Wiring miRNAs to pathways: a topological approach to integrate miRNA and mRNA expression profiles

Calura, Enrica; Martini, Paolo; Sales, Gabriele; Beltrame, Luca; Chiorino, Giovanna; D’Incalci, Maurizio; Marchini, Sergio; Romualdi, Chiara

doi:10.1093/nar/gku354

Cited by 37 publications

(41 citation statements)

References 45 publications

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“…We show that the proposed approach is able to identify the pathways that describe the underlying diseases as significant. The p-values and rankings of these pathways are significantly smaller than those obtained without data integration as well as when using microGraphite 8 .…”

Section: Introductionmentioning

confidence: 62%

“…First, we perform pathway analysis of 9 mRNA/miRNA sample-matched datasets using two different methods (Impact Analysis and ORA) and show that mirAP offers a significant improvement over analyzing mRNA data alone. We also compare the obtained results with the state-of-the-art method (microGraphite) 8 . Second, we perform disease subtyping of a colorectal cancer dataset from TCGA using our subtyping pipeline and compare with the traditional pipeline for subtyping.…”

Section: Resultsmentioning

confidence: 99%

“…We also analyze the nine GEO datasets using microGraphite 8 after quantile normalization to compare with our pipeline. The main goal of microGraphite is the identification of signal transduction paths correlated with the condition under study.…”

Section: Resultsmentioning

confidence: 99%

“…Relevant work has been done to elucidate the important interplay between miRNAs and biological pathways 5–9 . The state-of-the-art approach for miRNA-mRNA pathway analysis is microGraphite 8 which uses an empirical gene set approach. microGraphite’s main goal is the identification of signal transduction paths correlated with the condition under study 10 .…”

Section: Introductionmentioning

confidence: 99%

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MICRORNA-AUGMENTED PATHWAYS (mirAP) AND THEIR APPLICATIONS TO PATHWAY ANALYSIS AND DISEASE SUBTYPING

et al. 2016

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MicroRNAs play important roles in the development of many complex diseases. Because of their importance, the analysis of signaling pathways including miRNA interactions holds the potential for unveiling the mechanisms underlying such diseases. However, current signaling pathway databases are limited to interactions between genes and ignore miRNAs. Here, we use the information on miRNA targets to build a database of miRNA-augmented pathways (mirAP), and we show its application in the contexts of integrative pathway analysis and disease subtyping. Our miRNA-mRNA integrative pathway analysis pipeline incorporates a topology-aware approach that we previously implemented. Our integrative disease subtyping pipeline takes into account survival data, gene and miRNA expression, and knowledge of the interactions among genes. We demonstrate the advantages of our approach by analyzing nine sample-matched datasets that provide both miRNA and mRNA expression. We show that integrating miRNAs into pathway analysis results in greater statistical power, and provides a more comprehensive view of the underlying phenomena. We also compare our disease subtyping method with the state-of-the-art integrative analysis by analyzing a colorectal cancer database from TCGA. The colorectal cancer subtypes identified by our approach are significantly different in terms of their survival expectation. These miRNA-augmented pathways offer a more comprehensive view and a deeper understanding of biological pathways. A better understanding of the molecular processes associated with patients’ survival can help to a better prognosis and an appropriate treatment for each subtype.

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Section: Introductionmentioning

confidence: 62%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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MICRORNA-AUGMENTED PATHWAYS (mirAP) AND THEIR APPLICATIONS TO PATHWAY ANALYSIS AND DISEASE SUBTYPING

et al. 2016

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“…mRNA and miRNA relations involved in PMF were compared to CTR PB or CTR BM and have been identified using the Micrographite pathway analysis. 31 In the following we will report a brief description of the main steps of the method; for details refers to Calura et al 31 …”

Section: Methodsmentioning

confidence: 99%

A data-driven network model of primary myelofibrosis: transcriptional and post-transcriptional alterations in CD34+ cells

Calura

Pizzini

Bisognin

et al. 2016

Blood Cancer Journal

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microRNAs (miRNAs) are relevant in the pathogenesis of primary myelofibrosis (PMF) but our understanding is limited to specific target genes and the overall systemic scenario islacking. By both knowledge-based and ab initio approaches for comparative analysis of CD34+ cells of PMF patients and healthy controls, we identified the deregulated pathways involving miRNAs and genes and new transcriptional and post-transcriptional regulatory circuits in PMF cells. These converge in a unique and integrated cellular process, in which the role of specific miRNAs is to wire, co-regulate and allow a fine crosstalk between the involved processes. The PMF pathway includes Akt signaling, linked to Rho GTPases, CDC42, PLD2, PTEN crosstalk with the hypoxia response and Calcium-linked cellular processes connected to cyclic AMP signaling. Nested on the depicted transcriptional scenario, predicted circuits are reported, opening new hypotheses. Links between miRNAs (miR-106a-5p, miR-20b-5p, miR-20a-5p, miR-17-5p, miR-19b-3p and let-7d-5p) and key transcription factors (MYCN, ATF, CEBPA, REL, IRF and FOXJ2) and their common target genes tantalizingly suggest new path to approach the disease. The study provides a global overview of transcriptional and post-transcriptional deregulations in PMF, and, unifying consolidated and predicted data, could be helpful to identify new combinatorial therapeutic strategy. Interactive PMF network model: http://compgen.bio.unipd.it/pmf-net/.

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Topologically inferring active miRNA‐mediated subpathways toward precise cancer classification by directed random walk

et al. 2019

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Accurate predictions of classification biomarkers and disease status are indispensable for clinical cancer diagnosis and research. However, the robustness of conventional gene biomarkers is limited by issues with reproducibility across different measurement platforms and cohorts of patients. In this study, we collected 4775 samples from 12 different cancer datasets, which contained 4636 TCGA samples and 139 GEO samples. A new method was developed to detect miRNA‐mediated subpathway activities by using directed random walk (miDRW). To calculate the activity of each miRNA‐mediated subpathway, we constructed a global directed pathway network (GDPN) with genes as nodes. We then identified miRNAs with expression levels which were strongly inversely correlated with differentially expressed target genes in the GDPN. Finally, each miRNA‐mediated subpathway activity was integrated with the topological information, differential levels of miRNAs and genes, expression levels of genes, and target relationships between miRNAs and genes. The results showed that the proposed method yielded a more robust and accurate overall performance compared with other existing pathway‐based, miRNA‐based, and gene‐based classification methods. The high‐frequency miRNA‐mediated subpathways are more reliable in classifying samples and for selecting therapeutic strategies.

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Wiring miRNAs to pathways: a topological approach to integrate miRNA and mRNA expression profiles

Cited by 37 publications

References 45 publications

MICRORNA-AUGMENTED PATHWAYS (mirAP) AND THEIR APPLICATIONS TO PATHWAY ANALYSIS AND DISEASE SUBTYPING

MICRORNA-AUGMENTED PATHWAYS (mirAP) AND THEIR APPLICATIONS TO PATHWAY ANALYSIS AND DISEASE SUBTYPING

A data-driven network model of primary myelofibrosis: transcriptional and post-transcriptional alterations in CD34+ cells

Topologically inferring active miRNA‐mediated subpathways toward precise cancer classification by directed random walk

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