Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures

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 pat...

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Main Authors: Ow, Ghim Siong, Ivshina, Anna V., Fuentes, Gloria, Kuznetsov, Vladimir A.
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2016
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Online Access:https://hdl.handle.net/10356/82783
http://hdl.handle.net/10220/40276
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spelling sg-ntu-dr.10356-827832022-02-16T16:27:42Z Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures Ow, Ghim Siong Ivshina, Anna V. Fuentes, Gloria Kuznetsov, Vladimir A. School of Computer Engineering RPS6KA2 MLL4 CHEK2 Mutations Cancer driver mutation High-grade serous ovarian carcinoma Cancer sub-type Biomarker Gene signature Survival analysis Diagnostics Prognosis Patient’s stratification Chemotherapy resistance 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. ASTAR (Agency for Sci., Tech. and Research, S’pore) Published version 2016-03-15T04:25:24Z 2019-12-06T15:05:28Z 2016-03-15T04:25:24Z 2019-12-06T15:05:28Z 2014 Journal Article Ow, G. S., Ivshina, A. V., Fuentes, G., & Kuznetsov, V. A. (2014). Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures. Cell Cycle, 13(14), 2262-2280. 1538-410 https://hdl.handle.net/10356/82783 http://hdl.handle.net/10220/40276 10.4161/cc.29271 24879340 en Cell Cycle © 2014 Landes Bioscience. This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. The article may be redistributed, reproduced, and reused for non-commercial purposes, provided the original source is properly cited. Permission is granted subject to the terms of the License under which the work was published. Please check the License conditions for the work which you wish to reuse. Full and appropriate attribution must be given. This permission does not cover any third party copyrighted material which may appear in the work requested. 20 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic RPS6KA2
MLL4
CHEK2
Mutations
Cancer driver mutation
High-grade serous ovarian carcinoma
Cancer sub-type
Biomarker
Gene signature
Survival analysis
Diagnostics
Prognosis
Patient’s stratification
Chemotherapy resistance
spellingShingle RPS6KA2
MLL4
CHEK2
Mutations
Cancer driver mutation
High-grade serous ovarian carcinoma
Cancer sub-type
Biomarker
Gene signature
Survival analysis
Diagnostics
Prognosis
Patient’s stratification
Chemotherapy resistance
Ow, Ghim Siong
Ivshina, Anna V.
Fuentes, Gloria
Kuznetsov, Vladimir A.
Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures
description 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.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Ow, Ghim Siong
Ivshina, Anna V.
Fuentes, Gloria
Kuznetsov, Vladimir A.
format Article
author Ow, Ghim Siong
Ivshina, Anna V.
Fuentes, Gloria
Kuznetsov, Vladimir A.
author_sort Ow, Ghim Siong
title Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures
title_short Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures
title_full Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures
title_fullStr Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures
title_full_unstemmed Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures
title_sort identification of two poorly prognosed ovarian carcinoma subtypes associated with chek2 germ-line mutation and non-chek2 somatic mutation gene signatures
publishDate 2016
url https://hdl.handle.net/10356/82783
http://hdl.handle.net/10220/40276
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