Doering, Karen A

ABSTRACT Background Family history of pancreatic cancer (PC), pathogenic germline variants (PGVs), and increased intrapancreatic fat (IPF) are individually associated with increased PC risk. Whether IPF is elevated in high‐risk individuals (HRIs) with PC family history or PGVs is unknown. Although MRI is the preferred modality for IPF measurement, region‐of‐interest–based approaches are prone to sampling bias because pancreatic fat is heterogeneously distributed. We aimed to compare IPF among HRIs and matched non‐HRI controls using an Artificial intelligence (AI)‐based tool for whole pancreatic IPF measurement applied to magnetic resonance imaging (MRI). Methods We developed and validated a deep‐learning pipeline for IPF measurement that incorporates automated pancreas segmentation on T1‐weighted MRI images registered to the corresponding iterative decomposition of water and fat with echo asymmetry and least squares estimation images to compute IPF using proton density fat fraction (PDFF). This pipeline was used to quantify IPF and assess IPF distribution patterns in 85 HRIs and 170 non‐HRIs matched 1:2 for age, sex, BMI, and diabetes status. A surface erosion approach was developed to minimize the impact of peripancreatic fat on IPF measurement. Linear models adjusting for matching variables were used to assess associations. Results Model‐expert agreement for whole‐pancreas PDFF was excellent (intraclass correlation coefficient 0.99; 95% CI, 0.98–0.99 mean absolute error 1.4%). Mean PDFF did not differ between HRIs and controls (25.8% [11.5] vs. 26.9% [11.4]; p = 0.32). PDFF increased with age ( p = 0.015), male sex ( p < 0.001), presence of diabetes ( p = 0.009), BMI ( p < 0.001). IPF distribution patterns did not differ by risk group. Conclusion An AI‐based approach provides accurate, scalable, and objective assessment of IPF quantity and distribution. IPF quantity and spatial distribution do not appear to differ based on germline or familial predisposition to PC.

Introduction: Non-invasive assays are needed to better discriminate patients with prostate cancer (PCa) to avoid over-treatment of indolent disease. We analyzed 14 methylated DNA markers (MDMs) from urine samples of patients with biopsy-proven PCa relative to healthy controls and further studied discrimination of clinically significant PCa (csPCa) from healthy controls and Gleason 6 cancers. Methods: To evaluate the panel, urine from 24 healthy male volunteers with no clinical suspicion for PCa and 24 men with biopsy-confirmed disease across all Gleason scores was collected. Blinded to clinical status, DNA from the supernatant was analyzed for methylation signal within specific DNA sequences across 14 genes (HES5, ZNF655, ITPRIPL1, MAX.chr3.6187, SLCO3A1, CHST11, SERPINB9, WNT3A, KCNB2, GAS6, AKR1B1, MAX.chr3.8028, GRASP, ST6GALNAC2) by target enrichment long-probe quantitative-amplified signal assays. Results: Utilizing an overall specificity cut-off of 100% for discriminating normal controls from PCa cases across the MDM panel resulted in 71% sensitivity (95% CI: 49–87%) for PCa detection (4/7 Gleason 6, 8/12 Gleason 7, 5/5 Gleason 8+) and 76% (50–92%) for csPCa (Gleason ≥ 7). At 100% specificity for controls and Gleason 6 patients combined, MDM panel sensitivity was 59% (33–81%) for csPCa (5/12 Gleason 7, 5/5 Gleason 8+). Conclusions: MDMs assayed in urine offer high sensitivity and specificity for detection of clinically significant prostate cancer. Prospective evaluation is necessary to estimate discrimination of patients as first-line screening and as an adjunct to prostate-specific antigen (PSA) testing.

Background: Radiographic surveillance of colorectal cancer (CRC) after curative-intent therapy is costly and unreliable. Methylated DNA markers (MDMs) detected primary CRC and metastatic recurrence with high sensitivity and specificity in cross-sectional studies. This study evaluated using serial MDMs to detect recurrence and monitor the treatment response to anti-cancer therapies. Methods: A nested case-control study was drawn from a prospective cohort of patients with CRC who completed curative-intent therapy for CRC of all stages. Plasma MDMs were assayed vis target enrichment long-probe quantitative-amplified signal assays, normalized to B3GALT6, and analyzed in combination with serum carcinoembryonic antigen to yield an MDM score. Clinical information, including treatment and radiographic measurements of the tumor burden, were longitudinally collected. Results: Of the 35 patients, 18 had recurrence and 17 had no evidence of disease during the study period. The MDM score was positive in 16 out of 18 patients who recurred and only 2 of the 17 patients without recurrence. The MDM score detected recurrence in 12 patients preceding clinical or radiographic detection of recurrent CRC by a median of 106 days (range 90–232 days). Conclusions: Plasma MDMs can detect recurrent CRC prior to radiographic detection; this tumor-agnostic liquid biopsy approach may assist cancer surveillance and monitoring.

Plasma-based MDMs may offer a cost-effective alternative to imaging for melanoma detection. Early results show 80% sensitivity and 100% specificity against cancer-free controls. Further study needed. #MelanomaResearch #EarlyDetection

Abstract Lynch syndrome (LS) markedly increases risks of colorectal and endometrial cancers. Early detection biomarkers for LS cancers could reduce the needs for invasive screening and surgical prophylaxis. To validate a panel of methylated DNA markers (MDM) previously identified in sporadic colorectal cancer and endometrial cancer for discrimination of these cancers in LS. In a case–control design, previously identified MDMs for the detection of colorectal cancer and endometrial cancer were assayed by qMSP on tissue-extracted DNA. Results were normalized to ACTB values within each sample. Least absolute shrinkage and selection operator models to classify colorectal cancer and endometrial cancer were trained on sporadic cases and controls and then applied to classify colorectal cancer and endometrial cancer, in those with LS, and cross-validated. We identified colorectal cancer cases (23 with LS, 48 sporadic), colorectal controls (32 LS, 48 sporadic), endometrial cancer cases (30 LS, 48 sporadic), and endometrial controls (29 LS, 37 sporadic). A 3-MDM panel (LASS4, LRRC4, and PPP2R5C) classified LS-CRC from LS controls with an AUC of 0.92 (0.84–0.99); results were similar for sporadic colorectal cancer. A 6-MDM panel (SFMBT2, MPZ, CYTH2, DIDO1, chr10.4479, and EMX2OS) discriminated LS-EC from LS controls with an AUC of 0.92 (0.83–1.0); the AUC for sporadic endometrial cancer versus sporadic controls was nominally higher, 0.99 (0.96–1.0). MDMs previously identified in sporadic endometrial cancer and colorectal cancer discriminate between endometrial cancer and benign endometrium and colorectal cancer and benign colorectum in LS. This supports the inclusion of patients with LS within future prospective clinical trials evaluating endometrial cancer and colorectal cancer MDMs and may provide a new avenue for cancer screening or surveillance in this high-risk population. Prevention Relevance: Lynch syndrome (LS) markedly increases risks of colorectal and endometrial cancers. Early detection biomarkers for LS cancers could reduce the needs for invasive screening and surgery. Methylated DNA markers previously identified in sporadic endometrial cancer and colorectal cancer discriminate between benign and cancer tissue in LS.

9567 Background: Cutaneous melanoma surveillance is important to identify low-volume systemic disease, but imaging is costly and poorly accessible to patients; frequent skin checks lack sensitivity and specificity. We aimed to establish clinical feasibility of a liquid biopsy blood test, which quantifies validated, melanoma-specific, methylated DNA markers (MDMs), previously discovered, and reported by our team, using tissue extracted DNA. Methods: We prospectively collected blood from adult patients with histologically confirmed melanoma metastases and no other internal malignancies (within 5-years) who underwent surveillance by FDG-PET/CT (N = 88). Blood from age- and sex balanced cancer-free controls (N = 100) were compared. From PET/CT, we extracted the number of organs involved, SUV-max, and largest tumor diameter. Unequivocal metastasis was defined as SUV ≥ 4 and largest diameter > 5 mm. Because PET/CT is inadequate for the screening of brain metastases, we excluded the brain from the analysis. MDMs ( chr11.149, HOXA9, chr20.210, FLJ22536, CLIC5, SIX4, chr7.155, chr17.730, chr1.110) were assayed using target enrichment long-probe quantitative-amplified signal assays, normalized to B3GALT6, in blinded fashion. Using a logistic regression approach and nine candidate MDMs, we calculated the sensitivity for detecting patients with metastasis on PET/CT at 100% specificity. Results: 52/88 (59%) of melanoma patients showed evidence of metastasis on PET/CT at the time of blood draw. At 100% specificity, a panel of 4 MDMs ( HOXA9, chr20.210, chr17.730, chr1.110) yielded a sensitivity of 86.5% (45/52 cases) vs. 100 cancer-free controls. When applying this model to the 36 PET/CT-negative patients, specificity was as high as 97.2% (35/36 cases) while maintaining a sensitivity of 86.5% (one patient with a positive test result had a complete metabolic response to binimetinib / encorafenib prior to negative PET/CT). For patients with ≥ 2 organs involved by metastasis, sensitivity was 100% (29/29 cases). False-negative cases had metastasis in single organs and were characterized by minimal tumor burden and oral corticosteroid use. One false-negative patient had localized stage III disease without known primary melanoma. Conclusions: Plasma MDM levels appear highly concordant with FDG-PET/CT in patients with metastatic cutaneous melanoma. A liquid biopsy approach has potential to lower cost and improve patient access to surveillance. Additional prospective studies in larger intended use cohorts are needed to validate our results.

Abstract Purpose: We have previously identified tissue methylated DNA markers (MDMs) associated with pancreatic ductal adenocarcinoma (PDAC). In this case–control study, we aimed to assess the diagnostic performance of plasma MDMs for PDAC. Experimental Design: Thirteen MDMs (GRIN2D, CD1D, ZNF781, FER1L4, RYR2, CLEC11A, AK055957, LRRC4, GH05J042948, HOXA1, PRKCB, SHISA9, and NTRK3) were identified on the basis of selection criteria applied to results of prior tissue experiments and assays were optimized in plasma. Next, 340 plasma samples (170 PDAC cases and 170 controls) were assayed using target enrichment long-probe quantitative amplified signal method. Initially, 120 advanced-stage PDAC cases and 120 healthy controls were used to train a prediction algorithm at 97.5% specificity using random forest modeling. Subsequently, the locked algorithm derived from the training set was applied to an independent blinded test set of 50 early-stage PDAC cases and 50 controls. Finally, data from all 340 patients were combined, and cross-validated. Results: The cross-validated area under the receiver operating characteristic curve (AUC) for the training set was 0.93 (0.89–0.96) for the MDM panel alone, 0.91 (95% confidence interval, 0.87–0.96) for carbohydrate antigen 19-9 (CA19-9) alone, and 0.99 (0.98–1) for the combined MDM-CA19-9 panel. In the test set of early-stage PDAC, the AUC for MDMs alone was 0.84 (0.76–0.92), CA19-9 alone was 0.87 (0.79–0.94), and combined MDM-CA19-9 panel was 0.90 (0.84–0.97) significantly better compared with either MDMs alone or CA19-9 alone (P = 0.0382 and 0.0490, respectively). At a preset specificity of 97.5%, the sensitivity for the combined panel in the test set was 80% (28%–99%) for stage I disease and 82% (68%–92%) for stage II disease. Using the combined datasets, the cross-validated AUC was 0.9 (0.86–0.94) for the MDM panel alone and 0.89 for CA19-9 alone (0.84–0.93) versus 0.97 (0.94–0.99) for the combined MDM-CA19-9 panel (P ≤ 0.0001). Overall, cross-validated sensitivity of MDM-CA19-9 panel was 92% (83%–98%), with an observed specificity of 92% at the preset specificity of 97.5%. Conclusions: Plasma MDMs in combination with CA19-9 detect PDAC with significantly higher accuracy compared with either biomarker individually.

Abstract Purpose: We aimed to assess the concordance of colorectal cancer–associated methylated DNA markers (MDM) in primary and metastatic colorectal cancer for feasibility in detection of distantly recurrent/metastatic colorectal cancer in plasma. Experimental Design: A panel of previously discovered colorectal cancer–associated MDMs was selected. MDMs from primary and paired metastatic colorectal cancer tissue were assayed with quantitative methylation-specific PCR. Plasma MDMs were measured blindly by target enrichment long-probe quantitative-amplified signal assays. Random forest modeling was used to derive a prediction algorithm of MDMs in archival plasma samples from primary colorectal cancer cases. This algorithm was validated in prospectively collected plasma samples from recurrent colorectal cancer cases. The accuracy of the algorithm was summarized as sensitivity, specificity, and area under the curve (AUC). Results: Of the 14 selected MDMs, the concordance between primary and metastatic tissue was considered moderate or higher for 12 MDMs (86%). At a preset specificity of 95% (91%–98%), a panel of 13 MDMs, in plasma from 97 colorectal cancer cases and 200 controls, detected stage IV colorectal cancer with 100% (80%–100%) sensitivity and all stages of colorectal cancer with an AUC of 0.91 (0.87–0.95), significantly higher than carcinoembryonic antigen [AUC, 0.72 (0.65–0.79)]. This panel, in plasma from 40 cases and 60 healthy controls, detected recurrent/metastatic colorectal cancer with 90% (76%–97%) sensitivity, 90% (79%–96%) specificity, and an AUC of 0.96 (0.92–1.00). The panel was positive in 0.30 (0.19–0.43) of 60 patients with no evidence of disease in post-operative patients with colorectal cancer. Conclusions: Plasma assay of novel colorectal cancer–associated MDMs can reliably detect both primary colorectal cancer and distantly recurrent colorectal cancer with promising accuracy.

Abstract Background: Emerging colorectal cancer trends demonstrate increased incidence and mortality in younger populations, prompting consideration of average-risk colorectal cancer screening initiation at age 45 versus 50 years. However, screening test performance characteristics in adults 45–49 years have been minimally described. To inform the biologic rationale for multi-target stool DNA (mt-sDNA) screening in younger patients, we analyzed and compared tissue levels of methylation (BMP3, NDRG4) and mutation (KRAS) markers included in the FDA-approved, mt-sDNA assay (Cologuard; Exact Sciences Corporation). Methods: Within 40–44, 45–49, and 50–64 year age groups, archived colorectal tissue specimens were identified for 211 sporadic colorectal cancer cases, 123 advanced precancerous lesions (APLs; adenomas &gt;1 cm, high-grade dysplasia, ≥25% villous morphology, or sessile serrated polyp; 45–49 and 50–64 age groups only), and 204 histologically normal controls. Following DNA extraction, KRAS, BMP3, and NDRG4 were quantified using QuARTS assays, relative to ACTB (reference gene). Results: None of the molecular marker concentrations were significantly associated with age (P &gt; 0.05 for all comparisons), with the exception of NDRG4 concentration in APL samples (higher in older vs. younger cases; P = 0.008). However, NDRG4 levels were also statistically higher in APL case versus normal control samples in both the 45–49 (P &lt; 0.0001) and 50–64 (P &lt; 0.0001) year age groups. Conclusions: Overall, these findings support the potential for earlier onset of average-risk colorectal cancer screening with the mt-sDNA assay. Impact: These novel data address an identified knowledge gap and strengthen the biologic basis for earlier-onset, average-risk screening with the mt-sDNA assay.