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Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients
BACKGROUND: Due to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients’ prognosis. We aim to identify new prognostic markers for resected HCC patients. METHODS: 274 patients were retrospectively identified and samples collected fro...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6582497/ https://www.ncbi.nlm.nih.gov/pubmed/31215439 http://dx.doi.org/10.1186/s12967-019-1946-8 |
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author | Zhu, Gui-Qi Yang, Yi Chen, Er-Bao Wang, Biao Xiao, Kun Shi, Shi-Ming Zhou, Zheng-Jun Zhou, Shao-Lai Wang, Zheng Shi, Ying-Hong Fan, Jia Zhou, Jian Liu, Tian-Shu Dai, Zhi |
author_facet | Zhu, Gui-Qi Yang, Yi Chen, Er-Bao Wang, Biao Xiao, Kun Shi, Shi-Ming Zhou, Zheng-Jun Zhou, Shao-Lai Wang, Zheng Shi, Ying-Hong Fan, Jia Zhou, Jian Liu, Tian-Shu Dai, Zhi |
author_sort | Zhu, Gui-Qi |
collection | PubMed |
description | BACKGROUND: Due to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients’ prognosis. We aim to identify new prognostic markers for resected HCC patients. METHODS: 274 patients were retrospectively identified and samples collected from Zhongshan hospital, Fudan University. We analyzed the gene expression patterns of tumors and compared expression patterns with patient survival times. We identified a “9-gene signature” associated with survival by using the coefficient and regression formula of multivariate Cox model. This molecular signature was then validated in three patients cohorts from internal cohort (n = 69), TCGA (n = 369) and GEO dataset (n = 80). RESULTS: We identified 9-gene signature consisting of ZC2HC1A, MARCKSL1, PTGS1, CDKN2B, CLEC10A, PRDX3, PRKCH, MPEG1 and LMO2. The 9-gene signature was used, combined with clinical parameters, to fit a multivariable Cox model to the training cohort (concordance index, ci = 0.85), which was successfully validated (ci = 0.86 for internal cohort; ci = 0.78 for in silico cohort). The signature showed improved performance compared with clinical parameters alone (ci = 0.70). Furthermore, the signature predicted patient prognosis than previous gene signatures more accurately. It was also used to stratify early-stage, HBV or HCV-infected patients into low and high-risk groups, leading to significant differences in survival in training and validation (P < 0.001). CONCLUSIONS: The 9-gene signature, in which four were upregulated (ZC2HC1A, MARCKSL1, PTGS1, CDKN2B) and five (CLEC10A, PRDX3, PRKCH, MPEG1, LMO2) were downregulated in HCC with poor prognosis, stratified HCC patients into low and high risk group significantly in different clinical settings, including receiving adjuvant transarterial chemoembolization and especially in early stage disease. This new signature should be validated in prospective studies to stratify patients in clinical decisions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-019-1946-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6582497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65824972019-06-26 Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients Zhu, Gui-Qi Yang, Yi Chen, Er-Bao Wang, Biao Xiao, Kun Shi, Shi-Ming Zhou, Zheng-Jun Zhou, Shao-Lai Wang, Zheng Shi, Ying-Hong Fan, Jia Zhou, Jian Liu, Tian-Shu Dai, Zhi J Transl Med Research BACKGROUND: Due to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients’ prognosis. We aim to identify new prognostic markers for resected HCC patients. METHODS: 274 patients were retrospectively identified and samples collected from Zhongshan hospital, Fudan University. We analyzed the gene expression patterns of tumors and compared expression patterns with patient survival times. We identified a “9-gene signature” associated with survival by using the coefficient and regression formula of multivariate Cox model. This molecular signature was then validated in three patients cohorts from internal cohort (n = 69), TCGA (n = 369) and GEO dataset (n = 80). RESULTS: We identified 9-gene signature consisting of ZC2HC1A, MARCKSL1, PTGS1, CDKN2B, CLEC10A, PRDX3, PRKCH, MPEG1 and LMO2. The 9-gene signature was used, combined with clinical parameters, to fit a multivariable Cox model to the training cohort (concordance index, ci = 0.85), which was successfully validated (ci = 0.86 for internal cohort; ci = 0.78 for in silico cohort). The signature showed improved performance compared with clinical parameters alone (ci = 0.70). Furthermore, the signature predicted patient prognosis than previous gene signatures more accurately. It was also used to stratify early-stage, HBV or HCV-infected patients into low and high-risk groups, leading to significant differences in survival in training and validation (P < 0.001). CONCLUSIONS: The 9-gene signature, in which four were upregulated (ZC2HC1A, MARCKSL1, PTGS1, CDKN2B) and five (CLEC10A, PRDX3, PRKCH, MPEG1, LMO2) were downregulated in HCC with poor prognosis, stratified HCC patients into low and high risk group significantly in different clinical settings, including receiving adjuvant transarterial chemoembolization and especially in early stage disease. This new signature should be validated in prospective studies to stratify patients in clinical decisions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-019-1946-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-18 /pmc/articles/PMC6582497/ /pubmed/31215439 http://dx.doi.org/10.1186/s12967-019-1946-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Zhu, Gui-Qi Yang, Yi Chen, Er-Bao Wang, Biao Xiao, Kun Shi, Shi-Ming Zhou, Zheng-Jun Zhou, Shao-Lai Wang, Zheng Shi, Ying-Hong Fan, Jia Zhou, Jian Liu, Tian-Shu Dai, Zhi Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients |
title | Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients |
title_full | Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients |
title_fullStr | Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients |
title_full_unstemmed | Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients |
title_short | Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients |
title_sort | development and validation of a new tumor-based gene signature predicting prognosis of hbv/hcv-included resected hepatocellular carcinoma patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6582497/ https://www.ncbi.nlm.nih.gov/pubmed/31215439 http://dx.doi.org/10.1186/s12967-019-1946-8 |
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