Aug 2026· Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences· Vol 58 4, pp.
794-802
· 0 citations
Medicine
TL;DR
The 36-gene signature developed in this study demonstrates favorable predictive performance and stability across both the training and independent Chinese cohorts, and underscores the critical roles of energy metabolism and ECM remodeling in NMIBC recurrence.
A robust five-gene signature was established and validated for prognostic stratification of locally advanced NPC and outperformed a published metastasis-related model.
Huaping Li, Qiuyu Jing, J. Chow et al.· JCO Precision Oncology· 0 citations
The lung cancer-originated TME subtyping system cannot be directly extrapolated to Chinese CRC patients, and LAG3 serves as a promising independent transcriptomic candidate marker for distinguishing CRC TME subtypes.
Y. Huo, J. Li, J. Huang et al.· medRxiv· 0 citations
A novel three-gene immune-related prognostic signature comprising TNFRSF4, PPARG, and PDGFA provides insights into immune-related mechanisms in LSCC, presenting potential targets for therapeutic intervention.
Changding He, Wanqiu Peng, Yi Shi et al.· Journal of Clinical Medicine· 0 citations
The 36-gene-pair binary signature provides robust RFS risk stratification, and high-risk individuals exhibit transcriptional similarity to reported anti-PD-1 therapy responders, and CKS2 emerges as a prognostic hub warranting validation.
Yu He, Boyang Li, Zhaojie Tan et al.· Cancer Management and Resear...· 0 citations
A six-gene-fibrosis-based prognostic model based on six genes stratifies survival risk and correlates with immune features and drug sensitivity, but provides a preliminary framework requiring prospective clinical validation.
Yanyan Qiu, Cui Lv, Shubo Ding· Clinical and Translational O...· 0 citations
Findings indicate that prognostic gene expression signatures derived from NanoString data showed limited reproducibility across independent cohorts and provided little additional predictive value beyond established clinical factors, and suggest that robust clinical variables remain the most reliable predictors of recurrence risk in this setting.
P. Quarles van Ufford, R. Bojesen, L. R. Olsen et al.· medRxiv· 0 citations