Deciphering the cross-talking of human competitive endogenous RNAs in K562 chronic myelogenous leukemia cell line.

MOLECULAR BIOSYSTEMS(2016)

Cited 4|Views17
No score
Abstract
Chronic myelogenous leukemia (CML) is a myeloproliferative disorder characterized by increased proliferation or abnormal accumulation of granulocytic cell line without the depletion of their capacity to differentiate. A reciprocal chromosomal translocation proceeding to the `Philadelphia chromosome', involving the ABL proto-oncogene and BCR gene residing on Chromosome 9 and 22 respectively, is observed to be attributed to CML pathogenesis. Recent studies have been unraveling the crucial role of genomic `dark matter' or the non-coding repertoire in cancer initiation and progression. The intricate cross-talk between competitive endogenous RNAs (ceRNAs) provides a scaffold to systematically functionalize the miRNA response element harboring non-coding RNAs and incorporate them with the protein-coding RNA dimension in complex ceRNA networks. This network of coding and non-coding transcriptome linked by shared miRNAs evidently offers a platform to elucidate the complex regulatory interactions at the post-transcriptional level in human cancers. In this context, analyzing CML, from the perspective of the ceRNA hypothesis, surely craves intensive attention and a comprehensive discussion. Here, we performed RNA-seq data analysis to retrieve Lymphoblastoid and CML coding as well as non-coding repertoire and constructed a ceRNA network for the CML cell line, considering the non-cancer lymphoblastoid cell line as the control. We investigated if any alteration exists in the ceRNA landscape of the transcripts which are exhibiting differential expression across the two cell lines and observed that the major ceRNA regulators vary in cancer network when compared with the Lymphoblastoid network. The top ranked significant functional modules in the ceRNA network display cancer associated attributes and reveal putative regulators in CML pathogenesis.
More
Translated text
Key words
human competitive endogenous rnas,cell,cross-talking
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined