Web-based tools for microRNAs involved in human cancer

MicroRNA childhood Cancer Catalog (M3Cs) is a high-quality curated collection of published miRNA research studies on 16 pediatric cancer diseases. M3Cs scope was based on two approaches: data-driven clinical significance and data-driven human pediatric cell line models. Based on the translational bioinformatics spectrum, the main objective of this study is to bring miRNA research into clinical significance in both pediatric cancer patient care and drug discovery toward health informatics in childhood cancer. M3Cs development passed through three phases: 1. Literature Mining: It includes external database search and screening. 2. Data processing that includes three steps: (a) Data Extraction, (b) Data Curation and annotation, (c) Web Development. 3. Publishing: Shinyapps.io was used as a web interface for the deployment of M3Cs. M3Cs is now available online and can be accessed through https://m3cs.shinyapps.io/M3Cs/. For data-driven clinical significance approach, 538 miRNAs from 268 publications were reported in the clinical domain while 7 miRNAs from 5 publications were reported in the clinical & drug domain. For data-driven human pediatric cell line models approach, 538 miRNAs from 1268 publications were reported in the cell line domain while 211 miRNAs from 177 publications in the cell line & drug domain. M3Cs acted to fill the gap by applying translational bioinformatics general pathway to transfer data-driven research toward data-driven clinical care and/or hypothesis generation. Aggregated and well-curated data of M3Cs will enable stakeholders in health care to incorporate miRNA in the clinical policy. Database URL:https://m3cs.shinyapps.io/M3Cs/

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“…M3Cs has certain advantages over other available miRNA databases ( 9 , 19 ). The M3Cs construction and the involved variables are unique to M3Cs.…”

Section: Discussionmentioning

confidence: 99%

MicroRNA childhood cancer catalog (M3Cs): a resource for translational bioinformatics toward health informatics in pediatric cancer

et al. 2022

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“…RNA:RNA interaction prediction stands to be the most well investigated in large part due to the strong overlap with the small RNA/miRNA field. For instance, lncRNAs acting as ceRNAs can be predicted through their interactions with miRNAs for which a multitude of databases and tools already exist to predict their general propensity to bind certain RNA sequences ( Table 3 ); also see [ 149 ]. However, some lncRNA:RNA specific prediction tools have been developed too.…”

Section: Secondary Characterisation: Predicting and Detecting Intementioning

confidence: 99%

“…As such, most resources presented are databases integrating multiple sources of evidence from orthogonal experiments in repositories such as GEO [ 68 ], ArrayExpress [ 155 ], ENCODE [ 67 ], TCGA [ 64 ] and the SRA (Sequence Read Archive) [ 156 ] as well as pre-calculated prediction and annotation databases such as as LncRNADisease [ 94 ], MNDR (Mammal ncRNA-Disease Repository) [ 97 ], eDGAR (Database of Disease-Gene Associations with annotated Relationships among genes) [ 157 ], circRNADisease [ 114 ], RAIN (RNA-protein Association and Interaction Networks) [ 158 ], RAID (RNA Association Interaction Database) [ 159 ], NPInter [ 160 ] and RISE (RNA Interactome from Sequencing Experiments) [ 161 ] ( Table 3 ). For a comprehensive review of tools and databases dedicated to miRNA specific predictions please refer to [ 149 , 162 ].…”

Section: Secondary Characterisation: Predicting and Detecting Intementioning

confidence: 99%

Approaches to Identify and Characterise the Post-Transcriptional Roles of lncRNAs in Cancer

Carter

Ang

Sim

et al. 2021

ncRNA

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It is becoming increasingly evident that the non-coding genome and transcriptome exert great influence over their coding counterparts through complex molecular interactions. Among non-coding RNAs (ncRNA), long non-coding RNAs (lncRNAs) in particular present increased potential to participate in dysregulation of post-transcriptional processes through both RNA and protein interactions. Since such processes can play key roles in contributing to cancer progression, it is desirable to continue expanding the search for lncRNAs impacting cancer through post-transcriptional mechanisms. The sheer diversity of mechanisms requires diverse resources and methods that have been developed and refined over the past decade. We provide an overview of computational resources as well as proven low-to-high throughput techniques to enable identification and characterisation of lncRNAs in their complex interactive contexts. As more cancer research strategies evolve to explore the non-coding genome and transcriptome, we anticipate this will provide a valuable primer and perspective of how these technologies have matured and will continue to evolve to assist researchers in elucidating post-transcriptional roles of lncRNAs in cancer.

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“…Until now, there are at least 14 online open-access databases containing extensive information about miRNAs [31]. Some of these databases (SomammiR DB2.0) are useful to search for miRNAs somatic mutations and to predict their functional analysis based on these mutations, to identify miRNAs alterations involved in protein regulation (CancerNet) or to review the annotation changes for each miRNAs entry (miRbase Tracker).…”

Section: )mentioning

confidence: 99%

The Role of miRNAs in Diagnosis, Prognosis and Treatment Prediction in Cervical Cancer

Bălăcescu¹,

Bălăcescu²,

Baldasici³

et al. 2017

Colposcopy and Cervical Pathology

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Cervical cancer represents one of the major problems of health women worldwide, especially in the developing countries. If discovered in its earliest stages, cervical cancer is successfully treatable; however, due to lack of proper implementation of screening programs, the majority of cervical cancer patients are diagnosed in advanced stages, which dramatically influence their outcome. Almost a half of these patients will suffer recurrence or metastasis in the following 2 years after therapy. If there are no immediate prospects in terms of developing new or more effective therapies, identifying new tools for early diagnosis, prognosis and treatment prediction remains a big challenge for cervical cancer. miRNAs have been validated to be key players in cell physiology, alterations in miRNA expression being associated with cancer progression and response to therapy. Cervical cancer studies have showed that alterations of miRNA expression can be identified in tumor tissues, exfoliated cervical cells and patients serum and that their transcription pattern is regulated by the present HPV genotype. Furthermore, miRNAs have been associated with patients response to therapy, therefore suggesting their potential to be used as biomarkers for cervical cancer diagnosis, prognosis and treatment response.

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Web-based tools for microRNAs involved in human cancer

Cited by 4 publications

References 65 publications

MicroRNA childhood cancer catalog (M3Cs): a resource for translational bioinformatics toward health informatics in pediatric cancer

MicroRNA childhood cancer catalog (M3Cs): a resource for translational bioinformatics toward health informatics in pediatric cancer

Approaches to Identify and Characterise the Post-Transcriptional Roles of lncRNAs in Cancer

The Role of miRNAs in Diagnosis, Prognosis and Treatment Prediction in Cervical Cancer

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