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Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer
Objective: This study aimed to systematically analyze molecular subtypes and therapeutic targets of liver cancer using integrated multi-omics analysis. Methods: DNA copy number variations (CNVs), simple nucleotide variations (SNVs), methylation, transcriptome as well as corresponding clinical inform...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183685/ https://www.ncbi.nlm.nih.gov/pubmed/34109194 http://dx.doi.org/10.3389/fmed.2021.654635 |
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author | Shen, Yi Xiong, Wei Gu, Qi Zhang, Qin Yue, Jia Liu, Changsong Wang, Duan |
author_facet | Shen, Yi Xiong, Wei Gu, Qi Zhang, Qin Yue, Jia Liu, Changsong Wang, Duan |
author_sort | Shen, Yi |
collection | PubMed |
description | Objective: This study aimed to systematically analyze molecular subtypes and therapeutic targets of liver cancer using integrated multi-omics analysis. Methods: DNA copy number variations (CNVs), simple nucleotide variations (SNVs), methylation, transcriptome as well as corresponding clinical information for liver carcinoma were retrieved from The Cancer Genome Atlas (TCGA). Multi-omics analysis was performed to identify molecular subtypes of liver cancer via integrating CNV, methylation as well as transcriptome data. Immune scores of two molecular subtypes were estimated using tumor immune estimation resource (TIMER) tool. Key mRNAs were screened and prognosis analysis was performed, which were validated using RT-qPCR. Furthermore, mutation spectra were analyzed in the different subtypes. Results: Two molecular subtypes (iC1 and iC2) were conducted for liver cancer. Compared with the iC2 subtype, the iC1 subtype had a worse prognosis and a higher immune score. Two key mRNAs (ANXA2 and CHAF1B) were significantly related to liver cancer patients' prognosis, which were both up-regulated in liver cancer tissues in comparison to normal tissues. Seventeen genes with p < 0.01 differed significantly for SNV loci between iC1 and iC2 subtypes. Conclusion: Our integrated multi-omics analyses provided new insights into the molecular subtypes of liver cancer, helping to identify novel mRNAs as therapeutic targets and uncover the mechanisms of liver cancer. |
format | Online Article Text |
id | pubmed-8183685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81836852021-06-08 Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer Shen, Yi Xiong, Wei Gu, Qi Zhang, Qin Yue, Jia Liu, Changsong Wang, Duan Front Med (Lausanne) Medicine Objective: This study aimed to systematically analyze molecular subtypes and therapeutic targets of liver cancer using integrated multi-omics analysis. Methods: DNA copy number variations (CNVs), simple nucleotide variations (SNVs), methylation, transcriptome as well as corresponding clinical information for liver carcinoma were retrieved from The Cancer Genome Atlas (TCGA). Multi-omics analysis was performed to identify molecular subtypes of liver cancer via integrating CNV, methylation as well as transcriptome data. Immune scores of two molecular subtypes were estimated using tumor immune estimation resource (TIMER) tool. Key mRNAs were screened and prognosis analysis was performed, which were validated using RT-qPCR. Furthermore, mutation spectra were analyzed in the different subtypes. Results: Two molecular subtypes (iC1 and iC2) were conducted for liver cancer. Compared with the iC2 subtype, the iC1 subtype had a worse prognosis and a higher immune score. Two key mRNAs (ANXA2 and CHAF1B) were significantly related to liver cancer patients' prognosis, which were both up-regulated in liver cancer tissues in comparison to normal tissues. Seventeen genes with p < 0.01 differed significantly for SNV loci between iC1 and iC2 subtypes. Conclusion: Our integrated multi-omics analyses provided new insights into the molecular subtypes of liver cancer, helping to identify novel mRNAs as therapeutic targets and uncover the mechanisms of liver cancer. Frontiers Media S.A. 2021-05-24 /pmc/articles/PMC8183685/ /pubmed/34109194 http://dx.doi.org/10.3389/fmed.2021.654635 Text en Copyright © 2021 Shen, Xiong, Gu, Zhang, Yue, Liu and Wang. https://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 | Medicine Shen, Yi Xiong, Wei Gu, Qi Zhang, Qin Yue, Jia Liu, Changsong Wang, Duan Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer |
title | Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer |
title_full | Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer |
title_fullStr | Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer |
title_full_unstemmed | Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer |
title_short | Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer |
title_sort | multi-omics integrative analysis uncovers molecular subtypes and mrnas as therapeutic targets for liver cancer |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8183685/ https://www.ncbi.nlm.nih.gov/pubmed/34109194 http://dx.doi.org/10.3389/fmed.2021.654635 |
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