Mutation Rates in Cancer Susceptibility Genes in Patients With Breast Cancer With Multiple Primary Cancers

Abstract

PURPOSE

Women with breast cancer have a 4%-16% lifetime risk of a second primary cancer. Whether mutations in genes other than BRCA1/2 are enriched in patients with breast and another primary cancer over those with a single breast cancer (S-BC) is unknown.

PATIENTS AND METHODS

We identified pathogenic germline mutations in 17 cancer susceptibility genes in patients with BRCA1/2-negative breast cancer in 2 different cohorts: cohort 1, high-risk breast cancer program (multiple primary breast cancer [MP-BC], n = 551; S-BC, n = 449) and cohort 2, familial breast cancer research study (MP-BC, n = 340; S-BC, n = 1,464). Mutation rates in these 2 cohorts were compared with a control data set (Exome Aggregation Consortium [ExAC]).

RESULTS

Overall, pathogenic mutation rates for autosomal, dominantly inherited genes were higher in patients with MP-BC versus S-BC in both cohorts (8.5% v 4.9% [P = .02] and 7.1% v 4.2% [P = .03]). There were differences in individual gene mutation rates between cohorts. In both cohorts, younger age at first breast cancer was associated with higher mutation rates; the age of non–breast cancers was unrelated to mutation rate. TP53 and MSH6 mutations were significantly enriched in patients with MP-BC but not S-BC, whereas ATM and PALB2 mutations were significantly enriched in both groups compared with ExAC.

CONCLUSION

Mutation rates are at least 7% in all patients with BRCA1/2 mutation–negative MP-BC, regardless of age at diagnosis of breast cancer, with mutation rates up to 25% in patients with a first breast cancer diagnosed at age < 30 years. Our results suggest that all patients with breast cancer with a second primary cancer, regardless of age of onset, should undergo multigene panel testing.

INTRODUCTION

Patients with breast cancer (BC) have a 4%-16% risk of developing a second primary cancer, including contralateral BC (CBC).^1,2 The increased risk of a second cancer may be due to genetic factors, treatment effects, environmental exposures, or a combination. Although multiple primary (MP) cancers may indicate genetic susceptibility, there is a paucity of data examining mutation rates in patients with MP-BC other than in women with breast and ovarian cancer. In one small series, 20% of patients with a primary BC and a nonovarian primary cancer had mutations in BRCA1/2.³

CONTEXT

• Key Objective

• This study aimed to determine the frequency of mutations in genes commonly found on multiplex genetic testing panels in patients with breast and another primary cancer compared with patients with a single breast cancer.

• Knowledge Generated

• Mutation rates in BRCA1/2-negative patients with multiple primary breast cancer were approximately 7%-9% compared with approximately 5% in BRCA1/2-negative patients with a single breast cancer. Mutation rates for breast cancer susceptibility genes negatively correlate with increasing age of onset of breast cancer but do not correlate with age of onset of the non–breast cancer.

• Relevance

• These results confirm added diagnostic yield of multiplex panel testing in patients with multiple primary breast cancer.

As survival from BC improves, the development of a second primary cancer has become a significant issue in BC survivorship.² Patients with MP cancers have worsened overall survival⁴ and increased rates of depression.⁵ It is therefore critical to understand the frequency of mutations in genes other than BRCA1/2 in patients with MP-BC such that second primaries might be prevented or detected earlier. Under-referral for genetic testing is well documented in the United States.^6,7 Thus, it is important to clearly delineate which patients need to be referred for genetic testing and to identify subgroups of those who had undergone prior BRCA1/2 testing and may benefit from updated panel testing. Finally, understanding the cancer risk spectrum associated with various genes may help to determine appropriate screening protocols.

A number of large, multiplex panel testing studies of patients with BRCA1/2-negative BC have shown rates of mutations in germline cancer susceptibility genes to be between 5% and 15%,⁸ with enrichment in certain subgroups of patients, including triple-negative BC,⁹ early-onset BC,¹⁰ and family history of BC.¹¹ In this study, we investigated whether mutations in cancer susceptibility genes were enriched in patients with MP-BC compared with a single BC (S-BC).

PATIENTS AND METHODS

Patient Cohorts

For both cohorts, eligibility criteria for patients with S-BC were diagnosis of BC, high-risk criteria (age of BC onset < 40 years or family history of BC as defined by the presence of ≥ 3 first- to third-degree relatives with BC), and negative BRCA1/2 sequencing in a Clinical Laboratory Improvement Amendment (CLIA)–approved laboratory. Eligibility criteria for patients with MP-BC were diagnosis of BC and another primary cancer, including BC and excluding nonmelanoma skin cancers as per SEER Multiple Primary Rules,¹² and negative BRCA1/2 sequencing in a CLIA-approved laboratory. One patient was analyzed per family; if DNA samples from > 1 family member were available, the patient with the youngest age at BC diagnosis was chosen. Cohort 1 included 1,000 patients ascertained from Penn Medicine–affiliated clinical practices seen in a high-risk cancer genetics or BC clinic within a single institution (MP-BC, n = 551; S-BC, n = 449).¹⁰ Cohort 2 included 1,804 patients enrolled in a familial BC research registry with either MP-BC (n = 340) or S-BC (n = 1,464), as previously described,¹¹ excluding patients from cohort 1 (Table 1).

TABLE 1.

Phenotypic and Pathologic Features of Patients With BC With and Without Additional Primary Cancers

DNA Sequencing by Targeted Enrichment

DNA samples from cohorts 1 and 2 underwent targeted, massively parallel research-based sequencing. Acquisition of the patient samples was approved by the institutional review boards (IRBs) of the corresponding institutions, and informed consent was obtained from each participant for use of their samples in genetic studies (Data Supplement).

Sequencing by targeted enrichment for cohorts 1 and 2 was done as previously described.^10,11 Briefly, DNA libraries of sufficient quality were pooled precapture and hybridized to an Agilent SureSelect (Agilent Technologies, Santa Clara, CA) custom target library. The captured fragments underwent paired-end sequencing on an Illumina HiSeq system (Illumina, San Diego, CA). Samples underwent quality control as previously described.^10,11

Sequencing Data Analysis

Sequencing data were analyzed with a custom bioinformatics pipeline^10,11 to identify all presumed heterozygous (allele frequency [AF], 30%-70%) single nucleotide variants, small- and medium-sized insertion/deletions, and large genomic rearrangements. Variants were called into a 5-tiered classification scheme per guidelines of the American College of Medical Genetics,¹³ as described in Maxwell et al,¹⁴ and patients were considered to be mutation carriers if a pathogenic or likely pathogenic mutation was identified (Data Supplement). Genes analyzed for heterozygous mutations included high-penetrance BC susceptibility genes (high-breast; CDH1 [lobular breast cancer only], PALB2, PTEN, STK11, TP53), moderate-penetrance BC susceptibility genes (mod-breast; ATM, CHEK2, NBN [c.657_661del5 mutation only]),¹⁵ genes known to cause a high risk of other non-BCs (high-other; CDKN2A, MLH1, MSH2, MSH6, PMS2, MUTYH [biallelic mutations only]), and genes known to cause moderate risk of other non-BCs (mod-other; BRIP1, RAD51C, RAD51D). In addition, we performed an exploratory analysis of heterozygous mutations in proposed BC susceptibility genes (BARD1, BLM, MRE11A, RAD50, XRCC2). High penetrance was defined as a greater than fivefold increased risk of cancer compared with the general population, and moderate penetrance was defined as a two- to fivefold increased risk. Low penetrance (less than twofold) alleles were excluded.

Case-Control Analysis

Mutations in the study genes in the Exome Aggregation Consortium (ExAC) version 0.3.1, excluding samples from The Cancer Genome Atlas (accessed December 29, 2014) were identified and classified in Slavin et al.¹¹ ExAC is a set of reference genomes that were made publicly available as a set of population data.^15a Allele counts for mutations were summed for each gene in European patients with MP-BC and S-BC; non-Finnish European ExAC AFs were deter-mined previously.⁹ Associations with BC for each gene were generated using a 2-sided Fisher exact test using the minimum likelihood method.

Clinical and Statistical Analysis

Clinical data were obtained for the patients in both cohorts by IRB-approved chart review. Comparisons of rates in different groups were determined using a 2-sided Fisher exact test of significance. Correlation of age and mutation rate in 10-year age-of-onset groups was performed by a linear regression model.

RESULTS

Cancer Susceptibility Gene Mutations in Patients With BRCA1/2-Negative MP-BC

To determine whether mutations in 17 cancer susceptibility genes are enriched in patients with MP-BC versus those with S-BC, 2 different BRCA1/2 mutation–negative cohorts were studied (Data Supplement). As described previously, cohort 1 included 1,000 patients with either MP-BC (n = 551) or S-BC (n = 449), and cohort 2 included 1,804 patients with either MP-BC (n = 340) or S-BC (n = 1,464; Table 1). Compared with cohort 2, cohort 1 had significantly more patients with early-onset BC (35.4% v 21.2%; P < .0001) and significantly fewer patients with familial BC (49.8% v 100%; P < .0001; Table 1; Data Supplement). The average age of onset of BC was significantly lower in cohort 1 than in cohort 2 (46.6 v 48.1; P = .0003). The 2 cohorts also differed in the spectrum of second cancers. Cohort 1 had significantly fewer patients with a second BC (44.1% v 65.0%; P < .0001) and significantly more patients with another second primary cancer than cohort 2 (78.8% v 37.6%; P < .0001; Data Supplement).

Mutation rates overall were higher in patients with MP-BC versus those with S-BC in both cohorts (cohort 1, 8.5% v 4.9% [P = .02]; cohort 2, 7.1% v 4.2% [P = .03]; Table 2). However, the individual genes responsible for the differences in mutation rates between patients with MP-BC and S-BC differed in the 2 cohorts (Table 2; Data Supplement). In cohort 1, with an early median age of diagnosis, the mutation rates in high-breast and high-other genes were significantly higher in patients with MP-BC than in those with S-BC (2.4% v 0.5% [P = .007] and 1.8% v 0.2% [P = .03], respectively). However, mutation rates in mod-breast and mod-other genes were nearly identical in patients with MP-BC and S-BC in cohort 1 (3.6% v 3.6% [P = 1.000] and 0.7% v 0.7% [P = 1.000], respectively). In cohort 2, mutation rates in high-breast and high-other genes were higher but not statistically significant (2.4% v 1.3% [P = .21] and 0.9% v 0.3% [P = .18], respectively). In cohort 2, mutation rates in mod-breast genes were also similar in patients with MP-BC compared with those with S-BC (3.8% v 2.3%; P = .13).

TABLE 2.

Mutation Rates for Known and Cancer Susceptibility Genes in Patients With MP-BC v S-BC

A bilateral mastectomy at the time of initial BC diagnosis would prevent the development of a CBC. Surgical data were available for 78% of patients with S-BC in cohort 1 (Data Supplement). Mutation rates in patients with MP-CBC (9.1%) were higher than that of patients with S-BC both before (5.1%) and after (3.2%) exclusion of patients who underwent bilateral mastectomy (Data Supplement). Mutation rates for individual genes were similar in patients with S-BC before and after exclusion of patients who underwent bilateral mastectomy (Data Supplement).

MP Cancer Spectrum in Mutation Carriers

The percentage of MP-BC mutation carriers with a second BC and a primary non-BC varied among gene groups (Table 3). Among 61 v 93 carriers of high- versus moderate-penetrance gene mutations, 36% v 23% (P = .10) had a second primary BC, 34% v 23% (P = .14) had at least 1 primary non-BC, and 44% v 60% (P = .07) had no other cancer. Second primary BCs were seen in 43% and 26% of high- and mod-breast gene mutation carriers but no carriers of mutations in other genes (except MSH6; Table 3). Of 26 other primary cancers in mutation carriers of genes with a known non-BC association, 62% were part of the associated cancer spectrum for that gene (Data Supplement).

TABLE 3.

Secondary Cancers in Patients With BC With Gene Mutations

Of the 11 carriers of BRIP1, RAD51C, and RAD51D mutations, 6 (55%) had a personal or family history of ovarian cancer, which was significantly higher than individuals with no mutations in both cohorts (18% [P = .008] v 15% [P = .003] in cohorts 1 and 2, respectively; Data Supplement). Of the 19 carriers of a Lynch syndrome gene mutation, 12 (63%) had a personal or family history of a Lynch syndrome cancer compared with 56% (P = .645) and 36% (P = .028) of cohorts 1 and 2, respectively. Five Lynch mutation–positive families fulfilled Bethesda criteria (26%) compared with only 9% of cohort 1 (P = .028). Among TP53 mutation carriers, 50% of the 18 carriers either had BC at age ≤ 31 years or met modified Chompret criteria (Data Supplement). Hormone receptor (HR) status was available for 99 of the BC mutation carriers. The majority of BC (72%) in carriers of ATM, CHEK2, and Lynch syndrome gene mutations were estrogen receptor positive and human epidermal growth factor receptor 2 (HER2) negative (Data Supplement). HR distribution was significantly altered in PALB2 and TP53 carriers compared with individuals with no mutations, with triple-negative BC enriched in PALB2 carriers (40% v 15%; P = .004) and HER2-positive BC enriched in TP53 carriers (58% v 24%; P = .01; Data Supplement).

Mutation Rates Stratified by Age at Cancer Diagnosis

To investigate whether age of either BC or non-BC in patients with MP-BC was related to mutation status, patients were stratified by age-group (Data Supplement). Mutation rates were highest in patients with S-BC with BC diagnosed at age < 30 at 8.6% (n = 92), and rates progressively decreased with older age of onset of BC (Fig 1A). Mutation rates for high-breast and mod-breast genes were negatively correlated with age-group in patients with S-BC up to age 60 years (r² = 0.68 and 0.81, respectively), whereas mutation rates in high-other and mod-other genes showed no relationship with age (Data Supplement). A similar result was seen for age at BC diagnosis but not for age at diagnosis of non-BC in patients with MP-BC (Figs 1B and 1C). Mutation rates were 25.0% in patients with MP-BC with the first BC at age < 30 years (n = 24), 11.9% at age 31-40 years (n = 143), 8.8% at age 41-50 years (n = 143), and 4.5% at age 51-60 years (n = 319; Fig 1B). In contrast, mutation rates were nearly identical regardless of the age at diagnosis of non-BC (9%-15%; Fig 1C). In patients with MP-BC, mutation rates in high-breast and mod-breast genes were negatively correlated with age-group of first BC up to age 60 years (r² = 0.72 and 0.97, respectively), and there was no relationship of age with mutation rates in high-other or mod-other genes (Data Supplement). Mutation rates were not correlated with age of non-BC diagnosis (Data Supplement).

FIG 1.

Relationship of age of first breast cancer (BC) or other cancer diagnosis in 5 age-groups (< 30 years, 31-40 years, 41-50 years, 51-60 years, and > 60 years) with mutation rates in genes other than BRCA1/2. (A) Patients with a single BC (S-BC) from sequencing cohorts 1 and 2 in whom mutations were analyzed in high-penetrance BC susceptibility genes (high-breast), moderate-penetrance BC susceptibility genes (mod-breast), high-penetrance other cancer susceptibility genes (high-other), and moderate-penetrance other cancer susceptibility genes (mod-other). (B) Patients with multiple primary BC (MP-BC) from sequencing cohorts 1 and 2 in whom mutations were analyzed in high-breast, mod-breast, high-other, and mod-other genes. (C) Patients with MP-BC from sequencing cohorts 1 and 2 analyzed on the basis of age at diagnosis of their first non-BC; mutations were analyzed in high-breast, mod-breast, high-other, and mod-other genes.

Case-Control Study With ExAC

Mutation rates in European individuals in the MP-BC and S-BC combined cohort were compared with mutation rates in the non-Finnish European ExAC population¹¹ for genes with > 5 mutation carriers (Table 4). Mutation rates in TP53 and MSH6 were significantly enriched in patients with MP-BC but not in those with S-BC compared with ExAC. Mutations in ATM and PALB2 were significantly enriched in patients with MP-BC and those with S-BC relative to ExAC, although in both cases, the association was stronger in patients with MP-BC. Associations did not reach significance in either cohort for CHEK2.

TABLE 4.

Case-Control in MP-BC and S-BC Cohorts Compared With ExAC Non-Finnish European Individuals

Other Genetic Variations in MP-BC

To explore other possible genetic associations with MP-BC, mutations in a set of genes were analyzed in cohort 1 (BARD1, BLM, MRE11A, RAD50, XRCC2). Heterozygous BLM mutations were found at modestly higher rates in patients with MP-BC compared with those with S-BC (Data Supplement).

DISCUSSION

In this study, mutation rates in genes commonly found on multigene panels for cancer susceptibility were studied in patients with MP-BC or S-BC from 2 different cohorts. Our results indicate that mutation rates are higher in patients with BRCA1/2-negative MP-BC versus S-BC. However, the genes responsible for the differences in rates varied between the 2 cohorts. High-penetrance cancer genes were responsible for higher mutation rates in the cohort enriched for early-onset BC and non-BC second primaries, whereas moderate-penetrance cancer genes were responsible for the higher mutation rates in the cohort enriched for familial BC and second BC primaries. However, our data suggest that mutations in genes other than BRCA1/2 do not explain the majority of MP-BC cases.

We found that 7%-9% of patients with BRCA1/2-negative MP-BC carried a pathogenic mutation in 1 of 17 genes. Studies from the United Kingdom and Singapore found pathogenic mutations in the genes in our study in 5.2% (n = 440) and 13% (n = 110) of patients with multiple primary cancers of any type, respectively.^16,17 Patients with MP-BC with 1 of 6 other cancer types from a genetic testing company cohort found mutations in these genes in 7.4%-11% of patients.¹⁸

More than half of the non-BCs in mutation carriers in this study were cancers known to be associated with inherited mutations in the identified gene. In moderate-risk ovarian cancer gene carriers, Lynch syndrome gene mutation carriers, and TP53 carriers, the cancers associated with these genes were enriched in personal and family histories compared with the cohort overall. Approximately half of patients with BC who are found to have mutations in non-BC–related genes fit the genetic testing criteria for the identified gene. In the case that BC is the presenting cancer, the finding of a genetic mutation could lead to implementation of cancer prevention and screening strategies to identify future cancers, hopefully at an early stage to reduce morbidity and mortality.²

Mutation rates in BC susceptibility genes, but not genes associated with other cancers, were correlated with age at diagnosis of BC. Of note, although not the aim of the current study, we found that in patients with S-BC diagnosed at age > 61 years, 0.6% had pathogenic variants in high-penetrance and 1.9% in moderate-penetrance genes. The age of the other cancer was not correlated with the presence of a mutation in a BC susceptibility gene. Particularly for DNA repair germline mutation carriers where poly (ADP-ribose) polymerase inhibitors may be effective targeted therapy,¹⁹ it will be important to determine whether the non-BC in these patients is related to the germline mutation or is a sporadic cancer. Several lines of evidence suggest that noncanonical cancers (eg, other than breast, ovarian, prostate, and pancreatic for BRCA1/2 mutations) are less likely to have arisen as a result of the inherited mutation.^20,21

The limitations of this study include small numbers of patients in both cohorts, although, to our knowledge this is the largest study of patients with MP-BC to date. The patient cohorts were from academic cancer genetics clinics and research studies; therefore, they may not reflect mutation rates in the general population. In addition, other known or proposed cancer susceptibility genes were not evaluated, and there may be additional genes associated with MP-BC. Conversely, although there are studies supportive^22,23 of the groupings used for individual genes in this study, these categories may change with additional data. Among MP-BC cohorts, we noted a slightly increased rate of mutations in women with BC diagnosed at age ≥ 61 years compared with those age 51-60 years, which may reflect a particularly strong family history for women diagnosed at late ages to meet our eligibility criteria; therefore, studies in unselected patients will be helpful to generalize our results. Our results could be influenced by the possibility that some patients with S-BC may truly be patients with MP-BC if they had not had a bilateral mastectomy because those patients were excluded from cohort 2; however, we did not see a difference in mutation rates in patients with S-BC before and after excluding patients with bilateral mastectomy in cohort 1. Finally, mutation rates were compared with the ExAC population, which could inflate odds ratios; a well-matched case-control study is needed in patients with MP-BC.

The majority of patients with cancer who present for genetic testing are now undergoing multigene panel testing compared with gene- or syndrome-specific testing.^8,24 One potential benefit from this practice is the identification of unexpected cancer risk in a family.^25,26 However, mutation rates in genes other than BRCA1/2 are low, which leads to concerns about overtesting of patients who present for cancer risk evaluation.^27,28 Therefore, studies that define cohorts with both lower and higher mutation rates are critical. Our finding of a low rate of mutations in women age > 61 years with solitary breast cancer supports that if genetic testing is done, a limited panel, including BRCA1, BRCA2, and PALB2, may be appropriate, although the prevalence of PALB2 mutations in our study was 0.2%. Given that resources are often constrained and many individuals with a much higher risk of having pathogenic variants often do not undergo testing, the low yield must be recognized. Our study shows that regardless of age, mutation rates in genes other than BRCA1/2 are found in at least 5% of patients with BC and another primary cancer, with up to 25% in patients with their first BC at age < 30 years. These data support the current practice of multigene panel testing in all patients with BC and another primary cancer, regardless of age of onset or family history, and substantiate that all such patients should be referred for genetic counseling.

AUTHOR CONTRIBUTIONS

Conception and design: Kara N. Maxwell, Abha Kulkarni, Mark E. Robson, Angela M. DeMichele, Kenneth Offit, Susan M. Domchek, Katherine L. Nathanson

Financial support: Kara N. Maxwell, Katherine L. Nathanson

Administrative support: Benita Weathers, Judy E. Garber, Katherine L. Nathanson

Provision of study material or patients: Paolo Peterlongo, Bernardo Bonanni, James M. Ford, Judy E. Garber, Susan L. Neuhausen, Angela M. DeMichele, Kenneth Offit, Fergus J. Couch, Susan M. Domchek, Katherine L. Nathanson

Collection and assembly of data: Kara N. Maxwell, Brandon M. Wenz, Abha Kulkarni, Kurt D’Andrea, Benita Weathers, Noah Goodman, Joseph Vijai, Jenna Lilyquist, Steven N. Hart, Thomas P. Slavin, Kasmintan A. Schrader, Vignesh Ravichandran, Tinu Thomas, Chunling Hu, Paolo Peterlongo, Bernardo Bonanni, James M. Ford, Judy E. Garber, Susan L. Neuhausen, Angela M. DeMichele, Jeffrey N. Weitzel, Fergus J. Couch, Susan M. Domchek, Katherine L. Nathanson

Data analysis and interpretation: Kara N. Maxwell, Brandon M. Wenz, Bradley Wubbenhorst, Steven N. Hart, Kasmintan A. Schrader, Vignesh Ravichandran, Tinu Thomas, Chunling Hu, Mark E. Robson, Payal D. Shah, Angela R. Bradbury, Susan M. Domchek, Katherine L. Nathanson

Manuscript writing: All authors

Final approval of manuscript: All authors

Accountable for all aspects of the work: All authors

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/po/author-center.

Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).

Joseph Vijai

Patents, Royalties, Other Intellectual Property: Title: Diagnosis & Treatment of ERCC3-Mutant Cancer; inventors: Joseph Vijai, Sabine Topka, Kenneth Offit; US National Stage Patent Application No.: 16/493,214; filing date: September 11, 2019 (Inst)

Kasmintan A. Schrader

Consulting or Advisory Role: Pfizer, AstraZeneca

Research Funding: AstraZeneca (Inst)

Mark E. Robson

Consulting or Advisory Role: Change Health Care

Research Funding: AstraZeneca (Inst), InVitae (Inst), AbbVie (Inst), Pfizer (Inst), Merck (Inst)

Travel, Accommodations, Expenses: AstraZeneca, Pfizer, Merck

Other Relationship: Research to Practice, Clinical Care Options, Physician Education Resource

Uncompensated Relationships: Merck, Pfizer, Daiichi Sankyo, Epic Sciences

Open Payments Link: https://openpaymentsdata.cms.gov/physician/612669/summary

James M. Ford

Research Funding: Genentech (Inst), AstraZeneca (Inst), Puma Biotechnology (Inst), Pfizer (Inst)

Judy E. Garber

Consulting or Advisory Role: Novartis (I), GTx (I), Helix BioPharma, Konica Minolta, Aleta BioTherapeutics (I), H3 Biomedicine (I), Kronos Bio (I)

Research Funding: Novartis (I), Ambry Genetics, Invitae Genetics, Myriad Genetics

Other Relationship: Susan G. Komen for the Cure (I), American Association for Cancer Research, Diane Helis Henry Medical Foundation (I), James P. Wilmot Foundation (I), Adrienne Helis Malvin Medical Research Foundation (I), Breast Cancer Research Foundation, Facing our Risk of Cancer Empowered

Payal D. Shah

Stock and Other Ownership Interests: Johnson & Johnson (I), Novartis (I), Novo Nordisk (I), Pfizer (I), Merck (I), Amgen, Johnson & Johnson, Novo Nordisk

Consulting or Advisory Role: Tmunity Therapeutics

Angela R. Bradbury

Consulting or Advisory Role: AstraZeneca, Merck

Angela M. DeMichele

Consulting or Advisory Role: Context Therapeutics, Pfizer (I)

Research Funding: Pfizer (Inst), Genentech (Inst), Calithera Biosciences (Inst), Menarini (Inst), Silicon Biosystems (Inst)

Jeffrey N. Weitzel

Speakers’ Bureau: AstraZeneca

Fergus J. Couch

Consulting or Advisory Role: AstraZeneca

Speakers’ Bureau: Ambry Genetics, QIAGEN

Research Funding: Grail

Travel, Accommodations, Expenses: Grail, QIAGEN

Other Relationship: Ambry Genetics

Susan M. Domchek

Honoraria: AstraZeneca, Clovis Oncology, Bristol Myers Squibb

Research Funding: AstraZeneca (Inst), Clovis Oncology (Inst)

Open Payments Link: https://openpaymentsdata.cms.gov/physician/917904

No other potential conflicts of interest were reported.