Identification of signature of tumor-infiltrating CD8 T lymphocytes in prognosis and immunotherapy of colon cancer by machine learning.
Immunotherapy
Machine learning
Prognosis
Tumor-infiltrating CD8 T lymphocytes
colon cancer
Journal
Clinical immunology (Orlando, Fla.)
ISSN: 1521-7035
Titre abrégé: Clin Immunol
Pays: United States
ID NLM: 100883537
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
received:
30
07
2022
revised:
25
09
2023
accepted:
16
10
2023
pubmed:
20
10
2023
medline:
20
10
2023
entrez:
20
10
2023
Statut:
ppublish
Résumé
To explore the specific marker of CD8+ T cell subsets which are closely related to the prognosis and immunotherapy of patients with colon cancer. 18 kinds of immune cell expression profile data sets were obtained from GEO database. Compared with other immune cell types, the specific markers of CD8 (+) T cells (TI-CD8) in colorectal cancer were screened. Regression analyses were used to further screen prognostic related genes and construct a prognostic evaluation model. The patients were stratified and analyzed according to the risk scores, KRAS mutation status, stage, lymphatic infiltration and other indicators. The landscape of infiltration level, mutation and copy number variation of immune subsets in high and low TI-CD8Sig score groups were compared and analyzed. The difference of drug response between high and low TI-CD8Sig score groups was analyzed. Differential expression of the model genes was verified by the HPA database. Six prognostic-related CD8T cell-specific gene targets were further screened, and the prognostic evaluation model was constructed. The AUC value of the model is >0.75. FAT3 and UNC13C showed a high mutation state in the low-risk group, while USH2A, MUC5B et al. specifically showed a high mutation state in the high-risk group. Compared with the low-risk group, the high-risk group had lower effective rate of drug response. The expression of PD-1 gene was positively correlated with the level of TI-CD8Sig score. The risk assessment model based on CD8T cell-specific marker genes can effectively predict the prognosis and the drug response of patients with CRC.
Sections du résumé
BACKGROUND
BACKGROUND
To explore the specific marker of CD8+ T cell subsets which are closely related to the prognosis and immunotherapy of patients with colon cancer.
METHODS
METHODS
18 kinds of immune cell expression profile data sets were obtained from GEO database. Compared with other immune cell types, the specific markers of CD8 (+) T cells (TI-CD8) in colorectal cancer were screened. Regression analyses were used to further screen prognostic related genes and construct a prognostic evaluation model. The patients were stratified and analyzed according to the risk scores, KRAS mutation status, stage, lymphatic infiltration and other indicators. The landscape of infiltration level, mutation and copy number variation of immune subsets in high and low TI-CD8Sig score groups were compared and analyzed. The difference of drug response between high and low TI-CD8Sig score groups was analyzed. Differential expression of the model genes was verified by the HPA database.
RESULTS
RESULTS
Six prognostic-related CD8T cell-specific gene targets were further screened, and the prognostic evaluation model was constructed. The AUC value of the model is >0.75. FAT3 and UNC13C showed a high mutation state in the low-risk group, while USH2A, MUC5B et al. specifically showed a high mutation state in the high-risk group. Compared with the low-risk group, the high-risk group had lower effective rate of drug response. The expression of PD-1 gene was positively correlated with the level of TI-CD8Sig score.
CONCLUSION
CONCLUSIONS
The risk assessment model based on CD8T cell-specific marker genes can effectively predict the prognosis and the drug response of patients with CRC.
Identifiants
pubmed: 37858752
pii: S1521-6616(23)00574-0
doi: 10.1016/j.clim.2023.109811
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
109811Informations de copyright
Copyright © 2023. Published by Elsevier Inc.
Déclaration de conflit d'intérêts
Declaration of Competing Interest There are no conflicts of interest in this study.