Establishment and Validation of an Anoiki-Associated Gene Signature Capable of Predicting Hepatocellular Carcinoma-related Immune Cell Infiltration and Prognostic Outcomes

Abstract

Abstract Background Hepatocellular carcinoma (HCC) is extremely heterogeneous, abd predicting patient outcomes remains a challenge. Anoikis is a distinct type of cell death that exerts an essential role in oncogenic invasion and spread. The presence of anti-anoikis factors contributes to cancer aggressiveness and drug resistance. Methods HCC patient transcriptomic and clinical data were accessed using public databases. A least absolute shrinkage and selection operator (LASSO) Cox approach was used to define a multigenic prognostic biosignature in the Cancer Genome Atlas (TCGA) patients, after which International Cancer Genome Consortium (ICGC) patients were leveraged for validation of this signature. The overall survival (OS) of low- and high-risk patient groups was compared using Kaplan-Meier analyses, with univariate and multivariate approaches being employed to establish independent predictors related to patient OS. A single-sample gene-set enrichment analysis (ssGSEA) strategy was also used to calculate immune cell infiltration scores and immune pathway activity, while Kyoto encyclopedia of genes and genome (KEGG) and Hallmark enrichment was identified via GSEA approaches. Results Through the use of a LASSO Cox regression approach, a 9-gene anoikis-related biosignature model was established. High-risk patient OS was shorter relative to low-risk patients. Receiver operating characteristic (ROC) curves confirmed the robust prognostic utility of this 9-gene biosignature, and risk scores were independently related to patient OS in a multivariate Cox analysis. Functional differences in immune status were also detected between these groups, with greater enrichment of cancer-associated pathways in high-risk individuals. Risk scores were significantly related to tumor staging, grading, and immune infiltration types. Prognostic gene expression was also significantly related with tumor cell anti-tumor drug sensitivity. Conclusions These results highlight a novel signature comprised of 9 anoikis-related genes that can be employed to predict outcomes and evaluate HCC patient immunological status. Targeting these genes may also represent an effective therapeutic approach.