Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma - Liu, Zhaochen; Wang, Jingju; Li, Suxin; Li, Luhao; Li, Lin; Li, Dingyang; Guo, Huahu; Gao, Dute; Liu, Shengyan; Ruan, Chengshuo; Dang, Xiaowei (Frontiers in Immunology, 2022)
Ferroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively. We downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database for prognostic prediction model construction and validation respectively. The LASSO Cox regression analysis identified 13 crucial genes (3 ferroptosis-related genes, 9 EMT-related genes and 1 gene associated with both) for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-risk group had shorter overall survivals than the low-risk group (p<0.0001 in the TCGA cohort and p<0.05 in the ICGC cohort). The risk score was proved to be an independent prognostic risk factor (HR>1, p<0.01). Furthermore, the expression profiles analysis suggested that the high-FEPM group appeared to have a more suppressive ferroptosis status and a more active EMT status than the low- FEPM group. Immune infiltration analysis showed that the myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs) were highly enriched in the high-risk group. Finally, a nomogram enrolling FEPM score and TNM stage was constructed showing outstanding predictive capacity for the prognosis of patients in the two cohorts. In conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients.