Proteomic analysis to identification of hypoxia related markers in spinal tuberculosis: a study based on weighted gene co-expression network analysis and machine learning

This article aims at exploring the role of hypoxia-related genes and immune cells in spinal tuberculosis and tuberculosis involving other organs. In this study, label-free quantitative proteomics analysis was performed on the intervertebral discs (fibrous cartilaginous tissues) obtained from five sp...

Full description

Saved in:
Bibliographic Details
Published in:BMC medical genomics 2023-06, Vol.16 (1), p.142-142, Article 142
Main Authors: Wu, Shaofeng, Liang, Tuo, Jiang, Jie, Zhu, Jichong, Chen, Tianyou, Zhou, Chenxing, Huang, Shengsheng, Yao, Yuanlin, Guo, Hao, Ye, Zhen, Chen, Liyi, Chen, Wuhua, Fan, Binguang, Qin, Jiahui, Liu, Lu, Wu, Siling, Ma, Fengzhi, Zhan, Xinli, Liu, Chong
Format: Article
Language:English
Subjects:
Analysis
Atrophy
B cells
Calibration
Correlation analysis
Development and progression
Drug resistance
Gene set enrichment analysis
Genes
Genetic research
Health aspects
Humans
Hypoxia
Hypoxia - genetics
Infections
Inflammation
Intervertebral discs
Ions
Machine Learning
Membrane Transport Proteins
Methods
Multidrug resistance
Peptides
Pharmaco-transcriptomic analysis
Prevention
Proteasomes
Proteins
Proteomics
Risk factors
Software
Spinal tuberculosis
Spine
ssGSEA
Stat1 protein
Therapeutic targets
Transcriptomics
Tuberculosis
Tuberculosis, Extrapulmonary
Tuberculosis, Spinal - genetics
WGCNA
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This article aims at exploring the role of hypoxia-related genes and immune cells in spinal tuberculosis and tuberculosis involving other organs. In this study, label-free quantitative proteomics analysis was performed on the intervertebral discs (fibrous cartilaginous tissues) obtained from five spinal tuberculosis (TB) patients. Key proteins associated with hypoxia were identified using molecular complex detection (MCODE), weighted gene co-expression network analysis(WGCNA), least absolute shrinkage and selection operator (LASSO), and support vector machine recursive feature Elimination (SVM-REF) methods, and their diagnostic and predictive values were assessed. Immune cell correlation analysis was then performed using the Single Sample Gene Set Enrichment Analysis (ssGSEA) method. In addition, a pharmaco-transcriptomic analysis was also performed to identify targets for treatment. The three genes, namely proteasome 20 S subunit beta 9 (PSMB9), signal transducer and activator of transcription 1 (STAT1), and transporter 1 (TAP1), were identified in the present study. The expression of these genes was found to be particularly high in patients with spinal TB and other extrapulmonary TB, as well as in TB and multidrug-resistant TB (p-value 
ISSN:1755-8794
1755-8794
DOI:10.1186/s12920-023-01566-z