Background: Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC.Methods: We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic.Results: Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group.Conclusion: The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.

Background Frizzled 7, a G protein-coupled receptor, can regulate cell proliferation, migration, and tumorigenesis. The effect of FZD7 on prognosis and the immune microenvironment in pan-cancer remains elusive. Hence, we plan to provide insight into FZD7's role in pan-cancer. Methods FZD7 expression was analyzed by integrating RNA sequencing data from TCGA and GEO databases. Furthermore, we elucidated the correlation between FZD7 and prognosis, mutation landscape, immune infiltration, and biological function by analyzing multiple databases in pan-cancer. A prognostic risk model was constructed based on the sequencing data of HCC in the TCGA database and its validity was verified in the GEO database. In addition, reverse transcription-polymerase chain reaction assays were performed to validate FZD7 expression in HCC tumor tissues. Results Compared with adjacent noncancerous tissues, FZD7 was upregulated in several tumor tissues, especially HCC, and its elevated expression account for tumor progression and poor prognosis. Significant associations were found between FZD7 expression and TMB or MSI in several tumors. Immune infiltration analysis revealed a close link between FZD7 expression and the presence of myeloid-derived suppressor cells, T cell regulatory, as well as the cancer-associated fibroblasts. However, it negatively correlated with CD4+ Th1 cell and CD4+ Th2 infiltration. FZD7-related functional genes were successfully incorporated into the construction and validation of an HCC prognostic risk model. Conclusion Our study indicated that FZD7 is involved in regulating the progression of several tumors and immune infiltration, while it can serve as an effective prognosis biomarker in pan-cancer, especially HCC. This could shed light on tumor therapy.