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Updated: Sep 14, 2025

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Decoding epithelial-fibroblast interactions in lung adenocarcinoma through single-cell and spatial transcriptomics.

Jiajin Yang1, Qiuping Xu1, Yanjun Lu2

  • 1Department of Oncology, Fengcheng People's Hospital, Yichun, 331100, Jiangxi Province, China.

Journal of Cancer Research and Clinical Oncology
|July 24, 2025
PubMed
Summary

This study reveals crucial interactions between lung adenocarcinoma epithelial and fibroblast cells. These stromal-epithelial interactions, identified through advanced transcriptomics, offer new prognostic biomarkers and therapeutic targets for lung cancer.

Keywords:
Epithelial cellFibroblastLung adenocarcinomaSingle-cell transcriptomicsTumor microenvironment

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Area of Science:

  • Cancer Biology
  • Transcriptomics
  • Tumor Microenvironment

Background:

  • Lung adenocarcinoma (LUAD) displays significant cellular heterogeneity.
  • Interactions between epithelial and stromal cells in LUAD remain poorly understood.
  • Understanding these interactions is key to deciphering LUAD progression.

Purpose of the Study:

  • To delineate tumor microenvironment dynamics in LUAD using integrated transcriptomics.
  • To identify key cellular subpopulations and their roles in LUAD progression.
  • To uncover novel prognostic biomarkers and therapeutic targets.

Main Methods:

  • Analysis of single-cell RNA sequencing (scRNA-seq) data from 21 LUAD patients.
  • Spatial transcriptomic deconvolution and cell-cell communication inference (CellChat).
  • Identification of epithelial and fibroblast subpopulations, metabolic interactions (MEBOCOST), and prognostic signatures (MCI score).

Main Results:

  • Identification of eight epithelial and nine fibroblast subpopulations, with tumor-enriched subsets showing elevated copy number variations (CNVs) and metabolic crosstalk.
  • Prognostic significance of specific subpopulations (e.g., Fb_IGFBP4, MUC21+ Epi) and their interactions (e.g., COL1A1/SDC4-mediated signaling).
  • Development and validation of a six-gene Metabolic Crosstalk Index (MCI) score for independent survival prediction in LUAD patients.

Conclusions:

  • Key stromal-epithelial subset interactions driving LUAD progression have been identified.
  • Specific cellular subpopulations and their signaling pathways represent potential prognostic biomarkers.
  • The findings propose novel therapeutic targets for lung adenocarcinoma treatment.