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Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes

PURPOSE: The current clinical classification of pancreatic ductal adenocarcinoma (PDAC) cannot well predict the patient’s possible response to the treatment plan, nor can it predict the patient’s prognosis. We use the gene expression patterns of PDAC patients to reveal the heterogeneity of the tumor...

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Autores principales: Wang, Xiaoqin, Li, Lifang, Yang, Yang, Fan, Linlin, Ma, Ying, Mao, Feifei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8891159/
https://www.ncbi.nlm.nih.gov/pubmed/35252003
http://dx.doi.org/10.3389/fonc.2022.832715
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author Wang, Xiaoqin
Li, Lifang
Yang, Yang
Fan, Linlin
Ma, Ying
Mao, Feifei
author_facet Wang, Xiaoqin
Li, Lifang
Yang, Yang
Fan, Linlin
Ma, Ying
Mao, Feifei
author_sort Wang, Xiaoqin
collection PubMed
description PURPOSE: The current clinical classification of pancreatic ductal adenocarcinoma (PDAC) cannot well predict the patient’s possible response to the treatment plan, nor can it predict the patient’s prognosis. We use the gene expression patterns of PDAC patients to reveal the heterogeneity of the tumor microenvironment of pancreatic cancer and analyze the differences in the prognosis and immunotherapy response of different immune subtypes. METHODS: Firstly, use ICGC’s PACA-AU PDAC expression profile data, combined with the ssGSEA algorithm, to analyze the immune enrichment of the patient’s tumor microenvironment. Subsequently, the spectral clustering algorithm was used to extract different classifications, the PDAC cohort was divided into four subtypes, and the correlation between immune subtypes and clinical characteristics and survival prognosis was established. The patient’s risk index is obtained through the prognostic prediction model, and the correlation between the risk index and immune cells is prompted. RESULTS: We can divide the PDAC cohort into four subtypes: immune cell and stromal cell enrichment (Immune-enrich-Stroma), non-immune enrichment but stromal cell enrichment (Non-immune-Stroma), immune-enriched Collective but non-matrix enrichment (Immune-enrich-non-Stroma) and non-immune enrichment and non-stromal cell enrichment (Non-immune-non-Stroma). The five-year survival rate of immune-enrich-Stroma and non-immune-Stroma of PACA-CA is quite different. TCGA-PAAD’s immune-enrich-Stroma and immune-enrich-non-Stroma groups have a large difference in productivity in one year. The results of the correlation analysis between the risk index and immune cells show that the patient’s disease risk is significantly related to epithelial cells, megakaryocyte-erythroid progenitor (MEP), and Th2 cells. CONCLUSION: The tumor gene expression characteristics of pancreatic cancer patients are related to immune response, leading to morphologically recognizable PDAC subtypes with prognostic/predictive significance.
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spelling pubmed-88911592022-03-04 Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes Wang, Xiaoqin Li, Lifang Yang, Yang Fan, Linlin Ma, Ying Mao, Feifei Front Oncol Oncology PURPOSE: The current clinical classification of pancreatic ductal adenocarcinoma (PDAC) cannot well predict the patient’s possible response to the treatment plan, nor can it predict the patient’s prognosis. We use the gene expression patterns of PDAC patients to reveal the heterogeneity of the tumor microenvironment of pancreatic cancer and analyze the differences in the prognosis and immunotherapy response of different immune subtypes. METHODS: Firstly, use ICGC’s PACA-AU PDAC expression profile data, combined with the ssGSEA algorithm, to analyze the immune enrichment of the patient’s tumor microenvironment. Subsequently, the spectral clustering algorithm was used to extract different classifications, the PDAC cohort was divided into four subtypes, and the correlation between immune subtypes and clinical characteristics and survival prognosis was established. The patient’s risk index is obtained through the prognostic prediction model, and the correlation between the risk index and immune cells is prompted. RESULTS: We can divide the PDAC cohort into four subtypes: immune cell and stromal cell enrichment (Immune-enrich-Stroma), non-immune enrichment but stromal cell enrichment (Non-immune-Stroma), immune-enriched Collective but non-matrix enrichment (Immune-enrich-non-Stroma) and non-immune enrichment and non-stromal cell enrichment (Non-immune-non-Stroma). The five-year survival rate of immune-enrich-Stroma and non-immune-Stroma of PACA-CA is quite different. TCGA-PAAD’s immune-enrich-Stroma and immune-enrich-non-Stroma groups have a large difference in productivity in one year. The results of the correlation analysis between the risk index and immune cells show that the patient’s disease risk is significantly related to epithelial cells, megakaryocyte-erythroid progenitor (MEP), and Th2 cells. CONCLUSION: The tumor gene expression characteristics of pancreatic cancer patients are related to immune response, leading to morphologically recognizable PDAC subtypes with prognostic/predictive significance. Frontiers Media S.A. 2022-02-17 /pmc/articles/PMC8891159/ /pubmed/35252003 http://dx.doi.org/10.3389/fonc.2022.832715 Text en Copyright © 2022 Wang, Li, Yang, Fan, Ma and Mao 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 Oncology
Wang, Xiaoqin
Li, Lifang
Yang, Yang
Fan, Linlin
Ma, Ying
Mao, Feifei
Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes
title Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes
title_full Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes
title_fullStr Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes
title_full_unstemmed Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes
title_short Reveal the Heterogeneity in the Tumor Microenvironment of Pancreatic Cancer and Analyze the Differences in Prognosis and Immunotherapy Responses of Distinct Immune Subtypes
title_sort reveal the heterogeneity in the tumor microenvironment of pancreatic cancer and analyze the differences in prognosis and immunotherapy responses of distinct immune subtypes
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8891159/
https://www.ncbi.nlm.nih.gov/pubmed/35252003
http://dx.doi.org/10.3389/fonc.2022.832715
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