1990 and 1992. Follow-up continued through the end of 2015 or until death, whichever came first.

A total of 384 incident colorectal cancer cases and 144 deaths were seen over 290,249 person-years at risk. The patients’ mean age was 57 years, 54.9% were women, and 27.9% were black. At scheduled follow-up visits from 1996 to 1998, 22% of patients were taking lipid-lowering drugs, mostly statins.

Compared with patients who never used lipid-lowering medications, patients who had ever used a lipid-lowering drug had a lower risk of colorectal cancer incidence (hazard ratio, 0.72). The incidence of colorectal cancer was lower among all lipid-lowering drug users, including men (HR, 0.69), women (HR, 0.76), black patients (HR, 0.60), and white patients (HR, 0.77).

Similarly, colorectal cancer–related death was lower among patients who had ever used a lipid-lowering drug (HR, 0.44). That association was apparent in men (HR, 0.58), women (HR, 0.33), black patients (HR, 0.63), and white patients (HR, 0.40).

In addition, the mortality risk was lower among lipid-lowering drug users regardless of duration of use or age at first use. The HR was 0.50 for patients taking lipid-lowering drugs for less than 15 years and 0.44 for patients taking the drugs for 15 years or more. HRs by age were 0.69 for patients aged 50-59 years, 0.45 for patients aged 60-69 years, and 0.57 for patients aged 70 and older.

While results of this particular study do help “move the needle forward” in terms of characterizing the relationship between lipid-lowering drugs and colorectal cancer risk, further studies are needed to better characterize the effects of long-term statin use, said Jennifer M. Weiss, MD, of the University of Wisconsin–Madison.

Clinical studies of the impact of statins on colorectal neoplasias have produced inconsistent results, Dr. Weiss and coauthor Bryson W. Katona, MD, PhD, wrote in a review article on chemoprevention in colorectal cancer.

“I definitely think there have been some studies that showed a modestly reduced risk,” Dr. Weiss said in an interview. “Unfortunately, there are also are some studies that show an increased risk of adenomas, and then there’s some studies that show no significant change. So we just can’t unequivocally confirm that there’s a significant association between statin use and decreased risk of developing colorectal cancer or adenomas.”

This research was funded by grants from the National Cancer Institute; the National Heart, Lung, and Blood Institute; the National Program of Cancer Registries; and the American Association for Cancer Research. Dr. Marrone disclosed no conflicts of interest. Dr. Weiss was an investigator for the CPP FAP-310 trial (NCT01483144) and received no salary support for her participation in the trial.

SOURCE: Marrone MT et al. AACR 2020, Abstract 2357.