INTRODUCTION: Colorectal cancer (CRC) screening is broadly endorsed for individuals 50–75 years of age. Given recent increases in CRC incidence and mortality for patients <50 years old, the American Cancer Society now recommends initiation of average-risk CRC screening at age 45 (Wolf AMD CA Cancer J Clin 2018). The performance of recommended tests, including the multi-target stool DNA (mt-sDNA; marketed as Cologuard™) test, has been minimally described in populations under 50 years old. To address this knowledge gap, we conducted a retrospective study of DNA markers (KRAS, BMP3, NDRG4) included in the mt-sDNA assay to quantify and compare tissue marker levels in sporadic CRC cases and normal colon controls from patients in 45–49 and 50–64 year-old age groups. Our primary hypothesis was that mt-sDNA marker levels would be statistically similar between cases in both age groups. METHODS: Patient samples were identified from a pathology tissue archive at Mayo Clinic, excluding those with inflammatory bowel disease or familial cancer syndromes. Formalin-fixed, paraffin-embedded tissues were reviewed by a GI pathologist for 45–49 year-old (n = 90) and 50–64 year-old (n = 96) CRC cases; normal colon samples (45–49, n = 76; 50–64, n = 92) were also included for comparison. DNA extracted from core punches was blinded and processed in a randomized order. Quantitative Allele specific Realtime Target and Signal amplification (QuARTS) assays were used to quantify KRAS mutations, and BMP3 and NDRG4 methylation. Marker level in each sample was reported as the QuARTS product of mutant KRAS , methylated BMP3 or NDRG4 relative to the ACTB product in each sample, reported as a percentage. At least 60 patients per group provided sufficient power to demonstrate differences in marker levels of ±25% between case groups and between control groups using the Wilcoxon Rank Sum test. RESULTS: CRC cases in the 45–49 vs 50–64 year-old groups did not differ significantly with respect to sex ( P = 0.77) or race/ethnicity ( P = 0.06); left-sided CRC was more common in the 45–49 vs 50–64 year-old group (87% vs. 72%; P = 0.02). None of the marker levels were statistically different between cases of the younger vs older groups or between controls of these groups (Figure 1). CONCLUSION: These data support the expectation of no age-related differences in CRC detection by mt-sDNA, as the relevant molecular markers, when they occur, are present at similar levels across age groups 45–49 and 50–64 years.
Discovery, Validation, and Application of Novel Methylated DNA Markers for Detection of Esophageal Cancer in Plasma
Abstract Purpose: The burden of esophageal cancer continues to rise, and noninvasive screening tools are needed. Methylated DNA markers (MDM) assayed from plasma show promise in detection of other cancers. For esophageal cancer detection, we aimed to discover and validate MDMs in tissue, and determine their feasibility when assayed from plasma. Experimental Design: Whole-methylome sequencing was performed on DNA extracted from 37 tissues (28 EC; 9 normal esophagus) and 8 buffy coat samples. Top MDMs were validated by methylation specific PCR on tissue from 76 EC (41 adeno, 35 squamous cell) and 17 normal esophagus. Quantitative allele-specific real-time target and signal amplification was used to assay MDMs in plasma from 183 patients (85 EC, 98 controls). Recursive partitioning (rPART) identified MDM combinations predictive of esophageal cancer. Validation was performed in silico by bootstrapping. Results: From discovery, 23 candidate MDMs were selected for independent tissue validation; median area under the receiver operating curve (AUC) for individual MDMs was 0.93. Among 12 MDMs advanced to plasma testing, rPART modeling selected a 5 MDM panel (FER1L4, ZNF671, ST8SIA1, TBX15, ARHGEF4) which achieved an AUC of 0.93 (95% CI, 0.89–0.96) on best-fit and 0.81 (95% CI, 0.75–0.88) on cross-validation. At 91% specificity, the panel detected 74% of esophageal cancer overall, and 43%, 64%, 77%, and 92% of stages I, II, III, and IV, respectively. Discrimination was not affected by age, sex, smoking, or body mass index. Conclusions: Novel MDMs assayed from plasma detect esophageal cancer with moderate accuracy. Further optimization and clinical testing are warranted.
Novel Methylated DNA Markers Discriminate Advanced Neoplasia in Pancreatic Cysts: Marker Discovery, Tissue Validation, and Cyst Fluid Testing
OBJECTIVES: Pancreatic cystic lesions (PCLs) may be precancerous. Those likely to harbor high-grade dysplasia (HGD) or pancreatic cancer (PC) are targets for surgical resection. Current algorithms to predict advanced neoplasia (HGD/PC) in PCLs lack diagnostic accuracy. In pancreatic tissue and cyst fluid (CF) from PCLs, we sought to identify and validate novel methylated DNA markers (MDMs) that discriminate HGD/PC from low-grade dysplasia (LGD) or no dysplasia (ND). METHODS: From an unbiased whole-methylome discovery approach using predefined selection criteria followed by multistep validation on case (HGD or PC) and control (ND or LGD) tissues, we identified discriminant MDMs. Top candidate MDMs were then assayed by quantitative methylation-specific polymerase chain reaction on archival CF from surgically resected PCLs. RESULTS: Of 25 discriminant MDMs identified in tissue, 13 were selected for validation in 134 CF samples (21 cases [8 HGD, 13 PC], 113 controls [45 ND, 68 LGD]). A tree-based algorithm using 2 CF-MDMs ( TBX15 , BMP3 ) achieved sensitivity and specificity above 90%. Discrimination was significantly better by this CF-MDM panel than by mutant KRAS or carcinoembryonic antigen, with areas under the receiver operating characteristic curve of 0.93 (95% confidence interval: 0.86–0.99), 0.71 (0.57–0.85), and 0.72 (0.60–0.84), respectively. Cutoffs for the MDM panel applied to an independent CF validation set (31 cases, 56 controls) yielded similarly high discrimination, areas under the receiver operating characteristic curve = 0.86 (95% confidence interval: 0.77–0.94, P = 0.2). DISCUSSION: Novel MDMs discovered and validated in tissue accurately identify PCLs harboring HGD/PC. A panel of 2 MDMs assayed in CF yielded results with potential to enhance current risk prediction algorithms. Prospective studies are indicated to optimize and further evaluate CF-MDMs for clinical use.
A methylated DNA marker panel for the sensitive detection of lung cancer in tissue.
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.
Detection of Gastric Cancer with Novel Methylated DNA Markers: Discovery, Tissue Validation, and Pilot Testing in Plasma
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
Screen detection of serrated polyps by stool DNA multi-target testing (sDNA-MT): Comparison against fecal immunochemical occult blood testing (FIT).
341 Background: Precursors to 1/3 of colorectal cancer (CRC), serrated polyps have historically been underdetected by screening due to their inconspicuous, nonhemorrhagic, and proximal nature. New generation sDNA-MT show high sensitivity for both CRC and advanced adenomas (Gastroenterology 2012;142:248), but screen detection of serrated polyps by this approach requires further validation. Aim: To assess and compare noninvasive detection of sessile serrated polyps >1cm (SSP) by sDNA-MT and a commercial quantitative FIT. Methods: In a blinded prospective study, a single stool sample used for both tests was collected from 456 asymptomatic adults prior to screening or surveillance colonoscopy (criterion standard). All 29 patients with SSP were included as cases and all 232 with no neoplastic findings as controls. Buffered stool samples were processed and frozen on receipt; Exact Sciences performed sDNA-MT in batches using optimized analytical methods (Gastroenterology 2012;142:S770). The sDNA-MT panel targets methylated BMP3 (mBMP3) and NDRG4, mutant KRAS, β-actin, and hemoglobin. FIT (Polymedco OC-FIT Check) was performed in separate lab <2 days post defecation and evaluated at cutoffs of 50 (FIT-50) and 100 ng/ml (FIT-100). Results: Age/sex distributions were similar in cases and controls: 40% vs 45% > 65 years and 51% vs 59% women, p=NS respectively. SSP median size was 1.2cm (range 1-3cm), 93% were proximal, and 64% had synchronous diminutive polyps. Among sDNA-MT markers, mBMP3 proved highly discriminant for SSP detection (AUC=0.87, p<0.00001); other DNA markers were less informative and provided no incremental sensitivity. Hemoglobin alone showed no discrimination (AUC=0.50, p=NS). At matched specificities, SSP detection by stool mBMP3 was significantly greater than by either FIT-50 or FIT-100 (Table). Conclusions: From a screening and surveillance setting, SSP can be detected noninvasively by stool assay of exfoliated DNA markers, especially mBMP3. FIT appears to have no value in SSP detection. [Table: see text]
Abstract 4252: Accurate site prediction of gastrointestinal cancer by novel methylated DNA markers: Discovery & validation
Abstract Purpose: Methylated DNA markers can discriminate upper from lower GI neoplasms (Gastroenterology 2013;144(5):S84). It is unknown if organ-specific molecular prediction of GI tumor site can be achieved. Experimental design: An unbiased search for neoplasm markers at each major GI organ site was conducted by reduced representation bisulfite sequencing. Top marker candidates were then blindly validated by methylation specific PCR on independent tissue DNA samples from normal mucosa [17 esophagus (E), 13 stomach (S), 33 pancreas (P), 35 bile duct/liver (BD), 21 colorectal (CR)] and neoplasia [42 E, 43 S, 36 P, 48 BD, 97 CR]. Recursive partitioning (rPart) trees modeled all stepwise combinations of single markers to classify controls vs neoplasms and then neoplasms by site (CR, gastroesophageal or pancreaticobiliary). A 2nd model was designed from tissue data for blinded clinical piloting on 42 independent plasma DNA samples (14 normal and 28 cancers (14 P, 14 CR). Results: From the top 100 markers, 95 were validated and used for rPart modeling. A 3- marker panel (chr12.133484978-5047, BMP3, chr11.123301058-255) was selected for the universal detection of GI neoplasms, as it classified neoplasms and control tissues with 95% accuracy. Two markers (chr7.25896389-501, QKI) then assigned lower vs upper GI neoplasms with 94% accuracy. Finally, 3 markers (PDGFD, ELOVL2, PCBP3) called pancreaticobiliary vs gastroesophageal neoplasms with 94% accuracy. All 8 markers applied in a single model (Table) accurately predicted control vs tumor by site [88% (p <0.0001)]. In plasma, a 2-marker panel (BMP3, QKI) was 78% accurate in assigning patients to cancer or control groups (p<0.0009) and 83% accurate in assigning cancer origin to CR or P sites (p<0.0001). Predicted by ModelTissue SourceControlsColorectal neoplasiaPancreatico-biliary cancerGastro-esophageal neoplasiaControls1169102Colorectal neoplasia18617Pancreatico-biliary cancer10654Gastro-esophageal neoplasia12872 Conclusion: Panels of methylated DNA markers were identified for both universal detection of GI neoplasia and accurate prediction of tumor site. Pilot testing of these markers in plasma supports potential clinical feasibility. Citation Format: John B. Kisiel, William R. Taylor, Tracy C. Yab, Hassan M. Ghoz, Patrick H. Foote, Mary E. Devens, Douglas W. Mahoney, Thomas C. Smyrk, Lisa A. Boardman, Gloria M. Petersen, Navtej S. Buttar, Lewis R. Roberts, Graham P. Lidgard, David A. Ahlquist. Accurate site prediction of gastrointestinal cancer by novel methylated DNA markers: Discovery & validation. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4252. doi:10.1158/1538-7445.AM2015-4252
Abstract B12: An optimized molecular stool test for colorectal cancer screening: Evaluation of an automated analytic platform and logistic algorithm
Abstract We have demonstrated that colorectal cancer (CRC) and advanced pre-cancers can be detected non-invasively by a manual multi-target stool DNA-based test (sDNA-MT) comprising exfoliated DNA markers (methylated BMP3 and NDRG4, mutant KRAS (7 mutations, codons 12, 13), plus β-actin) and fecal hemoglobin (Hb) (Lidgard, Gastroenterology 2012;142(5);S-770). We now report the clinical performance of this sDNA-MT test using an optimized automated analytic platform and logistic algorithm. This platform could facilitate the routine performance of sDNA-MT for CRC screening by molecular diagnostics capable clinical laboratories. Method: Stool samples were collected from 1003 subjects at 36 study sites after informed consent and prior to colonoscopy bowel preparation from those presenting for average risk CRC screening (283) or surveillance (176) at 2 sites. From referred subjects with CRC, Advanced Adenoma (AA) or Sessile Serrate Adenoma ≥ 1 cm, (SSA) stool was collected at least 7 days post-colonoscopy and prior to surgery or chemo-radiation (135; 21 sites) and similarly for subjects with no neoplastic findings on colonoscopy (Neg) (409; 13 sites). The study population included: cases (207), 58% male, median age 65 yrs. (38-87), CRC (93), AA (84), SSA ≥ 1 cm (30) and controls (796), 42% male, median age 65 yrs. (50-84), Neg (641) and non-advanced adenomas (NA) (155). Stool sample collection and DNA isolation were previously described. Automated methylation, mutation and actin assays were performed with a Hamilton STARlet fluid handler (Hamilton Robotics, Reno NV), and QuARTS (Quantitative Allele-specific Real-time Target and Signal amplification) run on an ABI 7500 FastDx real time thermal cycler (Applied Biosystems, Foster City, CA). Fecal Hb (ng/ml buffer) analysis was performed by automated sandwich ELISA. A “Positive” or “Negative” result was determined with an algorithm that included the methylation and mutation results and a logistic regression score, which combines DNA marker results with Hb and actin results. Algorithm results exceeding a threshold were called “Positive”. The algorithm provided good discriminative ability, stability, sensitivity and specificity. Robustness was tested with computer simulations and statistical techniques (leave-one-out and 10-fold cross validation). Results: At a 90% nominal specificity, sDNA-MT sensitivity was 98% for CRC (91/93) [Stage: I, 95% (20/21), II, 100% (23/23), III 96% (26/27), IV 100% (7/7) and I-III combined 97% (69/71)], 57% (65/114) for precursors ≥1 cm (AA, SSA), and 86% (12/14) for precursors with high grade dysplasia. CRC patients were typically referred to colonoscopy for symptoms and test sensitivity may be elevated relative to that seen with screening. Conclusion: With this study using a novel automated sDNA-MT analytic platform with logistic algorithm, we corroborate our earlier findings using a manual process and demonstrate a platform that allows testing to be performed routinely by molecular diagnostic capable laboratories. The high sensitivity of sDNA-MT for CRC across all stages and for advanced precursors with high-grade dysplasia could lead to improved non-invasive CRC screening performance with wide accessibility to patients. A large multi-site pivotal CRC screening study (DeeP-C study clinicaltrials.gov, NCT01397747) to support such use is underway. Citation Format: Graham P. Lidgard, Michael J. Domanico, Janelle J. Bruinsma, James Light, Zubin D. Gagrat, Rebecca L. Oldham-Haltom, Keith D. Fourrier, Hatim Allawi, Tracy C. Yab, Julie A. Simonson, Mary Devens, Russell I. Heigh, David A. Ahlquist, Barry M. Berger. An optimized molecular stool test for colorectal cancer screening: Evaluation of an automated analytic platform and logistic algorithm. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr B12.