Document Type
Article
Publication Date
9-27-2024
Abstract
Patients diagnosed with early-stage cancers have a substantially higher chance of survival than those with late-stage diseases. However, the option for early cancer screening is limited, with most cancer types lacking an effective screening tool. Here we report a miRNA-based blood test for multi-cancer early detection based on examination of serum microRNA microarray data from cancer patients and controls. First, a large multi-cancer training set that included 1,408 patients across 7 cancer types and 1,408 age- and gender-matched non-cancer controls was used to develop a 4-microRNA diagnostic model using 10-fold cross-validation. In three independent validation sets comprising a total of 4,875 cancer patients across 13 cancer types and 3,722 non-cancer participants, the 4-microRNA model achieved greater than 90% sensitivity for 9 cancer types (lung, biliary tract, bladder, colorectal, esophageal, gastric, glioma, pancreatic, and prostate cancers) and 75-84% sensitivity for 3 cancer types (sarcoma, liver, and ovarian cancer), while maintaining greater than 99% specificity. The sensitivity remained to be > 99% for patients with stage 1 lung cancer. Our study provided novel evidence to support the development of an inexpensive and accurate miRNA-based blood test for multi-cancer early detection.
Recommended Citation
Zhang, Jason; Rui, Hallgeir; and Hu, Hai, "Noninvasive Multi-Cancer Detection Using Blood-Based Cell-Free MicroRNAs" (2024). Department of Pharmacology, Physiology, and Cancer Biology Faculty Papers. Paper 27.
https://jdc.jefferson.edu/ppcbfp/27
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Language
English
Included in
Diagnosis Commons, Health Services Research Commons, Neoplasms Commons, Nucleic Acids, Nucleotides, and Nucleosides Commons
Comments
This article is the author's final published version in Scientific reports, Volume 14, Issue 1, 2024, Article number 22136.
The published version is available at https://doi.org/10.1038/s41598-024-73783-0.
Copyright © The Author(s) 2024