Circulating TP73‐AS1 and CRNDE serve as diagnostic and prognostic biomarkers for non‐small cell lung cancer

Autor: Rong‐Xia Yuan, Chun‐Hua Dai, Ping Chen, Meng‐Jia Lv, Yang Shu, Zhi‐Peng Wang, Ya‐Ping Xu, Jian Li
Rok vydání: 2022
Předmět:
Zdroj: Cancer Medicine. 12:1655-1672
ISSN: 2045-7634
DOI: 10.1002/cam4.5013
Popis: Circulating long noncoding RNAs (lncRNAs) are considered a new class of biomarkers for the diagnosis and prognosis of various malignancies. We aimed to identify circulating lncRNAs as biomarkers for the diagnosis and prognosis of non-small cell lung cancer (NSCLC).The expression of 14 candidate lncRNAs was measured in matched cancer and ipsilateral normal lung tissues of 20 patients with NSCLC using quantitative reverse-transcription PCR. In plasma samples from training and testing sets, significantly and aberrantly expressed lncRNAs, TA73-AS1 and CRNDE, were further analyzed. Receiver operating characteristic (ROC) curves were constructed, and the areas under the ROC curves (AUC) were obtained to assess diagnostic performance. The Kaplan-Meier survival analysis was used to assess the impact of plasma TA73-AS1 and CRNDE expression on tumor-free survival (TFS) of patients with NSCLC. The effect of TP73-AS1 expression on NSCLC cells was investigated in vitro.AUC values of plasma TA73-AS1 and CRNDE were 0.822 and 0.815 in the training set and 0.843 and 0.804 in the testing set, respectively, to distinguish NSCLC from healthy controls. The combination of plasma TP73-AS1, CRNDE, and two classical tumor markers, carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1), showed excellent diagnostic performance for NSCLC (AUC =0.927 in the training set; AUC = 0.925 in the testing set). Furthermore, the high expression of the two plasma lncRNAs correlated with worse TFS in patients with NSCLC. In vitro cell model studies revealed that TP73-AS1 overexpression facilitated NSCLC cell survival, invasion, and migration.Circulating TP73-AS1 and CRNDE could be potential biomarkers for the diagnosis and prognostic prediction of NSCLC.
Databáze: OpenAIRE