ArticleCancer medicine2023
Circulating TP73-AS1 and CRNDE serve as diagnostic and prognostic biomarkers for non-small cell lung cancer.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Non-coding RNAs and regulation of the PI3K signaling pathway in lung cancer: Recent insights and potential clinical applications.Non-coding RNA research · 2025Review
- Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.Scientific reports · 2024Article
- lncRNA Biomarkers of Glioblastoma Multiforme.Biomedicines · 2024Review
- Circulating TP73-AS1 and CRNDE serve as diagnostic and prognostic biomarkers for non-small cell lung cancer.Cancer medicine · 2023Article
- Non-coding RNAs in lung cancer: molecular mechanisms and clinical applications.Frontiers in oncology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCirculating 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).
methodsThe 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.
resultsAUC 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.
conclusionCirculating TP73-AS1 and CRNDE could be potential biomarkers for the diagnosis and prognostic prediction of NSCLC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.