Real-world Overall Survival Using Oncology Electronic Health Record Data: Friends of Cancer Research Pilot.

In prior work, Friends of Cancer Research convened multiple data partners to establish standardized definitions for oncology real-world end points derived from electronic health records (EHRs) and claims data. Here, we assessed the performance of real-world overall survival (rwOS) from data sets sourced from EHRs by evaluating the ability of the end point to reflect expected differences from a previous randomized controlled trial across five data sources, after applying inclusion/exclusion criteria. The KEYNOTE-189 clinical trial protocol of platinum doublet chemotherapy (chemotherapy) vs. programmed cell death protein 1 (PD-1) in combination with platinum doublet chemotherapy (PD-1 combination) in first-line nonsquamous metastatic non-small cell lung cancer guided retrospective cohort selection. The Kaplan-Meier product limit estimator was used to calculate 12-month rwOS with 95% confidence intervals (CIs) in each data source. Cox proportional hazards models estimated hazard ratios (HRs) and associated 95% CIs, controlled for prognostic factors. Once the inclusion/exclusion criteria were applied, the five resulting data sets included 155 to 1,501 patients in the chemotherapy cohort and 36 to 405 patients in the PD-1 combination cohort. Twelve-month rwOS ranged from 45% to 58% in the chemotherapy cohort and 44% to 68% in the PD-1 combination cohort. The adjusted HR for death ranged from 0.80 (95% CI: 0.69, 0.93) to 1.15 (95% CI: 0.71, 1.85), controlling for age, gender, performance status, and smoking status. This study yielded insights regarding data capture, including ability of real-world data to precisely identify patient populations and the impact of criteria on end points. Sensitivity analyses could elucidate data set-specific factors that drive results.

The Friends of Cancer Research Real-World Data Collaboration Pilot 2.0: Methodological Recommendations from Oncology Case Studies.

The purpose of this study was to evaluate the potential collective opportunities and challenges of transforming real-world data (RWD) to real-world evidence for clinical effectiveness by focusing on aligning analytic definitions of oncology end points. Patients treated with a qualifying therapy for advanced non-small cell lung cancer in the frontline setting meeting broad eligibility criteria were included to reflect the real-world population. Although a trend toward improved outcomes in patients receiving PD-(L)1 therapy over standard chemotherapy was observed in RWD analyses, the magnitude and consistency of treatment effect was more heterogeneous than previously observed in controlled clinical trials. The study design and analysis process highlighted the identification of pertinent methodological issues and potential innovative approaches that could inform the development of high-quality RWD studies.

A combination of the immunohistochemical markers CK7 and SATB2 is highly sensitive and specific for distinguishing primary ovarian mucinous tumors from colorectal and appendiceal metastases.

Primary ovarian mucinous tumors can be difficult to distinguish from metastatic gastrointestinal neoplasms by histology alone. The expected immunoprofile of a suspected metastatic lower gastrointestinal tumor is CK7-/CK20+/CDX2+/PAX8-. This study assesses the addition of a novel marker SATB2, to improve the diagnostic algorithm. A test cohort included 155 ovarian mucinous tumors (105 carcinomas and 50 borderline tumors) and 230 primary lower gastrointestinal neoplasms (123 colorectal adenocarcinomas and 107 appendiceal neoplasms). All cases were assessed for SATB2, PAX8 CK7, CK20, and CDX2 expression on tissue microarrays. Expression was scored in a 3-tier system as absent, focal (1-50% of tumor cells) and diffuse ( >50% of tumor cells) and then categorized into either absent/present or nondiffuse/diffuse. SATB2 and PAX8 expression was further evaluated in ovarian tumors from an international cohort of 2876 patients (expansion cohort, including 159 mucinous carcinomas and 46 borderline mucinous tumors). The highest accuracy of an individual marker in distinguishing lower gastrointestinal from ovarian mucinous tumors was CK7 (91.7%, nondiffuse/diffuse cut-off) followed by SATB2 (88.8%, present/absent cut-off). The most effective combination was CK7 and SATB2 with accuracy of 95.3% using the 3-tier interpretation, absent/focal/diffuse. This combination outperformed the standard clinical set of CK7, CK20 and CDX2 (87.5%). Re-evaluation of outlier cases confirmed ovarian origin for all but one case. The accuracy of SATB2 was confirmed in the expansion cohort (91.5%). SATB2 expression was also detected in 15% of ovarian endometrioid carcinoma but less than 5% of other ovarian histotypes. A simple two marker combination of CK7 and SATB2 can distinguish lower gastrointestinal from ovarian primary mucinous tumors with greater than 95% accuracy. PAX8 and CDX2 have value as second-line markers. The utility of CK20 in this setting is low and this warrants replacement of this marker with SATB2 in clinical practice.

Genomic Analysis Using Regularized Regression in High-Grade Serous Ovarian Cancer.

High-grade serous ovarian cancer (HGSOC) is a complex disease in which initiation and progression have been associated with copy number alterations, epigenetic processes, and, to a lesser extent, germline variation. We hypothesized that, when summarized at the gene level, tumor methylation and germline genetic variation, alone or in combination, influence tumor gene expression in HGSOC. We used Elastic Net (ENET) penalized regression method to evaluate these associations and adjust for somatic copy number in 3 independent data sets comprising tumors from more than 470 patients. Penalized regression models of germline variation, with or without methylation, did not reveal a role in HGSOC gene expression. However, we observed significant association between regional methylation and expression of 5 genes (WDPCP, KRT6C, BRCA2, EFCAB13, and ZNF283). CpGs retained in ENET model for BRCA2 and ZNF283 appeared enriched in several regulatory elements, suggesting that regularized regression may provide a novel utility for integrative genomic analysis.

Mediation analysis of alcohol consumption, DNA methylation, and epithelial ovarian cancer.

Epigenetic factors and consumption of alcohol, which suppresses DNA methylation, may influence the development and progression of epithelial ovarian cancer (EOC). However, there is a lack of understanding whether these factors interact to affect the EOC risk. In this study, we aimed to gain insight into this relationship by identifying leukocyte-derived DNA methylation markers acting as potential mediators of alcohol-associated EOC. We implemented a causal inference test (CIT) and the VanderWeele and Vansteelandt multiple mediator model to examine CpG sites that mediate the association between alcohol consumption and EOC risk. We modified one step of the CIT by adopting a high-dimensional inference procedure. The data were based on 196 cases and 202 age-matched controls from the Mayo Clinic Ovarian Cancer Case-Control Study. Implementation of the CIT test revealed two CpG sites (cg09358725, cg11016563), which represent potential mediators of the relationship between alcohol consumption and EOC case-control status. Implementation of the VanderWeele and Vansteelandt multiple mediator model further revealed that these two CpGs were the key mediators. Decreased methylation at both CpGs was more common in cases who drank alcohol at the time of enrollment vs. those who did not. cg11016563 resides in TRPC6 which has been previously shown to be overexpressed in EOC. These findings suggest two CpGs may serve as novel biomarkers for EOC susceptibility.

Epigenetics in ovarian cancer.

Ovarian cancer is a disease with a poor prognosis and little progress has been made to improve treatment. It is now recognized that there are several histotypes of ovarian cancer, each with distinct epidemiologic and genomic characteristics. Cancer therapy is moving beyond classical chemotherapy to include epigenetic approaches. Epigenetics is the dynamic regulation of gene expression by DNA methylation and histone post translational modification in response to environmental cues. Improvement in technology to study DNA methylation has enabled a more agnostic approach and, with larger samples sets, has begun to unravel how epigenetics contributes to the etiology, response to chemotherapy and prognosis in of ovarian cancer. Investigations into histone modifications in ovarian cancer are more nascent. Much more is needed to be done to fully realize the potential that epigenetics holds for ovarian cancer clinical care.

Characterization of fusion genes in common and rare epithelial ovarian cancer histologic subtypes.

Gene fusions play a critical role in some cancers and can serve as important clinical targets. In epithelial ovarian cancer (EOC), the contribution of fusions, especially by histological type, is unclear. We therefore screened for recurrent fusions in a histologically diverse panel of 220 EOCs using RNA sequencing. The Pipeline for RNA-Sequencing Data Analysis (PRADA) was used to identify fusions and allow for comparison with The Cancer Genome Atlas (TCGA) tumors. Associations between fusions and clinical prognosis were evaluated using Cox proportional hazards regression models. Nine recurrent fusions, defined as occurring in two or more tumors, were observed. CRHR1-KANSL1 was the most frequently identified fusion, identified in 6 tumors (2.7% of all tumors). This fusion was not associated with survival; other recurrent fusions were too rare to warrant survival analyses. One recurrent in-frame fusion, UBAP1-TGM7, was unique to clear cell (CC) EOC tumors (in 10%, or 2 of 20 CC tumors). We found some evidence that CC tumors harbor more fusions on average than any other EOC histological type, including high-grade serous (HGS) tumors. CC tumors harbored a mean of 7.4 fusions (standard deviation [sd] = 7.4, N = 20), compared to HGS EOC tumors mean of 2.0 fusions (sd = 3.3, N = 141). Few fusion genes were detected in endometrioid tumors (mean = 0.24, sd = 0.74, N = 55) or mucinous tumors (mean = 0.25, sd = 0.5, N = 4) tumors. To conclude, we identify one fusion at 10% frequency in the CC EOC subtype, but find little evidence for common (> 5% frequency) recurrent fusion genes in EOC overall, or in HGS subtype-specific EOC tumors.

Genetic variation in phospholipid transfer protein modulates lipoprotein profiles in hyperalphalipoproteinemia.

We previously demonstrated the role of a phospholipid transfer protein (PLTP) gene variation (rs2294213) in determining levels of high-density lipoprotein cholesterol (HDL-C) in hypoalphalipoproteinemia (HypoA). We have now explored the role of PLTP in hyperalphalipoproteinemia (HyperA). The human PLTP gene was screened for sequence anomalies by DNA melting in 107 subjects with HyperA. The association with plasma lipoprotein levels was evaluated. We detected 7 sequence variations: 1 previously reported variation (rs2294213) and 5 novel mutations including 1 missense mutation (L106F). The PLTP activity was unchanged in the p.L106F mutation. The frequency of the rs2294213 minor allele was markedly increased in the HyperA group (7.0%) in comparison with a control group (4.3%) and the hypoalphalipoproteinemia group (2.2%). Moreover, rs2294213 was strongly associated with HDL-C levels. Linear regression models predict that possession of the rs2294213 minor allele increases HDL-C independent of triglycerides. These findings extend the association of rs2294213 with HDL-C levels into the extremes of the HDL distribution.

Genetic variation of PLTP modulates lipoprotein profiles in hypoalphalipoproteinemia.

Phospholipid transfer protein (PLTP) participates in key processes in lipoprotein metabolism, including interparticle phospholipid transfer, remodeling of HDL, cholesterol and phospholipid efflux from peripheral tissues, and the production of hepatic VLDL. The impact of PLTP on reverse cholesterol transport suggests that the gene may harbor sequence anomalies that contribute to disorders of HDL metabolism. The human PLTP gene was screened for sequence anomalies by DNA melting analysis in 276 subjects with hypoalphalipoproteinemia (HA) and 364 controls. The association with plasma lipid parameters was evaluated. We discovered 18 sequence variations, including four missense mutations and a novel polymorphism (c.-34G > C). In healthy controls, the c.-34G > C minor allele was associated with higher high density lipoprotein-cholesterol (HDL-C) and was depleted in subjects with HA. Linear regression models predict that possession of the rare allele decreases plasma triglyceride (TG) and TG/HDL-C and increases HDL-C independent of TG. Decreased PLTP activity was observed in one (p.R235W) of four (p.E72G, p.S119A, p.S124Y, and p.R235W) mutations in an in vitro activity assay. These findings indicate that PLTP gene variation is an important determinant of plasma lipoproteins and affects disorders of HDL metabolism.