Abstract 631: Validation of a panel of methylated DNA and protein markers for multi-cancer detection in plasma

Abstract

Abstract Purpose: Many cancer deaths could be avoided, and survival could be improved with detection of cancer at an earlier stage. Screening programs for breast, colon, and cervical cancer as well as the NLST trial for lung cancer screening demonstrated significant improvement in survival rates with screening. However, for 2021, the American Cancer Society estimates these screened cancers represent less than ~40% of cancer incidence and deaths. The remainder of cancer deaths occur because of tumors in unscreened organs and, therefore, a multicancer test that detects cancer in these organs can increase survival rates. By focusing on detection of unscreened cancers, this type of multicancer test would be complementary to current screening procedures. Here we describe the validation of a combined panel of methylated DNA markers (MDMs) and proteins for multicancer detection through testing an independent set of case/control samples. Experimental Procedures: In this study, we further evaluate the performance of our previously identified panel of 15 MDMs and 5 proteins for multicancer detection (Allawi et al., 2021 AACR Annual Meeting) by testing 315 controls and 160 cases encompassing 6 cancer types (liver, esophageal, lung, ovarian, pancreatic, and stomach). All samples used in the study were case-control collections with smoking status, age, and gender matching between cases and asymptomatic controls. Testing was performed in blinded fashion using multiplex PCR followed by LQAS (Long probe Quantitative Amplified Signal) assay on bisulfite converted DNA extracted from 3 mL of plasma collected in LB Gard® blood tubes. Protein concentrations were determined from paired serum aliquots and combined with MDMs for a multi-analyte analysis. The subjects were divided into training and validation with equal representation of cancer type, staging, gender, and age. Two thirds of the cases and controls were used to train with a logistic prediction algorithm, and the remaining 1/3 were used to validate the model. Results: Using stepwise logistic regression, a training model of MDMs and protein markers resulted in an area under the receiver operating characteristics curve (AUC) of 0.97 and cancer sensitivity of 89% at 98% specificity. The same model predicted the validation set with an AUC of 0.96 and cancer sensitivity of 85% at a specificity of 95%. Applying the algorithm to the combined training and validation sets resulted in sensitivities and specificities of 88% and 97%, respectively. The sensitivities per cancer type ranged from 73% for pancreatic cancer to 97% for lung cancer. Conclusion and Next Steps: This study demonstrates the performance of our MDMs and protein markers and their importance as components in our multi-omics strategy for multicancer detection. The next steps would be to expand the testing to include additional cancer types and combine with NGS-based methods to improve performance and optimize workflow. Citation Format: Hatim T. Allawi, Slava Katerov, Abram Vaccaro, Harrison L. Fleming, Debra E. Rugowski, Brittany Otto, Justin Heilberger, Jillian Cassel, Jacquelyn Hennek, William Taylor, Graham Lidgard. Validation of a panel of methylated DNA and protein markers for multi-cancer detection in plasma [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 631.