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Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...

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Modeling Oral-Esophageal Squamous Cell Carcinoma in 3D Organoids
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Multi-omics analysis reveals microbiome-associated subtypes of esophageal cancer with distinct immune profiles and

Hua Liu1,2,3, Haixing Song1,2,3, Lingling Pu1,2,3

  • 1Demonstration Center for Experimental Teaching in Biomedicine, Chengdu Medical College, Chengdu, China.

International Journal of Surgery (London, England)
|December 17, 2025
PubMed
Summary
This summary is machine-generated.

This study reveals two distinct esophageal cancer subtypes (C1 and C2) based on multi-omics data. Subtype C2 shows promise for immunotherapy, while C1 may respond to chemotherapy and EGFR inhibitors.

Keywords:
esophageal cancerimmunotherapymicrobiomemolecular subtypesmulti-omicstargeted therapy

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Area of Science:

  • Oncology
  • Genomics
  • Microbiome Research

Background:

  • Esophageal cancer is an aggressive malignancy with a poor prognosis.
  • Comprehensive molecular characterization is essential for identifying new therapeutic targets and improving patient outcomes.

Purpose of the Study:

  • To perform an integrative multi-omics analysis of esophageal tumors to identify molecular subtypes.
  • To characterize these subtypes for specific features and therapeutic vulnerabilities.

Main Methods:

  • Integrative multi-omics analysis (microbiome, transcriptome, epigenome, clinical data).
  • Unsupervised consensus clustering using ten algorithms to identify molecular subtypes.
  • Functional enrichment analyses and experimental validation for subtype characterization.

Main Results:

  • Two molecular subtypes (C1 and C2) identified with distinct clinical, prognostic, and molecular features.
  • Subtype C2 exhibits higher mutation burden, Pseudomonas abundance, and an active immune microenvironment, predicting higher immunotherapy response.
  • Subtype C1 shows elevated RNA expression and DNA methylation, with higher sensitivity to chemotherapy and EGFR inhibitors.

Conclusions:

  • Multi-omics analysis reveals significant molecular heterogeneity in esophageal cancer.
  • Microbiome and immune signatures are associated with prognosis and therapeutic response.
  • Identified subtypes provide a framework for developing personalized esophageal cancer treatments.