Identification and characterization of a novel molecular classification based on disulfidptosis-related genes to predict prognosis and immunotherapy efficacy in hepatocellular carcinoma

Background: Disulfidptosis has been discovered as a mechanism of cell death mediating by SLC7A11. Nonetheless, little is known about the relationship between disulfidptosis-related genes (DRG) and hepatocellular carcinoma (HCC). Methods: 7 datasets including 1,302 HCC patients and 62,530 cells were downloaded. We adopted consensus clustering algorithm to construct the consensus matrix and cluster the samples’ DRG related expression profile data. Then, weighted gene co-expression network analysis (WGCNA) was conducted to identify hub gene modules associated with the identified clusters and determine the correlation between modules. A DRG.score was constructed based on genes through differential analysis and WGCNA of the 2 clusters. Results: Univariate and multivariate Cox regression analysis show that SLC7A11 and LRPPRC can be used as an independent factor in HCC. Then, two molecular subgroups with significantly different survival were identified based on 10 DRG. The cluster.A showed a worse prognosis, higher immune infiltration, and higher immune checkpoint expression. Then, by differential analysis and WGCNA of the 2 clusters, we identified 5 hub genes, and constructed a DRG.score. Univariate and multivariate Cox regression analysis show that DRG.score can be used as an independent factor to predict the prognosis in HCC. Furthermore, high DRG.score group had a worse prognosis, and was validated in TCGA-LIHC, LIRI-JP, GSE14520, GSE36376, and GSE76427. Preclinically, patients with higher DRG.score demonstrated significant immunotherapy therapeutic advantages and transcatheter arterial chemoembolization clinical benefits. Conclusions: SLC7A11 and LRPPRC play an essential role in HCC prognosis prediction. The DRG.score might become useful biomarkers for novel therapeutic targets.