ArticleMediators of inflammation2023
RTP4, a Biomarker Associated with Diagnosing Pulmonary Tuberculosis and Pan-Cancer Analysis.
Article in Mediators of inflammation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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
5 citing papers in PubMed, 7 citations in OpenAlex.
- Pipettes and Pipelines: The Weapons of Omics Sciences for a New Age of Clinical Studies.Current issues in molecular biology · 2026Review
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- Identification of Crohn's Disease-Related Biomarkers and Pan-Cancer Analysis Based on Machine Learning.Mediators of inflammation · 2025Article
- Serum Ceruloplasmin-to-Albumin Ratio as a Biochemical Marker in Pulmonary Tuberculosis Before and After Treatment.Cureus · 2024Article
- Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Pulmonary tuberculosis (PTB) is a global epidemic of infectious disease; the purpose of our study was to explore new potential biomarkers for the diagnosis of pulmonary tuberculosis and to use the biomarkers for further pan-cancer analysis. Methods: Four microarray gene expression sets were downloaded from the GEO public databases and conducted for further analysis. Healthy control (HC) samples and samples of pulmonary tuberculosis (PTB) were calculated with enrichment scores in folate biosynthesis pathways. The scores acted as a new phenotype combined with clinical information (control or PTB) for subsequent analysis. Weight gene coexpression network analysis (WGCNA) was used to seek the modules mostly related to PTB and folate biosynthesis in training sets. Twenty-nine coexistence genes were screened by intersecting the genes in the green-yellow module of GSE28623 and the brown module of GSE83456. We used the protein-protein interaction network analysis to narrow the gene range to search for hub genes. Then, we downloaded the unified and standardized pan-cancer data set from the UCSC database for correlations between biomarkers and prognosis and tumor stage differences. Results: Eventually, RTP4 was selected as a biomarker. To verify the reliability of this biomarker, an area under the ROC (AUC) was calculated in gene sets (GSE28623, GSE83456, and GSE34608). Lastly, to explore the difference in RTP4 expression before and after antituberculosis treatment, the GSE31348 gene set was enrolled to compare the expressions in weeks 0 and 26. The results showed significant differences between these two time points ( Conclusion: RTP4 might be a new potential biomarker for diagnosing pulmonary tuberculosis.
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Registered trials
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