Background: Hepatocellular carcinoma (HCC) is a common malignancy. Ferroptosis and cuproptosis promote HCC spread and proliferation. While fewer studies have combined ferroptosis and cuproptosis to construct prognostic signature of HCC. This work attempts to establish a novel scoring system for predicting HCC prognosis, immunotherapy, and medication sensitivity based on ferroptosis-related genes (FRGs) and cuproptosis-related genes (CRGs). Methods: FerrDb and previous literature were used to identify FRGs. CRGs came from original research. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases included the HCC transcriptional profile and clinical information [survival time, survival status, age, gender, Tumor Node Metastasis (TNM) stage, etc.]. Correlation, Cox, and least absolute shrinkage and selection operator (LASSO) regression analyses were used to narrow down prognostic genes and develop an HCC risk model. Using "caret", R separated TCGA-HCC samples into a training risk set and an internal test risk set.As external validation, we used ICGC samples. We employed Kaplan-Meier analysis and receiver operating characteristic (ROC) curve to evaluate the model's clinical efficacy. CIBERSORT and TIMER measured immunocytic infiltration in high-and low-risk populations.

Background Cuproptosis is a recently discovered method of copper-induced cell death that serves an essential part in the progression and spread of stomach adenocarcinoma (STAD). Multiple studies have found that lncRNAs, or long non-coding RNAs, are strongly correlated with the outcome for STAD patients. However, the nature of the connection between cuproptosis and lncRNAs in STAD is still not completely understood. Our study set out to create a predictive hallmark of STAD based on lncRNAs associated with cuproptosis, with the hope that this would allow for more accurate prediction of STAD outcomes. Methods We retrieved the transcriptional profile of STAD as well as clinical information from The Cancer Genome Atlas (TCGA). The cuproptosis-related genes (CRGs) were gathered through the highest level of original research and complemented with information from the available literature. We constructed a risk model using co-expression network analysis, Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) analysis to identify lncRNAs associated with cuproptosis, and then validated its performance in a validation set. Survival study, progression-free survival analysis (PFS), receiver operating characteristic (ROC) curve analysis, Cox regression analysis, nomograms, clinicopathological characteristic correlation analysis, and principal components analysis were used to evaluate the signature's prognostic utility. Additionally, ssGSEA algorithms, KEGG, and GO were employed to assess biological functions. The tumor mutational burden (TMB) and tumor immune dysfunction and rejection (TIDE) scores were utilized in order to evaluate the effectiveness of the immunotherapy. Results In order to construct predictive models, nine distinct lncRNAs (AC087521.1, AP003498.2, AC069234.5, LINC01094, AC019080.1, BX890604.1, AC005041.3, DPP4-DT, AL356489.2, AL139147.1) were identified. The Kaplan-Meier and ROC curves, which were applied to both the training and testing sets of the TCGA, provided evidence that the signature contained a sufficient amount of predictive potential. The signature was shown to contain risk indicators that were independent of the other clinical variables, as demonstrated by the findings of a Cox regression and a stratified survival analysis. The ssGSEA study provided additional evidence that predictive variables were highly connected with the immunological condition of STAD patients. Surprisingly, the combination of high risk and high TMB reduced survival time for patients. A worse prognosis for the immune checkpoint blockade response was also suggested by the fact that patients in the high-risk group had higher TIDE scores. Conclusion The potential clinical uses of the identified risk profiles for the 10 cuproptosis-related lncRNAs include the assessment of the prognosis and molecular profile of STAD patients and the creation of more targeted therapy strategies.