ArticleOncology letters2022
Diagnostic value of abnormal chromosome 3p genes in small-cell lung cancer.
Article in Oncology letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The diagnosis of small cell lung carcinoma (SCLC) remains a great challenge. Changes in chromosome 3p (chr3) genes are usually observed in the pathogenesis of lung cancer, which suggests that these chr3 genes may be a diagnostic marker in the early stage of SCLC. The present study explored the diagnostic value of the chr3 gene in SCLC using Bioinformatics. Furthermore, reverse transcription-quantitative PCR (RT-qPCR) was used to reveal the expression patterns of diagnostic biomarkers in human pulmonary alveolar epithelial cells and in the SCLC cell line NCI-H146. A total of 33 differentially expressed (DE) chr3 genes and 1,156 module genes associated with clinical features of patients with SCLC were identified and functional enrichment analysis indicated that all these genes were significantly enriched in cell cycle terms. The area under the receiver operating characteristic curve demonstrated that the overlapping genes of the DE-chr3 and module genes, namely cell division cycle 25 A (CDC25A), FYVE and coiled-coil domain autophagy adaptor 1 (FYCO1) and lipid raft linker 1 (RFTN1), were relatively accurate in distinguishing normal from SCLC samples, and may thus be considered diagnostic biomarkers. CDC25A was overexpressed in SCLC samples, while FYCO1 and RFTN1 were highly expressed in normal samples, as evidenced by the RT-qPCR results. Single-gene gene set enrichment analysis suggested that the diagnostic biomarkers were significantly associated with cell cycle, ATP-binding cassette transporter, immune cell differentiation, immune response and multiple respiratory disease pathways. Furthermore, a total of 141 drugs were predicted by The Comparative Toxicogenomics Database to be able to modulate the expression of the diagnostic biomarkers, of which 8 drugs were shared among the three aforementioned diagnostic biomarkers. The present study identified three novel and powerful diagnostic biomarkers for SCLC based on chr3 genes. Suggestions for the development and selection of drugs for clinical treatment based on diagnostic biomarkers were also provided.
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