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.

中文翻译：

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具有致癌潜力的新型差异表达长非编码 RNA 的鉴定

摘要

最近，关于长链非编码 RNA (lncRNA) 在 mRNA 表达微调中的作用积累了大量数据。四种新的 lncRNA，即 TMEM92-AS1、FAM222A-AS、TXLNB 和 lnc-CCL28，使用深度机器学习被鉴定为在卵巢肿瘤中差异表达。肿瘤和正常组织样本中 lnc-CCL28 转录物的水平足以通过 RT-PCR 进行进一步分析。此外，有希望的卵巢癌生物标志物 lncRNA LINC00152、NEAT1 和 SNHG17 被添加到 RT-PCR 分析中。首次在卵巢肿瘤中发现lnc-CCL28和SNHG17 lncRNAs水平升高，证实了LINC00152和NEAT1的过表达。似乎 lnc-CCL28 与致癌作用有关，尤其是与卵巢癌进展有关。