Contribution of bioinformatics prediction in microRNA-based cancer therapeutics

Banwait, Jasjit K.; Bastola, Dhundy

doi:10.1016/j.addr.2014.10.030

Cited by 42 publications

(24 citation statements)

References 108 publications

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“…16 Integrative computational bioinformatics approaches have been utilized as an effective tool to detect the potential outlier miRNAs in cancer. 20,21 Furthermore, as a rational approach, preliminary detection of candidate miRNAs derived from large-scale expression profiling data and low-throughput experimental verification for the selected outlier miRNAs can be used to choose candidate miRNAs. 22,23 In the present study, according to literature reviews and data mining for were culled to be analyzed and confirmed by RT-qPCR.…”

Section: Discussionmentioning

confidence: 99%

Aberrant expression of a five‐microRNA signature in breast carcinoma as a promising biomarker for diagnosis

Bitaraf

Babashah

Garshasbi

2019

Clinical Laboratory Analysis

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Background Breast cancer (BC) is the most common malignancy among females with dismal quality of life in patients. It has been proven that epigenetic factors, especially microRNAs, are involved in breast carcinogenesis and progression. This study aimed to assess the expression and clinical performances of a five‐microRNA signature (miR‐127‐3p, miR‐133a‐3p, miR‐155‐5p, miR‐199b‐5p, and miR‐342‐5p) in breast cancer and adjacent normal tissues to identify a potential biomarker for BC and investigate the relationship between their expression and clinicopathological features of BC patients as well. Methods In this case‐control investigation, we recruited 50 pairs of tumor and matched non‐tumor surgical specimens from patients diagnosed with BC. Expression levels of miR‐127‐3p, miR‐133a‐3p, miR‐155‐5p, miR‐199b‐5p, and miR‐342‐5p were measured in BC and adjacent normal tissues by RT‐qPCR. Results We found that miR‐127‐3p, miR‐133a‐3p, miR‐199b‐5p, and miR‐342‐5p were significantly down‐regulated, while miR‐155‐5p was significantly up‐regulated in BC tumor tissues compared with the corresponding adjacent normal tissues. The decreased expression of miR‐127‐3p, miR‐133a‐3p, miR‐342‐5p, and up‐regulation of miR‐155‐5p showed a significant correlation with disease stage. We also found a significant down‐regulation of miR‐127‐3p, miR‐199b‐5p, and miR‐342‐5p compared in HER‐2‐negative patients. Our results indicated that miR‐155‐5p had a higher expression level in HER‐2‐positive patients. Receiver operating characteristic (ROC) curve analysis demonstrated that all these five microRNAs can serve as potential biomarkers to distinguish between tumor and non‐tumor breast tissue samples. Conclusions The present findings suggested that dysregulation of this five‐miRNA signature might be considered as a promising and functional biomarker for BC diagnosis.

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Section: Discussionmentioning

confidence: 99%

Aberrant expression of a five‐microRNA signature in breast carcinoma as a promising biomarker for diagnosis

Bitaraf

Babashah

Garshasbi

2019

Clinical Laboratory Analysis

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“…Since miRNAs started to be largely studied, multiple reviews dealing with these small non coding RNAs in cancer have been proposed (17)(18)(19). Some of them provide an overview of the existing methods for miRNAs discovery (18).…”

Section: Introductionmentioning

confidence: 99%

“…Some of them provide an overview of the existing methods for miRNAs discovery (18). Some others take into account the different approaches for the prediction of miRNAs target transcripts (19). Finally, others are more centered on the medical aspects concerning microRNAs in cancer and they briefly report some examples of computational tools (17).…”

Section: Introductionmentioning

confidence: 99%

A review of computational approaches detecting microRNAs involved in cancer

et al. 2017

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MicroRNAs (miRNAs) are small non-coding RNAs playing an essential role in gene expression regulation. Multiple studies have demonstrated that miRNAs are dysregulated in cancer initiation and progression, pointing out their potential as biomarkers for diagnosis, prognosis and response to treatment. With the introduction of high-throughput technologies several computational approaches have been proposed to identify cancer-associated miRNAs. Here, we present a systematic and comprehensive overview of the current knowledge concerning the computational detection of miRNAs involved in tumor onset and subtyping, with possible theranostic employment. An overview of the state of art in this field is thus proposed with the aim of supporting researchers, especially experimentalists and pathologists, in choosing the optimal approach for their case of study.

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“…Bioinformatics [105,106], DNA sequencing [107,108], omics [109,110] and algorithm (e.g., COXEN) [111,112] tools have allowed the identification of chemokines and cytokines involved in immune contexture (analysis of the location, density and functional orientation of the different immune cell populations [113]) and proteomic, genomic, transcriptomic and epigenomic alterations in cancers, consequently enabling a more rational design in target therapy discovery, cancer prevention and therapy. Outputs of such investigations have enabled the development of CIVO™ technology, for example, that enables the simultaneous assessment of up to eight drugs or drug combinations within a solid tumour in vivo [114].…”

Section: Rationale For Using 3d In Vitro Modelsmentioning

confidence: 99%