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Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and

Weiran Zhang1, Lin Tan2, Qiuqiao Mu1

  • 1Tianjin Chest Hospital, Tianjin University, Tianjin, China.

Frontiers in Immunology
|October 30, 2025
PubMed
Summary
This summary is machine-generated.

This study identifies key malignant features in EGFR-mutant lung adenocarcinoma (LUAD) cells. A new prognostic signature, EGFRmERS, predicts survival and immunotherapy response, highlighting PERP as a potential therapeutic target for LUAD patients.

Keywords:
EGFRLUADPERPimmunotherapymachine learningscRNA-seq

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Lung adenocarcinoma (LUAD) is a common non-small cell lung cancer subtype driven by EGFR mutations.
  • Significant heterogeneity exists in patient outcomes and treatment responses, necessitating better stratification methods.
  • Characterizing malignant features of EGFR-mutant epithelial cells is crucial for personalized therapeutic strategies.

Purpose of the Study:

  • To identify and characterize malignant programs in EGFR-mutant LUAD epithelial cells using single-cell RNA sequencing.
  • To develop a robust prognostic signature (EGFRmERS) for predicting patient survival and immunotherapy response.
  • To identify potential therapeutic targets within EGFR-mutant LUAD.

Main Methods:

  • Single-cell RNA sequencing data analysis to identify malignant epithelial cells and construct pseudotime trajectories.
  • Machine learning algorithms applied to transcriptomic data to develop the EGFRmERS prognostic signature.
  • Validation of EGFRmERS across independent cohorts and assessment of its association with immune infiltration, TMB, and CNVs.
  • In vitro functional validation of the core gene PERP.

Main Results:

  • EGFR-mutant epithelial cells were classified into subclusters with distinct malignant potentials and enriched pathways.
  • The developed EGFRmERS signature demonstrated robust prognostic value and outperformed existing models.
  • High EGFRmERS scores correlated with an immunosuppressive tumor microenvironment, reduced immunotherapy response, elevated TMB, and genomic instability.
  • The gene PERP was identified as a key driver of LUAD malignancy, promoting cell migration, invasion, and colony formation.

Conclusions:

  • The study presents a novel prognostic signature, EGFRmERS, for precise stratification and prediction of treatment benefit in EGFR-mutant LUAD.
  • EGFRmERS offers valuable insights into the molecular mechanisms driving LUAD progression and can guide personalized treatment strategies.
  • PERP emerges as a promising therapeutic target for improving outcomes in EGFR-mutant LUAD.