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New global analysis of the microRNA transcriptome of primary tumors and lymph node metastases of papillary thyroid cancer. | LitMetric

Background: Papillary Thyroid Cancer (PTC) is the most prevalent type of endocrine cancer. Its incidence has rapidly increased in recent decades but little is known regarding its complete microRNA transcriptome (miRNome). In addition, there is a need for molecular biomarkers allowing improved PTC diagnosis.

Methods: We performed small RNA deep-sequencing of 3 PTC, their matching normal tissues and lymph node metastases (LNM). We designed a new bioinformatics framework to handle each aspect of the miRNome: whole expression profiles, isomiRs distribution, non-templated additions distributions, RNA-editing or mutation. Results were validated experimentally by qRT-PCR on normal samples, tumors and LNM from 14 independent patients and in silico using the dataset from The Cancer Genome Atlas (small RNA deepsequencing of 59 normal samples, 495 PTC, and 8 LNM).

Results: We performed small RNA deep-sequencing of 3 PTC, their matching normal tissues and lymph node metastases (LNM). We designed a new bioinformatics framework to handle each aspect of the miRNome: whole expression profiles, isomiRs distribution, non-templated additions distributions, RNA-editing or mutation. Results were validated experimentally by qRT-PCR on normal samples, tumors and LNM from 14 independent patients and in silico using the dataset from The Cancer Genome Atlas (small RNA deep-sequencing of 59 normal samples, 495 PTC, and 8 LNM). We confirmed already described up-regulations of microRNAs in PTC, such as miR-146b-5p or miR-222-3p, but we also identified down-regulated microRNAs, such as miR-7-5p or miR-30c-2-3p. We showed that these down-regulations are linked to the tumorigenesis process of thyrocytes. We selected the 14 most down-regulated microRNAs in PTC and we showed that they are potential biomarkers of PTC samples. Nevertheless, they can distinguish histological classical variants and follicular variants of PTC in the TCGA dataset. In addition, 12 of the 14 down-regulated microRNAs are significantly less expressed in aggressive PTC compared to non-aggressive PTC. We showed that the associated aggressive expression profile is mainly due to the presence of the BRAF V600E mutation. In general, primary tumors and LNM presented similar microRNA expression profiles but specific variations like the down-regulation of miR-7-2-3p and miR-30c-2-3p in LNM were observed. Investigations of the 5p-to-3p arm expression ratios, non-templated additions or isomiRs distributions revealed no major implication in PTC tumorigenesis process or LNM appearance.

Conclusions: Our results showed that down-regulated microRNAs can be used as new potential common biomarkers of PTC and to distinguish main subtypes of PTC. MicroRNA expressions can be linked to the development of LNM of PTC. The bioinformatics framework that we have developed can be used as a starting point for the global analysis of any microRNA deep-sequencing data in an unbiased way.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4618137PMC
http://dx.doi.org/10.1186/s12864-015-2082-3DOI Listing

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