ArticleMolecular biology reports2016
Identifying significant microRNA-mRNA pairs associated with breast cancer subtypes.
Article in Molecular biology reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed, 3 citations in OpenAlex.
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Authors and funding
3 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs that help in post-transcriptional gene silencing. These endogenous RNAs develop a post-transcriptional gene-regulatory network by binding to complementary sequences of target mRNAs and essentially degrade them. Cancer is a class of diseases that is caused by the uncontrolled cell growth, thereby resulting into a gradual degradation of cell structure. Earlier researches have shown that miRNAs have significant biological involvement in cancer. Prolonged research in this genre has led to the identification of the functions of numerous miRNAs in cancer development. Studying the differential expression profiles of miRNAs and mRNAs together could help us in recognizing the significant miRNA-mRNA pairs from cancer samples. In this paper, we have analyzed the simultaneous over-expression of miRNAs and under-expression of mRNAs and vice versa to establish their association with cancer. This study focuses on breast tumor samples and the miRNA-mRNA target pairs that have a visible signature in such breast tumor samples. We have been able to identify the differentially expressed miRNAs and mRNAs, and further established relations between them to extract the miRNA-mRNA pairs that might be significant in the breast cancer types. This gives us the clue about the potential biomarkers for the breast cancer subtypes that can further help in understanding the progression of each of the subtypes separately. This might be helpful for the joint miRNA-mRNA biomarker identification.
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