Bruinsma, Janelle J.

4577 Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. Though biannual ultrasound surveillance with or without alpha-fetoprotein (AFP) testing is recommended for at-risk patients, its sensitivity for early-stage HCC detection is suboptimal. We therefore evaluated performance of a biomarker panel incorporating methylated DNA markers (MDMs) and proteins for early HCC detection in at-risk patients with chronic liver disease. Methods: In an international, multicenter, case-control study, blood specimens were collected from patients with HCC per AASLD criteria and controls matched for age and liver disease etiology. All patients had underlying cirrhosis or chronic HBV infection. Whole blood was collected in cell-free DNA stabilizing and serum-separation tubes and shipped to a central laboratory for processing. The levels of 5 MDMs, AFP, and AFP-L3 were assessed along with age and sex. We used 537 samples in a 5-fold validation for developing a LASSO regression algorithm to classify samples as HCC positive or negative. Model robustness was tested by perturbing the data in silico and analyzing results with the predictive algorithm. Algorithm performance was compared to AFP alone and the GALAD score (Gender, Age, AFP-L3, AFP, and DCP). Results: The study included 136 HCC cases (81 early-stage—BCLC stage 0/A) and 401 controls. With specificity set at 89%, we developed a model using sex, AFP, and 3 MDMs (HOXA1, TSPYL5, B3GALT6) with higher sensitivity (70%) for early-stage HCC compared to GALAD (54%) or AFP (31% at 20 ng/mL or 52% at ≥7.7 ng/mL) (Table). The AUC for the HCC marker panel was 0.91 (95% CI 0.89 – 0.94) compared to GALAD (0.88; 95% CI 0.85 – 0.91) or AFP (0.84; 95% CI 0.81 – 0.87). The panel performed similarly in viral (AUC = 0.94) and non-viral (AUC = 0.89) etiologies. Conclusions: The robust algorithm based on novel blood-based biomarkers presented here provides higher sensitivity for early-stage HCC compared to other available blood-based biomarkers and, therefore, could significantly impact HCC clinical management and patient outcomes. Further clinical studies to validate the algorithm are ongoing. Clinical trial information: NCT03628651 . [Table: see text]

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.