Karen A. Doering

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.

Supplemental Figure 2: Distributions of all methylated DNA markers tested for endometrial cancers and controls, stratified by Lynch syndrome. Log10 strand counts are adjusted based on the level of the control gene, ACTB, in all controls (SPOR-EC-CTRL and LS-EC-CTRL). P-value provided to show statistical significance of difference of medians between CASE and CTRL samples within SPOR and LS subgroups.

Supplemental Figure 1: Distributions of all methylated DNA markers tested for colorectal cancers and controls, stratified by Lynch syndrome. Log10 strand counts are adjusted based on the level of the control gene, ACTB, in all controls (SPOR-CRC-CTRL and LS-CRC-CTRL). P-value provided to show statistical significance of difference of medians between CASE and CTRL samples within SPOR and LS subgroups.

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.

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.

Regular screening for colorectal cancer (CRC) is critical for early detection and long-term survival. Despite the current screening options available and advancements in therapies there will be around 53,000 CRC related deaths this year. There is great interest in non-invasive alternatives such as plasma cell-free RNA (cfRNA) for diagnostic, prognostic, and predictive applications. In the current study, our aim was to identify and validate potential cfRNA candidates to improve early CRC diagnosis. In phase 1 (n = 49; 25 controls, 24 cancers), discovery total RNA sequencing was performed. Select exons underwent validation in phase 2 (n = 73; 35 controls, 29 cancers, 9 adenomas) using targeted capture sequencing (n = 10,371 probes). In phase 3 (n = 57; 30 controls, 27 cancers), RT-qPCR was performed on previously identified candidates (n = 99). There were 895 exons that were differentially expressed (325 upregulated, 570 downregulated) among cancers versus controls. In phases 2 and 3, fewer markers were validated than expected in independent sets of patients, most of which were from previously published literature (FGA, FGB, GPR107, CDH3, and RP23AP7). In summary, we optimized laboratory processes and data analysis strategies which can serve as methodological framework for future plasma RNA studies beyond just the scope of CRC detection. Additionally, further exploration is needed in order to determine if the few cfRNA candidates identified in this study have clinical utility for early CRC detection. Over time, advancements in technologies, data analysis, and RNA preservation methods at time of collection may improve the biological and technical reproducibility of cfRNA biomarkers and enhance the feasibility of RNA-based liquid biopsies.

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.

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.

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.