title: Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures.
abstract: High-grade serous ovarian cancer (HG-SOC), a major histologic type of epithelial ovarian cancer (EOC), is a poorly-characterized, heterogeneous and lethal disease where somatic mutations of TP53 are common and inherited loss-of-function mutations in BRCA1/2 predispose to cancer in 9.5-13% of EOC patients. However, the overall burden of disease due to either inherited or sporadic mutations is not known. We performed bioinformatics analyses of mutational and clinical data of 334 HG-SOC tumor samples from The Cancer Genome Atlas to identify novel tumor-driving mutations, survival-significant patient subgroups and tumor subtypes potentially driven by either hereditary or sporadic factors. We identified a sub-cluster of high-frequency mutations in 22 patients and 58 genes associated with DNA damage repair, apoptosis and cell cycle. Mutations of CHEK2, observed with the highest intensity, were associated with poor therapy response and overall survival (OS) of these patients (P = 8.00e-05), possibly due to detrimental effect of mutations at the nuclear localization signal. A 21-gene mutational prognostic signature significantly stratifies patients into relatively low or high-risk subgroups with 5-y OS of 37% or 6%, respectively (P = 7.31e-08). Further analysis of these genes and high-risk subgroup revealed 2 distinct classes of tumors characterized by either germline mutations of genes such as CHEK2, RPS6KA2 and MLL4, or somatic mutations of other genes in the signature. Our results could provide improvement in prediction and clinical management of HG-SOC, facilitate our understanding of this complex disease, guide the design of targeted therapeutics and improve screening efforts to identify women at high-risk of hereditary ovarian cancers distinct from those associated with BRCA1/2 mutations.
authors.affiliation: Bioinformatics Institute; A*STAR; Singapore.
authors.forename: Ghim Siong
authors.initials: GS
authors.lastname: Ow
authors.affiliation: Bioinformatics Institute; A*STAR; Singapore.
authors.forename: Anna V
authors.initials: AV
authors.lastname: Ivshina
authors.affiliation: Bioinformatics Institute; A*STAR; Singapore; Center for Life Science Technologies (CLST); RIKEN; Saitama, Japan.
authors.forename: Gloria
authors.initials: G
authors.lastname: Fuentes
authors.affiliation: Bioinformatics Institute; A*STAR; Singapore; Division of Software & Information Systems; School of Computer Engineering; Nanyang Technological University; Singapore; School for Integrative Science and Engineering; National University of Singapore; Singapore.
authors.forename: Vladimir A
authors.initials: VA
authors.lastname: Kuznetsov
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D000077216:Carcinoma, Ovarian Epithelial; D064447:Checkpoint Kinase 2 / Q000235:genetics*; D016000:Cluster Analysis; D019295:Computational Biology; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing / Q000379:methods*; D055106:Genome-Wide Association Study; D018095:Germ-Line Mutation; D006801:Humans; D053208:Kaplan-Meier Estimate; D060787:Neoplasm Grading; D009375:Neoplasms, Glandular and Epithelial / Q000201:enzymology / Q000235:genetics* / Q000401:mortality / Q000473:pathology / Q000628:therapy; D010051:Ovarian Neoplasms / Q000201:enzymology / Q000235:genetics* / Q000401:mortality / Q000473:pathology / Q000628:therapy; D010641:Phenotype; D011237:Predictive Value of Tests; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor; D064447:Checkpoint Kinase 2; C578634:CHEK2 protein, human
keywords: CHEK2; MLL4; RPS6KA2; biomarker; cancer driver mutation; cancer sub-type; chemotherapy resistance; diagnostics; gene signature; high-grade serous ovarian carcinoma; mutations; patient’s stratification; prognosis; survival analysis