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Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer

PURPOSE: Pancreatic cancer is one of the deadliest cancers worldwide. The extracellular matrix (ECM) microenvironment affects the drug sensitivity and prognosis of pancreatic cancer patients. This study constructed an 8-genes pancreatic ECM scoring (PECMS) model, to classify the ECM features of panc...

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Autores principales: Ji, Hongchen, Zhang, Qiong, Wang, Xiang-Xu, Li, Junjie, Wang, Xiaowen, Pan, Wei, Zhang, Zhuochao, Ma, Ben, Zhang, Hong-Mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9411435/
https://www.ncbi.nlm.nih.gov/pubmed/36006549
http://dx.doi.org/10.1007/s12672-022-00532-y
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author Ji, Hongchen
Zhang, Qiong
Wang, Xiang-Xu
Li, Junjie
Wang, Xiaowen
Pan, Wei
Zhang, Zhuochao
Ma, Ben
Zhang, Hong-Mei
author_facet Ji, Hongchen
Zhang, Qiong
Wang, Xiang-Xu
Li, Junjie
Wang, Xiaowen
Pan, Wei
Zhang, Zhuochao
Ma, Ben
Zhang, Hong-Mei
author_sort Ji, Hongchen
collection PubMed
description PURPOSE: Pancreatic cancer is one of the deadliest cancers worldwide. The extracellular matrix (ECM) microenvironment affects the drug sensitivity and prognosis of pancreatic cancer patients. This study constructed an 8-genes pancreatic ECM scoring (PECMS) model, to classify the ECM features of pancreatic cancer, analyze the impact of ECM features on survival and drug sensitivity, and mine key molecules that influence ECM features in pancreatic cancer. METHODS: GSVA score calculation and clustering were performed in TCGA-PAAD patients. Lasso regression was used to construct the PECMS model. The association between PECMS and patient survival was analyzed and validated in the CPTAC-3 dataset of TCGA and our single-center retrospective cohort. The relationships between PECMS and features of the matrix microenvironment were analyzed. Finally, PECMS feature genes were screened and verified in pancreatic cancer specimens to select key genes associated with the ECM microenvironment. RESULT: The survival of the PECMS-high group was significantly worse. The PECMS-high group showed higher oxidative stress levels, lower levels of antigen presentation- and MHC-I molecule-related pathways, and less immune effector cell infiltration. Data from IMvigor-210 cohort suggested that PECMS-low group patients were more sensitive to immune checkpoint blockers. The PECMS score was negatively correlated with chemotherapy drug sensitivity. The negative association of PECMS with survival and drug sensitivity was validated in our retrospective cohort. KLHL32 expression predicted lower oxidative stress level and more immune cells infiltrate in pancreatic cancer. CONCLUSION: PECMS is an effective predictor of prognosis and drug sensitivity in pancreatic cancer patients. KLHL32 may play an important role in the construction of ECM, and the mechanism is worth further study. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-022-00532-y.
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spelling pubmed-94114352022-08-27 Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer Ji, Hongchen Zhang, Qiong Wang, Xiang-Xu Li, Junjie Wang, Xiaowen Pan, Wei Zhang, Zhuochao Ma, Ben Zhang, Hong-Mei Discov Oncol Research PURPOSE: Pancreatic cancer is one of the deadliest cancers worldwide. The extracellular matrix (ECM) microenvironment affects the drug sensitivity and prognosis of pancreatic cancer patients. This study constructed an 8-genes pancreatic ECM scoring (PECMS) model, to classify the ECM features of pancreatic cancer, analyze the impact of ECM features on survival and drug sensitivity, and mine key molecules that influence ECM features in pancreatic cancer. METHODS: GSVA score calculation and clustering were performed in TCGA-PAAD patients. Lasso regression was used to construct the PECMS model. The association between PECMS and patient survival was analyzed and validated in the CPTAC-3 dataset of TCGA and our single-center retrospective cohort. The relationships between PECMS and features of the matrix microenvironment were analyzed. Finally, PECMS feature genes were screened and verified in pancreatic cancer specimens to select key genes associated with the ECM microenvironment. RESULT: The survival of the PECMS-high group was significantly worse. The PECMS-high group showed higher oxidative stress levels, lower levels of antigen presentation- and MHC-I molecule-related pathways, and less immune effector cell infiltration. Data from IMvigor-210 cohort suggested that PECMS-low group patients were more sensitive to immune checkpoint blockers. The PECMS score was negatively correlated with chemotherapy drug sensitivity. The negative association of PECMS with survival and drug sensitivity was validated in our retrospective cohort. KLHL32 expression predicted lower oxidative stress level and more immune cells infiltrate in pancreatic cancer. CONCLUSION: PECMS is an effective predictor of prognosis and drug sensitivity in pancreatic cancer patients. KLHL32 may play an important role in the construction of ECM, and the mechanism is worth further study. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-022-00532-y. Springer US 2022-08-25 /pmc/articles/PMC9411435/ /pubmed/36006549 http://dx.doi.org/10.1007/s12672-022-00532-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Ji, Hongchen
Zhang, Qiong
Wang, Xiang-Xu
Li, Junjie
Wang, Xiaowen
Pan, Wei
Zhang, Zhuochao
Ma, Ben
Zhang, Hong-Mei
Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer
title Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer
title_full Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer
title_fullStr Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer
title_full_unstemmed Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer
title_short Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer
title_sort identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9411435/
https://www.ncbi.nlm.nih.gov/pubmed/36006549
http://dx.doi.org/10.1007/s12672-022-00532-y
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