Identification and Validation of Prognosis-Related Necroptosis Genes for Prognostic Prediction in Hepatocellular Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35813858", "kind": "science-record", "revision": 4, "content_hash": "sha256:387f234dae0696ee833b1ae2f1b017e63cdc2d4e99739335e53a0757ae16ce57", "created_at": "2026-11-01T18:14:52Z", "updated_at": "2026-11-01T22:07:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Prognosis-Related Necroptosis Genes for Prognostic Prediction in Hepatocellular Carcinoma.", "doi": "10.1155/2022/3172099", "pmid": "35813858", "authors": ["Xin Gao", "Di Huang", "Shu-Guang Li", "Wen-Xin Wang", "Dong-Lei Sun", "Jia-Ming Qian", "Xiao-Lan Zhang"], "journal": "Journal of oncology", "year": 2022, "abstract": "Background: The prediction of hepatocellular carcinoma (HCC) survival is challenging because of its rapid progression. In recent years, necroptosis was found to be involved in the progression of multiple cancer types. However, the role of necroptosis in HCC remains unclear.\nMethods: Clinicopathological parameters and transcriptomic data of 370 HCC patients were obtained from TCGA-LIHC dataset. Prognosis-related necroptosis genes (PRNGs) were identified and utilized to construct a LASSO risk model. The GEO cohorts (GSE54236 and GSE14520) were used for external validation. We evaluated the distribution of HCC patients, the difference in prognosis, and the accuracy of the prognostic prediction of the LASSO risk model. The immune microenvironment and functional enrichment of different risk groups were further clarified. Finally, we performed a drug sensitivity analysis on the PRNGs that constructed the LASSO model and verified their mRNA expression levels in vitro. Results: A total of 48 differentially expressed genes were identified, 23 of which were PRNGs. We constructed the LASSO risk model using nine genes: SQSTM1, FLT3, HAT1, PLK1, MYCN, KLF9, HSP90AA1, TARDBP, and TNFRSF21. The outcomes of low-risk patients were considerably better than those of high-risk patients in both the training and validation cohorts. In addition, stronger bile acid metabolism, xenobiotic metabolism, and more active immune cells and immune functions were observed in low-risk patients, and high expressions of TARDBP, PLK1, and FLT3 were associated with greater drug sensitivity. With the exception of FLT3, the mRNA expression of the other eight genes was verified in Huh7 and 97H cells. Conclusions. The PRNG signature provides a novel and effective method for predicting the outcome of HCC as well as potential targets for further research.", "claims": [{"id": "claim-method", "statement": "We used the “GLMnet” R package to build the least absolute shrinkage and selection operator (LASSO) regression model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35813858", "locator": "sections[6] \"2.4. 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