Endometriosis-Associated Ovarian Cancer: A Review of Pathogenesis

Endometriosis is classically defined as the presence of endometrial glands and stroma outside of the endometrial lining and uterine musculature. With an estimated frequency of 5%–10% among women of reproductive age, endometriosis is a common gynecologic disorder. While in itself a benign lesion, endometriosis shares several characteristics with invasive cancer, has been shown to undergo malignant transformation, and has been associated with an increased risk of epithelial ovarian carcinoma (EOC). Numerous epidemiologic studies have shown an increased risk of EOC among women with endometriosis. This is particularly true for women with endometrioid and clear cell ovarian carcinoma. However, the carcinogenic pathways by which endometriosis associated ovarian carcinoma (EAOC) develops remain poorly understood. Current molecular studies have sought to link endometriosis with EAOC through pathways related to oxidative stress, inflammation and hyperestrogenism. In addition, numerous studies have sought to identify an intermediary lesion between endometriosis and EAOC that may allow for the identification of endometriosis at greatest risk for malignant transformation or for the prevention of malignant transformation of this common gynecologic disorder. The objective of the current article is to review the current data regarding the molecular events associated with EAOC development from endometriosis, with a primary focus on malignancies of the endometrioid and clear cell histologic sub-types

Impact of clinical characteristics on human chorionic gonadotropin regression after molar pregnancy

OBJECTIVES: This study aimed to determine the effects of age, race/ethnicity, body mass index, and contraception on human chorionic gonadotropin (hCG) regression following the evacuation of a molar pregnancy. METHODS: This was a retrospective cohort study of 277 patients with molar pregnancies between January 1, 1994 and December 31, 2015. The rate of hCG regression was estimated using mixed-effects linear regression models on daily log-transformed serum hCG levels after evacuation. RESULTS: There were no differences in hCG half-lives among age (p=0.13) or race/ethnicity (p=0.16) groups. Women with obesity and hormonal contraceptive use demonstrated faster hCG regression than their counterparts (3.2 versus. 3.7 days, p=0.02 and 3.4 versus. 4.0 days, p=0.002, respectively). CONCLUSION: Age and race/ethnicity were not associated with hCG regression rates. Hormonal contraceptive use and obesity were associated with shorter hCG half-lives, but with unlikely clinical significance. It is important to understand whether the clinical characteristics of patients may influence the hCG regression curve, as it has been proposed as a way to predict the risk of gestational trophoblastic neoplasia

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer

Mucinous epithelial ovarian cancers are clinically and morphologically distinct from the other histopathologic subtypes of ovarian cancer. Unlike other ovarian subtypes, epidemiologic studies have indicated that tobacco exposure is a significant risk factor for developing mucinous ovarian cancer. Detection of autoantibody reactivity is useful in biomarker discovery and for explaining the role of important pathophysiologic pathways in disease. In order to study if there are specific antibody biomarkers in the plasma samples of mucinous ovarian cancer patients, we have initiated a screen by employing a “reverse capture antibody microarray” platform that uses native host antigens derived from mucinous ovarian tissues as “baits” for the capture of differentially labeled patient and control autoantibodies. 35 autoantibodies that were significantly elevated in the cancer plasma samples compared with healthy controls, and six autoantibodies that segregated smoking and nonsmoking patients were identified. Functional annotation of the antibody targets has identified nine target antigens involved in integrin and Wnt signaling pathways. Immunohistochemistry of archived ovarian specimens showed significant overexpression of eight of the nine target antigens in mucinous ovarian tumor tissues, suggesting that plasma autoantibodies from mucinous ovarian cancer patients might have heightened reactivities with epitopes presented by these overexpressed antigens. Autoantibody profiling may have an unexpected utility in uncovering key signaling pathways that are dysregulated in the system of interest

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies