Dataset Information

TsRNA-49-73-Glu-CTC: A Promising Serum Biomarker in NSCLC

ABSTRACT: Objective Lung cancer has the highest incidence and mortality rates globally, with the majority of cases classified as non-small cell lung cancer (NSCLC). Due to the absence of specific tumor biomarkers, most lung cancer cases are diagnosed at an advanced stage. Therefore, the identification of novel molecular biomarkers with high sensitivity and specificity for early diagnosis is deemed crucial for enhancing the treatment of NSCLC. Transfer RNA-derived small RNA (tsRNA) is closely associated with malignant tumors and holds promise as a potential biomarker for tumor diagnosis. This study aimed to investigate whether serum tsRNA could serve as a biomarker for NSCLC. Methods Differentially expressed tsRNAs were identified through high-throughput sequencing of serum samples obtained from patients with NSCLC and healthy individuals. Additional serum samples were collected for validation using Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR). The diagnostic performance of these tsRNAs was assessed through Receiver Operating Characteristic (ROC) Curve Analysis. Furthermore, preliminary functional exploration was undertaken through cell experiments. Results tsRNA-49-73-Glu-CTC is highly expressed in the serum of patients with NSCLC and demonstrates superior diagnostic value compared to commonly used tumor markers in clinical practice, such as Carcinoembryonic Antigen (CEA), Neuron-Specific Enolase (NSE), and Cytokeratin 19 Fragment (CYFRA). A combined diagnostic approach enhances the accuracy of NSCLC detection. Additionally, tsRNA-49-73-Glu-CTC is highly expressed in A549 cells, and transfection with a tsRNA-49-73-Glu-CTC inhibitor significantly reduces both proliferation and migration capabilities. Conclusions tsRNA-49-73-Glu-CTC has the potential to serve as a novel molecular diagnostic biomarker for NSCLC and plays a significant role in the biological processes associated with NSCLC proliferation and migration.

ORGANISM(S): Homo sapiens

PROVIDER: GSE278659 | GEO | 2025/02/18

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:In cancer management, early and accurate diagnosis of hepatocellular carcinoma (HCC) is important for enhancing survival rate of patients. Currently, serum alpha-fetoprotein (AFP) is the only one biomarker for detection of HCC. However, serum AFP is not satisfactory for diagnosis of HCC due to its low accuracy (about 60-70%). In this study, we collected 109 serum samples (discovery set) from healthy control (HC) and patients with chronic hepatitis B (CHB), liver cirrhosis (LC) and HCC, and analyzed them with custom lncRNA microarray. Profiling analysis shows 181 differentially expressed lncRNAs between HCs and patients with CHB, LC and HCC. Then a 48-lncRNA diagnostic signature was identified with 100% predictive accuracy for all subjects in the discovery set. This diagnostic signature was verified with a cross-validation analysis in the discovery set. To further corroborate the signature, we gathered another 66 serum samples (validation set) and also analyzed them with microarray. The result indicates that the same signature has similar diagnostic accuracy for HC (100%), CHB (73%), LC (88%) and HCC (95%), implying a reproducible diagnostic biomarker for HCC. Receiver operating characteristic (ROC) analysis exhibits that this signature has significantly higher diagnostic accuracy for HCC and non-cancerous subjects (area under curve [AUC]: 0.994) than AFP (AUC: 0.773) in the discovery set and this was also verified in the validation set (0.964 vs 0.792). More importantly, the signature detected small HCC (<3cm) with 100% (13/13) accuracy while AFP with only 61.5% (8/13). Altogether, this study demonstrates that the serum 48-lncRNA signature is not only a powerful and sensitive biomarker for diagnosis of HCC but also a potential biomarker for LC. ***************************************************************** Submitter declares these data are subject to patent number ZL 2016 1 0397094. *****************************************************************

Project description:Background: There is a paucity of non-invasive markers for early detection of brain metastasis (BM) in patients with non-small cell lung cancer (NSCLC). Secretory proteomic approach based on quantitative tandem mass tag is believed to offer bright prospects for screening potential serum biomarkers for diseases. Methods: We used the secretory proteomics to identify up-regulated proteins in the highly brain metastatic cell line compared to the parental lung cancer cell line. Enzyme linked immunoassay and immunohistochemistry were performed on non-small cell lung cancer patients with brain metastasis and control samples from each cohort to verify the expression levels of candidate proteins. A logistic regression model was used to develop a biomarker panel composed of Cathepsin F (CTSF) and Fibulin-1 (FBLN1), and then an independent validation data set was used for verification. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curve analysis. Changes in serum CTSF levels of patients were tracked to monitor the effect of treatment, and progression-free survival (PFS) and overall survival (OS) were analyzed to assess their prognostic relevance. Results: CTSF and FBLN1 levels were specifically upregulated in sera and tissues of patients with NSCLC BM. Importantly, the combined diagnostic performance of CTSF and FBLN1 was superior to their individual diagnostic performance (sensitivity and specificity). CTSF serum changes were found to reflect the therapeutic response of patients with NSCLC BM and the trends of resistance and progression were detected earlier than the MRI changes. Elevated expression of CTSF in NSCLC BM tissues was associated with poor PFS. Moreover, CTSF tissue expression was found to be an independent prognostic factor. Conclusions: CTSF and FBLN1 are potential novel and specific serum markers for early diagnosis of BM in patients with NSCLC. CTSF can also be used as a biomarker for monitoring therapeutic efficacy and prognostic assessment.

Dataset Information

TsRNA-49-73-Glu-CTC: A Promising Serum Biomarker in NSCLC

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets