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Related Experiment Video

Updated: Mar 12, 2026

Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts
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Extracellular matrix gene expression profiling using microfluidics for colorectal carcinoma stratification.

Christopher J Hayes, Catriona M Dowling, Susan Dwane1

  • 1Stokes Laboratories, Bernal Institute, University of Limerick , Limerick, Ireland.

Biomicrofluidics
|November 9, 2016
PubMed
Summary

This study introduces a novel microfluidic platform for analyzing extracellular matrix genes in colorectal cancer. The findings highlight its potential for accurate biomarker classification and improved prognosis prediction in cancer patients.

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Area of Science:

  • Oncology
  • Molecular Biology
  • Biomarker Discovery

Background:

  • Biomarkers are crucial for cancer diagnosis, treatment response prediction, and disease monitoring.
  • Current molecular biomarkers often lack the required specificity and sensitivity, necessitating the identification of more accurate markers.
  • Extracellular matrix (ECM) genes play a significant role in cancer progression and can serve as potential prognostic indicators.

Purpose of the Study:

  • To evaluate the prognostic value of a panel of thirty-four extracellular matrix (ECM) genes in colorectal carcinoma.
  • To utilize a novel droplet-based, microfluidic platform for sensitive and accurate gene expression analysis.
  • To explore the potential of ECM gene expression patterns for biomarker classification and sub-classification of colorectal cancer.

Main Methods:

  • A droplet-based, microfluidic platform employing continuous-flowing Polymerase Chain Reaction (PCR) for gene expression analysis.
  • Real-time quantitative PCR (qPCR) using Taqman® reagents to measure the expression levels of 34 ECM genes.
  • Analysis of gene expression in twenty-four pairs of matched colorectal cancer and adjacent normal tissue samples.

Main Results:

  • Identified differential expression patterns of ECM genes between colorectal tumor and normal tissues.
  • Correlated ECM gene expression levels with histopathological parameters and overall surgical staging of colorectal cancer.
  • Demonstrated that the droplet-based microfluidic qPCR system enables effective biomarker classification and sub-classification of colorectal cancer.

Conclusions:

  • The novel microfluidic platform provides a sensitive and accurate method for quantifying gene expression in cancer tissues.
  • ECM gene expression patterns can serve as valuable prognostic biomarkers for colorectal carcinoma.
  • Sub-classification of colorectal cancer based on ECM protein expression groups correlates with patient prognosis, aiding in personalized treatment strategies.