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Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer

Simultaneous identification of multiple single genes and multi-gene prognostic signatures with higher efficacy in liver cancer has rarely been reported. Here, 1,173 genes potentially related to the liver cancer prognosis were mined with Coremine, and the gene expression and survival data in 370 samp...

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Autores principales: Liu, Meiliang, Liu, Xia, Liu, Shun, Xiao, Feifei, Guo, Erna, Qin, Xiaoling, Wu, Liuyu, Liang, Qiuli, Liang, Zerui, Li, Kehua, Zhang, Di, Yang, Yu, Luo, Xingxi, Lei, Lei, Tan, Jennifer Hui Juan, Yin, Fuqiang, Zeng, Xiaoyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7270198/
https://www.ncbi.nlm.nih.gov/pubmed/32547951
http://dx.doi.org/10.3389/fonc.2020.00847
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author Liu, Meiliang
Liu, Xia
Liu, Shun
Xiao, Feifei
Guo, Erna
Qin, Xiaoling
Wu, Liuyu
Liang, Qiuli
Liang, Zerui
Li, Kehua
Zhang, Di
Yang, Yu
Luo, Xingxi
Lei, Lei
Tan, Jennifer Hui Juan
Yin, Fuqiang
Zeng, Xiaoyun
author_facet Liu, Meiliang
Liu, Xia
Liu, Shun
Xiao, Feifei
Guo, Erna
Qin, Xiaoling
Wu, Liuyu
Liang, Qiuli
Liang, Zerui
Li, Kehua
Zhang, Di
Yang, Yu
Luo, Xingxi
Lei, Lei
Tan, Jennifer Hui Juan
Yin, Fuqiang
Zeng, Xiaoyun
author_sort Liu, Meiliang
collection PubMed
description Simultaneous identification of multiple single genes and multi-gene prognostic signatures with higher efficacy in liver cancer has rarely been reported. Here, 1,173 genes potentially related to the liver cancer prognosis were mined with Coremine, and the gene expression and survival data in 370 samples for overall survival (OS) and 319 samples for disease-free survival (DFS) were retrieved from The Cancer Genome Atlas. Numerous survival analyses results revealed that 39 genes and 28 genes significantly associated with DFS and OS in liver cancer, including 18 and 12 novel genes that have not been systematically reported in relation to the liver cancer prognosis, respectively. Next, totally 9,139 three-gene combinations (including 816 constructed by 18 novel genes) for predicting DFS and 3,276 three-gene combinations (including 220 constructed by 12 novel genes) for predicting OS were constructed based on the above genes, and the top 15 of these four parts three-gene combinations were selected and shown. Moreover, a huge difference between high and low expression group of these three-gene combination was detected, with median survival difference of DFS up to 65.01 months, and of OS up to 83.57 months. The high or low expression group of these three-gene combinations can predict the longest prognosis of DFS and OS is 71.91 months and 102.66 months, and the shortest is 6.24 months and 13.96 months. Quantitative real-time polymerase chain reaction and immunohistochemistry reconfirmed that three genes F2, GOT2, and TRPV1 contained in one of the above combinations, are significantly dysregulated in liver cancer tissues, low expression of F2, GOT2, and TRPV1 is associated with poor prognosis in liver cancer. Overall, we discovered a few novel single genes and multi-gene combinations biomarkers that are closely related to the long-term prognosis of liver cancer, and they can be potential therapeutic targets for liver cancer.
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spelling pubmed-72701982020-06-15 Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer Liu, Meiliang Liu, Xia Liu, Shun Xiao, Feifei Guo, Erna Qin, Xiaoling Wu, Liuyu Liang, Qiuli Liang, Zerui Li, Kehua Zhang, Di Yang, Yu Luo, Xingxi Lei, Lei Tan, Jennifer Hui Juan Yin, Fuqiang Zeng, Xiaoyun Front Oncol Oncology Simultaneous identification of multiple single genes and multi-gene prognostic signatures with higher efficacy in liver cancer has rarely been reported. Here, 1,173 genes potentially related to the liver cancer prognosis were mined with Coremine, and the gene expression and survival data in 370 samples for overall survival (OS) and 319 samples for disease-free survival (DFS) were retrieved from The Cancer Genome Atlas. Numerous survival analyses results revealed that 39 genes and 28 genes significantly associated with DFS and OS in liver cancer, including 18 and 12 novel genes that have not been systematically reported in relation to the liver cancer prognosis, respectively. Next, totally 9,139 three-gene combinations (including 816 constructed by 18 novel genes) for predicting DFS and 3,276 three-gene combinations (including 220 constructed by 12 novel genes) for predicting OS were constructed based on the above genes, and the top 15 of these four parts three-gene combinations were selected and shown. Moreover, a huge difference between high and low expression group of these three-gene combination was detected, with median survival difference of DFS up to 65.01 months, and of OS up to 83.57 months. The high or low expression group of these three-gene combinations can predict the longest prognosis of DFS and OS is 71.91 months and 102.66 months, and the shortest is 6.24 months and 13.96 months. Quantitative real-time polymerase chain reaction and immunohistochemistry reconfirmed that three genes F2, GOT2, and TRPV1 contained in one of the above combinations, are significantly dysregulated in liver cancer tissues, low expression of F2, GOT2, and TRPV1 is associated with poor prognosis in liver cancer. Overall, we discovered a few novel single genes and multi-gene combinations biomarkers that are closely related to the long-term prognosis of liver cancer, and they can be potential therapeutic targets for liver cancer. Frontiers Media S.A. 2020-05-28 /pmc/articles/PMC7270198/ /pubmed/32547951 http://dx.doi.org/10.3389/fonc.2020.00847 Text en Copyright © 2020 Liu, Liu, Liu, Xiao, Guo, Qin, Wu, Liang, Liang, Li, Zhang, Yang, Luo, Lei, Tan, Yin and Zeng. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Liu, Meiliang
Liu, Xia
Liu, Shun
Xiao, Feifei
Guo, Erna
Qin, Xiaoling
Wu, Liuyu
Liang, Qiuli
Liang, Zerui
Li, Kehua
Zhang, Di
Yang, Yu
Luo, Xingxi
Lei, Lei
Tan, Jennifer Hui Juan
Yin, Fuqiang
Zeng, Xiaoyun
Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer
title Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer
title_full Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer
title_fullStr Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer
title_full_unstemmed Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer
title_short Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer
title_sort big data-based identification of multi-gene prognostic signatures in liver cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7270198/
https://www.ncbi.nlm.nih.gov/pubmed/32547951
http://dx.doi.org/10.3389/fonc.2020.00847
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