PLX200430
GSE148862: Peripheral blood non-canonical small non-coding RNAs as novel biomarkers in lung cancer and pulmonary tuberculosis (validation cohort)
- Organsim human
- Type RNASEQ
- Target gene
- Project ARCHS4
One unmet challenge in current lung cancer diagnosis is to accurately differentiate lung cancer patients from those with other lung diseases with similar clinical symptoms and radiological features. Previous studies have reported cases of misdiagnosis for patients with lung cancer mimicking pulmonary tuberculosis (TB) or for TB patients with multiple lung nodules mimicking lung cancer progression, which is concerning for clinical practice in TB-endemic countries/regions. Here, we develop a molecular signature composed of non-canonical small non-coding RNAs in human peripheral blood mononuclear cells (PBMCs), including tRNA-derived small RNAs (tsRNAs), rRNA-derived small RNAs (rsRNAs), and YRNA-derived small RNAs (ysRNAs). This signature consists of i) the tsRNAs derived from tRNA-Ala, tRNA-Asn, tRNA-Leu, tRNA-Lys, and tRNA-Tyr that are upregulated in the lung cancer patients relative to the healthy controls and patients with pulmonary TB, ii) the rsRNAs derived from rRNA-5S that are upregulated in the lung cancer patients but downregulated in TB patients relative to the controls, and iii) the ysRNAs originating from YRNA-RNY1 that are downregulated in the lung cancer patients but upregulated in the TB patients compared with the controls. This diagnostic signature discriminates between healthy controls, lung cancer patients, and pulmonary TB subjects with high accuracy in both the discovery and validation cohorts. We conclude that the PBMC tsRNAs, rsRNAs, and ysRNAs are informative for both screening for and discriminating between lung cancer and pulmonary TB. SOURCE: Musheng Li (mushengl@unr.edu) - University of Nevada, Reno
View on GEOView in PlutoKey Features
Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreAnalyze and visualize data for this experiment
Use Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.
Read about post-pipeline analysisView QC data and experiment metadata
View quality control data and experiment metadata for this experiment.
Request import of other GEO data
Request imports from GEO or TCGA directly within Pluto Bio.
Chat with our Scientific Insights team