MicroRNAs (miRNAs) are small molecules that play an essential role in regulating gene expression by post-transcriptional gene silencing. Their study is crucial in revealing the fundamental processes underlying pathologies and, in particular, cancer. To date, most studies on miRNA regulation consider the effect of specific miRNAs on specific target mRNAs, providing wet-lab validation. However, few tools have been developed to explain the miRNAmediated regulation at the protein level. In this paper, the MoPC computational tool is presented, that relies on the partial correlation between mRNAs and proteins conditioned on the miRNA expression to predict miRNA-target interactions in multi-omic datasets. MoPC returns the list of significant miRNA-target interactions and plot the significant correlations on the heatmap in which the miRNAs and targets are ordered by the chromosomal location. The software was applied on three TCGA/CPTAC datasets (breast, glioblastoma, and lung cancer), returning enriched results in three independent targets databases.

Integrated microRNA and proteome analysis of cancer datasets with MoPC / Lovino, M.; Ficarra, E.; Martignetti, L.. - In: PLOS ONE. - ISSN 1932-6203. - 19:3(2024), pp. 1-11. [10.1371/journal.pone.0289699]

Integrated microRNA and proteome analysis of cancer datasets with MoPC

Lovino M.;Ficarra E.;
2024

Abstract

MicroRNAs (miRNAs) are small molecules that play an essential role in regulating gene expression by post-transcriptional gene silencing. Their study is crucial in revealing the fundamental processes underlying pathologies and, in particular, cancer. To date, most studies on miRNA regulation consider the effect of specific miRNAs on specific target mRNAs, providing wet-lab validation. However, few tools have been developed to explain the miRNAmediated regulation at the protein level. In this paper, the MoPC computational tool is presented, that relies on the partial correlation between mRNAs and proteins conditioned on the miRNA expression to predict miRNA-target interactions in multi-omic datasets. MoPC returns the list of significant miRNA-target interactions and plot the significant correlations on the heatmap in which the miRNAs and targets are ordered by the chromosomal location. The software was applied on three TCGA/CPTAC datasets (breast, glioblastoma, and lung cancer), returning enriched results in three independent targets databases.
2024
19
3
1
11
Integrated microRNA and proteome analysis of cancer datasets with MoPC / Lovino, M.; Ficarra, E.; Martignetti, L.. - In: PLOS ONE. - ISSN 1932-6203. - 19:3(2024), pp. 1-11. [10.1371/journal.pone.0289699]
Lovino, M.; Ficarra, E.; Martignetti, L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1342047
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