关键词: 数据挖掘, 铁死亡, 缺氧, 结肠癌, 作用机制

Abstract: Objective To study the mechanism of ferroptosis involved in colon cancer under hypoxia based on data mining technology. MethodsTaking TCGA-COAD as the experimental cohort and GSE39582 as the verification cohort，based on 174 hypoxia related genes and 517 ferroptosis-related genes，a risk-scoring prognostic model was constructed by Cox and LASSO regression analysis，and the patients were divided into high-risk and low-risk groups. Then，the clinical and immune characteristics of the two risk groups were further analyzed. Finally，GO（BP，MF，CC）and KEGG enrichment analysis of differential genes between the high and low-risk groups were performed. Results A risk-scoring model containing 9 genes（CDKN2A，FNDC5，ENO3，GSTM1，JDP2， ANGPTL4，ANKZF1，TKTL1，PPARGC1A） was constructed. Compared with the high-risk group，the low-risk group had a better prognosis，and the level of immune cell infiltration in the high-risk group was higher than that in the low-risk group. Through GO analysis and KEGG pathway enrichment analysis，the differential genes between the high low risk groups were shown to be correlated with the MAPK signaling pathway，Rap1 signaling pathway，Chemokine signaling pathway，and other tumor and immune-related pathways. Conclusion The risk-scoring model for colon cancer patients with ferroptosis under hypoxia conditions provides a new idea for individualized tumor treatment.

Key words: data mining technology, ferroptosis, hypoxia, colon cancer, mechanism