A Non-Coding RNA Network Involved in KSHV Tumorigenesis

Naipauer, Julián; Solá, Martín E García; Salyakina, Daria; Rosario, Santas; Williams, Siôn L.; Coso, Omar A.; Abba, Martı́n C.; Mesri, Enrique A.; Lacunza, Ezequiel

doi:10.3389/fonc.2021.687629

Cited by 6 publications

(4 citation statements)

References 65 publications

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“…It is a manually curated repository that features 2822 interactions in 177 diseases and 475 lncRNAs, based on experimental data. It is claimed that LncTarD understands regulatory networks in the pathogenesis of human diseases [ 111 , 112 ].…”

Section: Overview Of Available Methods For Reconstructing Interactions Between Ncrnas and Other Moleculesmentioning

confidence: 99%

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Rincón-Riveros

Morales

Rodríguez

et al. 2021

IJMS

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Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included.

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Section: Overview Of Available Methods For Reconstructing Interactions Between Ncrnas and Other Moleculesmentioning

confidence: 99%

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Rincón-Riveros

Morales

Rodríguez

et al. 2021

IJMS

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“…MALAT1 also serves as an example of those lncRNAs deregulated in HIV associated cancer and impacted by HIV. MALAT1 is an oncogenic lncRNA involved in proliferation, invasion and metastasis in KSHV tumorigenesis [ 177 ]. Additionally, highly upregulated MALAT1 promotes HIV transcription in HIV-infected CD4 + T lymphocytes [ 54 ].…”

Section: Cell Homeostasis and Cell Survival Processesmentioning

confidence: 99%

Long noncoding RNAs (lncRNAs) in HIV-mediated carcinogenesis: Role in cell homeostasis, cell survival processes and drug resistance

Makgoo

Mosebi

Mbita

2022

Non-coding RNA Research

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“…miRNAs are small ribonucleic acid molecules associated with the regulation of gene expression ( 15 ). They are involved in all cellular processes, and their expression profiles differ depending on physio-pathological conditions ( 16 ). miRNAs are expressed throughout development in various tissues, including the cardiovascular system ( 17 ).…”

Section: Introductionmentioning

confidence: 99%

Circulating microRNAs as biomarkers of Chagas cardiomyopathy

Antonietti,

Mariani,

Martínez

et al. 2023

Front. Cardiovasc. Med.

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BackgroundChagas cardiomyopathy (CHCM) is the most important clinical manifestation of Chagas disease. The analysis of cardiac miRNAs may contribute to predicting the progression to CHCM in Chagas indeterminate phase and/or to the differential diagnosis for cardiomyopathy.MethodsWe carried out a case-control study to identify circulating miRNAs associated with CHCM. We assigned 104 participants to four groups: healthy controls (HC), Chagas non-cardiomyopathy controls, CHCM cases, and ischemic cardiomyopathy controls. We performed a clinical, echocardiographic, and laboratory evaluation and profiled circulating miRNA in the serum samples.ResultsDifferences between groups were observed in clinical variables and in the analysis of miRNAs. Compared to HC, CHCM participants had 4 over-expressed and 6 under-expressed miRNAs; miR-95-3p and miR-130b-3p were upregulated in CHCM compared with controls, Chagas non-cardiomyopathy and ischemic cardiomyopathy participants, suggesting that might be a hallmark of CHCM. Analysis of gene targets associated with cardiac injury yielded results of genes involved in arrhythmia generation, cardiomegaly, and hypertrophy.ConclusionsOur data suggest that the expression of circulating miRNAs identified by deep sequencing in CHCM could be associated with different cardiac phenotypes in CHCM subjects, compared with Chagas non-CHCM, ischemic cardiomyopathy controls, and healthy controls.

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A Non-Coding RNA Network Involved in KSHV Tumorigenesis

Cited by 6 publications

References 65 publications

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Long noncoding RNAs (lncRNAs) in HIV-mediated carcinogenesis: Role in cell homeostasis, cell survival processes and drug resistance

Circulating microRNAs as biomarkers of Chagas cardiomyopathy

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