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Supplementary Figure Legend

Supplementary Table 4 - Summary of SNPs with p

Supplementary Table 3 - Summary of SNPs with p

Supplementary Figure 1. Principal component analysis for patients in ECOG-5103 Supplementary Figure 2. Regional association (locuszoom) plots of rs3125923.

Purpose: Taxane-induced peripheral neuropathy (TIPN) is an important survivorship issue for many cancer patients. Currently, there are no clinically implemented biomarkers to predict which patients might be at increased risk for TIPN. We present a comprehensive approach to identification of genetic variants to predict TIPN.Experimental Design: We performed a genome-wide association study (GWAS) in 3,431 patients from the phase III adjuvant breast cancer trial, ECOG-5103 to compare genotypes with TIPN. We performed candidate validation of top SNPs for TIPN in another phase III adjuvant breast cancer trial, ECOG-1199.Results: When evaluating for grade 3–4 TIPN, 120 SNPs had a P value of −4 from patients of European descent (EA) in ECOG-5103. Thirty candidate SNPs were subsequently tested in ECOG-1199 and SNP rs3125923 was found to be significantly associated with grade 3–4 TIPN (P = 1.7 × 10−3; OR, 1.8). Race was also a major predictor of TIPN, with patients of African descent (AA) experiencing increased risk of grade 2–4 TIPN (HR, 2.1; P = 5.6 × 10−16) and grade 3–4 TIPN (HR, 2.6; P = 1.1 × 10−11) compared with others. An SNP in FCAMR, rs1856746, had a trend toward an association with grade 2–4 TIPN in AA patients from the GWAS in ECOG-5103 (OR, 5.5; P = 1.6 × 10−7).Conclusions: rs3125923 represents a validated SNP to predict grade 3-4 TIPN. Genetically determined AA race represents the most significant predictor of TIPN. Clin Cancer Res; 21(22); 5082–91. ©2015 AACR.

Genome wide genotyping of E5103 samples. Quality controls for GWAS.

Purpose: Anthracycline-induced congestive heart failure (CHF) is a rare but serious toxicity associated with this commonly employed anticancer therapy. The ability to predict which patients might be at increased risk prior to exposure would be valuable to optimally counsel risk-to-benefit ratio for each patient. Herein, we present a genome-wide approach for biomarker discovery with two validation cohorts to predict CHF from adult patients planning to receive anthracycline.Experimental Design: We performed a genome-wide association study in 3,431 patients from the randomized phase III adjuvant breast cancer trial E5103 to identify single nucleotide polymorphism (SNP) genotypes associated with an increased risk of anthracycline-induced CHF. We further attempted candidate validation in two independent phase III adjuvant trials, E1199 and BEATRICE.Results: When evaluating for cardiologist-adjudicated CHF, 11 SNPs had a P value −5, of which nine independent chromosomal regions were associated with increased risk. Validation of the top two SNPs in E1199 revealed one SNP rs28714259 that demonstrated a borderline increased CHF risk (P = 0.04, OR = 1.9). rs28714259 was subsequently tested in BEATRICE and was significantly associated with a decreased left ventricular ejection fraction (P = 0.018, OR = 4.2).Conclusions: rs28714259 represents a validated SNP that is associated with anthracycline-induced CHF in three independent, phase III adjuvant breast cancer clinical trials. Clin Cancer Res; 23(1); 43–51. ©2016 AACR.

PDF file - 121K, Table 1. Supplemental Table 1. Comparison of the Patients Analyzable for VEGFA Amplification to All Patients Enrolled on E2100 Table 2. Estimated Progression Free Survival treatment hazard ratios (arm A vs. arm B) and 95% confidence intervals for various subsets. Comparison between the cases analyzable for VEGFA amplification and all cases in E2100

Supplementary Table 5 - Summary of SNPs with p

GWAS with E5103 samples and OpenArray Genotyping with E1199 samples.

Gene list for Fig.5B, C, D

Supplementary Data from Initial Phase I Safety Study of Gedatolisib plus Cofetuzumab Pelidotin for Patients with Metastatic Triple-Negative Breast Cancer

Purpose: Clinically validated biomarkers for anti-angiogenesis agents are not available. We have previously reported associations between candidate VEGFA single-nucleotide polymorphisms (SNP) and overall survival (OS) in E2100. The associations between tumor VEGFA amplification and outcome are evaluated here.Experimental Design: E2100 was a phase III trial comparing paclitaxel with or without bevacizumab for patients with metastatic breast cancer. FISH to assess gene amplification status for VEGFA was conducted on paraffin-embedded tumors from 363 patients in E2100. Evaluation for association between amplification status and outcomes was conducted.Results: Estrogen receptor (ER)+ or progesterone receptor (PR)+ tumors were less likely to have VEGFA amplification than ER/PR− tumors (P = 0.020). VEGFA amplification was associated with worse OS (20.2 vs. 25.3 months; P = 0.013) in univariate analysis with a trend for worse OS in multivariate analysis (P = 0.08). There was a significant interaction between VEGFA amplification, hormone receptor status, and study arm. Patients with VEGFA amplification and triple-negative breast cancers (TNBC) or HER2 amplification had inferior OS (P = 0.047); amplification did not affect OS for those who were ER+ or PR+ and HER2−. Those who received bevacizumab with VEGFA amplification had inferior progression-free survival (PFS; P = 0.010) and OS (P = 0.042); no association was seen in the control arm. Test for interaction between study arm and VEGFA amplification with OS was not significant.Conclusion:VEGFA amplification in univariate analysis was associated with poor outcomes; this was particularly prominent in HER2+ or TNBCs. Additional studies are necessary to confirm the trend for poor OS seen on multivariate analysis for patients treated with bevacizumab. Clin Cancer Res; 19(5); 1281–9. ©2012 AACR.

Acquired and intrinsic resistance to receptor tyrosine kinase inhibitors (RTKi) represents a major hurdle in improving the management of clear cell renal cell carcinoma (ccRCC). Recent reports suggest that drug resistance is driven by tumor adaptation via epigenetic mechanisms that activate alternative survival pathways. The histone methyl transferase EZH2 is frequently altered in many cancers, including ccRCC. To evaluate its role in ccRCC resistance to RTKi, we established and characterized a spontaneously metastatic, patient-derived xenograft model that is intrinsically resistant to the RTKi sunitinib, but not to the VEGF therapeutic antibody bevacizumab. Sunitinib maintained its antiangiogenic and antimetastatic activity but lost its direct antitumor effects due to kinome reprogramming, which resulted in suppression of proapoptotic and cell-cycle–regulatory target genes. Modulating EZH2 expression or activity suppressed phosphorylation of certain RTKs, restoring the antitumor effects of sunitinib in models of acquired or intrinsically resistant ccRCC. Overall, our results highlight EZH2 as a rational target for therapeutic intervention in sunitinib-resistant ccRCC as well as a predictive marker for RTKi response in this disease. Cancer Res; 77(23); 6651–66. ©2017 AACR.

Supplementary Table 2 - Summary of evaluated candidate SNPs in patients with NE in E1199 or E5103.

Purpose:The PI3K pathway is dysregulated in the majority of triple-negative breast cancers (TNBC), yet single-agent inhibition of PI3K has been ineffective in TNBC. PI3K inhibition leads to an immediate compensatory upregulation of the Wnt pathway. Dual targeting of both pathways is highly synergistic against TNBC models in vitro and in vivo. We initiated a phase I clinical trial combining gedatolisib, a pan-class I isoform PI3K/mTOR inhibitor, and cofetuzumab pelidotin, an antibody–drug conjugate against the cell-surface PTK7 protein (Wnt pathway coreceptor) with an auristatin payload.Patients and Methods:Participants (pt) had metastatic TNBC or estrogen receptor (ER) low (ER and PgR < 5%, HER2-negative) breast cancer, and had received at least one prior chemotherapy for advanced disease. The primary objective was safety. Secondary endpoints included overall response rate (ORR), clinical benefit at 18 weeks (CB18), progression-free survival (PFS), and correlative analyses.Results:A total of 18 pts were enrolled in three dose cohorts: gedatolisib 110 mg weekly + cofetuzumab pelidotin 1.4 mg/kg every 3 weeks (n = 4), 180 mg + 1.4 mg/kg (n = 3), and 180 mg + 2.8 mg/kg (n = 11). Nausea, anorexia, fatigue, and mucositis were common but rarely reached ≥grade 3 severity. Myelosuppression was uncommon. ORR was 16.7% (3/18). An additional 3 pts had stable disease (of these 2 had stable disease for >18 weeks); CB18 was 27.8%. Median PFS was 2.0 months (95% confidence interval for PFS: 1.2–6.2). Pts with clinical benefit were enriched with genomic alterations in the PI3K and PTK7 pathways.Conclusions:The combination of gedatolisib + cofetuzumab pelidotin was well tolerated and demonstrated promising clinical activity. Further investigation of this drug combination in metastatic TNBC is warranted.

Supplementary Figure from Initial Phase I Safety Study of Gedatolisib plus Cofetuzumab Pelidotin for Patients with Metastatic Triple-Negative Breast Cancer

Supplemental data on additional models to support the role of EZH2 in RTKi resistance

Purpose:The PI3K pathway is dysregulated in the majority of triple-negative breast cancers (TNBC), yet single-agent inhibition of PI3K has been ineffective in TNBC. PI3K inhibition leads to an immediate compensatory upregulation of the Wnt pathway. Dual targeting of both pathways is highly synergistic against TNBC models in vitro and in vivo. We initiated a phase I clinical trial combining gedatolisib, a pan-class I isoform PI3K/mTOR inhibitor, and cofetuzumab pelidotin, an antibody–drug conjugate against the cell-surface PTK7 protein (Wnt pathway coreceptor) with an auristatin payload.Patients and Methods:Participants (pt) had metastatic TNBC or estrogen receptor (ER) low (ER and PgR < 5%, HER2-negative) breast cancer, and had received at least one prior chemotherapy for advanced disease. The primary objective was safety. Secondary endpoints included overall response rate (ORR), clinical benefit at 18 weeks (CB18), progression-free survival (PFS), and correlative analyses.Results:A total of 18 pts were enrolled in three dose cohorts: gedatolisib 110 mg weekly + cofetuzumab pelidotin 1.4 mg/kg every 3 weeks (n = 4), 180 mg + 1.4 mg/kg (n = 3), and 180 mg + 2.8 mg/kg (n = 11). Nausea, anorexia, fatigue, and mucositis were common but rarely reached ≥grade 3 severity. Myelosuppression was uncommon. ORR was 16.7% (3/18). An additional 3 pts had stable disease (of these 2 had stable disease for >18 weeks); CB18 was 27.8%. Median PFS was 2.0 months (95% confidence interval for PFS: 1.2–6.2). Pts with clinical benefit were enriched with genomic alterations in the PI3K and PTK7 pathways.Conclusions:The combination of gedatolisib + cofetuzumab pelidotin was well tolerated and demonstrated promising clinical activity. Further investigation of this drug combination in metastatic TNBC is warranted.

BACKGROUND Despite favorable clinical outcomes, a subset of patients with thymic epithelial tumors (TETs) develop metastasis. The Cancer Genome Atlas (TCGA) provides genomic data on primary TETs (pTETs). This study assessed the molecular alterations and uncovered targetable pathways in metastatic TETs (mTETs). METHODS From 2015 to 2020, 49 patients with stage IV TETs underwent Clinical Laboratory Improvement Amendments–based sequencing using whole-exome sequencing (n = 33), panel-based testing (n = 12), and/or liquid biopsy (n = 24). Specimens were obtained from a metastatic organ (n = 36) or relapsed primary mediastinal mass (n = 10), whereas four patients underwent a liquid biopsy only. Data on pTETs were derived from the TCGA. RESULTS Compared with the pTET data set, patients with mTETs were younger (54 years v 60.5 years, P = .009) and had more aggressive histologies, with the most common tumor type being thymic carcinoma (n = 22, 40.7%) and B3 thymoma (n = 15, 27.8%). GTF2I was the most altered gene in primary thymomas (48.80%, n = 60). In metastatic thymoma and thymic carcinoma, TP53 was the most common genetic alteration (31% and 36%, respectively). In mTETs, the genomic alteration occurred in the TP53/CDK, EGFR/RAS, and PI3K/mTOR pathways. Biopsies obtained from distant metastasis were more commonly found to contain targetable mutations. There was an overlap of 61% (22 of 36) between tissue and liquid biopsy genomic alterations. CONCLUSION Clinically actionable genomic alterations are frequently observed in mTETs, indicating a value of repeat biopsy (preferably from a metastatic site of TETs for sequencing at the time of recurrence (TCGA data).

Germline whole exome sequencing from molecular tumor boards has the potential to be repurposed to support clinical pharmacogenomics. However, accurately calling pharmacogenomics-relevant genotypes from exome sequencing data remains challenging. Accordingly, this study assessed the analytical validity of the computational tool, Aldy, in calling pharmacogenomics-relevant genotypes from exome sequencing data for 13 major pharmacogenes. Germline DNA from whole blood was obtained for 164 subjects seen at an institutional molecular solid tumor board. All subjects had whole exome sequencing from Ashion Analytics and panel-based genotyping from an institutional pharmacogenomics laboratory. Aldy version 3.3 was operationalized on the LifeOmic Precision Health Cloud with copy number fixed to two copies per gene. Aldy results were compared with those from genotyping for 56 star allele–defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, and TPMT. Read depth was >100× for all variants except CYP3A4∗22. For 75 subjects in the validation cohort, all 3393 Aldy variant calls were concordant with genotyping. Aldy calls for 736 diplotypes containing alleles assessed by both platforms were also concordant. Aldy identified additional star alleles not covered by targeted genotyping for 139 diplotypes. Aldy accurately called variants and diplotypes for 13 major pharmacogenes, except for CYP2D6 variants involving copy number variations, thus allowing repurposing of whole exome sequencing to support clinical pharmacogenomics.

Background: Although there is increased awareness leading to early detection and prevention, Hispanic American (HA) men with prostate cancer (PC) continue to have greater mortality rates compared to their Non-Hispanic White (NHW) counterparts. Moreover, HA men with PC are more likely to have more advanced disease compared to NHW men. Here, we characterized the molecular and immune differences in HA and NHW tumors and their association with PC ethnic disparity. Methods: 88 PC samples (HA=34, NHW=54) obtained from treatment-naive metastatic hormone-sensitive PC (mHSPC) were analyzed by next-generation sequencing (592, NextSeq; WES, NovaSeq), Whole Transcriptome Sequencing (WTS; NovaSeq) (Caris Life Sciences, Phoenix, AZ). AR signature and NEPC score were calculated based on the expression level of previously defined genes (Hieronymus et al. 2006, Beltran et al. 2016). Medical record was reviewed in a deidentified fashion for clinal features. Statistical significance was determined using chi-square and Mann-Whitney U (p Results: HA patients with PC had higher level of PSA (111.5 vs 52.6 ng/ml, p=0.12) and stage (T4: 41% vs 14% p=0.01, M1c: 41% vs 16% p=0.04) but no significant difference in frequency of Gleason score > 4 (79% vs 73%, p=0.61) or stage N1 (69% vs 61%, p=0.85) compared to NHW. HA PC had a significantly higher frequency of TMPRSS2-fusion (46.4% vs 20.0%, p=0.04) compared to NHW PC. By Gene Set Enrichment Analysis, HA PC had enrichment of KRAS signaling (NES: 1.44, FDR=0.02), Hedgehog signaling (NES: 1.45, FDR=0.04), NOTCH signaling (NES: 1.41, FDR=0.07), Hypoxia (NES: 1.38, FDR=0.10) and IL2-STAT5 signaling (NES: 1.35, FDR=0.10) pathways compared to NHW tumors. There was no difference in median Androgen Receptor signature (p=0.78) or Neuroendocrine Prostate Cancer (NEPC) score (p=0.79). Also, no significant difference in AR positivity by IHC (100% vs 95.7%) between HA and NHW PC tumors (p=0.51). HA PC had significantly higher expression of stem cell markers ALDH1A1 (2.1-fold), ALDH1A2 (3-fold), and PROM1 (1.6-fold) and immunoinhibitory genes PDCD1LG2 (1.68-fold) and FOXP3 (1.45-fold) compared to NHW tumors (all p Conclusion: Our data suggest that HA mHSPC is associated with higher levels of PSA, stage, TMPRSS2-fusions, stemness marker expression, immunoinhibitory gene expression, and increased M1 Macrophage and NK cell infiltration. Together, these findings suggest a crucial role of differential molecular and tumor immune microenvironment in PC ethnic disparity. A better understanding of these differences with additional research may help in designing the approaches for reducing the ethnic disparities gaps in PC patients. Citation Format: Alejandro Recio-Boiles, Sachin Kumar Deshmukh, Juan Chipollini, Ken Batai, Sharon Wu, Joanne Xiu, Alex Farrell, Milan Radovich, Elisabeth Heath, Rana McKay, Chadi Nabhan. Molecular characterization of prostate cancer between Hispanic American and Non-Hispanic Whites: Implications for cancer ethnic health disparities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1895.

Background: Understanding how hereditary, lifestyle and demographic risk factors influence the development of breast cancer is critical for its prevention and treatment. For this purpose, the Susan G. Komen Tissue Bank at the IU Simon Comprehensive Cancer Center (KTB) serves as the world’s primary repository for normal breast tissue and blood samples from healthy women (~5,500 tissue + blood donors and ~4,500 blood-only donors). In addition, KTB has received mammograms, H&E images and additional longitudinal health and wellness data from its donors via ongoing annual surveys. Whole genome sequencing has also recently been completed on a subset of 500 donors, including ~125 initially healthy donors who later went on to develop breast cancer. To make these disparate, multi-modal data accessible to the larger research community and add advanced precision health analytics capabilities to the KTB database, LifeOmic's Precision Health Cloud (PHC), a secure healthcare-compliant cloud platform, was chosen to host the KTB data moving forward. The PHC provides browsing and querying capabilities across all data including genomic, demographic, histology, donor surveys, and scanned images. Data from donors can be viewed individually as well as analyzed across cohorts of interest. Computation resources, such as informatics workflows and machine learning infrastructure, are available on the same secure environment to leverage the power of cloud computing without having to download large files. This is in addition to visual and custom analytics using Jupyter Notebooks accessible to collaborators. Methods: We loaded all available KTB data from ~10,000 donors into the PHC. Donor-reported data collected at the time of donation and subsequent follow-up questionnaire responses were loaded as FHIR Observations and Medications in the PHC. Additional imaging and genomic data loaded into the PHC include approximately 12,000 mammogram images, 5,000 H&E images, 5,000 ancestry-informative genotypes and 500 VCF and BAM files from whole genome sequencing. A timeline view of each donor shows data collected from each donation and follow-up surveys. All genetic variants were annotated upon ingestion into the PHC with functional effect on genes, population allele frequency, ClinVar clinical significance and in silico predictions for functional impact. Results: To demonstrate the utility of KTB data hosted in the PHC, we will show how the PHC can be used to directly analyze genomic and donor-reported data, specifically focusing on the recent whole genome sequencing data from 500 donors. Whole genome sequencing data will be used to calculate the genetic ancestry of each donor compared to their self-reported ancestry and previously predicted ancestry from a 41-SNP ancestry panel. Additionally, we will calculate genomewide breast cancer polygenic risk scores and compare these with the survey-based Tyrer-Cuzick and Gail score risk measures. We will assess how the polygenic risk score further stratifies the donors that have germline pathogenic variants in a known breast cancer gene. For the ~125 sequenced donors that went on to develop breast cancer we will also investigate correlations between family history of cancer, age of diagnosis, prior gynecological history and lifestyle differences. All generated results will remain in the PHC for access by future KTB collaborators to continue to build the utility and value of the KTB data. Conclusions: We have shown how hosting KTB data in the PHC opens new opportunities for advanced precision health research for breast cancer researchers worldwide. As more specimens and diverse data sets including genomic, longitudinal and imaging information are being tracked and deposited into KTB, this resource will continue to grow to enable diverse research needs. Citation Format: Steven M Bray, Swee Seong Wong, Baiju G Parikh, Kevin C Wood, Samuel T Rysdyk, Jill E Henry, Natascia Marino, Milan Radovich, Anna Maria V Storniolo. Advanced precision health resources in the Susan G Komen tissue bank at the IU simon comprehensive cancer center [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS11-14.

Background: The PI3K pathway is dysregulated in the majority of triple-negative breast cancer (TNBCs), yet single agent inhibition of PI3K in TNBC has minimal clinical activity. We previously reported that PI3K inhibition leads to an immediate compensatory up-regulation of the Wnt pathway. Dual targeting of both pathways is highly synergistic against TNBC models in vitro and in vivo. We initiated a Phase I clinical trial of gedatolisib, a pan-class I isoform PI3K/mTOR inhibitor, and cofetuzumab pelidotin, an antibody-drug conjugate against the cell-surface PTK7 protein (Wnt pathway co-receptor) with an auristatin payload. PTK7 is up-regulated after PI3K inhibition and auristatin is in itself synergistic with gedatolisib providing the potential for a dual mechanism of synergy. Methods: Dose escalation proceeded using a traditional 3+3 schema with a small expansion cohort at the final dose level to better characterize safety. Participants had metastatic TNBC or ER low (ER and PgR Results: Between January 2018 and January 2020, 18 patients were enrolled in 3 dose cohorts: gedatolisib (qw) & cofetuzumab pelidotin (q3w) 110mg+1.4mg/kg (n=4), 180mg+1.4mg/kg (n=3), and 180mg+2.8mg/kg dose levels (n=11). The median age was 53 years (32-77). Nausea (n=16), anorexia (n=13), fatigue (n=12), and mucositis (n=12) were common but rarely reached >Grade 3 severity (nausea, n=1; fatigue, n=2). Myelosuppression was uncommon (Grade >3 neutropenia, n=2). 16 participants were evaluable for response. 3 achieved a confirmed partial response (PR), and 3 had stable disease (SD). ORR=18.8%. All 3 PRs lasted > 6 months. CB18=31.3%. Median PFS was 2.0 months (95% CI for PFS:1.2-6.2); median OS was 9.5 months (95% CI for OS:4.3-not reached). Correlative analyses of genomic, transcriptomic, and protein biomarkers with response are currently ongoing. Conclusions: The combination of gedatolisib + cofetuzumab pelidotin for the treatment of metastatic TNBC was found to be well tolerated and demonstrated promising clinical activity. Further investigation of this drug combination in metastatic TNBC is warranted. Trial Registration: NCT03243331 Citation Format: Milan Radovich, Jeffrey P. Solzak, Bradley A. Hancock, Sunil Badve, Anna Maria V. Storniolo, Tarah J. Ballinger, Bryan P. Schneider, Kathy D. Miller. An initial safety study of gedatolisib plus cofetuzumab pelidotin for metastatic triple-negative breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS10-26.

Background: A mouse model for thymoma was previously created serendipitously by the random introduction of a transgene consisting of a mouse α-cardiac promoter, a constitutively active human transforming growth factor-β, and a simian virus 40 integration sequence into C3HeB/FeJ mice. Previous data demonstrated that the likely cause of thymomas in the thymoma mouse model was due to insertional mutagenesis by the transgene. At the time, fluorescence in situ hybridization was used to localize the transgene to the short arm of chromosome 2 (Chr2qF2-G region). In this exploratory study, we aimed to identify the exact insertion site of the transgene as this could provide clues to the genetic causation of thymomas in humans. Materials and Methods: To identify the insertion site of the transgene, germline DNA from the thymoma mouse model was sequenced using low-pass, fragment-library, whole genome sequencing. Long-insert mate pair whole genome sequencing was employed to traverse the repetitive regions of the mouse’s genome and identify the integration site. Results: The transgene was found to be integrated into a repetitive area of the mouse genome, specifically on Chr2qF1 within the intron of the FAM227B gene. Tandem integration of the transgene was observed with enumeration of an estimated 30 copies. Initial results suggested that a nearby gene, fibroblast growth factor 7 (Fgf7), could be affected by the gene insertion. Conclusions: Whole genome sequencing of this thymoma mouse model identified the region of tandem integration of a transgene on Chr2qF1 that may have potential translational implications in helping to understand the genomic etiology of thymoma in humans.

PURPOSE Identification of incidental germline mutations in the context of next-generation sequencing is an unintended consequence of advancing technologies. These data are critical for family members to understand disease risks and take action. PATIENTS AND METHODS A retrospective cohort analysis was conducted of 1,028 adult patients with metastatic cancer who were sequenced with tumor and germline whole exome sequencing (WES). Germline variant call files were mined for pathogenic/likely pathogenic (P/LP) variants using the ClinVar database and narrowed to high-quality submitters. RESULTS Median age was 59 years, with 16% of patients ≤ 45 years old. The most common tumor types were breast cancer (12.5%), colorectal cancer (11.5%), sarcoma (9.3%), prostate cancer (8.4%), and lung cancer (6.6%). We identified 3,427 P/LP variants in 471 genes, and 84% of patients harbored one or more variant. One hundred thirty-two patients (12.8%) carried a P/LP variant in a cancer predisposition gene, with BRCA2 being the most common (1.6%). Patients with breast cancer were most likely to carry a P/LP variant (19.2%). One hundred ten patients (10.7%) carried a P/LP variant in a gene that would be recommended by the American College of Medical Genetics and Genomics to be reported as a result of clinical actionability, with the most common being ATP7B (2.7%), BRCA2 (1.6%), MUTYH (1.4%), and BRCA1 (1%). Of patients who carried a P/LP variant in a cancer predisposition gene, only 53% would have been offered correct testing based on current clinical practice guidelines. Of 471 mutated genes, 231 genes had a P/LP variant identified in one patient, demonstrating significant genetic heterogeneity. CONCLUSION The majority of patients undergoing clinical cancer WES harbor a pathogenic germline variation. Identification of clinically actionable germline findings will create additional burden on oncology clinics as broader WES becomes common.

Introduction: Triple negative breast cancer (TNBC) is a devastating disease responsible for a higher rate of morbidity and mortality compared to all other breast cancer subtypes. With few effective treatments, many have moved towards combination therapies. Using a genomically driven methodology, we show that Nuclear Protein 1 (NUPR1) is upregulated and activated in response to several targeted therapies and to standard chemotherapy. In this work, we show that targeting NUPR1 in conjunction with targeted therapies or paclitaxel, results in synergistic combinations. Methods: To evaluate a cohort of individuals with TNBC, 58 tumors were analyzed pre- versus post-chemotherapy using Ingenuity Pathway Analysis (IPA, Qiagen) after whole transcriptome sequencing. Six TNBC cell lines were utilized for in vitro work to reflect the heterogeneity of disease presentation. Four targeted therapies (Dasatinib, Erlotinib, Everolimus, and Trametinib) were chosen based on prior data suggesting activation of SRC, EGFR, mTOR, and MEK1/2 in TNBC respectively. Paclitaxel was used as the standard chemotherapy. IC50s were calculated using standard log dose escalations and Prism 7 (GraphPad). Next, whole transcriptome sequencing and pathway analysis using IPA was performed on treated cells at their designated IC50s for each drug and compared to vehicle controls. Trifluoperazine (TFP, a small molecule inhibitor of NUPR1) combined with targeted therapies and paclitaxel experiments were completed on TNBC cell lines and CI values were determined using the Chou-Talalay method. To observe the effects of NUPR1 inhibition, a NUPR1 siRNA was utilized in combination with paclitaxel at increasing doses with mock transfected cells for control. Results: We observed NUPR1 activation and RNA overexpression in all six cell lines treated with four targeted therapies. Combining the RNA sequencing analysis of these cell lines and focusing on common responses, NUPR1 was in the top three responses across all treatments. Our analysis of TNBC patient tumors (N=58) before and after chemotherapy resulted in observing an activation of NUPR1 (p=5.32E-10). In experiments on TFP combined with targeted therapies or paclitaxel, we observed CI values across cell lines ranging from .45-.90 denoting synergy. Experiments performed that knocked down NUPR1 with a siRNA displayed similar significant synergy with paclitaxel. Further, targeted therapy experiments where TFP was kept at its respective IC50 for each cell line, we saw a significant decrease in the IC50 of the primary therapeutic. Conclusion: Heterogeneous cell lines treated with targeted therapies as well as patients treated with chemotherapy demonstrate upregulation of the somatic pathway governing NUPR1. Targeting NUPR1’s ability to communicate using TFP in combination with targeted therapies or paclitaxel increased the potency of both treatment strategies. Further in vivo experiments testing these combinations, utilizing a precision medicine philosophy, are an obligate next step. Citation Format: Jeffrey P Solzak, Chao Wang, Brad Hancock, Milan Radovich. Targeting a common drug compensation pathway using NUPR1 inhibition in triple negative breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-10-12.

PURPOSE Precision medicine approaches, including germline pharmacogenetics (PGx) and management of drug-drug interactions (DDIs), are likely to benefit patients with advanced cancer who are frequently prescribed multiple concomitant medications to treat cancer and associated conditions. Our objective was to assess the potential opportunities for PGx and DDI management within a cohort of adults with advanced cancer. METHODS Medication data were collected from the electronic health records for 481 subjects since their first cancer diagnosis. All subjects were genotyped for variants with clinically actionable recommendations in Clinical Pharmacogenetics Implementation Consortium guidelines for 13 pharmacogenes. DDIs were defined as concomitant prescription of strong inhibitors or inducers with sensitive substrates of the same drug-metabolizing enzyme and were assessed for six major cytochrome P450 (CYP) enzymes. RESULTS Approximately 60% of subjects were prescribed at least one medication with Clinical Pharmacogenetics Implementation Consortium recommendations, and approximately 14% of subjects had an instance for actionable PGx, defined as a prescription for a drug in a subject with an actionable genotype. The overall subject-level prevalence of DDIs and serious DDIs were 50.3% and 34.8%, respectively. Serious DDIs were most common for CYP3A, CYP2D6, and CYP2C19, occurring in 24.9%, 16.8%, and 11.7% of subjects, respectively. When assessing PGx and DDIs together, approximately 40% of subjects had at least one opportunity for a precision medicine–based intervention and approximately 98% of subjects had an actionable phenotype for at least one CYP enzyme. CONCLUSION Our findings demonstrate numerous clinical opportunities for germline PGx and DDI management in adults with advanced cancer.

The identification of cancer-predisposing germline variants has potentially substantial clinical impact for patients and their families. Although management guidelines have been proposed for some genes, guidelines for other genes are lacking. This review focuses on the current surveillance and management guidelines for the most common hereditary cancer syndromes and discusses some of the most pivotal studies supporting the available guidelines. We also highlight the gaps in the identification of germline carriers, the cascade testing of at-risk relatives, and the challenges impeding the proper follow-up and optimal management of pathogenic germline carriers. The anticipated surge in the number of identified germline carriers, deficient management guidelines, poor cascade testing uptake, and long-term follow-up necessitate the development of multidisciplinary clinics as an obligatory step toward the improvement of cancer prevention.

Background/Objective: Antibody drug conjugates (ADCs) deliver potent cytotoxic therapy in a highly targeted manner by binding cancer-specific cell surface antigens. HER2 is a receptor tyrosine kinase that is commonly amplified in breast and gastric cancers, but more recently has been shown to harbor gain-of-function activating mutations in several cancer types. Recent observations have suggested that HER2-ADCs may be viable therapies for patients that harbor these activating mutations. This research retrospectively explores the efficacy of HER2-ADCs in metastatic cancer patients in a real-world setting. Methods: Patient information was gathered from the Precision Genomics program at IU Health, narrowed for specific mutation criteria (HER2 pathogenic mutation), cross referenced with OncoKB to legitimize oncogenicity, and selected for patients prescribed HER2-ADCs. For these patients, pre-treatment and mid-treatment CT-scans were analyzed following RECIST protocols. The primary outcomes were overall response rate (ORR), clinical benefit rate (CBR), and progression free survival (PFS). Secondary outcomes were to tabulate the frequency and clinical characteristics of HER2-mutated tumors. Results: Out of 517 patients with somatic HER2 mutations, 60 patients had a pathogenic HER2 mutation. Of these 60 patients, the most common tumor types were 26.67% Breast and 11.67% Bladder/Urothelial. 11 of 60 patients were prescribed a HER2-ADC (Trastuzumab Emtansine = 10, Trastuzumab Deruxtecan = 1). 8 of 11 patients were evaluable for response with RECIST criteria with 1 patient having a partial response, 4 patients having stable disease and 3 patients having progressive disease. ORR=13%, CBR=63%, Median PFS = 2.77 months (95% CI: 2.15-3.39 months). Conclusion/Implications: To our knowledge, this is the first report of HER2-ADCs demonstrating clinical activity in HER2-mutated cancers across tumor types. Further clinical trials are ongoing that will validate these initial findings.

Prediction of cancer-specific drug responses as well as identification of the corresponding drug-sensitive genes and pathways remains a major biological and clinical challenge. Deep learning models hold immense promise for better drug response predictions, but most of them cannot provide biological and clinical interpretability. Visible neural network (VNN) models have emerged to solve the problem by giving neurons biological meanings and directly casting biological networks into the models. However, the biological networks used in VNNs are often redundant and contain components that are irrelevant to the downstream predictions. Therefore, the VNNs using these redundant biological networks are overparameterized, which significantly limits VNNs’ predictive and explanatory power. To overcome the problem, we treat the edges and nodes in biological networks used in VNNs as features and develop a sparse learning framework ParsVNN to learn parsimony VNNs with only edges and nodes that contribute the most to the prediction task. We applied ParsVNN to build cancer-specific VNN models to predict drug response for five different cancer types. We demonstrated that the parsimony VNNs built by ParsVNN are superior to other state-of-the-art methods in terms of prediction performance and identification of cancer driver genes. Furthermore, we found that the pathways selected by ParsVNN have great potential to predict clinical outcomes as well as recommend synergistic drug combinations.