Leveraging machine learning and single-cell RNA sequencing strategies to develop a risk prognosis scoring based on liquid-liquid phase separation feature genes in pediatric hepatoblastoma.

Journal: Computers in biology and medicine
Published Date: Jul 4, 2025

Abstract

BACKGROUND: Considerable evidence highlights the intricate association between liquid-liquid phase separation (LLPS) and tumorigenesis, progression, and therapy resistance. However, there has been limited exploration of the role of LLPS in hepatoblastoma (HB). This study integrates machine learning techniques with single-cell RNA sequencing (scRNA-seq) to systematically analyze the molecular features of LLPS-associated genes in HB and establish the first LLPS-based prognostic prediction model for HB.

Authors

  • D Q Cai
    Guangdong Cardiovascular Institute, Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong Province, 510080, China.
  • DianKui Cai
    Department of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Guangzhou, Guangdong Province, 510120, China; Guangdong Laboratory, Guangzhou, Guangdong Province, 510320, China.
  • Zhen Zhao
  • Zehao Zheng
    Guangdong Cardiovascular Institute, Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong Province, 510080, China; Shantou University Medical College, Shantou, Guangdong Province, 515041, China.
  • Zhixiang Jian
    Guangdong Cardiovascular Institute, Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong Province, 510080, China.
  • Mude Shi
    Guangdong ACXEL Micro & Nano Tech Co., Ltd, Foshan, Guangdong Province, 528200, China. Electronic address: smooth.21cn@hotmail.com.
  • Yajin Chen
    Department of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Guangzhou, Guangdong, China shchzh2@mail.sysu.edu.cn chenyaj@mail.sysu.edu.cn zhuhaihong1214@126.com.
  • Jueming Chen
    Medical College of South China University of Technology, Guangzhou, Guangdong Province, 510080, China. Electronic address: cjm_007@126.com.
  • Ye Lin
    Peking Union Medical Collage, Beijing 100730, China.

Keywords

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