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Related Concept Videos

Tumor Immunotherapy01:27

Tumor Immunotherapy

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Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
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Related Experiment Video

Updated: May 4, 2026

An Oncogenic Hepatocyte-Induced Orthotopic Mouse Model of Hepatocellular Cancer Arising in the Setting of Hepatic Inflammation and Fibrosis
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Mitochondrial-associated PCD signature defines immune landscape, therapeutic sensitivity, and prognosis in

Xiao-Qin Luo1, Yi-Min Cao1, Yang Peng2

  • 1Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.

Discover Oncology
|December 30, 2025
PubMed
Summary

This study identifies mitochondrial-associated programmed cell death signatures (MPCDS) as key indicators in hepatocellular carcinoma (HCC). These signatures offer a novel prognostic biomarker for predicting patient outcomes and guiding personalized HCC treatment strategies.

Keywords:
BiopsyDrug sensitivityHepatocellular carcinomaImmune landscapeMachine learningMitochondrial-associated programmed cell death signaturesSomatic mutation

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Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma
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Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Mitochondrial-associated programmed cell death signatures (MPCDS) are crucial for cancer progression and treatment response.
  • Hepatocellular carcinoma (HCC) frequently exhibits mitochondrial dysfunction and altered programmed cell death (PCD) pathways.
  • The prognostic role of MPCDS in HCC is not well understood.

Purpose of the Study:

  • To identify and characterize MPCDS in HCC.
  • To evaluate the prognostic value of MPCDS in HCC.
  • To explore the potential of MPCDS for personalized HCC treatment.

Main Methods:

  • Integrated genomic data from TCGA-LIHC and HCCDB18 cohorts.
  • Identified 351 HCC MPCDS genes via differential expression analysis and intersection with known MPCDS genes.
  • Constructed and validated a prognostic model using 56 genes with significant influence on HCC survival via Cox regression and machine learning.

Main Results:

  • A prognostic model based on 56 HCC MPCDS genes demonstrated high predictive accuracy (1-, 3-, 5-year AUCs of 0.976, 0.984, 0.976).
  • Distinct molecular clusters associated with survival, immune landscape, somatic mutations, and drug sensitivity were identified.
  • Experimental validation confirmed significant upregulation of top genes (KIF2C, CDK4) in HCC tumor samples.

Conclusions:

  • HCC MPCDS serve as a valuable prognostic biomarker.
  • The identified MPCDS model can predict patient survival and guide personalized treatment strategies for HCC.
  • Further research into MPCDS could enhance therapeutic approaches for hepatocellular carcinoma.