Single-cell analysis reveals the prognostic role of immune escape in the colorectal cancer microenvironment.
1/5 보강
[BACKGROUND] Colorectal cancer (CRC) is a malignant disease that poses a significant threat to human health; however, early diagnostic and treatment strategies for it remain limited.
APA
Gan Q, Xu X, et al. (2026). Single-cell analysis reveals the prognostic role of immune escape in the colorectal cancer microenvironment.. Translational cancer research, 15(1), 26. https://doi.org/10.21037/tcr-2025-1466
MLA
Gan Q, et al.. "Single-cell analysis reveals the prognostic role of immune escape in the colorectal cancer microenvironment.." Translational cancer research, vol. 15, no. 1, 2026, pp. 26.
PMID
41674966
Abstract
[BACKGROUND] Colorectal cancer (CRC) is a malignant disease that poses a significant threat to human health; however, early diagnostic and treatment strategies for it remain limited. Immune evasion is a critical factor contributing to treatment failure in CRC. Various cell subtypes within the tumor microenvironment (TME) play essential roles in this process. However, there is currently a lack of a systematic and novel classification of immune evasion-related cell subtypes and an analysis of their dynamic interaction networks within the CRC TME. This study aims to explore a novel classification of immune evasion-related subtypes in CRC, elucidate their underlying mechanisms, and assess their value for immunotherapy and prognosis.
[METHODS] This study investigates immune escape-related gene expression profiles utilizing single-cell RNA sequencing (scRNA-seq), which were subsequently validated through multiple immunohistochemistry (mIHC) techniques. Non-negative matrix factorization (NMF) clustering was employed to identify novel subtypes associated with immune escape. Additionally, CellChat and pseudotime analysis were utilized to explore intercellular interactions and differentiation pathways. Kyoto Encyclopedia of Genes and Genomes (KEGG), Single-Cell Regulatory Network Inference and Clustering (SCENIC), and immune checkpoint analyses were conducted to elucidate the functional characteristics of these novel subtypes. Furthermore, Cox proportional hazards regression analysis and Kaplan-Meier survival analysis were performed to assess the response to immunotherapy and prognosis.
[RESULTS] The expression profile of immune escape-related genes in the TME of CRC was initially plotted. This analysis identified 11 distinct types of immune escape-related cells in the TME, and confirmed that TGF-βJAK1Calretinin could serve as a candidate cell marker for the immunosuppressive state of the TME. Furthermore, novel subtypes of cancer-associated fibroblasts (CAFs), CD8 T cells, macrophages, and B cells were identified. These subtypes exhibit unique gene expression profiles and functional characteristics associated with CRC immune escape. The cell interaction network, formed by these subtypes and other cells within the TME, facilitates CRC immune escape by reshaping the immunosuppressive microenvironment. Additionally, CFLARB_cells-C3, CALRCD8T_cells-C2, and TAP1Mac-C2 may serve as potential biomarkers for predicting responses to immunotherapy in CRC patients. In contrast, HEXIM1CAF-C1 may act as an independent risk factor for poor prognosis in CRC.
[CONCLUSIONS] Our findings enhance understanding of immune escape mechanisms in CRC, show how novel subtypes affect prognosis, and offer insights for new diagnostic and treatment strategies.
[METHODS] This study investigates immune escape-related gene expression profiles utilizing single-cell RNA sequencing (scRNA-seq), which were subsequently validated through multiple immunohistochemistry (mIHC) techniques. Non-negative matrix factorization (NMF) clustering was employed to identify novel subtypes associated with immune escape. Additionally, CellChat and pseudotime analysis were utilized to explore intercellular interactions and differentiation pathways. Kyoto Encyclopedia of Genes and Genomes (KEGG), Single-Cell Regulatory Network Inference and Clustering (SCENIC), and immune checkpoint analyses were conducted to elucidate the functional characteristics of these novel subtypes. Furthermore, Cox proportional hazards regression analysis and Kaplan-Meier survival analysis were performed to assess the response to immunotherapy and prognosis.
[RESULTS] The expression profile of immune escape-related genes in the TME of CRC was initially plotted. This analysis identified 11 distinct types of immune escape-related cells in the TME, and confirmed that TGF-βJAK1Calretinin could serve as a candidate cell marker for the immunosuppressive state of the TME. Furthermore, novel subtypes of cancer-associated fibroblasts (CAFs), CD8 T cells, macrophages, and B cells were identified. These subtypes exhibit unique gene expression profiles and functional characteristics associated with CRC immune escape. The cell interaction network, formed by these subtypes and other cells within the TME, facilitates CRC immune escape by reshaping the immunosuppressive microenvironment. Additionally, CFLARB_cells-C3, CALRCD8T_cells-C2, and TAP1Mac-C2 may serve as potential biomarkers for predicting responses to immunotherapy in CRC patients. In contrast, HEXIM1CAF-C1 may act as an independent risk factor for poor prognosis in CRC.
[CONCLUSIONS] Our findings enhance understanding of immune escape mechanisms in CRC, show how novel subtypes affect prognosis, and offer insights for new diagnostic and treatment strategies.