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Related Experiment Video

Updated: May 31, 2026

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells
10:37

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Published on: August 22, 2025

B3GNT6-Linked Multimodal Signatures Integrate Tissue Morphology and PTM-Related Transcriptomics to Stratify Tumor.

Kun Mei1, Yipeng Xu2,3, Renjun Gu1,4,5

  • 1Nanjing University of Chinese Medicine, Nanjing, China.

International Journal of Biological Sciences
|May 29, 2026
PubMed
Summary

This study introduces a new method combining protein modifications, tissue images, and gene activity to predict colon cancer outcomes. The developed risk score accurately separates patients into high and low-risk groups, identifying B3GNT6 as a potential therapeutic target.

Keywords:
B3GNT6colon adenocarcinomamultimodal integrationpathomics pathologypost-translational modifications

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Area of Science:

  • Oncology
  • Bioinformatics
  • Molecular Biology

Background:

  • Colon adenocarcinoma (COAD) presents significant heterogeneity, challenging single-omics biomarker reliability.
  • Post-translational modifications (PTMs) link genotype to phenotype, but prognostic models rarely integrate PTMs with tissue architecture and transcriptomics.
  • Existing prognostic models for COAD often overlook the interplay between molecular alterations and tissue morphology.

Purpose of the Study:

  • To develop a PTM-based multimodal framework for prognostic stratification and mechanistic analysis in COAD.
  • To integrate diverse datasets including bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics, and histopathology images for a comprehensive COAD analysis.
  • To identify novel biomarkers and therapeutic targets for colon adenocarcinoma through a multimodal approach.

Main Methods:

  • Integration of TCGA-COAD data (bulk RNA-seq, H&E images) with single-cell (GSE132465) and spatial transcriptomics (GSE225857).
  • Development of a PTM-related multimodal risk score (PTMLS) by fusing pathomic features and transcriptomic data using an autoencoder.
  • Identification of PTM-related differentially expressed genes and pathway enrichment analysis (glycan biosynthesis, ubiquitin-mediated pathways).

Main Results:

  • The PTMLS effectively stratified COAD patients into high- and low-risk groups with significant overall survival differences in both training and validation cohorts.
  • Low-risk tumors showed favorable immune profiles (higher immune/ESTIMATE scores, lower TIDE scores) and distinct immunotherapy responses.
  • Cross-modal analysis identified B3GNT6 as a key gene linked to histopathological features, with functional experiments confirming its tumor-suppressive role in colorectal cancer.

Conclusions:

  • The PTM-informed multimodal framework provides robust prognostic stratification for COAD by integrating routine pathology and transcriptomic data.
  • This approach offers clinically relevant immune and therapeutic phenotyping, highlighting B3GNT6 as a potential therapeutic target.
  • The study demonstrates the value of multimodal data integration for understanding COAD heterogeneity and improving patient outcomes.