Orcid Publication

Detalle de: Identification of the mobile elements differentially expressed in lung cancer

Title Identification of the mobile elements differentially expressed in lung cancer
Abstract

Introduction: Mobile elements, which include transposons, are DNA sequences that can move autonomously from one place to another of the genome. Its activation has been described in numerous diseases, including cancer, as they alter the DNA in the genome. Objectives: To reveal the relation between mobile elements and lung cancer. Methods: RNA-seq reads of healthy and tumoral samples from NCBI (17 patients with small-cell lung cancer [SCLC]) and EGA (50 patients with adenocarcinoma lung cancer) repositories were downloaded. Reads were processed with a bioinformatic pipeline including the cleaning with SeqTrimNext, mapping with the human reference genome hg38 using Bowtie 1, and RepEnrich together with the RepeatMasker database to correlate the expression of the repetitive elements with mobile elements, as usually done. Results: Overall transposon activity is not significantly higher or lower between tumor and adjacent healthy tissue. However, 21 mobile elements were differentially expressed in adenocarcinoma and 129 in SCLC, with 15 in common between both lung cancers. In the accompanying image, it can be observed that all but two are coexpressed in the same way. Conclusions: We have found that transposons are not globally deregulated in lung cancer tissue, but that individual transposons are. Also, we have found the set of transposons under and over expressed in those cancers.

Apa Reference Arroyo Varela, M., Bautista Moreno, R., Larrosa Jiménez, R., De la Cruz Ríos, J.L., Cobo, M. & Claros, M. (2017). Identification of the mobile elements differentially expressed in lung cancer. Lung Cancer, PA3302. 10.1183/1393003.congress-2017.pa3302
Doi 10.1183/1393003.congress-2017.pa3302
Publication Date Sep 2017
Publication Type Conference paper
Ontology Transcriptomics, RNA Sequencing (RNA-seq), Biological Databases, Expression Profiling
Researchers M. Gonzalo Claros Díaz
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