An Exosome-based Transcriptomic Signature for Noninvasive, Early Detection of Patients With Pancreatic Ductal Adenocarcinoma: A Multicenter Cohort Study

Abstract

Background & aims: Pancreatic ductal adenocarcinoma (PDAC) incidence is rising worldwide, and most patients present with an unresectable disease at initial diagnosis. Measurement of carbohydrate antigen 19-9 (CA19-9) levels lacks adequate sensitivity and specificity for early detection; hence, there is an unmet need to develop alternate molecular diagnostic biomarkers for PDAC. Emerging evidence suggests that tumor-derived exosomal cargo, particularly micro RNAs (miRNAs), offer an attractive platform for the development of cancer-specific biomarkers. Herein, genomewide profiling in blood specimens was performed to develop an exosome-based transcriptomic signature for noninvasive and early detection of PDAC.

Methods: Small RNA sequencing was undertaken in a cohort of 44 patients with an early-stage PDAC and 57 nondisease controls. Using machine-learning algorithms, a panel of cell-free (cf) and exosomal (exo) miRNAs were prioritized that discriminated patients with PDAC from control subjects. Subsequently, the performance of the biomarkers was trained and validated in independent cohorts (n = 191) using quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays.

Results: The sequencing analysis initially identified a panel of 30 overexpressed miRNAs in PDAC. Subsequently using qRT-PCR assays, the panel was reduced to 13 markers (5 cf- and 8 exo-miRNAs), which successfully identified patients with all stages of PDAC (area under the curve [AUC] = 0.98 training cohort; AUC = 0.93 validation cohort); but more importantly, was equally robust for the identification of early-stage PDAC (stages I and II; AUC = 0.93). Furthermore, this transcriptomic signature successfully identified CA19-9 negative cases (<37 U/mL; AUC = 0.96), when analyzed in combination with CA19-9 levels, significantly improved the overall diagnostic accuracy (AUC = 0.99 vs AUC = 0.86 for CA19-9 alone).

Conclusions: In this study, an exosome-based liquid biopsy signature for the noninvasive and robust detection of patients with PDAC was developed.

Keywords: Diagnostic Biomarker; Exosome; Liquid Biopsy; Pancreatic Cancer; miRNA Signature.

Figure 1.

Expression level of identified cell-free and exosomal miRNA candidates for the diagnosis of patients with early-stages of PDAC obtained from genome-wide small RNA sequencing. (A) Expression level of candidate cf-miRNAs and representative heatmap in patients with early-stage of PDAC (Stage I-II) versus non-disease control samples. (B) Expression level of candidate exo-miRNAs and representative heatmap in patients with PDAC (Stage I-II) versus non-disease control samples. The miRNA expression profile was z-normalized. [miRNA: micro RNA; CPM: counts per million; FC: fold change; PDAC: pancreatic ductal adenocarcinoma (light blue) and Non-disease controls (dark blue)].

Figure 2.

Performance evaluation of cell-free and exosomal miRNA biomarker panel in clinical cohorts by qRT-PCR. Representative heatmap of statistically significant and upregulated candidate (A) cf-miRNAs and (B) exo-miRNAs in patients with PDAC versus non-disease controls. (C) ROC curves analysis for the cf-miRNA, exo-miRNA or cf- and exocombination panel in the training cohort. (D) ROC curves analysis for the cf-miRNA, exo-miRNA and cf and exosomal combination panels in the validation cohort. [Exo: exosomal; miRNA: micro RNA; qRT-PCR: Quantitative Reverse transcription polymerase chain reaction; cf: cell-free; AUC: Area under the curve; ROC: receiver operating characteristic]

Figure 3.

Prioritization and performance evaluation of cell-free and exosomal miRNA biomarker panel in clinical cohorts. (A) ROC curve analysis for the cf-miRNA, exo-miRNA or cf and exosomal combination panel in the training cohort. (B) ROC curve analysis for the cf-miRNA, exo-miRNA or cf and exosomal combination panels in the validation cohort (C) ROC curve analysis to identify early-stages (stage I and II) and late stages (stage III and IV) PDAC patients from non-disease controls in validation cohort. (D) Risk score analysis in all stages PDAC patients and non-disease controls in the validation cohort. ROC curves are shown with 95% CIs. [*p< 0.001, Exo: exosomal; miRNA: micro RNA; cf: cell-free; AUC: Area under the curve; TNM: tumor-node-metastasis; PDAC: pancreatic ductal adenocarcinoma; ROC: receiver operating characteristic]

Figure 4.

Performance evaluation of the miRNA signature in combination with CA19-9, and diagnostic potential evaluation by decision curve analysis and calibration curve analysis. (A) ROC analysis to compare diagnostic performances between cf and exosomal combination miRNA signature and CA19-9 in all stages of PDAC patients. (B) ROC analysis to compare diagnostic performance between cf and exosomal combination miRNA signature and CA19-9 in early-stages (Stage I and II) of PDAC patients. (C) Performance of cf and exosomal combination miRNA signature in the cohort of 81 participant (22 PDAC and 59 non-disease controls) who presented with al CA19-9 level less than 37 U/mL. (D) Decision curve analysis and (E) Calibration curve analysis to evaluate the performance of the combined miRNA biomarker panel. ROC curves are shown with 95% CIs. [miRNA: micro RNA; CA19-9: carbohydrate antigen 19-9; AUC: Area under the curve; Exo: exosomal; cf: cell-free; ROC: receiver operating characteristic; PDAC: pancreatic ductal adenocarcinoma]