Cargando…

The modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world, with the second highest mortality rate among all cancer types. Growing evidence has demonstrated the notable effects of intratumor heterogeneity (ITH) and tumor immune microenvironment heterogeneity (TIMH) on the biological...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Liu-Bo, Yang, Lu, Xie, Guo-Qun, Zhou, Xiao-Cui, Shen, Xu-Bo, Xu, Qiu-Lin, Ma, Zheng-Yuan, Guo, Xiao-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500054/
https://www.ncbi.nlm.nih.gov/pubmed/32968455
http://dx.doi.org/10.3892/ol.2020.12096
_version_ 1783583790124236800
author Li, Liu-Bo
Yang, Lu
Xie, Guo-Qun
Zhou, Xiao-Cui
Shen, Xu-Bo
Xu, Qiu-Lin
Ma, Zheng-Yuan
Guo, Xiao-Dong
author_facet Li, Liu-Bo
Yang, Lu
Xie, Guo-Qun
Zhou, Xiao-Cui
Shen, Xu-Bo
Xu, Qiu-Lin
Ma, Zheng-Yuan
Guo, Xiao-Dong
author_sort Li, Liu-Bo
collection PubMed
description Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world, with the second highest mortality rate among all cancer types. Growing evidence has demonstrated the notable effects of intratumor heterogeneity (ITH) and tumor immune microenvironment heterogeneity (TIMH) on the biological processes involved in HCC. However, the interactive mechanisms between ITH and TIMH is still unclear. The present study systematically screened the mRNA expression, simple nucleotide variation data and clinical data of samples from The Cancer Genome Atlas (TCGA). The mutant-allele tumor heterogeneity (MATH) score was used to represent ITH, and TCGA cohort was divided into two groups according to the MATH score. Next, different immune-related signaling pathways and enriched immune-related genes were identified using Gene Set Enrichment Analysis of these two groups, and the results revealed that interleukin-1α (IL1A) and serine/threonine-protein kinase PAK4 were associated with prognosis. Furthermore, CIBERSORT was utilized to calculate the fractions of 22 types of leukocytes to represent TIMH, and the fractions of M1 and M2 macrophages were confirmed to be associated with prognosis. Therefore, PAK4, interleukin-1α (IL1A), and M1/M2 ratio were selected as the key factors involved in the interaction between ITH and TIMH. Afterwards, microRNAs (miRNAs) that were linearly related to the M1/M2 ratio and the potential target genes of the miRNAs were screened. Finally, the regulatory network between PAK4, IL1A, and the M1/M2 ratio was established, bridged by the above miRNAs and the target genes. In addition, PAK4, heat shock protein 105 kDa and miRNA-1911 were demonstrated to be a key factor involved in immune response via Weighted Correlation Network Analysis in HCC.
format Online
Article
Text
id pubmed-7500054
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher D.A. Spandidos
record_format MEDLINE/PubMed
spelling pubmed-75000542020-09-22 The modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma Li, Liu-Bo Yang, Lu Xie, Guo-Qun Zhou, Xiao-Cui Shen, Xu-Bo Xu, Qiu-Lin Ma, Zheng-Yuan Guo, Xiao-Dong Oncol Lett Articles Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world, with the second highest mortality rate among all cancer types. Growing evidence has demonstrated the notable effects of intratumor heterogeneity (ITH) and tumor immune microenvironment heterogeneity (TIMH) on the biological processes involved in HCC. However, the interactive mechanisms between ITH and TIMH is still unclear. The present study systematically screened the mRNA expression, simple nucleotide variation data and clinical data of samples from The Cancer Genome Atlas (TCGA). The mutant-allele tumor heterogeneity (MATH) score was used to represent ITH, and TCGA cohort was divided into two groups according to the MATH score. Next, different immune-related signaling pathways and enriched immune-related genes were identified using Gene Set Enrichment Analysis of these two groups, and the results revealed that interleukin-1α (IL1A) and serine/threonine-protein kinase PAK4 were associated with prognosis. Furthermore, CIBERSORT was utilized to calculate the fractions of 22 types of leukocytes to represent TIMH, and the fractions of M1 and M2 macrophages were confirmed to be associated with prognosis. Therefore, PAK4, interleukin-1α (IL1A), and M1/M2 ratio were selected as the key factors involved in the interaction between ITH and TIMH. Afterwards, microRNAs (miRNAs) that were linearly related to the M1/M2 ratio and the potential target genes of the miRNAs were screened. Finally, the regulatory network between PAK4, IL1A, and the M1/M2 ratio was established, bridged by the above miRNAs and the target genes. In addition, PAK4, heat shock protein 105 kDa and miRNA-1911 were demonstrated to be a key factor involved in immune response via Weighted Correlation Network Analysis in HCC. D.A. Spandidos 2020-11 2020-09-11 /pmc/articles/PMC7500054/ /pubmed/32968455 http://dx.doi.org/10.3892/ol.2020.12096 Text en Copyright: © Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Li, Liu-Bo
Yang, Lu
Xie, Guo-Qun
Zhou, Xiao-Cui
Shen, Xu-Bo
Xu, Qiu-Lin
Ma, Zheng-Yuan
Guo, Xiao-Dong
The modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma
title The modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma
title_full The modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma
title_fullStr The modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma
title_full_unstemmed The modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma
title_short The modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma
title_sort modulation relationship of genomic pattern of intratumor heterogeneity and immunity microenvironment heterogeneity in hepatocellular carcinoma
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500054/
https://www.ncbi.nlm.nih.gov/pubmed/32968455
http://dx.doi.org/10.3892/ol.2020.12096
work_keys_str_mv AT liliubo themodulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT yanglu themodulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT xieguoqun themodulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT zhouxiaocui themodulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT shenxubo themodulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT xuqiulin themodulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT mazhengyuan themodulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT guoxiaodong themodulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT liliubo modulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT yanglu modulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT xieguoqun modulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT zhouxiaocui modulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT shenxubo modulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT xuqiulin modulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT mazhengyuan modulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma
AT guoxiaodong modulationrelationshipofgenomicpatternofintratumorheterogeneityandimmunitymicroenvironmentheterogeneityinhepatocellularcarcinoma