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Candidate microRNA biomarkers of pancreatic ductal adenocarcinoma: meta-analysis, experimental validation and clinical significance.

ABSTRACT: BACKGROUND: The diagnostic and prognostic value of microRNA (miRNA) expression aberrations in pancreatic ductal adenocarcinoma (PDAC) has been studied extensively in recent years. However, differences in measurement platforms and lab protocols as well as small sample sizes can render gene expression levels incomparable. METHODS: A comprehensive meta-review of published studies in PDAC that compared the miRNA expression profiles of PDAC tissues and paired neighbouring noncancerous pancreatic tissues was performed to determine candidate miRNA biomarkers for PDAC. Both a miRNA vote-counting strategy and a recently published Robust Rank Aggregation method were employed. In this review, a total of 538 tumour and 206 noncancerous control samples were included. RESULTS: We identified a statistically significant miRNA meta-signature of seven up- and three down-regulated miRNAs. The experimental validation results showed that the miRNA expression levels were in accordance with the meta-signature. The results from the vote-counting strategy were consistent with those from the Robust Rank Aggregation method. The experimental validation confirmed that the statistically unique profiles identified by the meta-review approach could discriminate PDAC tissues from paired nonmalignant pancreatic tissues. In a cohort of 70 patients, the high expression of miR-21 (p=0.018, HR=2.610; 95% CI=1.179-5.777) and miR-31 (p=0.039, HR=2.735; 95% CI=1.317-6.426), the low expression of miR-375 (p=0.022, HR=2.337; 95% CI=1.431-5.066) were associated with poor overall survival following resection, independent of clinical covariates. CONCLUSIONS: The identified miRNAs may be used to develop a panel of diagnostic and prognostic biomarkers for PDAC with sufficient sensitivity and specificity for use in a clinical setting.

SUBMITTER: Ma MZ

PROVIDER: S-EPMC4176285 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Candidate microRNA biomarkers of pancreatic ductal adenocarcinoma: meta-analysis, experimental validation and clinical significance.

Ma Ming-Zhe MZ Kong Xiang X Weng Ming-Zhe MZ Cheng Kun K Gong Wei W Quan Zhi-Wei ZW Peng Cheng-Hong CH

Journal of experimental & clinical cancer research : CR 20130928

<h4>Background</h4>The diagnostic and prognostic value of microRNA (miRNA) expression aberrations in pancreatic ductal adenocarcinoma (PDAC) has been studied extensively in recent years. However, differences in measurement platforms and lab protocols as well as small sample sizes can render gene expression levels incomparable.<h4>Methods</h4>A comprehensive meta-review of published studies in PDAC that compared the miRNA expression profiles of PDAC tissues and paired neighbouring noncancerous pa ...[more]

PMID: 24289824

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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.

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Candidate microRNA biomarkers of pancreatic ductal adenocarcinoma: meta-analysis, experimental validation and clinical significance.

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Candidate microRNA biomarkers of pancreatic ductal adenocarcinoma: meta-analysis, experimental validation and clinical significance.

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