Briefing in family characteristics of microRNAs and their applications in cancer research

Wang, Qicong; Wei, Leyi; Guan, Xiao; Wu, Yunfeng; Zou, Quan; Ji, Zhiliang

doi:10.1016/j.bbapap.2013.08.002

Cited by 49 publications

(27 citation statements)

References 60 publications

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“…Furthermore, gene expression profiling was used to classify paediatric ALL subtypes by Yeoh et al [3]. Recently, apart from microarray technology for questions such as AML subtype determination [4], interest has been also turned towards searching for leukaemia biomarkers with miRNA [5–10] and lncRNA [11] analysis. Despite the existence of all those studies, there remains only one exceptional study which was conducted on a large scale to discriminate between all of the leukaemia subtypes [12].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers

Łabaj

Papież

Polański

et al. 2017

Interdiscip Sci Comput Life Sci

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Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments.Electronic supplementary materialThe online version of this article (doi:10.1007/s12539-017-0216-9) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers

Łabaj

Papież

Polański

et al. 2017

Interdiscip Sci Comput Life Sci

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“…Sixty-five percent of all miRNAs are part of multimember families (Wang et al 2014). Many of the miRNA families in humans regulate targets relevant for development and disease.…”

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confidence: 99%

Cooperative target mRNA destabilization and translation inhibition by miR-58 microRNA family in C. elegans

Subasic

Brümmer

et al. 2015

Genome Res.

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In animals, microRNAs frequently form families with related sequences. The functional relevance of miRNA families and the relative contribution of family members to target repression have remained, however, largely unexplored. Here, we used the Caenorhabditis elegans miR-58 miRNA family, composed primarily of the four highly abundant members miR-58.1, miR-80, miR-81, and miR-82, as a model to investigate the redundancy of miRNA family members and their impact on target expression in an in vivo setting. We found that miR-58 family members repress largely overlapping sets of targets in a predominantly additive fashion. Progressive deletions of miR-58 family members lead to cumulative up-regulation of target protein and RNA levels. Phenotypic defects could only be observed in the family quadruple mutant, which also showed the strongest change in target protein levels. Interestingly, although the seed sequences of miR-80 and miR-58.1 differ in a single nucleotide, predicted canonical miR-80 targets were efficiently up-regulated in the mir-58.1 single mutant, indicating functional redundancy of distinct members of this miRNA family. At the aggregate level, target binding leads mainly to mRNA degradation, although we also observed some degree of translational inhibition, particularly in the single miR-58 family mutants. These results provide a framework for understanding how miRNA family members interact to regulate target mRNAs.

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“…Onco‐miRNAs are usually highly expressed in tumor cells and promote the development and progression of the tumor. In contrast, tumor‐suppressor miRNAs are often downregulated or absent in tumor cells, and they suppress tumor growth . In recent years, miRNAs have been considered a novel therapeutic target for cancer .…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, tumor-suppressor miRNAs are often downregulated or absent in tumor cells, and they suppress tumor growth. 3,7 In recent years, miRNAs have been considered a novel therapeutic target for cancer. 8,9 These strategies include interfering with onco-miRNAs to suppress tumor growth and importing exogenous tumor-suppressor miRNAs into tumor cells to treat cancer.…”

Section: Introductionmentioning

confidence: 99%

Pattern of cell‐to‐cell transfer of microRNA by gap junction and its effect on the proliferation of glioma cells

et al. 2019

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Micro RNA is expected to be a novel therapeutic tool for tumors. Gap junctions facilitate the transfer of micro RNA , which exerts biological effects on tumor cells. However, the length of micro RNA that can pass through certain gap junctions composed of specific connexin remains unknown. To address this question, the present study investigated the permeability of gap junctions composed of various connexins, including connexin 43, connexin 32 or connexin 37, to micro RNA s consisting of 18‐27 nucleotides in glioma cells and cervical cancer cells. Results indicated that all of the micro RNA s were able to be transferred from donor glioma cells to neighboring cells through the connexin 43 composed gap junction, but not the gap junctions composed of connexin 32 or connexin 37, in cervical cancer cells. Downregulation of the function of gap junctions comprising connexin 43 by pharmacological inhibition and sh RNA significantly decreased the transfer of these micro RNA s. In contrast, gap junction enhancers and overexpression of connexin 43 effectively increased these transfers. In glioma cells, cell proliferation was inhibited by micro RNA ‐34a. Additionally, these effects of micro RNA ‐34a were significantly enhanced by overexpression of connexin 43 in U251 cells, indicating that gap junctions play an important role in the antitumor effect of micro RNA by transfer of micro RNA to neighboring cells. Our data are the first to clarify the pattern of micro RNA transmission through gap junctions and provide novel insights to show that antitumor micro RNA s should be combined with connexin 43 or a connexin 43 enhancer, not connexin 32 or connexin 37, in order to improve the therapeutic effect.

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Briefing in family characteristics of microRNAs and their applications in cancer research

Cited by 49 publications

References 60 publications

Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers

Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers

Cooperative target mRNA destabilization and translation inhibition by miR-58 microRNA family in C. elegans

Pattern of cell‐to‐cell transfer of microRNA by gap junction and its effect on the proliferation of glioma cells

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