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Establishment and Validation of the Novel Necroptosis-related Genes for Predicting Stemness and Immunity of Hepatocellular Carcinoma via Machine-learning Algorithm

  • 0Department of Forensic Science, Guangdong Police College, 500 Binjiang East Road, Guangzhou 510230, Guangdong, China.
Combinatorial Chemistry & High Throughput Screening +

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December 6, 2024

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December 6, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Necroptosis-related genes (NRGs) play a key role in liver cancer stemness and immune suppression. A new NRG-based model accurately predicts hepatocellular carcinoma patient prognosis and identifies potential therapeutic targets.

Area Of Science

  • Cancer Biology
  • Programmed Cell Death
  • Hepatocellular Carcinoma Research

Background

  • Necroptosis, a form of programmed cell death, influences tumor proliferation, stemness, metastasis, and immunosuppression.
  • The specific role of necroptosis-related genes (NRGs) in Hepatocellular Carcinoma (HCC) has not been fully elucidated.

Purpose Of The Study

  • To investigate the expression and prognostic significance of NRGs in HCC.
  • To develop a predictive model for HCC patient survival based on NRGs.
  • To explore the association between NRGs, tumor stemness, and immune infiltration in HCC.

Main Methods

  • Analysis of mutation, copy number variation, and expression of 37 NRGs in TCGA-LIHC and ICGC-LIRI-JP HCC datasets.
  • Construction of a prognostic model using LASSO regression and evaluation with machine learning algorithms.
  • Assessment of immune infiltration, stemness index, and drug sensitivity to CSCs inhibitors.
  • In vitro and in vivo validation of key NRG expression via qPCR.

Main Results

  • 18 of 37 NRGs were differentially expressed and correlated with HCC outcomes.
  • A six-gene prognostic model (NRGs-score) was developed, with a high score indicating a worse prognosis.
  • NRGs-score independently predicted survival and correlated with AFP, disease stage, and tumor grade.
  • High NRGs-score was linked to increased immune checkpoint molecule expression and higher stemness index.
  • External validation confirmed the model's universal applicability for HCC survival prediction.

Conclusions

  • NRGs are pivotal in driving stemness and immune suppression in HCC.
  • A robust NRG-based prognostic model effectively predicts HCC patient survival.
  • The findings offer insights into potential therapeutic strategies targeting NRGs in HCC.

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