High Detection Rates of Pancreatic Cancer Across Stages by Plasma Assay of Novel Methylated DNA Markers and CA19-9

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.

Figure 1:

Marker selection algorithm for identifying best candidate plasma MDMs from tissue RRBS libraries and subsequent plasma assay optimization steps prior to training and testing in case-control study.

Figure 2:

A) Receiver operating curves for CA 19–9, MDM panel and combination of both in the training set of advanced stage PDAC (n=120) B) Receiver operating curves for CA 19–9, MDM panel and combination of both in the test set of early stage PDAC (n=50) C) Cross validated AUC demonstrating that the MDM-CA19–9 combination significantly enhances PDAC detection accuracy compared to either marker component alone D) Sensitivity of MDM-CA 19–9 combination across different PDAC stages at 92% specificity.

Figure 3:

Box plot of the predicted probability of cancer from the cross-validated MDMs + CA 19–9 rForest model demonstrating no significant differences in model performance based on A) Tumor size, B) Tumor location, C) Presence of symptoms at the time of diagnosis, D) Timing of biopsy in relationship to blood draw. The Gray shaded area indicates probability values exceeding the 92nd percentile in controls with group sizes indicated above each box plot.

Figure 4:

Distributions in plasma from controls and PDAC patients by stage of disease of CA 19–9 values and standardized copy numbers of selected MDMs, HOXA1 and PRKCB.