Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma

High-grade serous ovarian carcinoma (HG-SOC) is a heterogeneous, poorly classified, lethal disease that frequently exhibits altered expressions of microRNAs. Let-7 family members are often reported as tumor suppressors; nonetheless, clinicopathological functions and prognostic values of individual l...

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Main Authors: Tang, Zhiqun, Ow, Ghim Siong, Thiery, Jean Paul, Ivshina, Anna V., 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/10356/82158
http://hdl.handle.net/10220/41100
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-821582020-05-28T07:18:10Z Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma Tang, Zhiqun Ow, Ghim Siong Thiery, Jean Paul Ivshina, Anna V. Kuznetsov, Vladimir A. School of Computer Engineering High-grade serous ovarian carcinoma MicroRNA let-7 High-grade serous ovarian carcinoma (HG-SOC) is a heterogeneous, poorly classified, lethal disease that frequently exhibits altered expressions of microRNAs. Let-7 family members are often reported as tumor suppressors; nonetheless, clinicopathological functions and prognostic values of individual let-7 family members have not been addressed in HG-SOC. In our work, we performed an integrative study to investigate the potential roles, clinicopathological functions and prognostic values of let-7 miRNA family in HG-SOC. Using microarray and clinical data of 1,170 HG-SOC patients, we developed novel survival prediction and system biology methods to analyze prognostic values and functional associations of let-7 miRNAs with global transcriptome and clinicopathological factors. We demonstrated that individual let-7 members exhibit diverse evolutionary history and distinct regulatory characteristics. Statistical tests and network analysis suggest that let-7b could act as a global synergistic interactor and master regulator controlling hundreds of protein-coding genes. The elevated expression of let-7b is associated with poor survival rates, which suggests an unfavorable role of let-7b in treatment response for HG-SOC patients. A novel let-7b-defined 36-gene prognostic survival signature outperforms many clinicopathological parameters, and stratifies HG-SOC patients into three high-confidence, reproducible, clinical subclasses: low-, intermediate- and high-risk, with 5-year overall survival rates of 56–71%, 12–29% and 0–10%, respectively. Furthermore, the high-risk and low-risk subclasses exhibit strong mesenchymal and proliferative tumor phenotypes concordant with resistance and sensitivity to primary chemotherapy. Our results have led to identification of promising prognostic markers of HG-SOC, which could provide a rationale for genetic-based stratification of patients and optimization of treatment regimes. ASTAR (Agency for Sci., Tech. and Research, S’pore) 2016-08-05T06:51:46Z 2019-12-06T14:47:44Z 2016-08-05T06:51:46Z 2019-12-06T14:47:44Z 2014 Journal Article Tang, Z., Ow, G. S., Thiery, J. P., Ivshina, A. V., & Kuznetsov, V. A. (2014). Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma. International Journal of Cancer, 134(2), 306-318. 0020-7136 https://hdl.handle.net/10356/82158 http://hdl.handle.net/10220/41100 10.1002/ijc.28371 en International Journal of Cancer © 2013 UICC. 13 p.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic High-grade serous ovarian carcinoma
MicroRNA let-7
spellingShingle High-grade serous ovarian carcinoma
MicroRNA let-7
Tang, Zhiqun
Ow, Ghim Siong
Thiery, Jean Paul
Ivshina, Anna V.
Kuznetsov, Vladimir A.
Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma
description High-grade serous ovarian carcinoma (HG-SOC) is a heterogeneous, poorly classified, lethal disease that frequently exhibits altered expressions of microRNAs. Let-7 family members are often reported as tumor suppressors; nonetheless, clinicopathological functions and prognostic values of individual let-7 family members have not been addressed in HG-SOC. In our work, we performed an integrative study to investigate the potential roles, clinicopathological functions and prognostic values of let-7 miRNA family in HG-SOC. Using microarray and clinical data of 1,170 HG-SOC patients, we developed novel survival prediction and system biology methods to analyze prognostic values and functional associations of let-7 miRNAs with global transcriptome and clinicopathological factors. We demonstrated that individual let-7 members exhibit diverse evolutionary history and distinct regulatory characteristics. Statistical tests and network analysis suggest that let-7b could act as a global synergistic interactor and master regulator controlling hundreds of protein-coding genes. The elevated expression of let-7b is associated with poor survival rates, which suggests an unfavorable role of let-7b in treatment response for HG-SOC patients. A novel let-7b-defined 36-gene prognostic survival signature outperforms many clinicopathological parameters, and stratifies HG-SOC patients into three high-confidence, reproducible, clinical subclasses: low-, intermediate- and high-risk, with 5-year overall survival rates of 56–71%, 12–29% and 0–10%, respectively. Furthermore, the high-risk and low-risk subclasses exhibit strong mesenchymal and proliferative tumor phenotypes concordant with resistance and sensitivity to primary chemotherapy. Our results have led to identification of promising prognostic markers of HG-SOC, which could provide a rationale for genetic-based stratification of patients and optimization of treatment regimes.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Tang, Zhiqun
Ow, Ghim Siong
Thiery, Jean Paul
Ivshina, Anna V.
Kuznetsov, Vladimir A.
format Article
author Tang, Zhiqun
Ow, Ghim Siong
Thiery, Jean Paul
Ivshina, Anna V.
Kuznetsov, Vladimir A.
author_sort Tang, Zhiqun
title Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma
title_short Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma
title_full Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma
title_fullStr Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma
title_full_unstemmed Meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma
title_sort meta-analysis of transcriptome reveals let-7b as an unfavorable prognostic biomarker and predicts molecular and clinical subclasses in high-grade serous ovarian carcinoma
publishDate 2016
url https://hdl.handle.net/10356/82158
http://hdl.handle.net/10220/41100
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