Multi-omics integration of TPX2 in prognostic prediction in resectable hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence and mortality rates globally, significantly affecting patient prognosis and quality of life. Currently, predicting postoperative recurrence risk and survival in HCC patients remains challenging, as precise and effective quantitative indicators are lacking, limiting clinicians' ability to make individualized treatment decisions. Multi-omics models, as an emerging predictive tool, combine tumor imaging features, molecular markers, and clinical data, offering a new direction for prognostic evaluation in HCC. Multi-omics models integrating radiomics, genomics, and clinical factors have shown potential in predicting prognosis and treatment response in HCC patients. This study aims to develop a multi-omics prognostic model that integrates radiomic features, the genetic biomarker Targeting Protein for Xklp2 (TPX2), and clinical data to accurately predict postoperative overall survival (OS) and recurrence-free survival (RFS) in patients with resectable HCC. Additionally, this study explores the role of the TPX2 gene in HCC using bioinformatics and cellular experiments, assessing its feasibility as a potential therapeutic target. Through these investigations, we aim to provide new theoretical insights and application prospects for the precision diagnosis and treatment of HCC.