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Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins

BACKGROUND: Immune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC. METHODS: We comprehensively profiled 14 soluble ICK-related prot...

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Autores principales: Pan, Sai, Zhao, Wenting, Li, Yizhan, Ying, Zhijun, Luo, Yihong, Wang, Qinchuan, Li, Xiawei, Lu, Wenjie, Dong, Xin, Wu, Yulian, Wu, Xifeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10225568/
https://www.ncbi.nlm.nih.gov/pubmed/37256126
http://dx.doi.org/10.3389/fimmu.2023.1189161
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author Pan, Sai
Zhao, Wenting
Li, Yizhan
Ying, Zhijun
Luo, Yihong
Wang, Qinchuan
Li, Xiawei
Lu, Wenjie
Dong, Xin
Wu, Yulian
Wu, Xifeng
author_facet Pan, Sai
Zhao, Wenting
Li, Yizhan
Ying, Zhijun
Luo, Yihong
Wang, Qinchuan
Li, Xiawei
Lu, Wenjie
Dong, Xin
Wu, Yulian
Wu, Xifeng
author_sort Pan, Sai
collection PubMed
description BACKGROUND: Immune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC. METHODS: We comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients’ clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell’s concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms. RESULTS: Soluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes’ expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16). CONCLUSION: Five soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype.
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spelling pubmed-102255682023-05-30 Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins Pan, Sai Zhao, Wenting Li, Yizhan Ying, Zhijun Luo, Yihong Wang, Qinchuan Li, Xiawei Lu, Wenjie Dong, Xin Wu, Yulian Wu, Xifeng Front Immunol Immunology BACKGROUND: Immune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC. METHODS: We comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients’ clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell’s concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms. RESULTS: Soluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes’ expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16). CONCLUSION: Five soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype. Frontiers Media S.A. 2023-05-15 /pmc/articles/PMC10225568/ /pubmed/37256126 http://dx.doi.org/10.3389/fimmu.2023.1189161 Text en Copyright © 2023 Pan, Zhao, Li, Ying, Luo, Wang, Li, Lu, Dong, Wu and Wu 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 Immunology
Pan, Sai
Zhao, Wenting
Li, Yizhan
Ying, Zhijun
Luo, Yihong
Wang, Qinchuan
Li, Xiawei
Lu, Wenjie
Dong, Xin
Wu, Yulian
Wu, Xifeng
Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins
title Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins
title_full Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins
title_fullStr Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins
title_full_unstemmed Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins
title_short Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins
title_sort prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10225568/
https://www.ncbi.nlm.nih.gov/pubmed/37256126
http://dx.doi.org/10.3389/fimmu.2023.1189161
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