A diagnostic model based on transcriptomic analysis reveals inflammation as a potential prognosis factor for hepatoblastoma with hepatocellular carcinoma features.

ABSTRACT:

Introduction

Hepatoblastoma (HB) with hepatocellular carcinoma (HCC) features (HBHF) is a rare liver malignancy. Due to its rarity and diverse histological presentations, the prognosis of HBHF remains controversial, and diagnostic differentiation poses significant challenges. To enable more accurate outcome evaluation and targeted therapeutic strategies, rapid, comprehensive, and cost-effective methods are needed to complement histopathological evaluation.

Methods

In this study, we conducted transcriptomic profiling on an HBHF cohort from our center and developed a machine-learning algorithm to quantify HCC-like expression features in HB tumors. Given overlapping histopathological and molecular charateristicss between HBHF and HCC, we further investigated shared risk factors

SUBMITTER: Shan Y 

PROVIDER: S-EPMC12528353 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature