The purpose of this investigation was to develop and validate a risk model based on natural killer (NK) cell-associated lncRNAs to predict outcomes in individuals with hepatocellular carcinoma (HCC). To further explore the role of NK cells in the HCC tumor microenvironment, we leveraged single-cell RNA sequencing data and the TCGA-LIHC dataset to identify NK cell-associated lncRNAs. Using Cox regression and LASSO techniques, we pinpointed four key lncRNAs as prognostic markers for the model. The model demonstrated robust predictive power across the training set, validation set, and entire dataset. Additionally, we identified a synergistic interaction between NK cells and other immune cells, particularly CD8 + T cells, in HCC. Moreover, we uncovered novel molecular subgroups of HCC and their associations with the immune microenvironment and drug sensitivity. To further validate these findings, we performed experimental validation of the expression and function of the model lncRNAs in HCC. These results suggest that the NK cell-associated lncRNA model not only serves as an effective prognostic tool for HCC patient outcomes but also offers potential molecular targets for immunotherapy and targeted therapies.
Li et al. (Tue,) studied this question.