Abstract
Recently, a wealth of data have been accumulating on the role of long non-coding RNAs (lncRNAs) in the fine-tuning of mRNA expression. Four new lncRNAs, namely, TMEM92-AS1, FAM222A-AS, TXLNB, and lnc-CCL28, were identified as differentially expressed in ovarian tumors using deep machine learning. The levels of lnc-CCL28 transcripts in both tumors and normal tissue samples were sufficient for further analysis by RT-PCR. In addition, the promising ovarian cancer biomarkers, lncRNAs LINC00152, NEAT1 and SNHG17 were added to RT-PCR analysis. For the first time, an increase in the level of lnc-CCL28 and SNHG17 lncRNAs was found in ovarian tumors, and the overexpression of LINC00152 and NEAT1 was confirmed. It seems that lnc-CCL28 is involved in carcinogenesis and, in particular, in ovarian cancer progression. Overexpression of LINC00152 and lnc-CCL28 was significantly associated with the later stages and metastasis.
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This work was supported by the Russian Science Foundation (grant no. 20-15-00368).
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O.I.B. and I.V.P. made equal contributions.
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Brovkina, O.I., Pronina, I.V., Uroshlev, L.A. et al. Identification of Novel Differentially Expressing Long Non-Coding RNAs with Oncogenic Potential. Mol Biol 55, 548–554 (2021). https://doi.org/10.1134/S0026893321020175
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DOI: https://doi.org/10.1134/S0026893321020175