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Related Experiment Video

Updated: May 13, 2025

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Predicting survival and immune status of breast cancer patients based on prognostic features related to PANoptosis.

Juanjuan Cui1, Dapeng Wu1, Da Lv2

  • 1Department of Oncology, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, 266071, China.

Discover Oncology
|April 15, 2025
PubMed
Summary

This study identifies novel biomarkers and a risk model for breast cancer (BRCA) prognosis. The findings offer new insights into BRCA treatment strategies and the role of programmed cell death in cancer progression.

Keywords:
Breast cancerDrug sensitivityPANoptosis-related genesRisk modelSingle-cell RNA-sequencing

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Area of Science:

  • Oncology
  • Molecular Biology
  • Immunology

Background:

  • Breast cancer (BRCA) is a common malignancy in women.
  • PANoptosis, a form of programmed cell death, plays a significant role in BRCA.
  • Further investigation into PANoptosis in BRCA is crucial for understanding disease progression and developing new therapies.

Purpose of the Study:

  • To identify novel biomarkers associated with PANoptosis in breast cancer.
  • To develop a prognostic risk model for breast cancer patients.
  • To explore the relationship between PANoptosis, tumor microenvironment, and drug sensitivity in BRCA.

Main Methods:

  • Utilized Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets.
  • Applied Weighted Gene Co-expression Network Analysis (WGCNA), Cox, and LASSO regression to identify biomarkers.
  • Conducted in-vitro experiments, immune cell infiltration analysis, and drug sensitivity prediction.

Main Results:

  • Identified 8 key biomarkers (ACY3, CD83, CXCL13, KLHDC7B, NR1H3, SMCO4, TRPM2, UPP1) and developed a risk model.
  • TRPM2 knockdown inhibited BRCA cell migration and invasion; high-risk group showed activated metabolic pathways and altered immune cell infiltration (enriched fibroblasts).
  • Macrophages exhibited higher PANoptosis activity; 13 drugs were linked to the risk score.

Conclusions:

  • The developed risk model offers a novel approach for breast cancer prognosis.
  • These findings provide a new perspective for developing targeted breast cancer treatment strategies.