Citations

Purpose The inclusion of metformin in the treatment arms of cancer clinical trials is based on improved survival that has been demonstrated in retrospective epidemiologic studies; however, unintended biases may exist when analysis is performed by using a conventional Cox proportional hazards regression model with dichotomous ever/never categorization. We examined the impact of metformin exposure definitions, analytical methods, and patient selection on the estimated effect size of metformin exposure on survival in a large cohort of patients with pancreatic ductal adenocarcinoma (PDAC). Patients and Methods Of newly diagnosed patients with PDAC with diabetes, 980 were retrospectively included, and exposure to metformin documented. Median survival was assessed by using Kaplan-Meier and log-rank methods. Hazard ratios (HR) and 95% CIs were computed to compare time-varying covariate analysis with conventional Cox proportional hazards regression analysis. Results Median survival of metformin users versus nonusers was 9.9 versus 8.9 months, respectively. By the time-varying covariate analysis, metformin use was not statistically significantly associated with improved survival (HR, 0.93; 95% CI, 0.81 to1.07; P = .28). There was no evidence of benefit in the subset of patients who were naïve to metformin at the time of PDAC diagnosis (most representative of patients enrolled in clinical trials; HR, 1.01; 95% CI, 0.80 to 1.30; P = .89); however, when the analysis was performed by using the conventional Cox model, an artificial survival benefit of metformin was detected (HR, 0.88; 95% CI, 0.77 to 1.01; P = .08), which suggested biased results from the conventional Cox analysis. Conclusion Our findings did not suggest the benefit of metformin use after patients are diagnosed with PDAC. We highlight the importance of patient selection and appropriate statistical analytical methods when studying medication exposure and cancer survival.

Whether aspirin use is protective against cholangiocarcinoma (CCA) remains unclear. We determined the association between aspirin use and other risk factors for each CCA subtype individually. In a hospital‐based case‐control study, 2395 CCA cases (1169 intrahepatic, 995 perihilar, and 231 distal) seen at the Mayo Clinic, Rochester, MN, from 2000 through 2014 were enrolled. Controls selected from the Mayo Clinic Biobank were matched two to one with cases by age, sex, race, and residence (n = 4769). Associations between aspirin use, other risk factors, and CCA risk were determined. Aspirin was used by 591 (24.7%) CCA cases and 2129 (44.6%) controls. There was a significant inverse association of aspirin use with all CCA subtypes, with adjusted odds ratios (AORs) of 0.35 (95% confidence interval [CI], 0.29‐0.42), 0.34 (95% CI 0.27‐0.42), and 0.29 (95% CI 0.19‐0.44) for intrahepatic, perihilar, and distal CCA, respectively (P < 0.001 for all). Primary sclerosing cholangitis was more strongly associated with perihilar (AOR = 453, 95% CI 104‐999) than intrahepatic (AOR = 93.4, 95% CI 27.1‐322) or distal (AOR = 34.0, 95% CI 3.6‐323) CCA, whereas diabetes was more associated with distal (AOR = 4.2, 95% CI 2.5‐7.0) than perihilar (AOR = 2.9, 95% CI 2.2‐3.8) or intrahepatic (AOR = 2.5, 95% CI 2.0‐3.2) CCA. Cirrhosis not related to primary sclerosing cholangitis was associated with both intrahepatic and perihilar CCA, with similar AORs of 14. Isolated inflammatory bowel disease without primary sclerosing cholangitis was not associated with any CCA subtype. Conclusions: Aspirin use was significantly associated with a 2.7‐fold to 3.6‐fold decreased risk for the three CCA subtypes; our study demonstrates that individual risk factors confer risk of different CCA subtypes to different extents. (Hepatology 2016;64:785‐796)

The hypoxia‐inducible factor (HIF), HIF‐1, is a central regulator of the response to low oxygen or inflammatory stress and plays an essential role in survival and function of immune cells. However, the mechanisms regulating nonhypoxic induction of HIF‐1 remain unclear. Here, we assess the impact of germline heterozygosity of a novel, oxygen‐independent ubiquitin ligase for HIF‐1α: hypoxia‐associated factor (HAF; encoded by SART1). SART1−/− mice were embryonic lethal, whereas male SART1+/− mice spontaneously recapitulated key features of nonalcoholic steatohepatitis (NASH)‐driven hepatocellular carcinoma (HCC), including steatosis, fibrosis, and inflammatory cytokine production. Male, but not female, SART1+/− mice showed significant up‐regulation of HIF‐1α in circulating and liver‐infiltrating immune cells, but not in hepatocytes, before development of malignancy. Additionally, Kupffer cells derived from male, but not female, SART1+/− mice produced increased levels of the HIF‐1‐dependent chemokine, regulated on activation, normal T‐cell expressed and secreted (RANTES), compared to wild type. This was associated with increased liver‐neutrophilic infiltration, whereas infiltration of lymphocytes and macrophages were not significantly different. Neutralization of circulating RANTES decreased liver neutrophilic infiltration and attenuated HCC tumor initiation/growth in SART1+/− mice. Conclusion: This work establishes a new tumor‐suppressor role for HAF in immune cell function by preventing inappropriate HIF‐1 activation in male mice and identifies RANTES as a novel therapeutic target for NASH and NASH‐driven HCC. (Hepatology 2016;63:1576‐1591)

The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data.

AbstractGenetic risk factors for cholangiocarcinoma (CCA) remain poorly understood. We assessed the effect of single‐nucleotide polymorphisms (SNPs) of genes modulating inflammation or carcinogenesis on CCA risk and survival. We conducted a case‐control, candidate gene association study of 370 CCA patients and 740 age‐, sex‐, and residential area‐matched healthy controls. Eighteen functional or putatively functional SNPs in nine genes were genotyped. The log‐additive genotype effects of SNPs on CCA risk and survival were determined using logistic regression and the log‐rank test, respectively. Initial analysis identified significant associations between SNP rs2143417 and rs689466 in cyclooxygenase 2 (COX‐2) and CCA risk, after adjusting for multiple comparisons (cutoff of P = 0.0028). However, these findings were not replicated in another independent cohort of 212 CCA cases and 424 matched controls. No significant association was found between any SNP and survival of CCA patients. Although COX‐2 has been shown to contribute to cholangiocarcinogenesis, the COX‐2 SNPs tested were not associated with risk of CCA. This study shows a lack of association between variants of genes related to inflammation and carcinogenesis and CCA risk and survival. Other factors than these genetic variants may play more important roles in CCA risk and survival.

Abstract Purpose: Methylated DNA markers can discriminate upper from lower GI neoplasms (Gastroenterology 2013;144(5):S84). It is unknown if organ-specific molecular prediction of GI tumor site can be achieved. Experimental design: An unbiased search for neoplasm markers at each major GI organ site was conducted by reduced representation bisulfite sequencing. Top marker candidates were then blindly validated by methylation specific PCR on independent tissue DNA samples from normal mucosa [17 esophagus (E), 13 stomach (S), 33 pancreas (P), 35 bile duct/liver (BD), 21 colorectal (CR)] and neoplasia [42 E, 43 S, 36 P, 48 BD, 97 CR]. Recursive partitioning (rPart) trees modeled all stepwise combinations of single markers to classify controls vs neoplasms and then neoplasms by site (CR, gastroesophageal or pancreaticobiliary). A 2nd model was designed from tissue data for blinded clinical piloting on 42 independent plasma DNA samples (14 normal and 28 cancers (14 P, 14 CR). Results: From the top 100 markers, 95 were validated and used for rPart modeling. A 3- marker panel (chr12.133484978-5047, BMP3, chr11.123301058-255) was selected for the universal detection of GI neoplasms, as it classified neoplasms and control tissues with 95% accuracy. Two markers (chr7.25896389-501, QKI) then assigned lower vs upper GI neoplasms with 94% accuracy. Finally, 3 markers (PDGFD, ELOVL2, PCBP3) called pancreaticobiliary vs gastroesophageal neoplasms with 94% accuracy. All 8 markers applied in a single model (Table) accurately predicted control vs tumor by site [88% (p &lt;0.0001)]. In plasma, a 2-marker panel (BMP3, QKI) was 78% accurate in assigning patients to cancer or control groups (p&lt;0.0009) and 83% accurate in assigning cancer origin to CR or P sites (p&lt;0.0001). Predicted by ModelTissue SourceControlsColorectal neoplasiaPancreatico-biliary cancerGastro-esophageal neoplasiaControls1169102Colorectal neoplasia18617Pancreatico-biliary cancer10654Gastro-esophageal neoplasia12872 Conclusion: Panels of methylated DNA markers were identified for both universal detection of GI neoplasia and accurate prediction of tumor site. Pilot testing of these markers in plasma supports potential clinical feasibility. Citation Format: John B. Kisiel, William R. Taylor, Tracy C. Yab, Hassan M. Ghoz, Patrick H. Foote, Mary E. Devens, Douglas W. Mahoney, Thomas C. Smyrk, Lisa A. Boardman, Gloria M. Petersen, Navtej S. Buttar, Lewis R. Roberts, Graham P. Lidgard, David A. Ahlquist. Accurate site prediction of gastrointestinal cancer by novel methylated DNA markers: Discovery & validation. [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 4252. doi:10.1158/1538-7445.AM2015-4252