Related Experiment Video
Updated: Jun 21, 2025

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection
Published on: June 8, 2020
Analytical Validation of the Multitarget Stool RNA Test for Colorectal Cancer Screening
Erica K Barnell1, Jack Land2, Kimberly Kruse2
1Department of Medicine, Washington University School of Medicine, St. Louis, Missouri; Geneoscopy Inc., St. Louis, Missouri.
Abstract:
The multitarget stool RNA (mt-sRNA) test (ColoSense) is a noninvasive diagnostic test that screens for colorectal cancer and advanced adenomas in average-risk individuals aged 45 years and older. The mt-sRNA test incorporates a commercially available fecal immunochemical test, concentration of eight RNA transcripts, and participant-reported smoking status. As part of the CRC-PREVENT (Colorectal Cancer and Pre-Cancerous Adenoma Non-Invasive Detection Test) clinical trial, 12 analytical validation studies were conducted to assess analytical sensitivity, linearity, precision, interfering substances, cross-reactivity, carry-over, cross-contamination, and robustness. Analytical validation of the mt-sRNA test demonstrated limit of blank, limit of detection, and limit of quantification of <0.6, <0.7, and ≤2.5 copies/μL for all markers, respectively. The mt-sRNA test demonstrated linearity between 2.5 and 2500 copies/μL, and <20% coefficient of variation, and/or ≥95% concordance with regard to precision, interfering substances, carry-over, cross-contamination, and robustness. There was no significant impact of cross-reactivity from non-colorectal cancer diseases. These data provide a framework for laboratories to complete analytical validation for RNA-based panels that require premarket approval as a class III medical device from the US Food and Drug Administration.
More Related Videos
08:12Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer
Published on: March 14, 2019
10:37Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform
Published on: November 30, 2016