Abstract 1269: Large-scale validaton studies of a blood-based effective and affordable test for multicancer early detection

Abstract Cancer early detection aims at reducing cancer deaths. Unfortunately, many established cancer screening methods are not suitable for use in low- and middle-income countries (LMICs) due to cost, complexity, and dependency on extensive medical infrastructure. Nearly 10, 000 participants (2003 cancer cases and 7888 non-cancer cases) were divided into one training and five independent validation cohorts across different races, sample types and platforms. One tube of peripheral blood was collected from each participant and quantified using a panel of seven protein tumor markers (PTMs) consisting of AFP, CA125, CA15-3, CA19-9, CA72-4, CEA and CYFRA 21-1 by common clinical immunoassay analyzers. An algorithm named OncoSeek was established using artificial intelligence (AI) to distinguish cancer cases from non-cancer cases by calculating the probability of cancer (POC) index based on the quantification of the seven PTMs and clinical information including sex and age, and to predict the possible affected tissue of origin (TOO). The conventional clinical method that relied only on a single threshold for each PTM would make a big problem when combining the results of those markers as the false positive rate would accumulate as the number of markers increased. Nevertheless, OncoSeek was empowered by AI to significantly reduce the false positive rate, increasing the specificity from 54. 0% to 93. 0%. The overall sensitivity of OncoSeek was 51. 7%, resulting in 84. 6% accuracy. The performance was consistent in the training and the five validation cohorts from three countries (Brazil, China and United States) including two sample types (plasma and serum) and three different platforms (Roche, Luminex and ELISA). The sensitivities ranged from 39. 0% to 77. 6% for the detection of the nine common cancer types (breast, colorectum, liver, lung, lymphoma, oesophagus, ovary, pancreas and stomach), which account for 59. 2% of global cancer deaths annually. Furthermore, it has shown excellent sensitivity in several high-mortality cancer types for which there are lacking routine screening tests in the clinic, such as the sensitivity of pancreatic cancer was 77. 6%. The overall accuracy of TOO prediction in the true positives was 65. 4%, which could assist the clinical diagnostic workup. OncoSeek significantly outperforms the conventional clinical method, representing a novel blood-based test for multicancer early detection (MCED) that is non-invasive, easy, efficient and robust. Moreover, the accuracy of TOO facilitates the follow-up diagnostic workup. OncoSeek is affordable (~20) and accessible requiring nothing more than a blood draw at the screening sites, which makes it adoptable in LMICs. Citation Format: Mao Mao, Bing Wei, Qingxia Xu, Yong Shen, Raphael Brandão, Shiyong Li, Wei Wu, Pingping Xing, Yinyin Chang, Dandan Zhu. Large-scale validaton studies of a blood-based effective and affordable test for multicancer early detection abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 1269.