Citations

Abstract Background: Genome wide association studies (GWAS) have recently identified 8 loci identified with multiple myeloma (MM) susceptibility. We hypothesized that germ line genetic variants may also affect MM progression. We performed the first GWAS of MM survival, by conducting a meta-analysis of two existing studies at University of California San Francisco (UCSF) and the Mayo Clinic, and replicating findings in the International Multiple Myeloma rESEarch (IMMEnSE) consortium. Methods: The UCSF study included 353 MM patients genotyped on an Illumina Omni5 and Illumina 660 array. The Mayo clinic study included 239 MM patients genotyped on an Affymetrix 6.0 array. We imputed missing genotypes using the 1000 Genomes dataset and performed a GWAS for survival using proportional hazards models adjusting for age and gender and genetic ancestry using principal components analysis. We conducted a meta-analysis of the results from the two GWAS. We replicated the top SNPs in the IMMEnSE cohort which included 772 patients with survival data from 7 European countries and one North American site. We used the dataset from Grundberg et al (Nat Genetics 2012) to test for an association between SNPs associated with survival and gene expression in immortalized lymphocytes. We used gene expression data from Zhan et al (Blood 2006) to analyze the association between expression and survival. Results: In meta-analysis, we found a genome wide significant association between SNPs on a region at 16p13 and survival (rs72773978; p=2.9x10e-10). Patients with the minor allele were at increased risk for mortality (HR 2.73; 95% CI: 1.99 - 3.73). The top associated SNPs were all in strong linkage disequilibrium and were centered over the gene FOPNL. We replicated the association in the IMMEnSE cohort and found a significant association between the top SNP from the discovery dataset (rs72773978 p=0.037). We used previously published data to determine the association between gene expression and the top associated SNPs from the GWAS. The top SNP (rs72773978) was not in previously published eQTL databases, so we used rs7201759 which was also associated with survival in our data (p=3.8x10e-10) as a proxy. The minor allele for this SNP was associated with increased levels of expression of FOPNL (p=9x10e-5), but not with expression of any other genes within a 1 megabase region. Finally, we also observed an association between increased expression of FOPNL and shorter survival (HR: 2.62 per standard deviation.; 95% CI: 1.08 - 6.32). Conclusion: Germ line variants at 16p13 near the FOPNL gene are associated with survival among MM patients. FOPNL is thought to be involved in centrosomal function, and centrosomal activity has previously been associated with survival in MM patients. Our results support this previous observation. Furthermore, they suggest that germ line variants could also be useful in assessing prognosis for patients with MM. Citation Format: Elad Ziv, Eric Dean, Donglei Hu, Alessandro Martino, Daniel Serie, Daniele Campa, Blake Aftab, Paige Bracci, Gabriele Buda, Jennifer Caswell, Charles Dumontet, Marek Dudziński, Laura Fejerman, Alexandra Greenberg, Scott Hunstman, Artur Jurczyszyn, Krzysztof Jamroziak, Shaji Kumar, Herlander Marques, Thomas Martin, Joaquin Martinez-Lopez, Vincent Rajkumar, Juan Sainz, Annette Juul Vangsted, Marzena Watek, Jeffrey Wolf, Susan Slager, Federico Canzian, Celine Vachon. Genome wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5078. doi:10.1158/1538-7445.AM2014-5078

Abstract Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score <-0.154. MP1/MP2 classification was added to HR and HER2 to define the cancer subtypes used in the I-SPY 2 adaptive randomization engine. Neratinib (N), one of the experimental agents evaluated in I-SPY 2, graduated in the HR-HER2+ signature. All patients received at least standard chemotherapy (paclitaxel followed by doxorubicin/cyclophosphamide; T->AC). HER2- patients were randomized to receive N+T- >AC vs. T->AC. For HER2+ patients, neratinib was administered in place of trastuzumab (N+T->AC vs. H+T->AC). Here, we assess the performance of MP1/MP2 class as a specific biomarker of neratinib response. Methods: 115 patients in the neratinib arm and 76 concurrently randomized controls had Agilent 44K microarrays and pCR data available for analysis. We assess association between MP1/MP2 and response in the neratinib and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p < 0.05) using a logistic model. This analysis is also performed adjusting for HR status as a covariate, and in receptor subsets. Our study is exploratory with no claims for generalizability of the data. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). Our analyses do not adjust for multiplicities of other biomarkers in the trial but outside this study. Results: There are 133 MP1 patients (neratinib: 74, Control: 59) and 58 MP2 patients (neratinib: 41, Control: 17), 84% (49) of which are Her2-. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. Neratinib (n=115)Control (n=76)MP1 (n=74)MP2 (n=41)MP1 (n=59)MP2 (n=17)HER2- (n=105)0 / 1715 / 337 / 395 / 16HER2+ (n=86)22 / 574 / 85 / 200 / 1 MP2, one of the 10 eligible signatures, did not meet the graduation threshold; and MP1/MP2 did not show a significant biomarker x treatment interaction (OR in neratinib relative to control arm = 1.25). The MP1/MP2 x treatment interaction remains non-significant after adjustment for HR and HER2 status (p=0.54). In HER2- patients receiving neratinib, 45% (15/33) of MP2 patients achieved a pCR, compared to 0% (0/17) of MP1 patients. In the HER2- controls, there is a 31% pCR rate in MP2 (5/16) vs. 18% in MP1 (7/39) patients (OR=2.14). This difference in performance between treatment arms appears significant (p=0.041). 90% of HER2+ patients are MP1, thus MP1/MP2 status x treatment interaction within the HER2+ subtype cannot be evaluated. Conclusion: Within the I-SPY 2 population as a whole, MP1/MP2 stratification does not appear to be a specific biomarker of response to neratinib relative to the control arm. The number of HER2- patients is small and precludes any definitive conclusion, but these data motivate further investigation of the biological mechanisms distinguishing MP1 from MP2 to better understand chemotherapy and/or neratanib responsiveness. Citation Format: Christina Yau, Denise M Wolf, Ashish Sanil, Jo Chien, Anne Wallace, Judy Boughey, Doug Yee, Debu Tripathy, Angela DeMichele, Rita Nanda, Steven Chiu, Claudine Isaacs, Kathy Albain, Hank Kaplan, Stacey Moulder, Rebecca Viscusi, Donald Northfelt, Kirsten Edmiston, Anthony Elias, Toncred Styblo, Barbara Haley, Lamorna Brown-Swigart, Susan Flynn, Gillian L Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, W Fraser Symmans, Laura Esserman, Don Berry, Minetta C Liu, John W Park, Laura van 't Veer. MammaPrint High1/High2 risk class as a biomarker of response to neratinib plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-29.

Abstract Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score <-0.154. MP1/MP2 classification was added to HR and Her2 to define the cancer subtypes used in the I-SPY 2 adaptive randomization engine. HER2- patients were randomized to receive standard chemotherapy or the oral PARP inhibitor veliparib in combination with carboplatin (V/C) and chemotherapy. V/C graduated in the triple-negative (TN) signature, where MP2 was not an eligible signature for graduation. Here, we assess the performance of MP1/MP2 class as a specific biomarker of response to V/C. Methods:115 HER2- patients (V/C: 71 and concurrent controls: 44) were considered in this analysis. We assess association between MP1/MP2 and response in the V/C and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p < 0.05) using a logistic model. This analysis is also performed adjusting for HR status as a covariate. To assess MP1/MP2 in the context of the graduating signature, we added the MP2 patients to the graduating TN subset and evaluated the treatment effect in this ‘biomarker-positive’ group. Our study is exploratory with no claims for generalizability of the data. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). This analysis does not adjust for multiplicities of other biomarkers in the trial but outside this study. Results: In the V/C arm vs. concurrent controls, there were 66 MP1 (V/C: 32, Control: 34) and 49 MP2 patients (V/C: 39, Control: 10), 78% of which are TN. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. V/C (n=71)Control (n=44)MP1 (n=32)MP2 (n=39)MP1 (n=34)MP2 (n=10)TN (n=59)3 / 819 / 303 / 132 / 8HR+HER2- (n=56)1 / 244 / 94 / 210 / 2 The OR between MP1/MP2 risk groups for predicting pCR is 9.71 in the V/C arm (p=6.63E-05), in comparison to an OR of 0.97 in the control arm (p=1). There is a significant biomarker x treatment interaction (p=0.023), which remains upon adjusting for HR status (p= 0.028). Based on the I-SPY 2 Bayesian model, a Phase III trial with 300 MP2 patients has a 95% predictive probability of success. When the MP2 patients are added to the graduating TN subset, the OR associated with V/C is 4.36, which is comparable to that of the TN signature (OR: 4.29), while increasing the prevalence of biomarker-positive patients by ∼10%. Conclusion: In our exploratory analysis, MP2 suggests higher sensitivity to V/C combination therapy relative to controls. This observation has prompted an investigation into the biological mechanisms distinguishing the MP1/MP2 subtype that may account for this specificity. Citation Format: Denise M Wolf, Christina Yau, Ashish Sanil, Jo Chien, Anne Wallace, Angela DeMichele, Hank Kaplan, Doug Yee, Claudine Isaacs, Kathy Albain, Rebecca Viscuzi, Judy Boughey, Stacey Moulder, Steven Chui, Qamar Khan, Toncred Styblo, Kirsten Edmiston, Donald Northfelt, Anthony Elias, Barbara Haley, Debu Tripathy, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, Fraser Symmans, Laura Esserman, Don Berry, Hope Rugo, Olufunmilayo I. Olopade, Laura van 't Veer. MammaPrint High1/High2 risk class as a biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-25.

Abstract Background: We hypothesize that response to the pan-ERBB inhibitor, neratinib (N), may be predicted by pre-treatment HER2-EGFR signaling. In the I-SPY 2 TRIAL, N graduated in the HR-/HER2+ signature. All patients received at least standard chemotherapy. For HER2+ patients, N was administered in place of trastuzumab. We evaluated 18 HER family signaling proteins as biomarkers of N response using reverse phase protein microarray (RPMA) data from pre-treatment LCM purified tumor epithelium. Methods: 168 patients (N: 106, concurrent controls: 62) had RPMA and pCR data. 18 biomarkers relating to HER family signaling were evaluated: AKT S473, AKT T308, EGFR, EGFR Y1068, EGFR Y1148, EGFR Y1173, EGFR Y992, ERBB2, ERBB2 Y1248, ERBB3 total, ERBB3 Y1289, ERK1/2 T202/Y204, Heregulin, mTOR, mTOR S2448, PI3K p85 Y458/p55 Y199, PTEN S380, and SHC Y317. We assessed association between biomarker and response in the N and control arms alone (likelihood ratio test), and relative performance between arms (biomarker x treatment interaction) using a logistic model. Analysis was also performed adjusting for HR/HER2 status. In an exploratory analysis, we selected the marker with the greatest interaction (phosphorylated EGFR (Y1173)) to dichotomize patients optimally based on the data and assessed it in the context of the graduating signature by adding the EGFR Y1173-High patients to the HR-/HER2+ subtype and evaluating the treatment effect in this ‘biomarker-positive’ group. Our study is exploratory with no claims for generalizability of the data and does not account for multiplicities. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). Results: 7 HER pathway markers (EGFR Y1068, EGFR Y1173, EGFR Y992, ERBB2 total, ERBB2 Y1248, ERBB3 Y1289, SHC Y317) are associated with response in the N but not the control arm. However, the difference in performance between arms did not reach significance by permutation testing. Adjusting for HR/HER2 status, EGFR Y1173 shows a significant biomarker x treatment interaction (p = 0.049). In an exploratory analysis, we dichotomized patients by their EGFR Y1173 levels and evaluated the distribution of pCR rates (Table 1). Neratinib (n=106)Control (n=62)EGFR Y1173 Low (n=31)EGFR Y1173 High (n=75)EGFR Y1173 Low (n=29)EGFR Y1173 High (n=33)HR-/HER2+ (n=28)0 / 412 / 181 / 11 / 5Not HR-/HER2+ (n=140)3 / 2724 / 575 / 285 / 28Table 1 OR between EGFR Y1173 groups in the N relative to control arm is 10.1. When EGFR Y1173 High patients are added to the graduating HR-/HER2+ subset, the OR associated with treatment is 3.2 and is comparable to that in the HR-/HER2+ signature (OR: 2.1), while increasing the prevalence of biomarker-positive patients by ∼50%. Evaluation of EGFR Y1173 under the I-SPY 2 Bayesian model is pending. Conclusion: Our sample size is too small to draw definitive conclusions. Our exploratory analysis reveals that HER family phosphoproteins associate with response to N, but only phosphorylated EGFR Y1173 appears to add value to the graduating signature. Given that this biomarker would expand the patient population that may benefit, it merits evaluation in other ongoing trials of neratinib. Citation Format: Julia D Wulfkuhle, Christina Yau, Denise M Wolf, Rosa I Gallagher, Ashish Sanil, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, I-SPY 2 TRIAL Investigators, Meredith Buxton, Angela DeMichele, Nola Hylton, William F Symmans, Laura van't Veer, Douglas Yee, Melissa Paoloni, Laura Esserman, Donald Berry, Minetta C Liu, John W Park, Emanuel F Petricoin III. Evaluation of HER family protein signaling network as a predictive biomarker for pCR for breast cancer patients treated with neratinib in the I-SPY 2 trial [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-15.

Abstract Introduction: A significant number of histologically triple negative breast cancer (TNBC) cells express substantial estrogen receptor (ER) mRNA but do not express ER protein as a result of rapid proteolytic degradation. Here we assessed whether proteasome inhibitors could sensitize such cells to tamoxifen-induced growth suppression. Methods: Data from the Katzenellenbogen laboratory elegantly demonstrate that in high ER mRNA MDA-MB-468 cells, ER protein is rapidly degraded via proteosomal degradation (Bhatt et al. MCB, 2012).Utilizing established human TNBC cell lines that express high ER mRNA (BT-20, MDA-MB-468, and newly established human TNBC cell lines from our laboratory MCJB2 and MCJB11), we defined a therapeutic strategy using the proteasome inhibitor carfilzomib in combination with the antiestrogen tamoxifen that demonstrates antitumor synergy. Results: We found that administration of carfilzomib in TNBC cell lines with high ER mRNA restored ER protein expression, and that combining this treatment with tamoxifen treatment led to enhanced growth suppression. We found that the TNBC MDA-MB-231 cells, which express no ER mRNA, show some growth suppression, but that tamoxifen provided no further growth suppression with these cells. We have previously shown that combined epigenetic therapy [methyltransferase inhibitor (decitabine) plus a histone deacetylase inhibitor (HDACi; romidepsin)] provided antitumor synergy in MDA-MB-231 cells via upregulation of the soluble Wnt suppressor, secreted frizzled protein 1 (sFRP1; Cooper et al. CCR, 2012). In addition, we show that this epigenetic therapy restores silenced ER mRNA and protein levels in MDA-MB-231 cells, and that combination of this epigenetic therapy with tamoxifen in MDA-MB-231 cells led to enhanced growth suppression by tamoxifen. We are currently testing these therapeutic strategies in vivo using established TNBC cell lines and our newly developed patient derived xenograft (PDX) mouse models that express either ERhigh or ERlow mRNA. Conclusions: If validated in animal models, we propose that ER mRNA expression level in TNBC patients could guide therapeutic choice, whereby, ERlow mRNA TNBC tumors could respond to epigenetic therapy followed by antiestrogen while ERhigh mRNA TNBC tumors could respond to a proteosome inhibitor followed by antiestrogen therapy. These results identify a novel epigenetic biomarker as predictive of therapeutic response. Citation Format: Christina A. von Roemeling, Laura A. Marlow, James Miller, Adam Mathias, Louis Dawson, Steadman Harrison, Beth A. Hollister, Derek C. Radisky, John Alton Copland. Estrogen receptor mRNA-directed therapy for triple-negative breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-95. doi:10.1158/1538-7445.AM2014-LB-95

Abstract Background: Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. Relatives of DLBCL patients are at elevated risk for DLBCL. In small genome-wide association studies (GWAS) in which all NHL subtypes were combined, no conclusive loci for DLBCL have been previously identified in individuals of European background, whereas a recent study conducted in East Asia identified a locus at 3q27. Methods: To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of three new GWAS and one prior scan, totaling 3,857 DLBCL cases and 7,666 controls of European ancestry. Imputation was used to combine all the data using the 1000 Genomes Project release v3 and IMPUTE2. Based on these findings, we selected 6 promising SNPs for genotyping in an additional 202 cases and 3,431 controls, which were then included in a second meta-analysis. SNPTEST was used to estimate odds ratios (ORs), using the additive model and adjusting for age, gender and significant eigenvectors. Results: In our multi-stage analysis, five independent SNPs in four loci achieved genome-wide significance marked by rs116446171 at 6p25.3 (EXOC2; OR=2.33, P=1.60x10-20), rs13255292 and rs4733601 at 8q24.21 (PVT1; OR=1.23, P=4.86x10-12 and OR=1.18, P=1.63x10-8, respectively), rs2523607 at 6p21.33 (HLA-B; OR=1.34, 3.35x10-9) and rs2681416 at 3q13.33 (CD86; OR=1.20, P=6.04x10-9). The two 8q24.21 SNPs displayed minimal linkage disequilibrium (r2=0.03) and conditional analysis supported their independence. We did not observe a notable signal for a locus previously reported for DLBCL on 3q27 in East Asia, rs6773854 (OR=1.06, P=0.81). We estimated that common SNPs, including but not limited to the loci discovered in this study, explain approximately 16% of the variance for DLBCL risk overall. Discussion: The susceptibility locus at 6p25.3 maps near a plausible DLBCL candidate gene, EXOC2 (exocyst complex component 2), which interacts with Ral proteins, and disruption of the Ral-exocyst regulatory node impacts cellular and developmental processes associated with malignant transformation and progression. The two 8q24.21 variants are approximately 1Mb telomeric to the 8q24 region linked with multiple cancers including CLL. Both variants are positioned in close proximity to PVT1, which is a non-coding RNA implicated in the MYC activation, and MYC is known to be deregulated in some DLBCLs. The locus at 3q13.33 maps to CD86 (B7-2), a B-7 family member that along with CD80 (B7-1) is essential in cognate interactions between T- and B-lymphocytes; both play key roles in immunodeficiency, autoimmune diseases, and in anti-tumor immunity. Finally, we had multiple signals in the HLA region, the strongest of which was at 6p21.33 near HLA-B. HLA-B encodes the HLA class I heavy chain paralogue, which heterodimerizes with a light chain (β2 microglobulin) and plays a central role in presenting intracellularly processed self or foreign antigens to CD8+ cytotoxic T lymphocytes. Class I molecules have been extensively linked to the risk of a variety of immune-mediated diseases and cancers including DLBCL. Conclusions: These data provide substantial new evidence for genetic susceptibility to this B-cell malignancy, and point towards pathways involved in immune recognition and immune function in the pathogenesis of DLBCL. Citation Format: James R. Cerhan, Sonja I. Berndt, Joseph Vijai, Hervé Ghesquières, James McKay, Sophia S. Wang, Zhaoming Wang, Meredith Yeager, Alexandra Nieters, David Cox, Alain Monnereau, Christopher Flowers, Anneclaire J. De Roos, Angela R. Brooks-Wilson, Qing Lan, Gianluca Severi, Mads Melbye, Rebecca D. Jackson, Lauren R. Teras, Mark Purdue, Claire Vajdic, Demetrius Albanes, Kimberly A. Bertrand, Anne Zeleniuch-Jacquotte, Simon Crouch, Yawei Zhang, Paolo Vineis, Susan L. Slager, Karin E. Smedby, Gilles Salles, Christine F. Skibola, Nathaniel Rothman, Stephen J. Chanock, on behalf of the NHL GWAS Project. Genome-wide association study identifies multiple susceptibility loci for diffuse large B-cell lymphoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-272. doi:10.1158/1538-7445.AM2014-LB-272

Abstract Introduction: Renal cell carcinoma (RCC) is the most common malignancy of the kidney, responsible for 13,000 deaths in the United States annually. Patients who present with the clear cell (ccRCC) variant of this disease demonstrate a worse prognosis as compared to other subtypes. Due to its asymptomatic nature, patients often do not demonstrate signs of illness until the disease has progressed to an advanced stage. It is estimated that 30% of patients present with metastatic disease at initial diagnosis, and 20-30% of patients with localized cases treated surgically relapse with metastatic disease likely due to the presence of undetectable micrometastases. The treatment for metastatic disease is limited due to its profound resistance against chemotherapy, radiation, and current FDA approved targeted therapies. Despite advances in treatment strategies for patients with metastatic RCC, there remains a need for identification of tumor-specific therapeutic targets. Additionally, elucidation of key signatures which contribute to the development of metastatic disease is paramount. Our group has identified secreted neuronal pentraxin 2 (NPTX2) as a novel oncogenic factor that is highly overexpressed specifically in ccRCC at all stages of disease, and facilitates tumor cell invasion through its interaction with the ionotropic glutamate receptor 4 subunit (GluR4). Methods: NPTX2 expression was evaluated by Affymetrix gene array and immunohistochemistry analysis of patient tumor tissue compared to matched normal samples. Nextbio meta-analysis was used to evaluate NPTX2 expression patterns among RCC subtypes and disease staging. Lentiviral mediated knock-down of NPTX2 and GluR4 was performed in representative ccRCC cell lines and resulting changes in proliferation, viability, morphology, and invasion were evaluated. NPTX2-GluR4 interactions were evaluated via immunoprecipitation, immunofluorescence, and intracellular calcium assays. Results: NPTX2 mRNA and protein is consistently elevated in the clear cell variant of RCC at all stages of disease, and is important for tumor cell viability. We correlate NPTX2 expression with an invasive phenotype, and demonstrate that over-expression of NPTX2 in tumor cells leads to actin cytoskeletal remodeling and increased invasion. We identify GluR4 as a mediator for NPTX2 activity which leads to increased intracellular calcium influx in tumor cells. Conclusions: NPTX2 is a tumor-specific factor that is consistently over-expressed in ccRCC. We further identify GluR4 as a downstream mediator of NPTX2 activity, whereby it modulates intracellular calcium levels, actin cytoskeletal remodeling, and tumor cell invasion. Inhibition of NPTX2 or GluR4 expression via shRNA leads to decreased tumor cell proliferation and invasion, and induces programed cell death. We propose NPTX2 as a new candidate for targeted therapy not previously described in cancer, whose inhibition may demonstrate a clinical benefit in patients suffering from metastatic ccRCC. Citation Format: Christina A. von Roemeling, Derek C. Radisky, Laura A. Marlow, Simon J. Cooper, Stefan K. Grebe, Panagiotis Z. Anastasiadis, Han W. Tun, John A. Copland. Neuronal Pentraxin 2: a novel tumor-specific molecular target that mediates clear cell renal cell carcinoma malignancy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-111. doi:10.1158/1538-7445.AM2014-LB-111

Abstract Background: I-SPY 2 is a multicenter, phase II neoadjuvant trial in women with high-risk stage II/III breast cancer using adaptive randomization within biomarker subtypes to evaluate novel agents added to standard chemotherapy. Primary endpoint is pathologic complete response (pCR). Goal is to identify regimens that meet a high Bayesian predictive probability of statistical significance in a neoadjuvant 300-patient phase III trial defined by hormone-receptor (HR), HER2 status, and MammaPrint (MP). Experimental regimens may “graduate” in 1 of 10 signatures, with a maximum of 120 patients. We report efficacy results for neratinib (N). Methods: Tumors ≥2.5cm by clinical exam & ≥2cm by imaging are eligible for screening. MP low risk/HR+/HER2- tumors are ineligible for randomization. Patients receive chemotherapy (paclitaxel qwk x 12, doxorubicin and cyclophosphamide q2-3 wk x 4, T->AC). HER2- pts were randomized to N+T->AC vs. T->AC and HER2+ pts to N+T->AC vs. trastuzumab+T->AC. Analysis is intent-to-treat with pts who switch to non-protocol therapy regarded as non-pCRs. We provide estimated pCR rates (95% Bayesian probability intervals), probabilities of superiority of neratinib over control, and Bayesian predictive probabilities of success in an equally randomized phase III trial. Results: Neratinib met the predictive probability criterion in HR-/HER2+, “graduated”, and accrual ceased [115 N patients (65 HER2+), 78 concurrently randomized controls (22 HER2+)]. The table shows results for all 10 signatures. Two patients (1 N and 1 control) withdrew consent and are not included. Conclusion: I-SPY 2's standing trial mechanism efficiently evaluates agents in biomarker-defined patient subsets. In a modest number of patients, adaptive randomization successfully identified a biomarker signature (HR-/HER2+) for neratinib's further development. All HER2+ and MP+ tumors may also benefit from this regimen, consistent with preclinical data. Evaluation in I-SPY 3, a phase III registration trial, is planned. SignatureEstimated pCR Rate (95% probability interval)Probability NeratinibIs Superior to ControlPredictive Probability of Success in Phase IIINeratinibControlALL32% (28-36%)23% (19%-28%)92%44%HR+23% (18%-28%)17% (11%-22%)81%40%HR-43% (37%-49%)31% (24%-38%)89%53%HER2+39% (33%-45%)23% (15%-30%)95%73%HER2-26% (21%-32%)24% (18%-29%)63%20%MP+*45% (38%-53%)29% (20%-39%)91%66%HR-/HER2-36% (29%-43%)30% (23%-38%)72%34%HR-/HER2+55% (46%-64%)32% (22%-43%)94%78%HR+/HER2+31% (24%-37%)17% (10%-24%)91%65%HR+/HER2-14% (8%-19%)16% (10%-21%)39%12%* MammaPrint 44K Array Low/High score was adjusted to MammaPrint High1 (MP-) or High2 (MP+), using a pre-defined median cut-point of I-SPY 1 participants, who fit the eligibility criteria of I-SPY 2. Citation Format: John W. Park, Minetta C. Liu, Douglas Yee, Angela DeMichele, Laura van 't Veer, Nola Hylton, Fraser Symmans, Meredith B. Buxton, A. Jo Chien, Amy Wallace, Michelle Melisko, Richard Schwab, Judy Boughey, Debashish Tripathy, Hank Kaplan, Rita Nanda, Stephen Chui, Kathy S. Albain, Stacy Moulder, Anthony Elias, Julie E. Lang, Kirsten Edminston, Donald Northfelt, David Euhus, Qamar Khan, Julia Lyandres, Sarah E. Davis, Christina Yau, Ashish Sanil, Laura J. Esserman, Donald A. Berry. Neratinib plus standard neoadjuvant therapy for high-risk breast cancer: Efficacy results from the I-SPY 2 TRIAL. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr CT227. doi:10.1158/1538-7445.AM2014-CT227

Abstract Background: Nulliparity is an established endometrial cancer risk factor, but whether this association is related to infertility is unclear. Although there are many underlying causes of infertility, few studies have assessed risk relationships according to specific causes. Despite concerns that most treatments induce ovulation and that the endometrium is highly hormonally-responsive, previous studies have provided conflicting results on treatment associations. Methods: To address these issues, we conducted a pooled analysis of 8,151 cases and12,471 controls from 2 cohort and 12 case-control studies conducted in 1982 to 2009 (N. America, Europe, Australia, Asia). All studies provided self-reported infertility, causes and treatments, except for 1 study that relied on data from national registries. Study-specific exposures and covariate data were harmonized across studies. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), adjusted for study, age, interview year, race, parity, oral contraceptive and menopausal hormone use, and body mass index. If data were not reported for a particular variable, that study was excluded from the variable-specific analysis. Results: Nulliparous women had an elevated endometrial cancer risk compared with parous women (adjusted OR=1.73; 95% CI: 1.58-1.90).Women with self-reported infertility also had an increased risk (adjusted OR=1.22; 95% CI: 1.13-1.32) compared with those without infertility issues, even after adjusting for parity; the strongest associations was seen among studies that defined infertility as unsuccessfully trying to conceive for 2+ years (adjusted OR=1.31; 95% CI: 1.07-1.60). Infertility was associated with similar risks among nulliparous (1.22; 1.10-1.48) and parous (1.22; 1.12-1.34) women, although there was no increased risk associated with infertility among those who had given birth to 3+ children. Two infertility causes associated with risk elevation were endometriosis (adjusted OR=2.08; 95% CI: 1.46-2.95 compared with women no infertility problems) and anovulation (adjusted OR=1.40; 95% CI: 1.16-1.70). Based on relatively small numbers, none of the individual treatments (in vitro fertilization, selective estrogen response modulators, gonatropins, progestins, estrogens) were substantially related to risk. Conclusion: Based on mainly self-reported infertility data, we found that parity and infertility independently contribute to endometrial cancer risk, with parity seemingly being the predominant risk predictor. Understanding residual endometrial cancer relationships related to causes of infertility and infertility treatment may benefit from documented medical information on causes of infertility and treatment parameters. Citation Format: Hannah P. Yang, Linda S. Cook, Elisabete Weiderpass, Hans-Olov Adami, Kristin E. Anderson, Hui Cai, James R. Cerhan, Tess Clendenen, Ashley S. Felix, Christine Friedenreich, Montserrat Garcia-Closas, Marc T. Goodman, Xiaolin Liang, Jolanta Lissowska, Lingeng Lu, Anthony M. Magliocco, Susan E. McCann, Kristen B. Moysich, Sara H. Olson, Malcolm C. Pike, Silvia Polidoro, Fulvio Ricceri, Harvey Risch, Carlotta Sacerdote, V. Wendy Setiawan, Xiao Ou Shu, Amanda B. Spurdle, Britton Trabert, Penelope M. Webb, Nicolas Wentzensen, Yong-Bing Xiang, Youming Xu, Herbert Yu, Anne Zeleniuch-Jacquotte, Louise A. Brinton. Infertility and risk of incident endometrial carcinoma: a pooled analysis from the Epidemiology of Endometrial Cancer Consortium. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2167. doi:10.1158/1538-7445.AM2014-2167

Abstract Background: Treatment options for women with ovarian cancer remain very limited and acquired resistance to current therapies is very common. Altered DNA repair capability in epithelial ovarian cancer (EOC) may underlie response to both standard therapy and novel treatments, such as PARP inhibitors. Molecular sub-classification of high-grade serous ovarian cancer (HG-SOC) may uncover potential drug targets and possible mechanisms of drug resistance. Understanding the contribution of DNA repair and other driver mutations to drug response and resistance requires the development of molecularly annotated preclinical models reflective of the clinic. Methods: A patient derived xenograft (PDX) cohort has been generated from consecutive, chemotherapy-naïve human HG-SOC and stratified according to in vivo response to standard chemotherapy, DNA repair capability and molecular characteristics, including next generation sequencing by Foundation Medicine. Resistance to therapy is driven by re-treating relapsed PDX in vivo providing invaluable “paired samples” (pre and post drug treatment), which are difficult to obtain from patients, to allow clonal evolution analysis of mechanisms of drug response and resistance. Results: The xenograft success rate was 83%. Of ten HG-SOC PDX, all exhibited mutations in TP53, five in BRCA1/2 (two of which were germline) and two were methylated for BRCA1. In vivo cisplatin response, determined as platinum sensitive (progression-free interval (PFI) ≥100 d, n=4), platinum resistant (PFI <100 d, n=3) or platinum refractory (n=3), was largely consistent with patient outcome. Three of four platinum sensitive HG-SOC PDX contained DNA repair gene mutations, and the fourth was methylated for BRCA1. In contrast, all three platinum refractory PDX overexpressed dominant oncogenes (CCNE1, LIN28B and/or BCL2). Molecular analysis of this cohort has revealed actionable targets for novel therapeutic strategies. In vivo studies, including with PARP inhibitors, are underway. Conclusion: PDX with histologic, molecular and therapeutic annotation, as well as clinical outcome data allow interrogation of molecular aberrations and drug resistance in vivo. This will inform targeting of novel therapies and the design of clinical trials for women. Citation Format: Monique D. Topp, Lynne Hartley, Michele Cook, Valerie Heong, Emma Boehm, Lauren McShane, Jan Pyman, Orla McNally, Sumi Ananda, Maria I. Harell, Dariush Etemadmoghadam, Laura Galletta, Kathryn Alsop, Gillian Mitchell, Stephen B. Fox, Jeff B. Kerr, Karla J. Hutt, Scott H. Kaufmann, Australian Ovarian Cancer Study (AOCS), Elizabeth M. Swisher, David D. Bowtell, Matthew M. Wakefield, Clare L. Scott. Using molecularly characterized patient-derived models to delineate underlying drivers and vulnerabilities of epithelial ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference: Cancer Susceptibility and Cancer Susceptibility Syndromes; Jan 29-Feb 1, 2014; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(23 Suppl):Abstract nr 38. doi:10.1158/1538-7445.CANSUSC14-38