Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer

Abstract

Purpose: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival of < 10% because of diffuse symptoms leading to late-stage diagnosis. That survival could increase significantly if localized tumors could be detected early. Therefore, we used multiparametric analysis of blood samples to obtain a novel biomarker signature of early-stage PDAC. The signature was derived from a large patient cohort, including patients with well-defined early-stage (I and II) PDAC. This biomarker signature was validated subsequently in an independent patient cohort.

Patients and methods: The biomarker signature was derived from a case-control study, using a Scandinavian cohort, consisting of 16 patients with stage I, 132 patients with stage II, 65 patients with stage III, and 230 patients with stage IV PDAC, and 888 controls. This signature was validated subsequently in an independent case-control cohort in the United States with 15 patients with stage I, 75 patients with stage II, 15 patients with stage III, and 38 patients with stage IV PDAC, and 219 controls. An antibody microarray platform was used to identify the serum biomarker signature associated with early-stage PDAC.

Results: Using the Scandinavian case-control study, a biomarker signature was created, discriminating samples derived from patients with stage I and II from those from controls with a receiver operating characteristic area under the curve value of 0.96. This signature, consisting of 29 biomarkers, was then validated in an independent case-control study in the United States. The biomarker signature could discriminate patients with stage I and II PDAC from controls in this independent patient cohort with a receiver operating characteristic area under the curve value of 0.96.

Conclusion: This serum biomarker signature might represent a tenable approach to detecting early-stage, localized PDAC if these findings are supported by a prospective validation study.

Trial registration: ClinicalTrials.gov NCT03311776.

Figures

Fig 1.

Classification of individual pancreatic ductal carcinoma stages in the Scandinavian cohort. All 349 antibodies were used to distinguish controls from patient samples of different pancreatic ductal adenocarcinoma (PDAC) stages, using support vector machine leave-one-out cross validation. The results are presented with receiver operating characteristic curves and their corresponding area under the curve (AUC) values for normal control (NC) v (A) stage I, (B) stage II, (C) stage III, and (D) stage IV PDAC.

Fig 2.

Classification of pancreatic ductal carcinoma stages in the Scandinavian cohort, using biomarker signatures. Using data from the Scandinavian study, predictive models that were based on frozen support vector machine were built. Two biomarker signatures were defined, using the backward elimination algorithm, for classification of (A) normal control (NC) samples from pancreatic ductal adenocarcinoma (PDAC) stage I and II, and (B) PDAC stage III and IV, respectively. The results are presented as receiver operating characteristic curves and their corresponding area under the curve (AUC) values.

Fig 3.

Validation of the consensus signature in stage I and II pancreatic ductal carcinoma from the United States cohort. The consensus signature generated from the Scandinavian cohort was validated in the independent cohort in the United States by classifying (A) normal controls (NC) v patients with pancreatic ductal adenocarcinoma (PDAC) stage I and II, and (B) patients with PDAC stage I and II v patients with chronic pancreatitis (CP). The results are presented as representative receiver operating characteristic curves and their corresponding area under the curve (AUC) values.

Fig 4.

Serum markers that are differentially expressed between different pancreatic ductal adenocarcinoma (PDAC) stages. Serum markers that were differentially expressed over progression from stage I to IV were identified by multigroup analysis of variance. Presented are the most significant markers. Roman numerals indicate PDAC stage. IL-2, interleukin-2; MAGI-1, membrane-associated guanylate kinase; PRDM8, PR domain zinc finger protein 8. *P < .05, q > 0.05; **P < .05, q < 0.05.

Fig A1.

Influence of diabetes on normal controls (NC) v pancreatic ductal adenocarcinoma (PDAC) classification accuracy. Decision values from a support vector machine model that had been trained on NC v PDAC were used to analyze differences between diabetic and nondiabetic PDAC samples in the discovery cohort. Significance values were calculated using the Wilcoxon signed-rank test. NOD, new-onset diabetes.

Fig A2.

Classification of intraductal papillary mucinous neoplasm (IPMN) stages from normal control (NC) samples. The consensus signature was used to classify NC v the different IPMN stages. All IPMN samples from the United States cohort were fed into a support vector machine model that had been trained on NC v pancreatic ductal adenocarcinoma (PDAC). Significance values were calculated using the Wilcoxon signed-rank test and were adjusted for multiple testing by the Benjamini-Hochberg procedure (false discovery rate, 0.05). The generated P values were as follows: NC v PDAC: 6.69 × 10−18; PDAC v benign and borderline IPMN: 0.034; PDAC v malignant IPMN: 0.401.