<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>13</volume><submitter>Ren H</submitter><pubmed_abstract>&lt;b>Background:&lt;/b> Hepatocellular carcinoma (HCC) is a common type of primary liver cancer and has a poor prognosis. In recent times, necroptosis has been reported to be involved in the progression of multiple cancers. However, the role of necroptosis in HCC prognosis remains elusive. &lt;b>Methods:&lt;/b> The RNA-seq data and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Differentially expressed genes (DEGs) and prognosis-related genes were explored, and the nonnegative matrix factorization (NMF) clustering algorithm was applied to divide HCC patients into different subtypes. Based on the prognosis-related DEGs, univariate Cox and LASSO Cox regression analyses were used to construct a necropt</pubmed_abstract><journal>Frontiers in genetics</journal><pagination>900713</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9357940</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Establishment of a Necroptosis-Related Prognostic Signature to Reveal Immune Infiltration and Predict Drug Sensitivity in Hepatocellular Carcinoma.</pubmed_title><pmcid>PMC9357940</pmcid><pubmed_authors>Ren H</pubmed_authors><pubmed_authors>Yang X</pubmed_authors><pubmed_authors>Zheng J</pubmed_authors><pubmed_authors>Fu Q</pubmed_authors><pubmed_authors>Cheng Q</pubmed_authors></additional><is_claimable>false</is_claimable><name>Establishment of a Necroptosis-Related Prognostic Signature to Reveal Immune Infiltration and Predict Drug Sensitivity in Hepatocellular Carcinoma.</name><description>&lt;b>Background:&lt;/b> Hepatocellular carcinoma (HCC) is a common type of primary liver cancer and has a poor prognosis. In recent times, necroptosis has been reported to be involved in the progression of multiple cancers. However, the role of necroptosis in HCC prognosis remains elusive. &lt;b>Methods:&lt;/b> The RNA-seq data and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Differentially expressed genes (DEGs) and prognosis-related genes were explored, and the nonnegative matrix factorization (NMF) clustering algorithm was applied to divide HCC patients into different subtypes. Based on the prognosis-related DEGs, univariate Cox and LASSO Cox regression analyses were used to construct a necropt</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022</publication><modification>2025-04-05T08:56:18.172Z</modification><creation>2025-04-05T08:56:18.172Z</creation></dates><accession>S-EPMC9357940</accession><cross_references><pubmed>35957699</pubmed><doi>10.3389/fgene.2022.900713</doi></cross_references></HashMap>