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MicroRNAs

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...

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Related Experiment Video

Updated: Oct 2, 2025

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform

Published on: November 30, 2016

miRNAs expression pattern and machine learning models elucidate risk for gastric GIST.

Ioannis K Stefanou^1,1, Nikolas Dovrolis^2,1, Maria Gazouli^3,4

¹1st Propaedeutic Department of Surgery, Hippocration General Hospital, National and Kapodistrian University of Athens, Athens, Greece.

Cancer Biomarkers : Section a of Disease Markers

|February 25, 2022

Summary

Gastrointestinal stromal tumors (GISTs) are characterized by distinct molecular underpinnings. This study identifies specific microRNAs (miRNAs) that can predict GIST development and prognosis, offering potential diagnostic biomarkers.

Keywords:

GISTs artificial intelligence cancer machine learning miRNAs

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Last Updated: Oct 2, 2025

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform

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Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

Published on: September 18, 2020

Area of Science:

Oncology
Molecular Biology
Bioinformatics

Background:

Gastrointestinal stromal tumors (GISTs) are the primary mesenchymal neoplasms of the digestive tract.
Significant variability exists in GIST clinical presentations, with incomplete understanding of their molecular drivers.
MicroRNAs (miRNAs) play a crucial role in cancer development by regulating gene expression post-transcriptionally.

Purpose of the Study:

To investigate miRNA expression patterns associated with gastric GIST carcinogenesis.
To identify miRNA signatures capable of distinguishing GIST cases from normal tissues.
To explore the potential of machine learning for predicting GIST risk.

Main Methods:

Utilized the miScript™ miRNA PCR Array Human Cancer PathwayFinder kit for miRNA expression analysis.
Applied machine learning algorithms to identify predictive miRNA profiles for GIST development.
Compared miRNA expression in GIST samples against healthy controls.

Main Results:

Identified several differentially expressed miRNAs in GIST cases versus controls.
hsa-miR-218-5p emerged as the most potent predictor of GIST development in the study cohort.
hsa-miR-146a-5p, hsa-miR-222-3p, and hsa-miR-126-3p showed significantly reduced expression in GISTs and were key predictors in all models.

Conclusions:

Machine learning classification demonstrates high accuracy in assessing GIST development risk.
A select group of miRNAs, notably hsa-miR-218-5p, significantly influences GIST prognosis.
These miRNA signatures hold promise as biomarkers for GIST risk stratification and patient management.