作者
Kota Nakamura,Zhenzhen Zhu,Roy S,Eunsung Jun,Haiyong Han,Rubén M. Muñoz,Satoshi Nishiwada,Geeta G. Sharma,Derek Cridebring,Frédéric Zenhausern,Kim S,Denise J. Roe,Sourat Darabi,In Woong Han,Douglas B. Evans,Suguru Yamada,Michael J. Demeure,Carlos Becerra,Scott Celinski,Erkut Borazanci,Susan Tsai,Yasuhiro Kodera,Joon Oh Park,John S. Bolton,Xin Wang,Song Cheol Kim,Daniel D. Von Hoff,Ajay Goel
摘要
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.