INTRODUCTION

Anoikis is a distinct form of programmed cell death, differing from classical apoptosis, and its role in malignant tumor progression, particularly in hepatocellular carcinoma (HCC), remains insufficiently understood. This study aims to elucidate the prognostic significance and therapeutic relevance of anoikis-related genes (ARGs) in HCC.

METHODS

We systematically analyzed the expression, mutation, and copy number variation profiles of 27 known ARGs in HCC using public datasets. Unsupervised consensus clustering was performed to classify patients into anoikis subtypes. Weighted Gene Co-expression Network Analysis (WGCNA) identified hub gene modules, and LASSO Cox regression was applied to construct a prognostic risk score model. Correlations between the risk model and clinical outcomes, tumor microenvironment (TME) characteristics, and immunotherapy responses were evaluated. Single-cell RNA-seq and pan-cancer analyses were conducted to explore gene expression across cell types and cancer types. Finally, in vitro experiments were performed to validate the biological function of model genes.

RESULTS

Two distinct anoikis subtypes with differing prognoses and TME features were identified in HCC. A two-gene prognostic model (TTC26 and TPX2) was developed, demonstrating robust performance in predicting patient outcomes. High-risk patients exhibited lower overall survival and distinct immune infiltration profiles. Pan-cancer analysis showed widespread dysregulation of TTC26 and TPX2. In vitro experiments confirmed that TTC26 promotes HCC cell proliferation, migration, and invasion.

DISCUSSION

Our findings reveal that anoikis-related molecular classification is closely linked to HCC prognosis and immune landscape. The established prognostic model has potential clinical utility for risk stratification and treatment guidance. TTC26 may serve as a novel biomarker and therapeutic target in HCC.