Cell-Free DNA Methylation as Blood-Based Biomarkers for Pancreatic Adenocarcinoma—A Literature Update

Pancreatic adenocarcinoma has a horrible prognosis, which is partly due to difficulties in diagnosing the disease in an early stage. Additional blood-born biomarkers for pancreatic adenocarcinoma are needed. Epigenetic modifications, as changes in DNA methylation, is a fundamental part of carcinogenesis. The aim of this paper is to do an update on cell-free DNA methylation as blood-based biomarkers for pancreatic adenocarcinoma. The current literature including our studies clearly indicates that cell-free DNA methylation has the potential as blood-based diagnostic and prognostic biomarkers for pancreatic adenocarcinoma. However, still no clinical applicable biomarker for pancreatic adenocarcinoma based on DNA methylation do exist. Further well-designed validation studies are needed

Prediction of pancreatic cancer risk in patients with new-onset diabetes using a machine learning approach based on routine biochemical parameters; Prediction of Pancreatic Cancer Risk in New Onset Diabetes

ObjectiveTo develop a machine-learning model that can predict the risk of pancreatic ductal adenocarcinoma (PDAC) in people with new-onset diabetes (NOD).MethodsFrom a population-based sample of individuals with NOD aged >50 years, patients with pancreatic cancer-related diabetes (PCRD), defined as NOD followed by a PDAC diagnosis within 3 years, were included (n = 716). These PCRD patients were randomly matched in a 1:1 ratio with individuals having NOD. Data from Danish national health registries were used to develop a random forest model to distinguish PCRD from Type 2 diabetes. The model was based on age, gender, and parameters derived from feature engineering on trajectories of routine biochemical variables. Model performance was evaluated using receiver operating characteristic curves (ROC) and relative risk scores.ResultsThe most discriminative model included 20 features and achieved a ROC-AUC of 0.78 (CI:0.75–0.83). Compared to the general NOD population, the relative risk for PCRD was 20-fold increase for the 1 % of patients predicted by the model to have the highest cancer risk (3-year cancer risk of 12 % and sensitivity of 20 %). Age was the most discriminative single feature, followed by the rate of change in haemoglobin A1c and the latest plasma triglyceride level. When the prediction model was restricted to patients with PDAC diagnosed six months after diabetes diagnosis, the ROC-AUC was 0.74 (CI:0.69–0.79).ConclusionIn a population-based setting, a machine-learning model utilising information on age, sex and trajectories of routine biochemical variables demonstrated good discriminative ability between PCRD and Type 2 diabetes

Validation of SFRP1 Promoter Hypermethylation in Plasma as a Prognostic Marker for Survival and Gemcitabine Effectiveness in Patients with Stage IV Pancreatic Adenocarcinoma

SIMPLE SUMMARY: Pancreatic adenocarcinoma (PDAC) is a disease with an incredibly grim prognosis. Most patients die within one year of receiving the diagnosis. There are currently very few tools to help the clinician decide between treatment options and evaluate prognosis at an individual level. The aim of the current study was to assess the effect of promoter hypermethylation of secreted frizzled-related protein 1 (phSFRP1) as an independent prognostic blood-based biomarker in gemcitabine-treated patients with advanced PDAC. The study was conducted as a combined discovery and validation study. Analysis in both cohorts confirmed that patients with phSFRP1 had overall poorer survival compared to those without hypermethylation. Thus, phSFRP1 shows promise as an independent prognostic biomarker in this patient group and can hopefully aid the clinician and patient find the correct balance between quantity and quality of life. ABSTRACT: No reliable predictive blood-based biomarkers are available for determining survival from pancreatic adenocarcinoma (PDAC). This combined discovery and validation study examines promoter hypermethylation (ph) of secreted frizzled-related protein 1 (SFRP1) in plasma-derived cell-free DNA as an independent prognostic marker for survival and Gemcitabine effectiveness in patients with stage IV PDAC. We conducted methylation-specific polymerase chain reaction analysis of the promoter region of the SFRP1 gene, based on bisulfite treatment. Survival was analyzed with Kaplan–Meier curves, log-rank test, and Cox regression. The discovery cohort included 40 patients, 25 receiving Gem. Gem-treated patients with phSFRP1 had a shorter median overall survival (mOS) (4.4 months) than unmethylated patients (11.6 months). Adjusted Cox-regression yielded a hazard rate (HR) of 3.48 (1.39–8.70). The validation cohort included 58 Gem-treated patients. Patients with phSFRP1 had a shorter mOS (3.2 months) than unmethylated patients (6.3 months). Adjusted Cox regression yielded an HR of 3.53 (1.85–6.74). In both cohorts, phSFRP1 was associated with poorer survival in Gem-treated patients. This may indicate that tumors with phSFRP1 are more aggressive and less sensitive to Gem treatment. This knowledge may facilitate tailored treatment of patients with stage IV PDAC. Further studies are planned to examine phSFRP1 in more intensive chemotherapy regimens