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Related Concept Videos

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  9. Predictive And Prognostic Markers
  11. A Novel Super-enhancer-related Risk Model For Predicting Prognosis And Guiding Personalized Treatment In Hepatocellular Carcinoma.
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. A Novel Super-enhancer-related Risk Model For Predicting Prognosis And Guiding Personalized Treatment In Hepatocellular Carcinoma.

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A novel super-enhancer-related risk model for predicting prognosis and guiding personalized treatment in hepatocellular carcinoma.

Qing Wu1,2,3, Ping Li1, Xuan Tao4

  • 1Department of Oncology, The First Affiliated Hospital of Fujian Medical University, No. 20 Chazhong Road, Fuzhou, 350005, China.

BMC Cancer
|September 2, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

A new prognostic model using super-enhancer-related genes (SERGs) predicts survival and immune microenvironment in hepatocellular carcinoma (HCC). High-risk patients have worse outcomes and may respond less to immunotherapy.

Keywords:
Hepatocellular carcinomaPrognosisSuper-enhancerTumor immune microenvironment

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Area of Science:

  • Oncology
  • Genomics
  • Immunotherapy

Background:

  • Hepatocellular carcinoma (HCC) prognosis and tumor immune microenvironment (TiME) require improved predictive tools.
  • Super-enhancer-related genes (SERGs) play a role in cancer development and progression.

Purpose of the Study:

  • To develop a robust predictive signature based on SERGs for forecasting survival and evaluating TiME in HCC.
  • To identify potential therapeutic targets within HCC.

Main Methods:

  • Utilized HCC RNA-sequencing data from The Cancer Genome Atlas (TCGA) for 365 patients, divided into training and testing sets.
  • Identified a SERGs signature using a training set and validated its prognostic value using internal and external datasets.
  • Assessed the model for functional enrichment, tumor immune infiltration, and performed in vitro experiments on CBX2 gene function.

Main Results:

  • An SE-related prognostic model comprising CBX2, TPX2, EFNA3, DNASE1L3, and SOCS2 was established and validated.
  • High-risk patients exhibited significantly worse prognosis, distinct immune cell infiltration patterns, and enrichment of tumor-associated pathways.
  • The SERGs signature correlated positively with Tumor Immune Dysfunction and Exclusion (TIDE) scores, indicating potential for immunotherapy response screening. CBX2 downregulation inhibited HCC cell viability and promoted apoptosis.

Conclusions:

  • A novel HCC prognostic model based on SERGs was developed, identifying high-risk patients with poorer prognosis and potential reduced response to immune checkpoint inhibitors (ICIs).
  • This model facilitates personalized treatment strategies for HCC patients.
  • CBX2 emerges as a promising therapeutic target for HCC intervention.