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Pathological images for personal medicine in Hepatocellular carcinoma: Cross-talk of gene sequencing and pathological images

BACKGROUND: Considering the great heterogeneity of Hepatocellular carcinoma (HCC), more accurate prognostic models are urgently needed. This paper combined the advantages of genomics and pathomics to construct a prognostic model. METHODS: First, we collected data from hepatocellular carcinoma patien...

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Autores principales: YANG, LI, DENG, KUN, MOU, ZHIQIANG, XIONG, PINGFU, WEN, JIAN, LI, JING
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tech Science Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208011/
https://www.ncbi.nlm.nih.gov/pubmed/37305349
http://dx.doi.org/10.32604/or.2022.027958
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author YANG, LI
DENG, KUN
MOU, ZHIQIANG
XIONG, PINGFU
WEN, JIAN
LI, JING
author_facet YANG, LI
DENG, KUN
MOU, ZHIQIANG
XIONG, PINGFU
WEN, JIAN
LI, JING
author_sort YANG, LI
collection PubMed
description BACKGROUND: Considering the great heterogeneity of Hepatocellular carcinoma (HCC), more accurate prognostic models are urgently needed. This paper combined the advantages of genomics and pathomics to construct a prognostic model. METHODS: First, we collected data from hepatocellular carcinoma patients with complete mRNA expression profiles and clinical annotations from the TCGA database. Then, based on immune-related genes, we used random forest plots to screen prognosis-related genes and build prognostic models. Bioinformatics was used to identify biological pathways, evaluate the tumor microenvironment, and perform drug susceptibility testing. Finally, we divided the patients into different subgroups according to the gene model algorithm. Pathological models were constructed by obtaining HE-stained sections from TCGA in corresponding subgroups of patients. RESULTS: In this study, we constructed a stable prognostic model that could predict overall survival in HCC patients. The signature consisted of six immune-related genes (BX537318.1, TMEM147, CSPG4P12, AC015908.3, CEBPZOS, and SRD5A3). We found increased levels of infiltration of immune cells in the tumor microenvironment in patients with low risk scores, indicating significant antitumor immunity and corresponding to better clinical outcomes. We then screened nine drugs that were more sensitive in the low-risk group than in the high-risk group. Finally, we addressed the complex cellular changes and phenotypic heterogeneity in the HCC microenvironment by combining genomics and pathomics analysis methods. CONCLUSION: Our study showed that the prognostic evaluation model of HCC based on the immune signaling pathway is feasible and provided a reference value for potential immunotherapy for HCC.
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spelling pubmed-102080112023-06-10 Pathological images for personal medicine in Hepatocellular carcinoma: Cross-talk of gene sequencing and pathological images YANG, LI DENG, KUN MOU, ZHIQIANG XIONG, PINGFU WEN, JIAN LI, JING Oncol Res Article BACKGROUND: Considering the great heterogeneity of Hepatocellular carcinoma (HCC), more accurate prognostic models are urgently needed. This paper combined the advantages of genomics and pathomics to construct a prognostic model. METHODS: First, we collected data from hepatocellular carcinoma patients with complete mRNA expression profiles and clinical annotations from the TCGA database. Then, based on immune-related genes, we used random forest plots to screen prognosis-related genes and build prognostic models. Bioinformatics was used to identify biological pathways, evaluate the tumor microenvironment, and perform drug susceptibility testing. Finally, we divided the patients into different subgroups according to the gene model algorithm. Pathological models were constructed by obtaining HE-stained sections from TCGA in corresponding subgroups of patients. RESULTS: In this study, we constructed a stable prognostic model that could predict overall survival in HCC patients. The signature consisted of six immune-related genes (BX537318.1, TMEM147, CSPG4P12, AC015908.3, CEBPZOS, and SRD5A3). We found increased levels of infiltration of immune cells in the tumor microenvironment in patients with low risk scores, indicating significant antitumor immunity and corresponding to better clinical outcomes. We then screened nine drugs that were more sensitive in the low-risk group than in the high-risk group. Finally, we addressed the complex cellular changes and phenotypic heterogeneity in the HCC microenvironment by combining genomics and pathomics analysis methods. CONCLUSION: Our study showed that the prognostic evaluation model of HCC based on the immune signaling pathway is feasible and provided a reference value for potential immunotherapy for HCC. Tech Science Press 2023-02-03 /pmc/articles/PMC10208011/ /pubmed/37305349 http://dx.doi.org/10.32604/or.2022.027958 Text en © 2022 Yang et al. https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
YANG, LI
DENG, KUN
MOU, ZHIQIANG
XIONG, PINGFU
WEN, JIAN
LI, JING
Pathological images for personal medicine in Hepatocellular carcinoma: Cross-talk of gene sequencing and pathological images
title Pathological images for personal medicine in Hepatocellular carcinoma: Cross-talk of gene sequencing and pathological images
title_full Pathological images for personal medicine in Hepatocellular carcinoma: Cross-talk of gene sequencing and pathological images
title_fullStr Pathological images for personal medicine in Hepatocellular carcinoma: Cross-talk of gene sequencing and pathological images
title_full_unstemmed Pathological images for personal medicine in Hepatocellular carcinoma: Cross-talk of gene sequencing and pathological images
title_short Pathological images for personal medicine in Hepatocellular carcinoma: Cross-talk of gene sequencing and pathological images
title_sort pathological images for personal medicine in hepatocellular carcinoma: cross-talk of gene sequencing and pathological images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208011/
https://www.ncbi.nlm.nih.gov/pubmed/37305349
http://dx.doi.org/10.32604/or.2022.027958
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