International journal of molecular sciences · 2026
A Cytokine-Related Gene Signature for Pan-Cancer Prognostic Stratification and Malignant Phenotype Characterization.
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Chen Shih-Chieh, Chang Kai-Fu, Chao Chien-Cheng, Lin Chung-Hsien, Chang Chih-Hsuan, Ko Ching-Chung, Lin Hui-Ru, Wu Chi-Jen, Yuan Chien-Han, Kumar Sachin, Solomon Dahlak Daniel, Xuan Do Thi Minh, Palekkode Neethu, Fathima Ayman, Waikhom Junanda, Wang Chih-Yang, Lee Yung-Kuo, Liu Hui-Pu
Аннотация
Cytokines are central regulators of inflammation and immune responses within the tumor microenvironment and have been implicated in cancer progression and prognosis. However, the prognostic value of coordinated cytokine-related transcriptional programs across cancer types has not been systematically explored. Pan-cancer transcriptomic and clinical data were analyzed to construct a cytokine-related prognostic signature using least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were stratified into high-risk and low-risk groups based on the derived risk score. Prognostic performance was evaluated in training and test cohorts, and biological relevance was assessed through survival analyses and pathway-level investigations. A 16-gene cytokine-related signature was established that consistently stratified patients into distinct prognostic groups across multiple cancer types. High cytokine-related risk scores were significantly associated with unfavorable survival outcomes and were linked to enhanced cell cycle activity, epithelial-mesenchymal transition, and extracellular matrix remodeling. Integration of the risk score with clinical variables improved individualized survival prediction. Immunohistochemical analyses further confirmed increased protein expression of representative risk-associated genes, including pannexin 1 (PANX1) and FERM domain containing 8 (FRMD8), in multiple tumor tissues compared with corresponding normal tissues. The cytokine-related prognostic signature captures key inflammatory and immune-related programs underlying tumor aggressiveness and provides a robust tool for pan-cancer risk stratification with potential clinical utility.