Oberg, Ann L.

Pancreatic cancer is one of the most fatal common cancers affecting both men and women, representing about 3% of all new cancer cases in the United States. In this study, we aimed to investigate the association of pancreatic cancer risk with alcohol consumption as well as folate intake. We performed a case-control study of 384 patients diagnosed with pancreatic cancer from May 2004 to December 2009 and 983 primary care healthy controls in a largely white population (>96%). Our findings showed no significant association between risk of pancreatic cancer and either overall alcohol consumption or type of alcohol consumed (drinks/day). Our study showed dietary folate intake had a modest effect size, but was significantly inversely associated with pancreatic cancer (odds ratio (OR) = 0.99, p < 0.0001). The current study supports the hypothesis that pancreatic cancer risk is reduced with higher food-based folate intake.

Abstract Purpose: Here we assess whether molecular subtyping identifies biological features of tumors that correlate with survival and surgical outcomes of high-grade serous ovarian cancer (HGSOC). Experimental Design: Consensus clustering of pooled mRNA expression data from over 2,000 HGSOC cases was used to define molecular subtypes of HGSOCs. This de novo classification scheme was then applied to 381 Mayo Clinic HGSOC patients with detailed survival and surgical outcome information. Results: Five molecular subtypes of HGSOC were identified. In the pooled dataset, three subtypes were largely concordant with prior studies describing proliferative, mesenchymal, and immunoreactive tumors (concordance &gt; 70%), and the group of tumors previously described as differentiated type was segregated into two new types, one of which (anti-mesenchymal) had downregulation of genes that were typically upregulated in the mesenchymal subtype. Molecular subtypes were significantly associated with overall survival (P &lt; 0.001) and with rate of optimal surgical debulking (≤1 cm, P = 1.9E−4) in the pooled dataset. Among stage III-C or IV Mayo Clinic patients, molecular subtypes were also significantly associated with overall survival (P = 0.001), as well as rate of complete surgical debulking (no residual disease; 16% in mesenchymal tumors compared with &gt;28% in other subtypes; P = 0.02). Conclusions: HGSOC tumors may be categorized into five molecular subtypes that associate with overall survival and the extent of residual disease following debulking surgery. Because mesenchymal tumors may have features that were associated with less favorable surgical outcome, molecular subtyping may have future utility in guiding neoadjuvant treatment decisions for women with HGSOC. Clin Cancer Res; 23(15); 4077–85. ©2017 AACR.

Abstract Background: Epidemiologic associations of leukocyte telomere length (LTL) and pancreatic ductal adenocarcinoma (PDAC) have been inconsistent owing, in part, to variation in telomere length (TL) assessment across studies. To overcome this limitation and address concerns of potential reverse causation, we used carriage of telomere-related alleles to genetically predict TL and examined its association with PDAC. Methods: A case–control study of 1,500 PDAC cases and 1,500 controls, frequency-matched on age and sex was performed. Eight of nine polymorphisms previously associated with variation in LTL were analyzed. Genetic risk scores (GRS) consisting of the TL-related polymorphisms were computed as the number of long TL alleles carried by an individual scaled to published kilobase pairs of TL associated with each allele. Participants were further categorized on the basis of the number of short TL alleles they carry across all eight SNPs. Associations were examined in additive and dominant models using logistic regression to calculate ORs and 95% confidence intervals (CI). Results: In age- and sex-adjusted models, one short TL allele (rs10936599, T) was associated with reduced risk, whereas another short TL allele (rs2736100, A) was associated with increased risk, with per-allele ORs of 0.89 (95% CI, 0.79–0.99) and 1.13 (95% CI, 1.01–1.24), respectively. No association was observed with GRS or short TL allele counts, and no associations were observed in the dominant models. Conclusions: Findings suggest that genetically predicted short TL is not associated with PDAC risk. Impact: Common genetic determinants of short TL do not appear to influence PDAC risk. Cancer Epidemiol Biomarkers Prev; 26(6); 971–4. ©2017 AACR.

11 Background: Currently there are no serum markers of response to AA. We performed a proteome based analysis of serum from prostate cancer patients, followed by mapping of candidate markers to networks based on known molecular interactions in Ingenuity Knowledge Base (IKB). Methods: Isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS) was performed in serum of 3 non-localized prostate cancer cohorts. The first cohort included 15 paired untreated hormone-sensitive “pre AA” and 3-month “post AA” specimens; the second included 10 “early AA failure” (median failure time: 11 months) and the third included 10 “late AA failure” specimens (median failure time: 95 months). Differentially expressed candidate proteins were identified by comparisons of (i) paired pre/post AA proteomes and (ii) post AA proteome with the combined AA failure cohorts at a False Discovery Rate of 0.2. To facilitate biological interpretation of multiple candidates identified in the comparisons, IPA was used. Candidate markers implicated in IPA networks with statistical significance were pursued in a second, independent patient cohort for association with time to AA failure using univariate Cox regression analysis. Results: Median PSA for pre/post AA first cohort were 3.15 and 0.29 ng/ml. Median PSA for the second and third cohorts were 27.3 and 4.3 ng/ml. Between post AA and AA failure cohorts, 149 proteins were differentially expressed. Between early and late AA failure 98 proteins were differentially expressed; 47 proteins were common in both comparisons. Network enrichment analysis of the 47 proteins by IPA identified four interaction networks (p<0.01), one of which highlighted a role for 17-β-estradiol (E1). Gas chromatography used for measuring 3-month post AA initiation serum E1, estrone (E2) and testosterone levels (N=38) detected high E1, E2 levels associated with longer time to AA failure (P=0.07 for E1; P=0.08 for E2) in the independent cohort. Conclusions: A global proteomic analysis identified post AA initiation serum E1, E2 levels as potential response markers, which needs validation.

18 Background: Benign breast disease (BBD) is diagnosed in 1-2 million women/year in the US, and while these patients are known to be at substantially increased risk for subsequent development of breast cancer, existing models for risk assessment perform poorly at the individual level. Here, we describe a DNA-microarray-based transcriptional model for breast cancer risk prediction for patients with sclerosing adenosis (SA), a lesion found in ¼ of all BBD patients that is characterized by epithelial proliferation, disordered acinar architecture, and stromal fibrosis. Methods: A training set was developed from 86 patients diagnosed with sclerosing adenosis (SA), of which 27 subsequently developed cancer within 10 years (cases) and 59 remained cancer-free at 10 years (controls). A diagonal linear discriminate analysis (DLDA)-prediction model for prediction of cancer within 10 years (SA TTC10) was generated from transcriptional profiles of formalin fixed, paraffin-embedded (FFPE) biopsy-derived RNA. This model was tested on a separate validation case-control set composed of 65 SA patients. Results: The SA TTC10 gene signature model, composed of 35 gene features, achieved a clear and significant separation between case and control with receiver operating characteristic area under the curve of 0.913 in the training set and 0.836 in the validation set. Conclusions: Our results provide the first demonstration that benign breast tissue contains transcriptional alterations that indicate risk of breast cancer development, and that essential precursor biomarkers of malignancy are present many years prior to cancer development. Furthermore, the SA TTC10 gene signature model, which can be assessed on FFPE biopsies, constitutes a novel prognostic biomarker for patients with SA.

104 Background: Currently there are no serum predictive markers of response to AA. We used a proteomic based analytic approach to identify candidates. Methods: Serum from three non-localized prostate cancer cohorts was analyzed. The first included15 paired untreated hormone-sensitive “pre-AA” and 3-month “post-AA” specimens; the second included 10 “early AA failure” (median time to AA failure:11 months) and the third included 10 “late AA failure” specimens (median time to AA failure: 95 months). Proteomic analysis was performed with isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS). Differentially expressed candidate proteins were identified by comparisons of (i) paired pre/post-AA proteomes and (ii) post-AA proteome with the combined AA failure cohorts at a False Discovery Rate of 0.2. ELISA assays were used to verify candidate markers in a second stored aliquot of first cohort specimens. This cohort was followed for AA failure. Association of post-AA ELISA levels of candidate markers with time to AA failure was performed using Cox proportional hazards regression, summarized as relative risk (RR) for AA failure. Results: Median PSA in pre/post-AA first cohort were 3.15 ng/ml and 0.29 ng/ml. Median PSA in the second and third cohorts were 27.3 and 4.3 ng/ml. Between post-AA and AA failure cohorts, 149 proteins were differentially expressed. Between early and late AA failure 98 proteins were differentially expressed; 47 proteins were common in both comparisons. ELISA assays verified expression levels of 2/47 proteins in the first cohort; zinc alpha-2 macroglobulin (ZAG), and Neuropilin-2 (NPL2). Median change in ZAG decreased by 2073.5 ng/ml (post versus pre-AA) while median change in NPL2 levels increased by 2.9 ng/ml. After a median follow-up of 43 months from the post-AA time-point, 4/15 first cohort subjects had failed AA. The RR of AA failure for ZAG levels below the median change was 3.8 (95% CI: 0.4-37) and 3.0 (95% CI: 0.3-29) for NPL2. Conclusions: A global proteomic analysis identified ZAG and NPL2 as candidate serum predictive markers of AA response which needs further validation.

Abstract Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer. Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed. Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34–0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44–1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27–0.74), P = 0.0015]. Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794–801. ©2017 AACR.