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Identification of Breast Cancer Subtypes Based on Endoplasmic Reticulum Stress-Related Genes and Analysis of Prognosis and Immune Microenvironment in Breast Cancer Patients

  • 0Department of Biomedical Engineering, Nanchang Hangkong University, Jiangxi, China.
Technology in Cancer Research & Treatment +

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May 10, 2024

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May 10, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Endoplasmic reticulum stress (ERS) is implicated in breast cancer. This study identified 8 core ERS genes that, when interacting synergistically, serve as excellent diagnostic and prognostic biomarkers for breast cancer patients.

Area Of Science

  • Oncology
  • Molecular Biology
  • Genomics

Background

  • Endoplasmic reticulum stress (ERS) is a cellular response to unfolded proteins, contributing to tumor development, invasion, metastasis, and immune evasion.
  • The precise regulatory mechanisms of ERS in breast cancer (BC) are not fully understood, necessitating further investigation into its role.

Purpose Of The Study

  • To identify and characterize core genes associated with ERS in breast cancer.
  • To evaluate the diagnostic and prognostic value of these ERS-related genes in breast cancer patients.
  • To assess the impact of these genes on the tumor immune microenvironment and drug sensitivity.

Main Methods

  • Analysis of RNA sequencing data from The Cancer Genome Atlas (TCGA) for breast cancer.
  • Identification of 8 core ERS-associated genes: ELOVL2, IFNG, MAP2K6, MZB1, PCSK6, PCSK9, IGF2BP1, and POP1.
  • Evaluation of individual and synergistic expression, diagnostic, and prognostic values, including Cox analysis and validation with external datasets; assessment of immune infiltration and drug sensitivity.

Main Results

  • The identified eight core genes significantly influence the immune microenvironment of breast cancer (BRCA) patients.
  • While individual gene expression showed limited independent diagnostic and prognostic value, synergistic interaction of these genes proved effective as biomarkers.
  • Logistic regression, neural networks, and risk prognosis models confirmed the synergistic utility of these genes for diagnosis and prognosis, validated by qPCR and GEO database.

Conclusions

  • Eight core genes associated with endoplasmic reticulum stress were identified as potential diagnostic and prognostic indicators in breast cancer.
  • The synergistic interaction of these genes is crucial for their utility as biomarkers in breast cancer.
  • These findings provide a foundation for understanding ERS mechanisms and developing targeted therapies in breast cancer.

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