Integrating machine learning and single-cell trajectories to analyze T-cell exhaustion to predict prognosis and immunotherapy in colon cancer patients
IntroductionThe incidence of colon adenocarcinoma (COAD) has recently increased, and patients with advanced COAD have a poor prognosis due to treatment resistance. Combining conventional treatment with targeted therapy and immunotherapy has shown unexpectedly positive results in improving the progno...
Main Authors: | Xiaogang Shen, Xiaofei Zuo, Liang Liang, Lin Wang, Bin Luo |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2023-05-01
|
Series: | Frontiers in Immunology |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1162843/full |
Similar Items
-
Construction of a prognostic model for colorectal adenocarcinoma based on Zn transport-related genes identified by single-cell sequencing and weighted co-expression network analysis
by: Hua Chen, et al.
Published: (2023-09-01) -
Copper metabolism patterns and tumor microenvironment characterization in colon adenocarcinoma
by: Jianwei Lin, et al.
Published: (2022-09-01) -
A Prognostic Pyroptosis-Related lncRNAs Risk Model Correlates With the Immune Microenvironment in Colon Adenocarcinoma
by: Fada Xia, et al.
Published: (2021-12-01) -
Comprehensive analysis of the prognosis, tumor microenvironment, and immunotherapy response of SDHs in colon adenocarcinoma
by: Han Nan, et al.
Published: (2023-03-01) -
Prognostic Immune-Related Analysis Based on Differentially Expressed Genes in Left- and Right-Sided Colon Adenocarcinoma
by: Jun-Nan Guo, et al.
Published: (2021-03-01)