Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements

Gosline, Sara J.C.; Gurtan, Allan M.; JnBaptiste, Courtney K.; Bosson, Andrew; Milani, Pamela; Dalin, Simona; Matthews, Bryan J.; Yap, Yoon Sing; Sharp, Phillip A.; Fraenkel, Ernest

doi:10.1016/j.celrep.2015.12.031

Cited by 88 publications

(84 citation statements)

References 56 publications

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“…This result not only is consistent with Gosline et al . [48], which suggested the strong regulation of miRNAs on transcription factors in mice, but also suggests most of these SDEmiRNAs could promote the activity of transcription factors.…”

Section: Resultsmentioning

confidence: 99%

Identification of key differentially expressed MicroRNAs in cancer patients through pan-cancer analysis

Dingerdissen

Gupta

et al. 2018

Computers in Biology and Medicine

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microRNAs (miRNAs) functioning in gene silencing have been associated with cancer progression. However, common abnormal miRNA expression patterns and their potential roles in cancer have not yet been evaluated. To account for individual differences between patients, we retrieved miRNA sequencing data for 575 patients with both tumor and adjacent nontumorous tissues from 14 cancer types from The Cancer Genome Atlas (TCGA). We then performed differential expression analysis using DESeq2 and edgeR. Results showed that cancer types can be grouped based on the distribution of miRNAs with different expression patterns between tumor and non-tumor samples. We found 81 significantly differentially expressed miRNAs (SDEmiRNAs) in a single cancer. We also found 21 key SDEmiRNAs (nine over-expressed and 12 under-expressed) associated with at least eight cancers each and enriched in more than 60% of patients per cancer, including four newly identified SDEmiRNAs (hsa-mir-4746, hsa-mir-3648, hsa-mir-3687, and hsa-mir-1269a). The downstream effects of these 21 SDEmiRNAs on cellular function were evaluated through enrichment and pathway analysis of 7,186 protein-coding gene targets mined from literature reports of differential expression of miRNAs in cancer. This analysis enables identification of SDEmiRNA functional similarity in cell proliferation control across a wide range of cancers, and assembly of common regulatory networks over cancer-related pathways. These findings were validated by construction of a regulatory network in the PI3K pathway. This study provides evidence for the value of further analysis of SDEmiRNAs as potential biomarkers and therapeutic targets for cancer diagnosis and treatment.

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Section: Resultsmentioning

confidence: 99%

Identification of key differentially expressed MicroRNAs in cancer patients through pan-cancer analysis

Dingerdissen

Gupta

et al. 2018

Computers in Biology and Medicine

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“…We use a randomization scheme to assign p-values to network nodes, similar to [22]. We use two criteria for selecting targets: i) statistical significance and ii) biological support, as detailed below.…”

Section: Methodsmentioning

confidence: 99%

Network modeling of kinase inhibitor polypharmacology reveals pathways targeted in chemical screens

et al. 2017

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Small molecule screens are widely used to prioritize pharmaceutical development. However, determining the pathways targeted by these molecules is challenging, since the compounds are often promiscuous. We present a network strategy that takes into account the polypharmacology of small molecules in order to generate hypotheses for their broader mode of action. We report a screen for kinase inhibitors that increase the efficacy of gemcitabine, the first-line chemotherapy for pancreatic cancer. Eight kinase inhibitors emerge that are known to affect 201 kinases, of which only three kinases have been previously identified as modifiers of gemcitabine toxicity. In this work, we use the SAMNet algorithm to identify pathways linking these kinases and genetic modifiers of gemcitabine toxicity with transcriptional and epigenetic changes induced by gemcitabine that we measure using DNaseI-seq and RNA-seq. SAMNet uses a constrained optimization algorithm to connect genes from these complementary datasets through a small set of protein-protein and protein-DNA interactions. The resulting network recapitulates known pathways including DNA repair, cell proliferation and the epithelial-to-mesenchymal transition. We use the network to predict genes with important roles in the gemcitabine response, including six that have already been shown to modify gemcitabine efficacy in pancreatic cancer and ten novel candidates. Our work reveals the important role of polypharmacology in the activity of these chemosensitizing agents.

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“…The role of miRNAs as biomarkers and regulators of gene expression and their role in physiological and pathological processes have been addressed in several reviews (66–70). In the context of SCA, studies show PlGF attenuates levels of miR-648, with seed sequence complementary to the 3′-UTR of ET-1, in cultured endothelial cells (71).…”

Section: Mirnas In Post-transcriptional Regulation Of Et-1mentioning

confidence: 99%

Placenta growth factor mediated gene regulation in sickle cell disease

2018

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Sickle cell anemia (SCA) is an autosomal recessive disorder caused by mutation in the β-globin gene. Pulmonary hypertension (PH), a complication of SCA, results in severe morbidity and mortality. PH is a multifactorial disease: systemic vasculopathy, pulmonary vasoconstriction, and endothelial dysfunction and remodeling. Placenta growth factor (PlGF), an angiogenic growth factor, elaborated from erythroid cells, has been shown to contribute to inflammation, pulmonary vasoconstriction and airway hyper-responsiveness (AH) in mouse models of sickle cell disease. In this review, we summarize the cell-signaling mechanism(s) by which PlGF regulates the expression of genes involved in inflammation, PH and AH in cell culture and corroborate these findings in mouse models of SCA and in individuals with SCA. The role of microRNAs (miRNAs) in the post-transcriptional regulation of these genes is presented and how these miRNAs located in their host genes are transcriptionally regulated. An understanding of the transcriptional regulation of these miRNAs provides a new therapeutic approach to ameliorate the clinical manifestations of SCA.

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Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements

Cited by 88 publications

References 56 publications

Identification of key differentially expressed MicroRNAs in cancer patients through pan-cancer analysis

Identification of key differentially expressed MicroRNAs in cancer patients through pan-cancer analysis

Network modeling of kinase inhibitor polypharmacology reveals pathways targeted in chemical screens

Placenta growth factor mediated gene regulation in sickle cell disease

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