Zhang, Quan

Abstract Introduction: A test that detects cancer signal across multiple cancer types and predicts signal (tissue) origin (SO) could aid in more efficient diagnostic workup and shorten time to cancer diagnosis in individuals with signs and symptoms.Methods: The Circulating Cell-free Genome Atlas (CCGA; NCT02889978) study is a prospective, longitudinal, multicenter, case-control study to develop and validate a multi-cancer detection test. The 2nd CCGA substudy utilized a targeted methylation-based cell-free DNA assay and machine learning algorithm and included assessment of test performance (sensitivity and SO prediction accuracy) in a subgroup of participants with clinically presenting cancers (CPCs) that were undiagnosed prior to blood draw. Specificity was assessed in the noncancer group and subgroups with confounding (nonmalignant) conditions (CCs; eg, cirrhosis) and noncancer participants enrolled in hematology clinics (HCs).Results: Specificity was 99.5% (95% confidence interval: 98.2-99.9%; 396/398), 93.8% (71.7-99.7%; 15/16), and 99.3% (96.0-100.0%; 136/137) for the noncancer group, CCs subgroup, and HCs subgroup, respectively. Overall sensitivity among those with CPCs was 66.4% (62.2-70.3%; 344/518). Sensitivity of cancer signal detection increased with increasing clinical stage (Table). SO prediction accuracy was 91.7% (88.3-94.3%; 300/327) among CPC participants with cancers detected, excluding those with multiple or unknown primaries. The test demonstrated prognostic value as detected cancer participants had worse survival probability than those not detected. Conclusions: This multi-cancer detection test detected cancer signals and predicted SO in individuals with CPCs with high specificity. These findings support further clinical development of this multi-cancer detection test that could accelerate the diagnostic resolution of symptomatic cancers. Table. Sensitivity by Clinical Stage Across Cancer Type in Clinically Presenting CancersClinical StagePositive Test/Total Cancer; Sensitivity (95% CI)All*344/518; 66.4% (62.2-70.3%)I33/122; 27.0% (20.0-35.5%)II60/102; 58.8% (49.1-67.9%)III103/121; 85.1% (77.7-90.4%)IV136/147; 92.5% (87.1-95.8%)Not expected to be staged9/21; 42.9% (24.5-63.5%)Non-informative2/4; 50.0% (15.0-85.0%)CI, confidence interval.*One participant who had a positive test result had multiple primaries with clinical stage I and not-expected-to-be-staged. Citation Format: Alan H. Bryce, Minetta C. Liu, Michael V. Seiden, David D. Thiel, Donald Richards, Carlos Becerra, Kathryn N. Kurtzman, Xiaoji Chen, Tony Wu, Quan Zhang, Jingjing Gao, Nan Zhang, Earl Hubbell, Arash Jamshidi, Eric T. Fung, Eric A. Klein. Performance of a cell-free DNA-based multi-cancer detection test as a tool for diagnostic resolution of symptomatic cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB058.

Abstract Background: The Circulating Cell-free Genome Atlas study (NCT02889978) is a multi-center, case-control, observational study with longitudinal follow-up (n=15,254; 56% cancer, 44% non-cancer) to support development of a cell-free DNA (cfDNA) multi-cancer early detection test. Previously, we reported that a targeted methylation assay detected and localized >20 cancer types at >99% specificity in individuals with cancer.1,2 Here, we report prediction of cancer (presence/absence) and tissue of origin (TOO) in individuals enrolled with clinical suspicion of cancer but without pathologic diagnosis or treatment at time of enrollment. Methods: Plasma cfDNA from blood samples collected prior to clinical diagnosis was subjected to targeted methylation sequencing. Samples were divided into a training set and an independent validation set to train and validate a machine learning classifier to assess cancer and predict TOO. Performance was assessed in a subset of participants enrolled with suspicion of cancer; subsequently, cancer was confirmed by evaluating a pathologic specimen. Results: Participants being evaluated for suspicion of cancer were classified as confirmed cancer (>20 cancer types; n=164 in training, n=75 in validation) or confirmed non-cancer (n=49 training, n=15 validation). In the confirmed non-cancer group, all training and validation samples were correctly predicted as non-cancer (100% specificity). In the confirmed cancer group, cancer detection across all stages was 40.2% (66/164; 95% confidence interval [CI], 32.7-48.2%) in training and 46.7% (35/75; 95% CI, 35.1-58.6%) in validation. Excluding stage I renal cancers (where detection/tumor fraction is low in plasma and which comprised 20% of participants in this subset) detection across stages was 50.4% (66/131; 95% CI, 41.5-59.2%) and 59.3% (35/59; 95% CI, 45.7-71.9%), respectively. In stages II and above, detection was 70.7% (58/82; 95% CI, 59.6-80.3%) and 78.9% (30/38; 95% CI, 62.7-90.4%), respectively. For detected cancers, TOO was predicted in 93.9% (62/66) samples in training and 100% (35/35) in validation. Of those with a TOO call, accuracy was 85.5% (53/62; 95% CI, 74.2-93.1%) and 97.1% (34/35; 95% CI, 85.1-99.9%), respectively. Conclusion: A cfDNA multi-cancer detection test has shown the potential to predict cancer and TOO in individuals with suspicion of cancer ahead of histologic diagnosis with performance comparable to those with confirmed cancer at the time of blood collection. This was achieved with high specificity and TOO accuracy. The high specificity suggests that the false positive rate could be comparable in populations with average versus higher risk (suspicion) of cancer. These findings suggest that a cfDNA multi-cancer detection test could accelerate the diagnostic resolution of suspicion of cancer. References: 1. Oxnard GR, et al. ASCO Breakthrough Meeting 2019; Abstract 44. 2. Oxnard GR, et al. ESMO Annual Meeting 2019; Abstract 5639. Citation Format: David D. Thiel, Xiaoji Chen, Kathryn N. Kurtzman, Jessica Yecies, Tony Wu, Quan Zhang, Hai Liu, Nan Zhang, Eric T. Fung, Michael V. Seiden, Minetta C. Liu, Geoffrey R. Oxnard, Earl Hubbell, Alexander M. Aravanis, Anne-Renee Hartman, Eric A. Klein. Prediction of cancer and tissue of origin in individuals with suspicion of cancer using a cell-free DNA multi-cancer early detection test [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT021.