Giakoumopoulos, Maria

6072 Background: Effective screening tests for ovarian cancer (OC) are lacking; most cases present at advanced stage and portend poor prognosis. DNA methylation is an early event in carcinogenesis and can be detected in blood plasma samples from cancer patients. In DNA extracted from tissues, we first discovered, then validated discriminant methylated DNA marker (MDM) candidates for OC and subsequently tested independent plasma from women with and without OC. Methods: For discovery, DNA from 67 frozen tissues (18 high grade serous (HGS), 18 endometrioid, 15 clear cell (CC), 6 mucinous OCs; 10 benign fallopian tube epithelium (FT); and 19 buffy coats from cancer-free women underwent reduced representation bisulfite sequencing (RRBS) to identify MDMs associated with OC. Candidate MDM selection was based on receiver operating characteristic (ROC) discrimination, methylation fold change, and low background methylation among controls. Blinded biological validation was performed using methylated specific PCR on DNA extracted from independent FFPE tissues from OCs (36 HGS, 22 endometrioid, 21 CC, and 14 mucinous) and 29 FT. Top performing MDMs in tissue were tested using long-probe quantitative amplified signal assays in independent pre-treatment plasma samples from women newly-diagnosed with OC and population-sampled healthy women. A random forest modeling analysis was performed to generate predictive probability of disease; results were 500-fold in silico cross-validated. Results: After RRBS discovery and biological validation, 33 MDMs showed marked methylation fold changes (10 to > 1000) across all OC histologies vs FT. The top 11 MDMs ( GPRIN1, CDO1, SRC, SIM2, AGRN, FAIM2, CELF2, DSCR6, GYPC, CAPN2, BCAT1) were tested on plasma from 91 women with OC (76 (84%) HGS) and 91 without OC; the cross-validated 11-MDM panel highly discriminated OC from controls (96% (95%CI 89-99%) specificity; 79% (69-87%) sensitivity, and AUC 0.91 (0.86 - 0.96)). Among HGS, the panel correctly identified 83%, including 5/6 stage I/II, and the majority of other subtypes (Table). Conclusions: Whole methylome sequencing, stringent filtering criteria, and biological validation yielded outstanding candidate MDMs for OC that performed with promisingly high sensitivity and specificity in plasma. Larger plasma-based OC MDM testing studies, with larger numbers of non-HGS histologies are warranted. [Table: see text]

Early detection improves hepatocellular carcinoma (HCC) outcomes, but better noninvasive surveillance tools are needed. We aimed to identify and validate methylated DNA markers (MDMs) for HCC detection. Reduced representation bisulfite sequencing was performed on DNA extracted from 18 HCC and 35 control tissues. Candidate MDMs were confirmed by quantitative methylation‐specific PCR in DNA from independent tissues (74 HCC, 29 controls). A phase I plasma pilot incorporated quantitative allele‐specific real‐time target and signal amplification assays on independent plasma‐extracted DNA from 21 HCC cases and 30 controls with cirrhosis. A phase II plasma study was then performed in 95 HCC cases, 51 controls with cirrhosis, and 98 healthy controls using target enrichment long‐probe quantitative amplified signal (TELQAS) assays. Recursive partitioning identified best MDM combinations. The entire MDM panel was statistically cross‐validated by randomly splitting the data 2:1 for training and testing. Random forest (rForest) regression models performed on the training set predicted disease status in the testing set; median areas under the receiver operating characteristics curve (AUCs; and 95% confidence interval [CI]) were reported after 500 iterations. In phase II, a six‐marker MDM panel (homeobox A1 [HOXA1], empty spiracles homeobox 1 [EMX1], AK055957 , endothelin‐converting enzyme 1 [ECE1], phosphofructokinase [PFKP], and C‐type lectin domain containing 11A [CLEC11A]) normalized by beta‐1,3‐galactosyltransferase 6 (B3GALT6) level yielded a best‐fit AUC of 0.96 (95% CI, 0.93‐0.99) with HCC sensitivity of 95% (88%‐98%) at specificity of 92% (86%‐96%). The panel detected 3 of 4 (75%) stage 0, 39 of 42 (93%) stage A, 13 of 14 (93%) stage B, 28 of 28 (100%) stage C, and 7 of 7 (100%) stage D HCCs. The AUC value for alpha‐fetoprotein (AFP) was 0.80 (0.74‐0.87) compared to 0.94 (0.9‐0.97) for the cross‐validated MDM panel (P < 0.0001). Conclusion : MDMs identified in this study proved to accurately detect HCC by plasma testing. Further optimization and clinical testing of this promising approach are indicated.

Abstract Purpose: Lung cancer is the leading cause of cancer deaths worldwide. Most present symptomatically at late stage with high lethality. Early detection reduces mortality but accurate and readily accessible tools for population screening are limited. By whole methylome sequencing, we have identified novel methylated DNA markers (MDMs) for lung cancer in tissue (Giakoumopoulos et al. ASCO 2016). Using top candidate MDMs in the present study, we now explore their clinical accuracy for lung cancer detection when assayed from plasma. Experimental Procedures: Archival plasmas from two independent study groups were tested in blinded fashion. Lung cancer cases and controls (apparently healthy smokers) for each group were balanced on age and sex (Group 1: 64 cases, 231 controls; Group 2: 23 cases, 80 controls). Using multiplex PCR followed by QuARTS (Quantitative Allele-Specific Real-time Target and Signal amplification) assay, a post-bisulfite quantification of MDMs on DNA extracted from plasma was performed. We selected 31 MDM candidates for initial evaluation in Group 1 (1 ml plasma/patient); top individual MDMs were subsequently tested in Group 2 to identify optimal MDM panels for lung cancer detection (2 ml/patient). Results: From Group 1 analyses, 13 high performance MDMs were selected for further testing (CYP26C1, SOBP, SUCLG2, SHOX2, ZDHHC1, NFIX, FLJ45983, HOXA9, B3GALT6, ZNF781, SP9, BARX1, EMX1) with individual areas under the receiver operator curve (AUCs) ranging from 0.593 to 0.939. Discrimination by individual MDMs was corroborated in Group 2 in which data was analyzed using two methods: a logistic regression fit and a regression partition tree approach. The logistic fit model identified a 4-marker panel (ZNF781, BARX1, EMX1, and SOBP) with an AUC of 0.96 and an overall sensitivity of 91% and 90% specificity. Analysis of the data using a regression partition tree approach identified 4 markers (ZNF781, BARX1, EMX1, and HOXA9) with AUC of 0.93 and an overall sensitivity of 96% and specificity of 94%. For both approaches, B3GALT6 was used as a standardizing marker of total DNA input. Conclusion: A panel of MDMs assayed in plasma achieved high sensitivity and specificity for all types of lung cancer. Further clinical evaluation and validation of this promising panel in larger patient groups are clearly indicated. Citation Format: Hatim T. Allawi, Maria Giakoumopoulos, Evan Flietner, Austin Oliphant, Carla Volkmann, Brian Aizenstein, Tamara Sander, Drew Eckmayer, Ashley Poenitzsch Strong, Melissa Gray, Barry Berger, Tracy Yab, William Taylor, Douglas Mahoney, John B. Kisiel, David E. Midthun, David A. Ahlquist, Graham P. Lidgard. Detection of lung cancer by assay of novel methylated DNA markers in plasma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 712. doi:10.1158/1538-7445.AM2017-712