mRNAsi-related metabolic risk score model identifies poor prognosis, immunoevasive contexture, and low chemotherapy response in colorectal cancer patients through machine learning

Colorectal cancer (CRC) is one of the most fatal cancers of the digestive system. Although cancer stem cells and metabolic reprogramming have an important effect on tumor progression and drug resistance, their combined effect on CRC prognosis remains unclear. Therefore, we generated a 21-gene mRNA s...

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Published in:Frontiers in immunology Vol. 13; p. 950782
Main Authors: Weng, Meilin, Li, Ting, Zhao, Jing, Guo, Miaomiao, Zhao, Wenling, Gu, Wenchao, Sun, Caihong, Yue, Ying, Zhong, Ziwen, Nan, Ke, Liao, Qingwu, Sun, Minli, Zhou, Di, Miao, Changhong
Format: Journal Article
Language:English
Published: Frontiers Media S.A 23.08.2022
Subjects:
colorectal cancer
Immunology
immunotherapy
metabolism
mRNAsi
risk score model
stemness
ISSN:1664-3224, 1664-3224
Online Access:Get full text
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Summary:Colorectal cancer (CRC) is one of the most fatal cancers of the digestive system. Although cancer stem cells and metabolic reprogramming have an important effect on tumor progression and drug resistance, their combined effect on CRC prognosis remains unclear. Therefore, we generated a 21-gene mRNA stemness index-related metabolic risk score model, which was examined in The Cancer Genome Atlas and Gene Expression Omnibus databases (1323 patients) and validated using the Zhongshan Hospital cohort (200 patients). The high-risk group showed more immune infiltrations; higher levels of immunosuppressive checkpoints, such as CD274, tumor mutation burden, and resistance to chemotherapeutics; potentially better response to immune therapy; worse prognosis; and advanced stage of tumor node metastasis than the low-risk group. The combination of risk score and clinical characteristics was effective in predicting overall survival. Zhongshan cohort validated that high-risk score group correlated with malignant progression, worse prognosis, inferior adjuvant chemotherapy responsiveness of CRC, and shaped an immunoevasive contexture. This tool may provide a more accurate risk stratification in CRC and screening of patients with CRC responsive to immunotherapy.
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Edited by: Meng Zhou, Wenzhou Medical University, China
Reviewed by: Fangfang Duan, Shenzhen Campus of Sun Yat-sen University, China; Ping Zheng, The University of Melbourne, Australia; Zhenhuan Zhao, University of Virginia, United States
These authors have contributed equally to this work and share first authorship
This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology
ISSN:1664-3224
1664-3224
DOI:10.3389/fimmu.2022.950782