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MicroRNAs in stool samples as potential screening biomarkers for pancreatic ductal adenocarcinoma cancer.

ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) accounts for approximately 90-95% exocrine malignant tumors of the pancreas. The high prevalence of metastasis and the difficulty of early diagnosis lead to a dismal prognosis. MicroRNAs (miRNAs) play a critical role in extensive biological processes. The purpose of this study was to evaluate the feasibility of stool miRNAs as novel biomarker for PDAC screening. MiRNAs were extracted from clinical specimens which included cancer and matched adjacent benign pancreatic tissues of 30 PDAC patients, pancreatic juice of 20 from the 30 PDAC patients and 10 chronic pancreatitis (CP) patients, stool samples of the 30 PDAC patients, the 10 CP patients and 15 healthy volunteers. Relative expression of a panel of 5 dysregulated miRNAs (miR-21, miR-155, miR-196a, miR-216 and miR-217) was analyzed with qRT-PCR. Receiver operating characteristic curve (ROC) analysis was performed to assess the diagnosing value of stool miRNAs in PDAC patients. The study showed that our methods of extracting and detecting miRNAs from pancreatic juice and stool specimens had high reproducibility. Compared to matched adjacent benign pancreatic tissues and pancreatic juice of CP patients, the expression of miR-21 (P = 0.0021 and P = 0.0027) as well as miR-155 (P = 0.0087 and P = 0.0067) was significantly higher and the expression of miR-216 (P < 0.0001 and P = 0.0044) was significantly lower in primary tumor tissues and pancreatic juice of PDAC patients. PDAC patients had a significantly higher stool miR-21 and miR-155 (P = 0.0049 and P = 0.0112) and lower miR-216 level (P = 0.0002) compared to normal controls. The same results were obtained in the expression levels of stool miR-21, miR-155 and miR-216 between PDAC and CP patients (P = 0.0337, P = 0.0388 and P = 0.0117, respectively). Receiver operating characteristic (ROC) analysis by using stool miRNAs expression indicated that combination of miR-21 and miR-155 had best sensitivity of 93.33% while the combination of miR-21, miR-155 and miR-216 would be best for detecting and screening PDAC with area under the curve (AUC) of 0.8667 (95% CI: 0.7722-0.9612) and a better balance of sensitivity and specificity (83.33% vs. 83.33%). Our data indicate that miRNAs could be extracted and detected from pancreatic juice and stool efficiently and reproducibly. MiR-21, miR-155 and miR-216 in stool have the potential of becoming biomarkers for screening PDAC.

SUBMITTER: Yang JY

PROVIDER: S-EPMC4266702 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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MicroRNAs in stool samples as potential screening biomarkers for pancreatic ductal adenocarcinoma cancer.

Yang Jian-Yu JY Sun Yong-Wei YW Liu De-Jun DJ Zhang Jun-Feng JF Li Jiao J Hua Rong R

American journal of cancer research 20141119 6

Pancreatic ductal adenocarcinoma (PDAC) accounts for approximately 90-95% exocrine malignant tumors of the pancreas. The high prevalence of metastasis and the difficulty of early diagnosis lead to a dismal prognosis. MicroRNAs (miRNAs) play a critical role in extensive biological processes. The purpose of this study was to evaluate the feasibility of stool miRNAs as novel biomarker for PDAC screening. MiRNAs were extracted from clinical specimens which included cancer and matched adjacent benign ...[more]

PMID: 25520858

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Project description:Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal common cancer because of late diagnosis. Novel biomarkers for PDAC early detection are urgently needed. tRNA-derived small RNAs (tsRNAs) are novel small RNAs might serve as biomarkers for cancer diagnosis and participate in diverse physiological and pathological process. We investigated whether the expression of tsRNAs in serum could be a noninvasive method in the early detection of PDAC. Blood sample of PDAC patients and healthy controls were collected from Ruijin Hospital, Shanghai, China. Tumor and adjacent normal pancreas tissues were collected from 51 patients with PDAC undergoing therapeutic surgery. The testing cohort comprised 6 PDAC patients and 6 healthy controls and the expression of small RNAs in serum was analyzed by small RNA sequence. We verified the diagnostic performance of serum tsRNAs by qPCR in validation cohort including 110 PDAC patients and 100 healthy controls. Expression level of tsRNAs in tissue was also verified in another independent cohort including 51 tumor and 51 adjacent normal pancreas tissues. Unpaired t-test and paired t-test are used for comparing depending on whether the samples are paired. The predictive performance of tsRNAs was evaluated by Kaplan-Meier survival and receiver operating characteristic (ROC) curve. There were 45 tsRNAs expressed at remarkably higher levels, 6 tsRNAs expressed at lower levels in PDAC patients, respectively, compared with healthy volunteers. tsRNA-ValTAC-41, tsRNA-MetCAT-37 and tsRNA-ThrTGT-23 expressed significant highly (P < 0.05) in serum of PDAC patients in validation cohort. tsRNA-ValTAC-41 or tsRNA-MetCAT-37 combined with CA19-9 could increase the AUC of PDAC prediction (AUC = 0.947 and 0.949 respectively), relative to CA19-9 test alone. Besides, patients with higher serum tsRNA-ValTAC-41 level showed shorter overall survival (OS). tsRNA-ValTAC-41 also expressed at remarkably higher level in tumor tissue, and it was obviously associated with tumor staging both in serum and tissue. We provide tsRNAs profiles observed by small RNA sequencing. The diagnostic accuracy of tsRNA-ValTAC-41 and tsRNA-MetCAT-37 in serum of PDAC patients were verified. Further studies for tsRNA-ValTAC-41 are needed to confirm the findings. These tsRNAs may be promising and effective candidates in the development of highly sensitive, noninvasive biomarkers for PDAC diagnosis.

Project description:Background: Pancreatic ductal adenocarcinoma (PDAC) leads to the majority of cancer-related deaths due to its morbidity with similar mortality. Lack of effective prognostic biomarkers are the main reason for belated post-operative intervention of recurrence which causes high mortality. Numerous systematic reviews and meta-analyses have explored the prognostic value of biomarkers in PDAC so far. In this article, we performed an umbrella review analyzing these studies to provide an overview of associations between prognostic biomarkers and PDAC survival outcome and synthesized these results to guide better clinical practice. Methods: Systematic reviews and meta-analyses investigating the associations between PDAC survival outcomes and prognostic biomarkers were acquired via the PubMed and Embase databases from inception till February 1, 2020. Associations supported by nominally statistically significant results were classified into strong, highly suggestive, suggestive, and weak based on several critical factors such as the statistical significance of summary estimates, the number of events, the estimate of the largest study included, interstudy heterogeneity, small-study effects, 95% predictive interval (PI), excess significance bias, and the results of credibility ceiling sensitivity analyses. Results: We included 41 meta-analyses containing 63 associations between PDAC survival outcomes and prognostic biomarkers. Although, none was supported by strong evidence among these associations, an association between C-reactive protein to albumin ratio (CAR) and PDAC overall survival (OS) and an association between neutrophil-lymphocyte ratio (NLR) and PDAC OS were supported by highly suggestive evidence. Otherwise, the association between lactate dehydrogenase (LDH) and PDAC OS was supported by suggestive evidence. The remaining 60 associations were supported by weak or not suggestive evidence. Conclusion: Associations between CAR or NLR and PDAC OS were supported by highly suggestive evidence. And the association between LDH and PDAC OS was supported by suggestive evidence. Although the methodological quality of the included systematic reviews and meta-analyses which were evaluated by AMSTAR2.0 is generally poor, the identification of the relatively robust prognostic biomarkers of PDAC may guide better post-operative intervention and follow-up to prolong patients' survival.

Project description:Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

Dataset Information

MicroRNAs in stool samples as potential screening biomarkers for pancreatic ductal adenocarcinoma cancer.

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MicroRNAs in stool samples as potential screening biomarkers for pancreatic ductal adenocarcinoma cancer.

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