Evidence Hub

RMRP, RMST, FTX and IPW: novel potential long non-coding RNAs in medullary thyroid cancer

B. Luzón-Toro, L. Villalba-Benito, R. M. Fernández, Ana Torroglosa, G. Antiñolo, S. Borrego

Orphanet Journal of Rare Diseases, 2021

13 citations

Abstract

The relevant role of long non-coding RNAs (lncRNAs) in cancer is currently a matter of increasing interest. Medullary thyroid cancer (MTC) is a rare neuroendocrine tumor (2–5% of all thyroid cancer) derived from the parafollicular C-cells which secrete calcitonin. About 75% of all medullary thyroid cancers are believed to be sporadic medullary thyroid cancer (sMTC), whereas the remaining 25% correspond to inherited cancer syndromes known as Multiple Endocrine Neoplasia type 2 (MEN2). MEN2 syndrome, with autosomal dominant inheritance is caused by germline gain of function mutations in RET proto-oncogene. To date no lncRNA has been associated to MEN2 syndrome and only two articles have been published relating long non-coding RNA (lncRNA) to MTC: the first one linked MALAT1 with sMTC and, in the other, our group determined some new lncRNAs in a small group of sMTC cases in fresh tissue ( RMST, FTX , IPW , PRNCR1 , ADAMTS9-AS2 and RMRP ). The aim of the current study is to validate such novel lncRNAs previously described by our group by using a larger cohort of patients, in order to discern their potential role in the disease. Here we have tested three up-regulated ( RMST, FTX , IPW ) and one down-regulated ( RMRP ) lncRNAs in our samples (formalin fixed paraffin embedded tissues from twenty-one MEN2 and ten sMTC patients) by RT-qPCR analysis. The preliminary results reinforce the potential role of RMST, FTX , IPW and RMRP in the pathogenesis of MTC.

How strong is the evidence?

Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free