Citations

Glycosylphosphatidylinositol (GPI)-anchored proteins are resistant to solubilization with Triton X-100 at 4 °C, and they can be recovered in Triton-insoluble membranes (TIMs) that float to a characteristic buoyant density. Because the GPI structure itself has been shown to target GPI-anchored proteins to TIMs, we investigated the association of GPI-anchor intermediates with TIMs. GPI-anchor biosynthesis involves a pathway of some 10 steps that take place in the endoplasmic reticulum (ER). These intermediates include glucosaminyl-acylphosphatidylinositol [GlcN-(acyl)PI] and later mannosylated GPIs, denoted H6, H7 and H8, that are present not only in the ER but also in other cell compartments, including the plasma membrane. At least two-thirds of the GlcN-(acyl)PI in HeLa D cells and mannosylated GPIs in K562 cells were found in TIMs. Although previous reports have considered TIMs to be derived primarily from the plasma membrane, we recovered TIMs from subcellular fractions enriched in ER membranes. The ER marker calnexin and GPI-anchored proteins as well as N-acetylglucosaminyl-phosphatidylinositol and mannosylated GPIs were present in ER-TIMs. Interestingly, GlcN-PI and H7 were less enriched in ER-TIM than the other GPIs, suggesting that ER-TIMs might reflect a compartmentalization of the GPI-anchor biosynthetic pathway in the ER.

Abstract Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1574–84. ©2015 AACR.

Abstract Purpose: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. Experimental Design: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. Results: Five SNPs were significantly associated (P ≤ 1.0 × 10−5) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10−6). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤6 × 10−3). Conclusions: We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies. Clin Cancer Res; 21(23); 5264–76. ©2015 AACR.

Abstract Objective Clinicians’ ability to use and interpret genetic information depends upon how those data are displayed in electronic health records (EHRs). There is a critical need to develop systems to effectively display genetic information in EHRs and augment clinical decision support (CDS). Materials and Methods The National Institutes of Health (NIH)-sponsored Clinical Sequencing Exploratory Research and Electronic Medical Records & Genomics EHR Working Groups conducted a multiphase, iterative process involving working group discussions and 2 surveys in order to determine how genetic and genomic information are currently displayed in EHRs, envision optimal uses for different types of genetic or genomic information, and prioritize areas for EHR improvement. Results There is substantial heterogeneity in how genetic information enters and is documented in EHR systems. Most institutions indicated that genetic information was displayed in multiple locations in their EHRs. Among surveyed institutions, genetic information enters the EHR through multiple laboratory sources and through clinician notes. For laboratory-based data, the source laboratory was the main determinant of the location of genetic information in the EHR. The highest priority recommendation was to address the need to implement CDS mechanisms and content for decision support for medically actionable genetic information. Conclusion Heterogeneity of genetic information flow and importance of source laboratory, rather than clinical content, as a determinant of information representation are major barriers to using genetic information optimally in patient care. Greater effort to develop interoperable systems to receive and consistently display genetic and/or genomic information and alert clinicians to genomic-dependent improvements to clinical care is recommended.

Carriers of germline mutations in DNA mismatch repair (MMR) genes are at increased risk of several cancers including colorectal and gynecologic cancers (Lynch syndrome). There is no substantial evidence that these mutations are associated with an increased risk of cervical cancer. A total of 369 families with at least one carrier of a mutation in a MMR gene (133 MLH1, 174 MSH2, 35 MSH6 and 27 PMS2) were ascertained via population cancer registries or via family cancer clinics in Australia, New Zealand, Canada, and USA. Personal and family histories of cancer were obtained from participant interviews. Modified segregation analysis was used to estimate the hazard ratio (incidence rates for carriers relative to those for the general population), and age‐specific cumulative risks of cervical cancer for carriers. A total of 65 cases of cervical cancer were reported (including 10 verified by pathology reports). The estimated incidence was 5.6 fold (95% CI: 2.3–13.8; p = 0.001) higher for carriers than for the general population with a corresponding cumulative risk to 80 years of 4.5% (95% CI: 1.9–10.7%) compared with 0.8% for the general population. The mean age at diagnosis was 43.1 years (95% CI: 40.0–46.2), 3.9 years younger than the reported USA population mean of 47.0 years (p = 0.02). Women with MMR gene mutations were found to have an increased risk of cervical cancer. Due to limited pathology verification we cannot be certain that a proportion of these cases were not lower uterine segment endometrial cancers involving the endocervix, a recognized cancer of Lynch syndrome.