Machine learning unveils immune-related signature in multicenter glioma studies
Sha Yang,
Xiang Wang,
Renzheng Huan,
Mei Deng,
Zhuo Kong,
Yunbiao Xiong,
Tao Luo,
Zheng Jin,
Jian Liu,
Liangzhao Chu,
Guoqiang Han,
Jiqin Zhang,
Ying Tan
Affiliations
Sha Yang
Guizhou University Medical College, Guiyang 550025, Guizhou Province, China
Xiang Wang
Department of Neurosurgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China
Renzheng Huan
Department of Neurosurgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
Mei Deng
Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
Zhuo Kong
Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
Yunbiao Xiong
Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
Tao Luo
Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
Zheng Jin
Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
Jian Liu
Guizhou University Medical College, Guiyang 550025, Guizhou Province, China; Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
Liangzhao Chu
Department of Neurosurgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China
Guoqiang Han
Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China; Corresponding author
Jiqin Zhang
Department of Anesthesiology, Guizhou Provincial People’s Hospital, Guiyang, China; Corresponding author
Ying Tan
Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China; Corresponding author
Summary: In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets.
