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Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review

BACKGROUND: Since the application of Immune checkpoint inhibitors (ICI), the clinical outcome for metastatic cancer has been greatly improved. Nevertheless, treatment response varies in patients, making it urgent to identify patients who will receive clinical benefits after ICI therapy. Adipose body...

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Autores principales: Pei, Xinyu, Xie, Ye, Liu, Yixuan, Cai, Xinyang, Hong, Lexuan, Yang, Xiaofeng, Zhang, Luyao, Zhang, Manhuai, Zheng, Xinyi, Ning, Kang, Fang, Mengyuan, Tang, Huancheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616831/
https://www.ncbi.nlm.nih.gov/pubmed/37916163
http://dx.doi.org/10.3389/fonc.2023.1198723
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author Pei, Xinyu
Xie, Ye
Liu, Yixuan
Cai, Xinyang
Hong, Lexuan
Yang, Xiaofeng
Zhang, Luyao
Zhang, Manhuai
Zheng, Xinyi
Ning, Kang
Fang, Mengyuan
Tang, Huancheng
author_facet Pei, Xinyu
Xie, Ye
Liu, Yixuan
Cai, Xinyang
Hong, Lexuan
Yang, Xiaofeng
Zhang, Luyao
Zhang, Manhuai
Zheng, Xinyi
Ning, Kang
Fang, Mengyuan
Tang, Huancheng
author_sort Pei, Xinyu
collection PubMed
description BACKGROUND: Since the application of Immune checkpoint inhibitors (ICI), the clinical outcome for metastatic cancer has been greatly improved. Nevertheless, treatment response varies in patients, making it urgent to identify patients who will receive clinical benefits after ICI therapy. Adipose body composition has proved to be associated with tumor response. In this systematic review, we aimed to summarize the current evidence on imaging adipose biomarkers that predict clinical outcomes in patients treated with ICI in various cancer types. METHODS: Embase and PubMed were searched from database inception to 1st February 2023. Articles included investigated the association between imaging-based adipose biomarkers and the clinical outcomes of patients treated with ICI. The methodological quality of included studies was evaluated through Newcastle- Ottawa Quality Assessment Scale and Radiomics Quality Score tools. RESULTS: Totally, 22 studies including 2256 patients were selected. Non-small cell lung cancer (NSCLC) had the most articles (6 studies), followed by melanoma (5 studies), renal cell carcinoma (RCC) (3 studies), urothelial carcinoma (UC) (2 studies), head and neck squamous cell carcinoma (HNSCC) (1 study), gastric cancer (1 study) and liver cancer (1 study). The remaining 3 studies investigated metastatic solid tumors including various types of cancers. Adipose biomarkers can be summarized into 5 categories, including total fat, visceral fat, subcutaneous fat, intramuscular fat and others, which exerted diverse correlations with patients’ prognosis after being treated with ICI in different cancers. Most biomarkers of body fat were positively associated with survival benefits. Nevertheless, more total fat was predictable of worse outcomes in NSCLC, while inter-muscular fat was associated with poor clinical benefits in UC. CONCLUSION: There is relatively well-supported evidence for imaging-based adipose biomarkers to predict the clinical outcome of ICI. In general, most of the studies show that adipose tissue is positively correlated with clinical outcomes. This review summarizes the significant biomarkers proven by researches for each cancer type. Further validation and large independent prospective cohorts are needed in the future. The protocol of this systematic review has been registered at the International Prospective Register of Systematic Reviews (http://www.crd.york.ac.uk/PROSPERO, registration no: CRD42023401986).
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spelling pubmed-106168312023-11-01 Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review Pei, Xinyu Xie, Ye Liu, Yixuan Cai, Xinyang Hong, Lexuan Yang, Xiaofeng Zhang, Luyao Zhang, Manhuai Zheng, Xinyi Ning, Kang Fang, Mengyuan Tang, Huancheng Front Oncol Oncology BACKGROUND: Since the application of Immune checkpoint inhibitors (ICI), the clinical outcome for metastatic cancer has been greatly improved. Nevertheless, treatment response varies in patients, making it urgent to identify patients who will receive clinical benefits after ICI therapy. Adipose body composition has proved to be associated with tumor response. In this systematic review, we aimed to summarize the current evidence on imaging adipose biomarkers that predict clinical outcomes in patients treated with ICI in various cancer types. METHODS: Embase and PubMed were searched from database inception to 1st February 2023. Articles included investigated the association between imaging-based adipose biomarkers and the clinical outcomes of patients treated with ICI. The methodological quality of included studies was evaluated through Newcastle- Ottawa Quality Assessment Scale and Radiomics Quality Score tools. RESULTS: Totally, 22 studies including 2256 patients were selected. Non-small cell lung cancer (NSCLC) had the most articles (6 studies), followed by melanoma (5 studies), renal cell carcinoma (RCC) (3 studies), urothelial carcinoma (UC) (2 studies), head and neck squamous cell carcinoma (HNSCC) (1 study), gastric cancer (1 study) and liver cancer (1 study). The remaining 3 studies investigated metastatic solid tumors including various types of cancers. Adipose biomarkers can be summarized into 5 categories, including total fat, visceral fat, subcutaneous fat, intramuscular fat and others, which exerted diverse correlations with patients’ prognosis after being treated with ICI in different cancers. Most biomarkers of body fat were positively associated with survival benefits. Nevertheless, more total fat was predictable of worse outcomes in NSCLC, while inter-muscular fat was associated with poor clinical benefits in UC. CONCLUSION: There is relatively well-supported evidence for imaging-based adipose biomarkers to predict the clinical outcome of ICI. In general, most of the studies show that adipose tissue is positively correlated with clinical outcomes. This review summarizes the significant biomarkers proven by researches for each cancer type. Further validation and large independent prospective cohorts are needed in the future. The protocol of this systematic review has been registered at the International Prospective Register of Systematic Reviews (http://www.crd.york.ac.uk/PROSPERO, registration no: CRD42023401986). Frontiers Media S.A. 2023-10-17 /pmc/articles/PMC10616831/ /pubmed/37916163 http://dx.doi.org/10.3389/fonc.2023.1198723 Text en Copyright © 2023 Pei, Xie, Liu, Cai, Hong, Yang, Zhang, Zhang, Zheng, Ning, Fang and Tang 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
Pei, Xinyu
Xie, Ye
Liu, Yixuan
Cai, Xinyang
Hong, Lexuan
Yang, Xiaofeng
Zhang, Luyao
Zhang, Manhuai
Zheng, Xinyi
Ning, Kang
Fang, Mengyuan
Tang, Huancheng
Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review
title Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review
title_full Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review
title_fullStr Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review
title_full_unstemmed Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review
title_short Imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review
title_sort imaging-based adipose biomarkers for predicting clinical outcomes of cancer patients treated with immune checkpoint inhibitors: a systematic review
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616831/
https://www.ncbi.nlm.nih.gov/pubmed/37916163
http://dx.doi.org/10.3389/fonc.2023.1198723
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