Hennek, Jacquelyn

ABSTRACT Lymphoma is one of the leading causes of cancer and cancer deaths and yet has not been amenable to population screening. The role of methylated DNA markers (MDMs) in the detection of lymphoma has not been extensively studied. We aimed to discover, validate, and test tissue–derived MDMs of lymphoma in archival plasma specimens. Reduced representation bisulfite sequencing (RRBS) was performed on a discovery set of frozen tissues. MDMs identified were converted to methylation–specific PCR assays and validated on independent formalin–fixed, paraffin‐embedded (FFPE) tissues. Target enrichment long–probe quantitative‐amplified signal (TELQAS) assays were developed and assayed in plasma–extracted, bisulfite‐converted DNA from independent treatment‐naïve lymphoma patients and healthy controls. Prediction of cancer status was modeled using random forest model with in silico cross‐validation. After discovery and validation in tissue, 16 TELQAS assays ( ZNF503 , VWA5B1 , HOXA9 , GABRG3 , ITGA5 , MAX.chr17.7190 , BNC1 , CDK20 , MAX.chr4.4069 , TPBG , DNAH14 , SYT6 , CACNG8 , FAM110B , ADRA1D , and NRN1 ) were selected for testing in plasma. These detected 78% (95% CI, 74%–82%) of lymphoma cases at 90% specificity. Excluding marginal zone and T‐cell lymphomas, sensitivity increased to 84% (80%–88%). MDMs in plasma show promise to detect lymphoma and are candidates for inclusion in multi‐cancer detection studies.

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.

7562 Background: Lymphoma is the 6th most common cancer and a top 10 cause of cancer deaths. To date, there are no blood test approaches to population screening, and accurate surveillance markers are limited. Methylated DNA markers (MDMs) are broadly informative for early detection of cancer but have not been extensively studied for lymphomas. We sought to discover and validate MDMs in DNA extracted from lymphoma tissue, then test these MDMs in archival blood plasma specimens. Methods: Reduced representation bisulfite sequencing (RRBS) was performed on DNA extracted from a discovery set of frozen tissues of classic Hodgkin lymphoma (CHL, n=24), non-Hodgkin lymphoma (NHL, n=78: T-cell-TCL (8); diffuse large B-cell-DLBCL (18); follicular-FL (12); mantle cell-MCL (20); marginal zone-MZL (15)), and lymphoma cell line samples (27); controls included benign lymph node (n=11) and healthy donor buffy coat (n=30). 30 MDMs were ranked by fold-change and AUC and used to design methylation-specific PCR assays for biological validation on independent DNA samples extracted from FFPE tissue from 13 normal lymph node and 63 lymphoma samples and 36 buffy coats from healthy patients. Target enrichment long-probe quantitative-amplified signal assays were developed for 16 MDMs and then assayed in plasma-extracted, bisulfite-converted DNA samples from 390 independent treatment-naïve lymphoma patients (100 CHL and 290 NHL:100 DLBCL, 73 FL, 41 MCL, 41 MZL, 35 TCL), and 210 controls without cancer. Lymphoma plasma samples and 159 controls were provided by the Lymphoma SPORE (CA97274); 51 controls came from a 7-county population archive. Classification of lymphoma cases vs controls was modeled with random forest method and cross-validated across 500 bootstrap samples of each dataset. Results: For MDMs tested in DNA from independent biological validation samples, cross-validated random forest models identified 60/63 cases (95% sensitivity) and 12/13 normal controls (92% specificity). In plasmas, a panel of 16 MDMs ( ZNF503, VWA5B1, HOXA9_5195, GABRG3, ITGA5, MAX_chr17_793, BNC1_2407, CDK20, MAX_chr4_184, TPBG, DNAH14, SYT2, CACNG8, FAM110B, and NRN1) detected 78% (95% CI, 74-82%) of lymphoma cases at 90% specificity. Excluding MZL and TCL, sensitivity increased to 84% (80-88%) including 26/49 (53% (38-67%)) of stage I and 59/71 (83% (71-90%)) of stage II cases. Conclusions: MDMs show promise to detect lymphoma. These markers could be evaluated as part of multicancer early detection testing and could also be evaluated as response markers to treatment and subsequent surveillance.[Table: see text]

Abstract Purpose: Screening for high prevalence cancers (breast, colorectum and uterine cervix) reduces mortality; however, most cancer deaths arise in unscreened organs. An ideal solution would accurately detect multiple currently unscreened cancers in a single round of testing. We aimed to assess the feasibility of a targeted assay panel of methylated DNA markers (MDMs) and proteins for detection of highly lethal cancers in a multi-cancer case-control study. Experimental Procedures: Prospectively collected plasmas from 180 cases of 6 cancer types (stage A-D liver (n=36), and TNM stage II-IV esophageal (n=18), lung (n=36), ovarian (n=30), pancreatic (n=30), and stomach (n=30)) and 257 smoking status, age-, and gender-matched asymptomatic controls were tested in blinded fashion. To quantify 26 MDMs previously found to be common among many cancers, multiplex PCR followed by LQAS (Long probe Quantitative Amplified Signal) assay was performed on bisulfite converted DNA extracted from 3 mL of plasma. Additionally, 5 proteins were tested from paired serum aliquots and combined with MDMs for a multi-analyte analysis. Two-thirds of the cases and controls were used to develop prediction algorithms, both logistic regression and random forest models, and the remaining 1/3 were used to validate the models. Results: Using stepwise logistic regression, a combination of 3 proteins (CEA, CA-125, CA19-9) and 5 MDMs (ZNF671, GRIN2D, NDGR4, SHOX2, B3GALT6) resulted in an AUC of 0.95 and an overall sensitivity of 87% for all cancers at 95% specificity. The logistic model on the validation set of the samples resulted in an AUC of 0.96 and a sensitivity of 83% with an observed specificity of 94%. The cancer-specific sensitivities ranged from 78% for lung cancer to 90% for ovarian and pancreatic cancer (Table). Random forest and logistic analyses were in agreement. Conclusion: Targeted assay of select MDMs and proteins show high discrimination for multiple cancers in a case control study, which included early stage patients. Performance with 95% confidence intervals of multi-target assay for multi-cancer detectionSensitivitySpecificityModelOverallBy cancer typeLungEsophagealGastricPancreaticLiverOvarianLogisticTraining set87%(79-92%)79%83%90%95%88%85%95%(90-97%)Test set83%(72-91%)75%100%80%80%75%100%94%(87%-98%)Training + Test186%(80-90%)78%89%87%90%83%90%95%(91-97%)Training + Test275%(68-81%)50%89%83%76%81%80%98%(96-99%)Random forest377%(70-83%)58%78%83%77%81%87%95%(92-97%)195% specificity goal, 5 MDMs and 3 proteins.298% specificity goal, 5 MDMs and 3 proteins.3With 500-fold in silico cross-validation on all samples and all markers (26 MDMs + 5 proteins) Citation Format: Slava Katerov, Abram Vaccaro, Jacquelyn Hennek, Jennifer Carlson, William R. Taylor, Douglas Mahoney, John B. Kisiel, Hatim T. Allawi. Accurate multi-cancer detection using methylated DNA markers and proteins in plasma [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 111.