Establishment and external verification of an oxidative stress-related gene signature to predict clinical outcomes and therapeutic responses of colorectal cancer - Cao, Sha; Chen, Cheng; Gu, Dezhi; Wang, Zhengdong; Xu, Guanghui (Frontiers in Pharmacology, 2023)
Objective: Accumulated evidence highlights the biological significance of oxidative stress in tumorigenicity and progression of colorectal cancer (CRC). Our study aimed to establish a reliable oxidative stress-related signature to predict patients’ clinical outcomes and therapeutic responses. Methods: Transcriptome profiles and clinical features of CRC patients were retrospectively analyzed from public datasets. LASSO analysis was used to construct an oxidative stress-related signature to predict overall survival, disease-free survival, disease-specific survival, and progression-free survival. Additionally, antitumor immunity, drug sensitivity, signaling pathways, and molecular subtypes were analyzed between different risk subsets through TIP, CIBERSORT, oncoPredict, etc. approaches. The genes in the signature were experimentally verified in human colorectal mucosal cell line (FHC) along with CRC cell lines (SW-480, HCT-116) through RT-qPCR or western blot. Results: An oxidative stress-related signature was established, composed of ACOX1, CPT2, NAT2, NRG1, PPARGC1A, CDKN2A, CRYAB, NGFR, and UCN. The signature displayed an excellent capacity of survival prediction, and was linked to worse clinicopathological features. Moreover, the signature correlated to antitumor immunity, drug sensitivity and CRC-related pathways. Among molecular subtypes, CSC subtype had the highest risk score. Experiments demonstrated that CDKN2A and UCN were up-regulated and ACOX1, CPT2, NAT2, NRG1, PPARGC1A, CRYAB, and NGFR were down-regulated in CRC than normal cells. In H2O2-induced CRC cells, their expression was notably altered. Conclusion: Altogether, our findings constructed an oxidative stress-related signature that can predict survival outcomes and therapeutic response in CRC patients, thus potentially assisting prognosis prediction and adjuvant therapy decisions.