Abstract

Abstract Introduction: Early detection is critical to reduce cancer deaths as treating early stage cancers is more likely to be successful. We aimed to develop and validate a noninvasive blood-based diagnostic model capable of detecting multiple cancers by assessing the expression levels of serum microRNAs (miRNAs). Patients and Methods: Four microarray datasets assessing expression profiles of 2588 serum miRNAs with a standardized platform were assembled from Gene Expression Omnibus (GEO) totaling 7536 participants including 3604 cancer patients across 13 cancer types and 3932 non-cancer controls. A diagnostic model was built in a training set of 416 participants, including 208 lung cancer patients and 208 non-cancer controls matched for age, sex, and smoking history. The model performance was assessed in the validation sets consisting of all the remaining 7120 participants. Results: A 4-miRNA diagnostic model was developed from the lung cancer training set. The model showed 99% sensitivity and specificity in the lung cancer validation set (n=3328, 1358 cancer & 1970 non-cancer participants); and the sensitivity remained to be >99% for patients with stage 1 disease. When applied to the additional dataset of 3792 participants including 2038 cancer patients across 12 cancer types and 1754 independent non-cancer controls, the model showed high sensitivities ranging from 83⋅2% to 100% for biliary tract, bladder, colorectal, esophageal, gastric, glioma, liver, pancreatic, and prostate cancers, and reasonable sensitivities of 68⋅2% and 72⋅0% for ovarian cancer and sarcoma, respectively, while maintaining 99⋅3% specificity (Table 1). Conclusion: The study provided a proof-of-concept demonstrating that the 4-miRNA model has the potential to be developed into a simple, inexpensive and noninvasive blood test for early detection of multiple cancers with high accuracy. Table 1. Sensitivities of the 4-miRNA diagnostic model in 12 cancer types. N Sensitivity Lung Cancer 1358 99.3% Biliary Tract Cancer 40 97.5% Bladder Cancer 392 98.2% Colorectal Cancer 155 85.8% Esophageal Cancer 124 84.7% Gastric Cancer 150 100% Glioma 40 87.5% Liver Cancer 348 84.2% Ovarian Cancer 333 68.2% Pancreatic Cancer 149 83.2% Prostate Cancer 40 92.5% Sarcoma 132 72.0% Citation Format: Andrew Zhang, Hai Hu. Development and validation of a novel circulating cell-free microRNA diagnostic model with high accuracy for multi-cancer early detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5931.

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