Dataset Information

Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients With Pancreatic Ductal Adenocarcinoma.

ABSTRACT:

Objective

We performed genome-wide expression profiling to develop an exosomal miRNA panel for predicting recurrence following surgery in patients with PDAC.

Summary of background data

Pretreatment risk stratification is essential for offering individualized treatments to patients with PDAC, but predicting recurrence following surgery remains clinically challenging.

Methods

We analyzed 210 plasma and serum specimens from 4 cohorts of PDAC patients. Using a discovery cohort (n = 25), we performed genome-wide sequencing to identify candidate exosomal miRNAs (exo-miRNAs). Subsequently, we trained and validated the predictive performance of the exo-miRNAs in two clinical cohorts (training cohort: n = 82, validation cohort: n = 57) without neoadjuvant therapy (NAT), followed by a post-NAT clinical cohort (n = 46) as additional validation.

Results

We performed exo-miRNA expression profiling in plasma specimens obtained before any treatment in a discovery cohort. Subsequently we optimized and trained a 6-exo-miRNA risk-prediction model, which robustly discriminated patients with recurrence [area under the curve (AUC): 0.81, 95% confidence interval (CI): 0.70-0.89] and relapse-free survival (RFS, P < 0.01) in the training cohort. The identified exo-miRNA panel was successfully validated in an independent validation cohort (AUC: 0.78, 95% CI: 0.65- 0.88, RFS: P < 0.01), where it exhibited comparable performance in the post-NAT cohort (AUC: 0.72, 95% CI: 0.57-0.85, RFS: P < 0.01) and emerged as an independent predictor for RFS (hazard ratio: 2.84, 95% CI: 1.30-6.20).

Conclusions

We identified a novel, noninvasive exo-miRNA signature that robustly predicts recurrence following surgery in patients with PDAC; highlighting its potential clinical impact for optimized patient selection and improved individualized treatment strategies.

SUBMITTER: Nishiwada S

PROVIDER: S-EPMC8674379 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients With Pancreatic Ductal Adenocarcinoma.

Nishiwada Satoshi S Cui Ya Y Sho Masayuki M Jun Eunsung E Akahori Takahiro T Nakamura Kota K Sonohara Fuminori F Yamada Suguru S Fujii Tsutomu T Han In Woong IW Tsai Susan S Kodera Yasuhiro Y Park Joon Oh JO Von Hoff Daniel D Kim Song Cheol SC Li Wei W Goel Ajay A

Annals of surgery 20210616 6

<h4>Objective</h4>We performed genome-wide expression profiling to develop an exosomal miRNA panel for predicting recurrence following surgery in patients with PDAC.<h4>Summary of background data</h4>Pretreatment risk stratification is essential for offering individualized treatments to patients with PDAC, but predicting recurrence following surgery remains clinically challenging.<h4>Methods</h4>We analyzed 210 plasma and serum specimens from 4 cohorts of PDAC patients. Using a discovery cohort ...[more]

PMID: 34132691

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Project description:BackgroundOptimal patient selection for radiotherapy in pancreatic ductal adenocarcinoma (PDAC) is unestablished. Molecular profiling may select patients at high risk for locoregional recurrence (LRR) who would benefit from radiation.MethodsWe included resectable pancreatic cancer (R-PDAC) patients, divided into training and validation cohorts, treated among three institutions with surgery and adjuvant chemotherapy, and borderline resectable or locally advanced pancreatic cancer (BR/LA-PDAC) patients treated with chemotherapy with or without radiation at the primary study institution. We isolated RNA from R-PDAC surgical specimens. Using NanoString, we identified miRNAs differentially expressed between normal and malignant pancreatic tissue. ElasticNet regression identified two miRNAs most predictive of LRR in the training cohort, miR-181b/d and miR-575, which were used to generate a risk score (RS). We evaluated the association of the median-dichotomized RS with recurrence and overall survival (OS).ResultsWe identified 183 R-PDAC and 77 BR/LA-PDAC patients with median follow up of 37 months treated between 2001 and 2014. On multivariable analysis of the R-PDAC training cohort (n = 90), RS was associated with worse LRR (HR = 1.34; 95%CI 1.27-11.38; p = 0.017) and OS (HR = 2.89; 95%CI 1.10-4.76; p = 0.027). In the R-PDAC validation cohort, RS was associated with worse LRR (HR = 2.39; 95%CI 1.03-5.54; p = 0.042), but not OS (p = 0.087). For BR/LA-PDAC, RS was associated with worse LRR (HR = 2.71; 95%CI 1.14-6.48; p = 0.025), DR (HR = 1.93; 95%CI 1.10-3.38; p = 0.022), and OS (HR = 1.97; 95%CI 1.17-3.34; p = 0.011). Additionally, after stratifying by RS and receipt of radiation in BR/LA-PDAC patients, high RS patients who did not receive radiation had worse LRR (p = 0.018), DR (p = 0.006), and OS (p < 0.001) compared to patients with either low RS or patients who received radiation, irrespective of RS.ConclusionsRS predicted worse LRR and OS in R-PDAC and worse LRR, DR, and OS in BR/LA-PDAC. This may select patients who would benefit from radiation and should be validated prospectively.

Project description:Background & aimsPancreatic ductal adenocarcinomas (PDACs) frequently metastasize to the lymph nodes; strategies are needed to identify patients at highest risk for lymph node metastases. We performed genome-wide expression profile analyses of PDAC specimens, collected during surgery or endoscopic ultrasound-guided fine-need aspiration (EUS-FNA), to identify a microRNA (miRNA) signature associated with metastasis to lymph nodes.MethodsFor biomarker discovery, we analyzed miRNA expression profiles of primary pancreatic tumors from 3 public data sets (The Cancer Genome Atlas, GSE24279, and GSE32688). We then analyzed 157 PDAC specimens (83 from patients with lymph node metastases and 74 without) from Japan, collected from 2001 through 2017, for the training cohort and 107 PDAC specimens (63 from patients with lymph node metastases and 44 without) from a different medical center in Japan, from 2002 through 2016, for the validation cohort. We also analyzed samples collected by EUS-FNA before surgery from 47 patients (22 patients with lymph node metastases and 25 without; 17 for the training cohort and 30 from the validation cohort) and 62 specimens before any treatment from patients who received neoadjuvant chemotherapy (9 patients with lymph node metastasis and 53 without) for additional validation. Multivariate logistic regression analyses were used to evaluate the statistical differences in miRNA expression between patients with vs without metastases.ResultsWe identified an miRNA expression pattern associated with diagnosis of PDAC metastasis to lymph nodes. Using logistic regression analysis, we optimized and trained a 6-miRNA risk prediction model for the training cohort; this model discriminated patients with vs without lymph node metastases with an area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.77-0.89). In the validation cohort, the model identified patients with vs without lymph node metastases with an AUC of 0.73 (95% CI, 0.64-0.81). In EUS-FNA biopsy samples, the model identified patients with vs without lymph node metastases with an AUC of 0.78 (95% CI, 0.63-0.89). The miRNA expression pattern was an independent predictor of PDAC metastasis to lymph nodes in the validation cohort (odds ratio, 17.05; 95% CI, 2.43-119.57) and in the EUS-FNA cohort (95% CI, 0.65-0.87).ConclusionsUsing data and tumor samples from 3 independent cohorts, we identified an miRNA signature that identifies patients at risk for PDAC metastasis to lymph nodes. The signature has similar levels of accuracy in the analysis of resected tumor specimens and EUS-FNA biopsy specimens. This model might be used to select treatment and management strategies for patients with PDAC.

Project description:BackgroundThe diagnostic performance and prognostic value of serum exosomal glypican 1 (GPC-1) in pancreatic ductal adenocarcinoma (PDAC) remain controversial. In this study, we detected serum exosomal GPC-1 using enzyme-linked immunosorbent assay (ELISA) and determined whether it serves as a predictor of diagnosis and recurrence for early-stage PDAC.MethodsSerum samples were obtained from patients with 50 PDAC, 6 benign pancreatic tumor (BPT), or 9 chronic pancreatitis (CP) and 50 healthy controls (HCs). Serum exosomes were isolated using an exosome isolation kit. Exosomal and serum GPC-1 levels were measured using ELISA. The freeze-thaw process was carried out to analyze the stability of GPC-1. Receiver operating characteristic (ROC) analysis was employed to assess the diagnostic value of GPC-1. Kaplan-Meier and multivariate Cox analyses were used to evaluate the prognostic value of GPC-1.ResultsThe average concentrations of serum exosomal and serum GPC-1 were 1.5 and 0.8 ng/ml, respectively. GPC-1 expression levels were stable under repeated freezing and thawing (d1-5 freeze-thaw cycles vs. d0 P > 0.05). Serum exosomal and serum GPC-1 were significantly elevated in patients with PDAC compared with HCs (P < 0.0001) but were slightly higher compared with that in patients with CP and BPT (P > 0.05). The expression levels of exosomal and serum GPC-1 were elevated 5 days after surgery in patients with PDAC, CP, and BPT (P < 0.05). Patients with high levels of exosomal and serum GPC-1 had a shorter relapse-free survival (RFS) (P = 0.006, and P = 0.010). Multivariate analyses showed that serum exosomal and serum GPC-1 were independent prognostic indicators for early RFS (P = 0.008, and P = 0.041).ConclusionELISA is an effective and sensitive method to detect exosomal and serum GPC-1. The detection of GPC-1 was stable under repeated freezing and thawing cycles and could distinguish early-stage PDAC from HCs but not CP and BPT. Exosomal and serum GPC-1 may be good independent predictors of early recurrence in early-stage PDAC.

Dataset Information

Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients With Pancreatic Ductal Adenocarcinoma.

Objective

Summary of background data

Methods

Results

Conclusions

Publications

Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients With Pancreatic Ductal Adenocarcinoma.

Similar Datasets

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