Pathak, Harsh B.

505 Background: SWOG S1007 was a phase 3 randomized trial to evaluate the benefit of endocrine therapy alone (ET) or with chemotherapy (CET) in pts with HR+/HER2- invasive breast cancer with recurrence score (RS) ≤ 25. There was no invasive disease-free survival (IDFS) benefit for CET compared to ET in postmenopausal women However, in premenopausal women CET had an IDFS improvement compared to ET (HR=0.60; 95% 0.43-0.83). The objective was to further refine patient subgroups who benefit from CET, we measured baseline hormone levels in S1007 pts to quantify their menstrual status by serum hormone levels and associated clinical outcomes. Methods: Serum estradiol (E), progesterone (P), follicular stimulating hormone (FSH), luteinizing hormone (LH), anti-Müllerian hormone (AMH), and inhibin B (IB) were assessed on baseline serum samples from 1,015 pts who self-reported being premenopausal and age < 55. Magnetic fluorescent bead-based immunoassays ( i.e., Luminex assays) or colorimetric ELISAs were performed at the Biomarker Discovery Laboratory at the University of Kansas Medical Center to measure hormone levels. Associations of the markers (both continuous and dichotomized) with IDFS and distant relapse-free survival (DRFS) were tested for prognosis and prediction of CET benefit using Cox regression. Results: Single baseline measurement of IB, P, E, LH, FSH, or combination of E/LH/FSH, was not prognostic for IDFS or predictive for chemotherapy benefit. However, AMH levels (≥10 pg/mL) showed significant interaction with chemotherapy benefit (p=0.019), and risk increased with continuous AMH with ET alone, but not CET (p=0.03). Compared to ET alone, CET was beneficial in the 79% of premenopausal patients with AMH levels ≥10 pg/mL, a standard cutoff to define normal ovarian reserve (HR=0.48; 95% 0.33-0.69, adjusting for RS). CET was not beneficial in the 21% with AMH < 10 (HR=1.21; 95% 0.60-2.43). Absolute 5-year IDFS benefit of CET for RS ≤ 25 was 7.8% (95.2%-87.4%) for AMH ≥ 10 vs. -1.7% (89.1%-90.8%) for AMH < 10. DRFS showed a similar pattern with CET benefit in AMH ≥10 pg/mL (5-year DRFS benefit: 4.4%; HR=0.41; 95% 0.25-0.68, adjusting for RS) and no benefit in AMH < 10 (5-year DRFS benefit: -0.9%, HR=1.50; 95% 0.62-3.63). Conclusions: Among self-reported premenopausal patients < age 55, pts with baseline serum AMH levels ≥10 pg/mL showed significant benefit from CET compared to patients with AMH levels <10 pg/mL. AMH levels were a better indicator of CET benefit than self-reported menopause status, age, or E/LH/FSH levels. Use of AMH-based selection of patients may inform who most benefits from the addition of adjuvant chemotherapy to ET. Clinical trial information: NCT01272037 .

Abstract Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer death among women in the United States (5% of cancer deaths). The standard treatment for patients with advanced EOC is initial debulking surgery followed by carboplatin-paclitaxel combination chemotherapy. Unfortunately, even with modern chemotherapy, most patients relapse and die with the five-year overall survival around 45%. In addition, those patients that initially respond to taxane-platinum therapy eventually develop platinum-resistant tumors and relapse. Thus, finding novel therapeutics for treating EOC is essential. One approach that has been used widely in cancer drug discovery is Connectivity Mapping (CMAP) using gene expression data and drug phenotype data assessed on cancer cell lines (CCL) (i.e. “sensitive” or “resistant” based on dose-response drug data). However, recent publications have highlighted some issues with the use of these standard CCL sets that are often used in these drug screening studies. Therefore, instead of CMAP analysis based on gene expression signatures developed on drug response data collected on a small set of EOC cell lines, we took a novel CMAP approach based on information collected on EOC patients and clinical endpoints. That is, we determined the gene expression signature (e.g., set of genes) that were associated with time to recurrence in data collected on EOC patients within TCGA (n = 518) and a Mayo Clinic study (n = 474). The set of genes associated with time to recurrence (with and without adjustment for additional clinical covariates) was completed separately for TCGA and Mayo Clinic studies, restricting all analyses to EOC tumor of high-grade serous histology. Each of these 4 sets of genes, where genes with hazard ratios (HR) &gt; 1 coded as “positively” associated and genes with HR &lt; 1 coded as “negatively” associated with the phenotype, were inputted into CMAP software (Broad Institute) to determine a set of drugs for which our signature “matches” the “reference” signature. The drugs that overlapped between the CMAP analyses on the two studies were carried forward for validation studies involving drug screens on a set of 10 EOC cell lines. Of the 11 drugs carried forward, we a priori hypothesized that 5 of these drugs would kill EOC cells (mitoxantrone, podophyllotoxin, wortmannin, doxorubicin, and 17-AAG), for which all 5 showed an ability to kill EOC cells in vitro (cell lines were treated using serial dilutions of the drugs (20-0 μM) for 72 h followed by measuring cell viability using the CellTiter-Blue assay). Further research is on-going to understand the functional mechanism by which these candidate drugs might treat EOC and to apply this bioinformatics approach to other cancer drug screening studies. Note: This abstract was not presented at the meeting. Citation Format: Brooke L. Fridley, Rama Raghavan, Gottfried E. Konecny, Chen Wang, Ellen L. Goode, Harsh B. Pathak, Stephen Hyter. A bioinformatics approach to drug discovery: patient based connectivity mapping. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4853. doi:10.1158/1538-7445.AM2015-4853

Abstract The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with the risk of ovarian cancer. Here, we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 OR, 1.10; 95% confidence interval (CI), 1.05–1.15; P = 3.49 × 10−5] and triple-negative (ER-, PR-, and HER2-negative) breast cancer (rs8170: OR, 1.22; 95% CI, 1.13–1.31; P = 2.22 × 10−7). However, rs8170 was no longer associated with ER-negative breast cancer risk when triple-negative cases were excluded (OR, 0.98; 95% CI, 0.89–1.07; P = 0.62). In addition, a combined analysis of triple-negative cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC; N = 3,566) identified a genome-wide significant association between rs8170 and triple-negative breast cancer risk (OR, 1.25; 95% CI, 1.18–1.33; P = 3.31 × 10−13]. Thus, 19p13.1 is the first triple-negative–specific breast cancer risk locus and the first locus specific to a histologic subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple-negative tumors and other subtypes likely arise through distinct etiologic pathways. Cancer Res; 72(7); 1795–803. ©2012 AACR.

Abstract Triple-negative breast cancers are an aggressive subtype of breast cancer with poor survival, but there remains little known about the etiologic factors that promote its initiation and development. Commonly inherited breast cancer risk factors identified through genome-wide association studies display heterogeneity of effect among breast cancer subtypes as defined by the status of estrogen and progesterone receptors. In the Triple Negative Breast Cancer Consortium (TNBCC), 22 common breast cancer susceptibility variants were investigated in 2,980 Caucasian women with triple-negative breast cancer and 4,978 healthy controls. We identified six single-nucleotide polymorphisms, including rs2046210 (ESR1), rs12662670 (ESR1), rs3803662 (TOX3), rs999737 (RAD51L1), rs8170 (19p13.1), and rs8100241 (19p13.1), significantly associated with the risk of triple-negative breast cancer. Together, our results provide convincing evidence of genetic susceptibility for triple-negative breast cancer. Cancer Res; 71(19); 6240–9. ©2011 AACR.