Citations

Abstract Recent years have seen an explosion in the availability of paired molecular profiling and drug screen data, providing an unprecedented opportunity for the development of targeted therapies based on an individual’s genetic background. Despite a number of recent successes in diseases ranging from cystic fibrosis to cancer, significant hurdles remain in our ability to accurately predict treatments based on molecular profiling data. In particular, few such tools exist that allow the integration of heterogeneous data types (e.g. genomic, transcriptomic, and somatic mutations), along with high-throughput drug screen data to make predictions about treatment efficacy. Here, we describe a generalized open-source pipeline developed for the analysis of precision medicine data, Pharmacogenomics Prediction Pipeline, or “P3”. The modular design of P3 enables the inclusion of arbitrary input data types and the selection from multiple alternative machine learning algorithms, while automated statistical and visualization reporting steps incorporated throughout the pipeline assist in parameter tuning and early detection of problematic data components. Molecular profiling data is further enriched by the incorporation of external biological information in the form of pathway and gene set annotations such and Gene Ontology (GO) and The Molecular Signatures Database (MSigDB). To demonstrate the use of P3 for preclinical biomarker prediction, we applied P3 to an unpublished multiple myeloma dataset consisting of exome, RNA-Seq, CNV, and drug screen data for 1,912 compounds across 47 tumor cell lines. Specifically, P3 was used to predict molecular features associated with response to treatment for all drugs where a differential response to treatment was observed across patients. Furthermore, molecular profiling and drug screen data for 267 drugs and over a thousand cell lines spanning multiple cancer types from the Genomics of Drug Sensitivity in Cancer (GDSC) project were analyzed using P3, providing insights into shared mechanisms of drug sensitivity and resistance across different cancer and treatment types. Citation Format: V Keith Hughitt, Sayeh Gorjifard, Aleksandra M. Michalowski, John K. Simmons, Ryan Dale, Eric C. Polley, Jonathan J. Keats, Beverly A. Mock. A flexible pipeline for precision medicine biomarker detection and prediction of treatment response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5113.

Abstract Background: Understanding the joint effect on breast cancer risk of rare pathogenic variants in cancer predisposition genes and polygenic risk scores (PRS) from common variants can enable a precision approach to breast cancer management. Previous work found that PRS were associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers recruited from cancer genetics clinics (Kuchenbaecker et al. JNCI 2017). The joint effects of pathogenic variants and PRS have not been studied in samples drawn from the general population. There is also no existing study evaluating the effect of PRS in mutation carriers in genes other than BRCA1/2. Here we evaluate the joint effects of PRS and pathogenic mutations in established cancer predisposition genes in a population-based case-control sample. Method: We analyzed 53,199 European-ancestry individuals (20,730 controls and 21,272 cases) drawn from 7 cohorts and 2 population-based case-control studies in the CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) consortium. Targeted sequencing was performed using dual bar-coded QIAseq. Mutation calling was conducted with Haplotype Caller and Vardict. We sequenced 18 breast cancer predisposition genes: ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CDKN2A, CHECK2, FANCC, MLH1, MSH2, MSH6, NF1, PALB2, PTEN, RAD51C, RAD51D and TP53. The PRS was calculated based on 128 common variants using effect estimates from the largest published breast cancer GWAS. The PRS was standardized to a mean of 0 and standard deviation of 1. Logistic regression was performed to assess the combined effect of identified mutation and common variants (including main and interaction effects for carrier status and PRS). Results: A total of 1,770 pathogenic mutations were observed. About 1% of the study sample had mutations in either BRCA1 (n=209) or BRCA2 gene (n=305), and 2.2% had mutations in other genes (n=1,176). The effect of PRS in BRCA1 carriers was OR= 0.97 (95%CI: 0.62, 1.52); however, this is not statistically significantly different from the PRS in non-carriers [OR=1.23 (95%CI: 1.20, 1.25)] or previous estimates in carriers [OR: 1.14, 95%CI: 1.11-1.17]. The effect of PRS in BRCA2 carriers was OR=1.87 (95%CI: 1.31, 2.78) which was statistically significantly different from that of the non-carriers. Among the mutation carriers in genes other than BRCA, the effect of PRS on breast cancer was OR=1.00 (95%CI: 0.88,1.15). Conclusion: Consistent with previous studies, we did not find evidence that the effect of the PRS among BRCA1 carriers was statistically significantly different than non-carriers. We found some evidence that the PRS effect may be larger among BRCA2 carriers than non-carriers. Our results also suggest that PRS may not have a strong effect on breast cancer risk in mutation carriers of other predisposition genes; further work is needed for verification. Citation Format: Chi Gao, Chunling Hu, Steven N. Hart, Rohan Gnanaolivu, Kun Y. Lee, Jenna Lilyquist, Nicholas J. Boddicker, Bruce Eckloff, Raed Samara, Josh Klebba, Paul Auer, Leslie Bernstein, Mia Gaudet, Hoda Anton-Culver, Amy Trentham-Dietz, Julie R. Palmer, Song Yao, Christopher Haiman, Janet E. Olson, Susan Domchek, Jeffrey Weitzel, David Goldgar, Katherine L. Nathanson, Eric C. Polley, Fergus J. Couch, Peter Kraft. The joint effects of polygenic risk scores and pathogenic variants in cancer predisposition genes on breast cancer risk in the general population: results from the CARRIERS study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4177.

Abstract Clinical germline genetic testing of cancer predisposition gene panels is used to identify women at increased risk for breast cancer. Pathogenic mutations in cancer predisposition genes are associated with established risks of breast cancer and are actively used for risk management of breast cancer for women qualifying for genetic testing because of a family history of breast and/or ovarian cancer or young age of diagnosis. However, the risks of breast cancer associated with mutations in these genes have likely been overestimated for many women in the general population. The goal of the “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) study was to estimate breast cancer risks associated with mutations in hereditary cancer panel genes. Germline DNA from 32,298 breast cancer patients and 31,869 matched unaffected controls enrolled in cohorts and population-based case-control studies were sequenced to identify pathogenic mutations in 37 cancer predisposition genes.The average age at diagnosis was 61.2 years and the average age of last follow-up was 62.1 years. DNA was subjected to dual bar-coded QIAseq multiplex PCR-based amplification of 1733 target regions in 37 predisposition genes. Products from 768 samples were pooled and sequenced in a single lane of a HiSeq 4000 system. Mutations were called by GATK Haplotype Caller and Vardict.High quality sequence data was obtained for 99.3% of target regions. Pathogenic mutations in 12 known breast cancer predisposition genes were identified in 6.2% of all breast cancer cases and 2.1% of controls; and in 6.7% of African American breast cancer cases and 1.8% of controls. In case-control association analyses adjusted for age at diagnosis or last follow up and family history of breast and ovarian cancer, mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (odds ratio (OR)>4.0). Mutations in CHEK2 and BARD1 were associated with moderate risks of breast cancer (OR>2.0), whereas mutations in ATM had lower clinical relevance (OR=1.6). Stratification by ER, PR, and HER2 status of tumors found that BRCA1, BRCA2, PALB2 and TP53 were associated with high risks of studies of triple negative breast cancer (TNBC), and that BARD1, BRIP1, FANCM, and RAD51C were associated with moderate risks of TNBC. Overall, results from the CARRIERS study establish that mutations in predisposition genes are associated with lower risks of breast cancer in the general population than in high-risk families. The age-related estimates of breast cancer risk for each of the hereditary cancer panel genes in this study may inform on the use of cancer screening and other risk management strategies for women in the general population with mutations in predisposition genes. Citation Format: Fergus J. Couch, Chunling Hu, Steven N. Hart, Rohan Gnanaolivu, Jenna Lilyquist, Kun Y. Lee, Chi Gao, Bruce Eckloff, Hoda Anton-Culver, Paul Auer, Leslie Bernstein, Mia Gaudet, Christopher Haiman, Julie Palmer, Amy Tentham-Dietz, Song Yao, Susan Domchek, Jeffrey N. Weitzel, David E. Goldgar, Katherine L. Nathanson, Peter Kraft, Eric C. Polley. Population-based breast cancer risk estimates associated with cancer predisposition gene mutations from 32,298 breast cancer patients and 31,869 matched unaffected controls from the CARRIERS study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4169.

PURPOSE Older women with breast cancer remain under-represented in clinical trials. The Cancer and Leukemia Group B 49907 trial focused on women age 65 years and older. We previously reported the primary analysis after a median follow-up of 2.4 years. Standard adjuvant chemotherapy showed significant improvements in recurrence-free survival (RFS) and overall survival compared with capecitabine. We now update results at a median follow-up of 11.4 years. PATIENTS AND METHODS Patients age 65 years or older with early breast cancer were randomly assigned to either standard adjuvant chemotherapy (physician’s choice of either cyclophosphamide, methotrexate, and fluorouracil or cyclophosphamide and doxorubicin) or capecitabine. An adaptive Bayesian design was used to determine sample size and test noninferiority of capecitabine. The primary end point was RFS. RESULTS The design stopped accrual with 633 patients at its first sample size assessment. RFS remains significantly longer for patients treated with standard chemotherapy. At 10 years, in patients treated with standard chemotherapy versus capecitabine, the RFS rates were 56% and 50%, respectively (hazard ratio [HR], 0.80; P = .03); breast cancer–specific survival rates were 88% and 82%, respectively (HR, 0.62; P = .03); and overall survival rates were 62% and 56%, respectively (HR, 0.84; P = .16). With longer follow-up, standard chemotherapy remains superior to capecitabine among hormone receptor–negative patients (HR, 0.66; P = .02), but not among hormone receptor–positive patients (HR, 0.89; P = .43). Overall, 43.9% of patients have died (13.1% from breast cancer, 16.4% from causes other than breast cancer, and 14.1% from unknown causes). Second nonbreast cancers occurred in 14.1% of patients. CONCLUSION With longer follow-up, RFS remains superior for standard adjuvant chemotherapy versus capecitabine, especially in patients with hormone receptor–negative disease. Competing risks in this older population dilute overall survival benefits.

BackgroundThis multicenter, randomized phase 2 trial evaluated complete responses (CRs), efficacy, and safety with ofatumumab and bendamustine and with ofatumumab, bendamustine, and bortezomib in patients with untreated, high‐risk follicular lymphoma (FL).MethodsPatients with grade 1 to 3a FL and either a Follicular Lymphoma International Prognostic Index (FLIPI) score of 2 with 1 lymph node >6 cm or an FLIPI score of 3 to 5 were randomized to arm A (ofatumumab, bendamustine, and maintenance ofatumumab) or to arm B (ofatumumab, bendamustine, bortezomib, and maintenance ofatumumab and bortezomib).ResultsOne hundred twenty‐eight patients (66 in arm A and 62 in arm B) received treatment. The median age was 61 years, and 61% had disease >6 cm; 29% had an FLIPI score of 2, and 71% had an FLIPI score of 3 to 5. In arm A, 86% completed induction, and 64% completed maintenance. In arm B, 66% and 52% completed induction and maintenance, respectively. Dose modifications were required in 65% and 89% in arms A and B, respectively. Clinically significant grade 3 to 4 toxicities included neutropenia (A, 36%; B, 31%), nausea/vomiting (A, 0%; B, 8%), diarrhea (A, 5%; B, 11%), and sensory neuropathy (A, 0%; B, 5%). The estimated CR rates were 62% (95% confidence interval [CI], 50%‐74%) and 60% (95% CI, 47%‐72%) in arms A and B, respectively (P = .68). With a median follow‐up of 3.3 years, the estimated 2‐year progression‐free survival (PFS) and overall survival (OS) rates were 80% and 97%, respectively, for arm A and 76% and 91%, respectively, for arm B.ConclusionsThe CR rates, PFS, and OS were not improved with the addition of bortezomib to ofatumumab and bendamustine in patients with high‐risk FL. Although grade 3 to 4 toxicities were similar, more patients treated with bortezomib required dose modifications and early discontinuation.

1514 Background: The prevalence of germline mutations in non-white patients with breast cancer and the germline genetic drivers of breast cancer risk in non-white populations are largely unknown. Methods: The study population included 77,900 women with breast cancer (Non-Hispanic white: 57,003; Black: 6,722; Asian: 4,183; Hispanic: 5,194; Ashkenazi-Jewish: 4,798) who underwent germline multigene panel testing of cancer predisposition genes from March 2012 to December 2016. The prevalence of predisposition gene mutations in racial and ethnic populations relative to non-Hispanic Whites was assessed while accounting for age at diagnosis of breast cancer, family history of breast and ovarian cancer, and estrogen receptor status of breast tumors. Associations between mutations in each gene and breast cancer risk were evaluated using reference controls. Results: The overall frequency of pathogenic mutations in known breast cancer predisposition genes was 9.1% for non-Hispanic Whites, 9.8% for African Americans, 10.2% for Hispanics, 7.6% for Ashkenazi-Jewish, and 7.5% for Asians. BRCA1 mutations were enriched (p < 0.05) and CHEK2 mutations were under-represented in all racial and ethnic populations relative to non-Hispanic Whites. BRCA2 and BARD1 mutations were enriched in African Americans and Hispanics relative to non-Hispanic Whites, whereas PALB2 and RAD51C mutations were enriched in Hispanics. Among genes with mutation counts large enough for assessment, mutations in BARD1, BRCA1, BRCA2, PALB2 and TP53 were significantly associated with clinically relevant increased risks (odds ratio (OR) > 2) of breast cancer across all ethnicities and races. Rates of variants of uncertain significance were highest among Asians (29%), followed by blacks (27%), Hispanics (21%), non-Hispanic whites (16%) and Ashkenazi-Jews (14%). Conclusions: While there is some similarity across ethnic groups, substantial heterogeneity exists in the prevalence of mutations in breast cancer predisposition genes across major racial and ethnic groups in the US population. These findings contribute to our understanding of breast cancer risk and have significant implications for genetic testing, screening, and management of patients with an inherited predisposition to breast cancer, with a need for continued analysis with increased cohort size in ethnic minority groups.

591 Background: Both Cb and Bev demonstrate activity when combined with standard chemotherapy in TNBC. CALGB 40603 is a 2x2 randomized trial that previously demonstrated that adding Cb to NACT significantly increased pathologic complete responses in the breast/axilla (pCR), while adding Bev did not (Sikov, JCO 2015). Here we report 5-year LTOs and assess factors that influenced them. Methods: 443 patients with clinical stage II-III previously untreated TNBC received 12 weeks of paclitaxel (wP) +/- Cb then dose-dense AC, +/- Bev before surgery. The primary endpoint was pCR. Analyses of LTOs (event-free survival (EFS), distant recurrence-free interval (DRFI) and overall survival (OS)), impact of residual cancer burden and other variables were secondary. Results: Median follow-up was 5.7 years (y); 5y EFS was 70.9% (95% CI; 66.7%-75.4%), DRFI 76.3% (72.3%-80.5%) and OS 76.9% (72.9%-81.2%). Pretreatment clinical stage and achieving pCR correlated with LTOs, while age, race, subtype (basal-like vs. not) and tumor grade did not. Among pCR 5y EFS was 86.4% vs. 57.5% for non-pCR (HR 0.28, 0.19-0.43), OS was 88.7% vs 66.5% (HR = 0.28, 0.17-0.44). This relationship was similar in all trial arms. Any residual disease conferred poorer outcome; compared with pCR/Residual Cancer Burden (RCB) 0, EFS HRs were 2.29 (1.32-3.97), 3.01 (1.90-4.74), and 9.67 (5.66-16.51) for RCBI, II and III, respectively. There were no improvements in LTOs with Cb (EFS HR 0.99, 0.70-1.40) or Bev (EFS HR 0.91, 0.64-1.29). In an exploratory analysis, receipt of ≥11 doses of wP was associated with better EFS (HR 1.92, 1.33-2.77); this was particularly notable in Cb-treated arms. Conclusions: As expected, regardless of treatment arm pCR was associated with markedly better LTOs, and pts with any residual disease had significantly worse outcomes. The addition of Cb or Bev to standard NACT for TNBC did not improve LTOs in this trial, although it should be noted that the trial was not powered for this endpoint. Omission of chemotherapy doses may result in poorer outcomes, especially among Cb-treated pts, which may warrant further evaluation. Support: U10CA180821; U10CA180882; Genentech; https://acknowledgments.alliancefound.org ; NCT00861705 Clinical trial information: NCT00861705.

104 Background: The identification of pathogenic mutations in breast cancer susceptibility genes through clinical genetic testing leads to focused screening and prevention strategies for women at increased risk of cancer. However, the frequency of mutations and the risks of cancer associated with breast cancer predisposition genes has not been established for the African American population. Methods: Germline DNA samples from African American women (5,054 breast cancer cases and 4,993 age-matched unaffected controls) from 10 U.S. studies were tested for mutations in 20 established breast cancer predisposition genes using a QIAseq multiplex amplicon panel as part of the “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) study. The frequency of mutations in each gene and associations between mutations and breast cancer risk, adjusted for study design, age, and first-degree family history of breast cancer, were evaluated. Results: The mean age at diagnosis of breast cancer cases was 54.4 years and the mean age of controls was 55.2 years. 18.2% of cases and 10.8% of controls reported a first-degree family history of breast cancer. Pathogenic mutations in any of the 20 breast cancer predisposition genes were identified in 7.6% of breast cancer cases and 2.4% of controls. In multivariable analyses, mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (odds ratio (OR) > 5.0). Mutations in CHEK2 were associated with moderate risks of breast cancer (OR > 2.0), whereas mutations in ATM had lower clinical relevance (OR = 1.8). Mutations in BRCA1, BRCA2, PALB2, and RAD51D, but not CHEK2 or ATM, were associated with increased risks of estrogen receptor negative breast cancer. Conclusions: Cancer predisposition genes confer similar risks of breast cancer in the African American population as in non-Hispanic Whites. These studies provide important insights into the risks of breast cancer associated with predisposition gene mutations in the African American population.

Abstract Background: In CALGB 40601 (Alliance, NCT00770809), a neoadjuvant phase III trial of paclitaxel and trastuzumab with or without lapatinib for 12 weeks for patients with HER2-positive breast cancer, 33% of pretreatment tumors were Luminal A subtype, however, 69% of post-treatment samples with residual disease were Luminal A subtype. In addition, 71% of Luminal B (12/17) and 67% of HER2-Enriched (6/9) tumors changed into Luminal A, while 80% of Luminal A (20/24) remained Luminal A (Carey et al. J Clin Oncol. 2016). It is not known whether this shift to Luminal A was transient or permanent. Methods: We selected matched pairs of pre- and post-treatment 40601 samples with tumor purity &gt;10% based upon DNA analyses to ensure all samples contained tumor. PAM50 intrinsic subtyping was applied to the 40601 samples gene expression data using a two-step normalization process based on The Genome Cancer Atlas, and PAM50 training set. In addition, a HER2-enriched expression subtype patient-derived xenograft (PDX) tumor called WHIM35, was studied and was either untreated (n=10), or treated with lapatinib at 220 mg/kg for 1 week (wk) (n=5), for 2 wks (n=8), or for 3 wks (n=4). We also treated WHIM35 tumors with lapatinib for 2 wks (on) and then removed laptinib for 1 wk (off) (n=6), or for 2 wks on and 2-4 wk off (n=6), and finally for 3 wks on, and 1 wk off (n=3). PAM50 intrinsic subtyping was applied to the PDX gene expression data and subtype assessed as well as a genomic-based proliferation score. ANOVA p-values were calculated by comparing median values across all gene signature or correlation scores. Results: We found 10 pairs of 40601 samples that kept their tumor purity values, however, their subtype changed to Luminal A after treatment (i.e., in the residual disease), and in these cases no minor tumor subclone became a dominant clone in the post treatment sample. Pretreatment subtypes were 6 Luminal B, 3 Luminal A, and 1 HER2-enriched. The tumor purity values did not change after the treatments, but correlation to Luminal A was significantly higher (p=0.01), while correlation to HER2-enriched (p=0.004) and proliferation signature scores (p=0.003) were significantly lower in the post-treatment samples. Among the WHIM35 PDX tumors, one sample changed its subtype from HER2-enriched to Luminal A after the lapatinib treatment and the rest remained HER2-enriched, suggesting environmental differences between patient samples and the PDX model. However, correlation to Luminal A was significantly higher in all lapatinib treated WHIM35 samples (p=8.3e-12), and notably went back to the initial low levels just one week after removing lapatinib. Likewise, correlation to HER2-enriched (p=1.2e-10) and proliferation signature scores (p=6.2e-12) also got lower while treated with lapatinib, but went back to the initial levels after cessation of treatment. Conclusions: Our findings suggest that the apparent subtype change during HER2-targeting therapy is not permanent, but is more likely a transient state change from a HER2-enriched subtype into a more Luminal A-like state. When we plan additional treatment strategies using residual disease phenotypes, it may not be clear what is the true subtype of the sample due to this inherent plasticity. Citation Format: Tanioka M, Parker JS, Henry LN, Tolaney S, Dang C, Krop IE, Harris L, Polley M, Berry DA, Winer EP, Carey LA, Perou CM. Transient state change, but not permanent subtype change, after HER2-targeted therapy for HER2-positive breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-08-04.