Multiomics study on the tertiary lymphatic structure signature of colon cancer.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
901 patients with colon cancer were analyzed, including 458 from The Cancer Genome Atlas (TCGA) and 443 from the Gene Expression Omnibus (GEO).
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSIONS] TSG expression may serve as a novel biomarker and has the potential to assess the infiltration of immune cells in the TME of patients with colon cancer. This evaluation can aid in determining prognosis and providing guidance for clinical treatment.
[BACKGROUND] Tertiary lymphoid structures (TLSs) are abnormal clusters of immune cells found in inflamed, infected, or cancerous tissues.
APA
Wang J, Sun Y, et al. (2026). Multiomics study on the tertiary lymphatic structure signature of colon cancer.. Translational cancer research, 15(2), 104. https://doi.org/10.21037/tcr-2025-1717
MLA
Wang J, et al.. "Multiomics study on the tertiary lymphatic structure signature of colon cancer.." Translational cancer research, vol. 15, no. 2, 2026, pp. 104.
PMID
41815175
Abstract
[BACKGROUND] Tertiary lymphoid structures (TLSs) are abnormal clusters of immune cells found in inflamed, infected, or cancerous tissues. These structures contain high concentrations of T cells, B cells, plasma cells, follicular helper T cells, follicular dendritic cells, germinal centers, and high endothelial venules. TLSs serve as sites favorable for immune cell infiltration and facilitate the generation of an inflammatory response against tumors. We aimed to determine whether the TLS-related signature can stratify prognosis, predict immune microenvironment characteristics, and inform treatment for patients with colon cancer.
[METHODS] The gene expression profiles of 901 patients with colon cancer were analyzed, including 458 from The Cancer Genome Atlas (TCGA) and 443 from the Gene Expression Omnibus (GEO). TLS patterns were assessed in all patients. TLS signature genes (TSGs) risk scores were constructed to quantify the TLS patterns of individuals via the Cox regression model and the least absolute shrinkage and selection operator (LASSO) algorithm, and their correlation with immune checkpoint and cell invasion characteristics of the tumor microenvironment (TME) was examined.
[RESULTS] In the prognostic model, TLS-related genes (TRGs), including C, , , , and , exhibited significant expression differences between the high- and low-risk groups. The TSG risk scores were significantly correlated with immune cell infiltration levels and could be used to evaluate the infiltration level of immune cells in the TME of patients and determine their prognostic status.
[CONCLUSIONS] TSG expression may serve as a novel biomarker and has the potential to assess the infiltration of immune cells in the TME of patients with colon cancer. This evaluation can aid in determining prognosis and providing guidance for clinical treatment.
[METHODS] The gene expression profiles of 901 patients with colon cancer were analyzed, including 458 from The Cancer Genome Atlas (TCGA) and 443 from the Gene Expression Omnibus (GEO). TLS patterns were assessed in all patients. TLS signature genes (TSGs) risk scores were constructed to quantify the TLS patterns of individuals via the Cox regression model and the least absolute shrinkage and selection operator (LASSO) algorithm, and their correlation with immune checkpoint and cell invasion characteristics of the tumor microenvironment (TME) was examined.
[RESULTS] In the prognostic model, TLS-related genes (TRGs), including C, , , , and , exhibited significant expression differences between the high- and low-risk groups. The TSG risk scores were significantly correlated with immune cell infiltration levels and could be used to evaluate the infiltration level of immune cells in the TME of patients and determine their prognostic status.
[CONCLUSIONS] TSG expression may serve as a novel biomarker and has the potential to assess the infiltration of immune cells in the TME of patients with colon cancer. This evaluation can aid in determining prognosis and providing guidance for clinical treatment.
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