Abstract 1096: OncoSeek 2.0: An advanced multi-cancer blood test enhancing early detection and aiding cancer diagnosis

Abstract Background: Early cancer detection and timely diagnosis are critical for improving patient outcomes and reducing healthcare costs. OncoSeek is an AI-driven, low-cost multi-cancer early detection (MCED) assay integrating seven protein tumor markers (PTMs) with clinical data, previously demonstrating 58.4% sensitivity, 92.0% specificity, and 70.6% tissue-of-origin accuracy in over 15,000 participants. Here, we present OncoSeek 2.0, an upgraded version that incorporates three additional PTMs to enhance the detection of prostate, lung, and squamous cell carcinomas, and evaluate its performance in validation cohorts and its expanded use for assisting cancer diagnosis in patients with tissue masses. Methods: OncoSeek 2.0 retained the original machine learning framework with expanded biomarker inputs. MCED performance was assessed in a retrospective cohort including 722 cancer and 355 non-cancer subjects. To further evaluate clinical utility, a prospective cohort of 732 patients with tissue masses, clinically deemed likely malignant and scheduled for surgery, was analyzed to assess the assay’s effectiveness in aiding cancer diagnosis. Results: Compared with OncoSeek 1.0, OncoSeek 2.0 achieved a higher AUC (0.934 vs. 0.888) and improved sensitivity from 70.4% to 83.5% at 90.1% specificity across 15 prespecified cancer types collectively accounting for 76.5% of global cancer mortality. Sensitivity gains were notable in lung (79.9% → 89.6%), prostate (58.8% → 94.1%), cervical (44.4% → 72.2%), and esophageal (41.6% → 64.4%) cancers. In the prospective tissue-mass cohort, OncoSeek 2.0 correctly identified 573 of 682 confirmed cancers (84.0% sensitivity). Across the same 15 cancer types, sensitivities exceeded 80% in 12, with slightly lower values observed in ovary (76.9%), breast (72.3%), and lymphoma (63.6%). Among the remaining 50 patients with pathologically confirmed benign lesions, 28 (56.0%) were correctly classified as non-cancer, potentially sparing them from unnecessary surgical procedures. Conclusion: OncoSeek 2.0 significantly improves sensitivity while maintaining high specificity and affordability (∼$30 reagent cost per test). The upgraded assay strengthens its utility for multi-cancer early detection and demonstrates validated diagnostic value in clinically suspected cancer cases. Its ability to correctly identify 84% of confirmed cancer cases in a tissue-mass cohort demonstrates meaningful diagnostic support to help prioritize patients needing confirmatory procedures. These findings position OncoSeek 2.0 as a practical and scalable solution for both population-level cancer early detection and real-world diagnostic support, particularly for cancers without USPSTF-recommended screening modalities or established non-invasive diagnostic pathways, where surgical procedures are commonly needed for definitive diagnosis. Citation Format: Mao Mao, Yong Shen, Shiyong Li, Wei Wu, Yinyin Chang, PingPing Xing, Chenyu Ding, Dandan Zhu, Qingxia Xu, Wei Cui. OncoSeek 2.0: An advanced multi-cancer blood test enhancing early detection and aiding cancer diagnosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1096.

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Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-1096
Primary Topic
Machine Learning in Bioinformatics
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article

Abstract 1096: OncoSeek 2.0: An advanced multi-cancer blood test enhancing early detection and aiding cancer diagnosis

Mao Mao, Yinyin Chang, Qingxia Xu, P. W. Xing et al.
Cancer Research
Machine Learning in Bioinformatics
article

Abstract 1096: OncoSeek 2.0: An advanced multi-cancer blood test enhancing early detection and aiding cancer diagnosis

Mao Mao, Yinyin Chang, Qingxia Xu, P. W. Xing, Wei Cui, Yong Shen, Wei Wu, Dandan Zhu, Shiyong Li, Chenyu Ding
article en

Abstract

Abstract Background: Early cancer detection and timely diagnosis are critical for improving patient outcomes and reducing healthcare costs. OncoSeek is an AI-driven, low-cost multi-cancer early detection (MCED) assay integrating seven protein tumor markers (PTMs) with clinical data, previously demonstrating 58.4% sensitivity, 92.0% specificity, and 70.6% tissue-of-origin accuracy in over 15,000 participants. Here, we present OncoSeek 2.0, an upgraded version that incorporates three additional PTMs to enhance the detection of prostate, lung, and squamous cell carcinomas, and evaluate its performance in validation cohorts and its expanded use for assisting cancer diagnosis in patients with tissue masses. Methods: OncoSeek 2.0 retained the original machine learning framework with expanded biomarker inputs. MCED performance was assessed in a retrospective cohort including 722 cancer and 355 non-cancer subjects. To further evaluate clinical utility, a prospective cohort of 732 patients with tissue masses, clinically deemed likely malignant and scheduled for surgery, was analyzed to assess the assay’s effectiveness in aiding cancer diagnosis. Results: Compared with OncoSeek 1.0, OncoSeek 2.0 achieved a higher AUC (0.934 vs. 0.888) and improved sensitivity from 70.4% to 83.5% at 90.1% specificity across 15 prespecified cancer types collectively accounting for 76.5% of global cancer mortality. Sensitivity gains were notable in lung (79.9% → 89.6%), prostate (58.8% → 94.1%), cervical (44.4% → 72.2%), and esophageal (41.6% → 64.4%) cancers. In the prospective tissue-mass cohort, OncoSeek 2.0 correctly identified 573 of 682 confirmed cancers (84.0% sensitivity). Across the same 15 cancer types, sensitivities exceeded 80% in 12, with slightly lower values observed in ovary (76.9%), breast (72.3%), and lymphoma (63.6%). Among the remaining 50 patients with pathologically confirmed benign lesions, 28 (56.0%) were correctly classified as non-cancer, potentially sparing them from unnecessary surgical procedures. Conclusion: OncoSeek 2.0 significantly improves sensitivity while maintaining high specificity and affordability (∼$30 reagent cost per test). The upgraded assay strengthens its utility for multi-cancer early detection and demonstrates validated diagnostic value in clinically suspected cancer cases. Its ability to correctly identify 84% of confirmed cancer cases in a tissue-mass cohort demonstrates meaningful diagnostic support to help prioritize patients needing confirmatory procedures. These findings position OncoSeek 2.0 as a practical and scalable solution for both population-level cancer early detection and real-world diagnostic support, particularly for cancers without USPSTF-recommended screening modalities or established non-invasive diagnostic pathways, where surgical procedures are commonly needed for definitive diagnosis. Citation Format: Mao Mao, Yong Shen, Shiyong Li, Wei Wu, Yinyin Chang, PingPing Xing, Chenyu Ding, Dandan Zhu, Qingxia Xu, Wei Cui. OncoSeek 2.0: An advanced multi-cancer blood test enhancing early detection and aiding cancer diagnosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1096.

Cancer ResearchVol. 86(7_Supplement)
BGI Group (China) (CN), Henan Cancer Hospital (CN), Henan Bioengineering Technology Research Center (CN)
Good health and well-being
Openalex Percentile: Top 31%
Machine Learning in Bioinformatics
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