Identification of Potential Biomarkers and Related Transcription Factors in Peripheral Blood of Tuberculosis Patients

Xie, Longxiang; Chao, Xiaoyu; Teng, Tieshan; Xie, Jingwei

doi:10.3390/ijerph17196993

Cited by 11 publications

(9 citation statements)

References 29 publications

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“…To systematically explore the roles of the lncRNA-associated genes, we further performed functional enrichment analysis on their mRNAs to conduct the significant correlation ( P < 0.05) with the corresponding lncRNAs by Metascape ( 11 ). The AL138831.2-correlated genes were significantly enriched in DNA repair, peptidyl-lysine modification, and negative regulation of I-κB kinase/NF-κB signalling pathways ( Figures 3A, B ).…”

Section: Resultsmentioning

confidence: 99%

A Combined Long Noncoding RNA Signature as a Candidate Prognostic Biomarker for Ovarian Cancer

Wang

Yao

et al. 2021

Front. Oncol.

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AimsDysregulated long noncoding RNAs (lncRNAs) contributing to ovarian cancer (OC) development may serve as prognostic biomarker. We aimed to explore a lncRNA signature to serve as prognostic biomarker of OC.MethodsUnivariate Cox regression was conducted on the lncRNA expression dataset from the TCGA cohort, and 246 genes significantly associated with survival were retained for building a model. A random forest survival model was carried out, and a model was developed using 6 genes with the highest frequency. The selected genes were applied in a Cox multivariate regression model for prognostic prediction by calculating the risk score. We also used CCK-8, EdU, and colony formation assays to validate the function of these lncRNAs in OC cells.ResultsThis study confirmed that the 6-lncRNA combined signature was related to OC prognosis. Systematic analysis demonstrated that lncRNA-associated genes were enriched in oncogenic signalling pathways. Five out of the 6 lncRNAs participated in OC proliferation.ConclusionWe established a 6-lncRNA combined signature for OC prognosis, which may serve as powerful prognostic biomarker for OC after further validation.

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Section: Resultsmentioning

confidence: 99%

A Combined Long Noncoding RNA Signature as a Candidate Prognostic Biomarker for Ovarian Cancer

Wang

Yao

et al. 2021

Front. Oncol.

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“…Similar to PRKAR1B, when comparing TB-T2D with T2D patients, an eQTL (rs56369375) of Khoe-San ancestry origin was identified using LocalAA while adjusting for Khoe-San ancestry. ARID3A is a potential biomarker for TB diagnosis and treatment response in peripheral blood of TB patients [17]. In addition,…”

Section: Discussionmentioning

confidence: 99%

cis-eQTL mapping of TB-T2D comorbidity elucidates the involvement of African ancestry in TB susceptibility

Swart

Uren

Eckold

et al. 2022

Preprint

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The validation of genome-wide association signals for tuberculosis (TB) susceptibility and the development of type 2 diabetes (T2D) across diverse populations remain problematic. The ancestry-specific variants (coding and non-coding) that contribute to previously identified differentially expressed genes (DEG) in patients with TB, T2D and comorbid TB-T2D, remain unknown. Identifying ancestry-specific expression quantitative trait loci (eQTLs) can aid in distinguishing the most probable disease-causing variants for population-specific therapeutic interventions. Therefore, this study conducted cis-eQTL mapping in TB, T2D and TB-T2D patients to identify variants associated with DEG. Both genotyping (Infinium H3A array with ~2.3 M markers) and RNA sequencing data of 96 complex multi-way admixed South Africans were used for this purpose. Importantly, both global-and local ancestry adjustment were included in statistical analysis to account for complex admixture. Unique gene-variant pairs were associated with TB-T2D on chromosome 7p22 whilst adjusting for Bantu-speaking African ancestry (PRKAR1B:rs4464850; P=7.68e-07) and Khoe-San ancestry (PRKAR1B:rs117842122; P=3.66e-07). In addition, IFITM3 (a biomarker for the development of TB) was associated with three SNPs (rs11025530, rs3808990, and rs10896664) on chromosome 11p15 while adjusting for Khoe-San ancestry. Our results also indicated that the upregulation of the NLRP6 inflammasome is strongly associated with people with TB-T2D while adjusting for Khoe-San ancestry. Three African-specific eGenes (NLRP6, IFITM3 and PRKAR1B) would have been missed if local ancestry adjustment was not conducted. This study determined a list of ancestry-specific eQTLs in TB-T2D patients that could potentially guide the search for new therapeutic targets for TB-T2D in African populations.

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“…Although these OP-related core genes have been validated by other laboratories, they failed to identify them as hub genes of SCI-induced OP as we did in our computational analysis. It is also extremely familiar that many potential biomarkers were obtained by text mining and bioinformatical analysis with or without verification, finally guiding us to later experimental and mining candidate medicines ( 64 , 65 ), which offered us a new study project that hub genes screened out by text mining combining with known genes are likely to construct novel mechanisms.…”

Section: Discussionmentioning

confidence: 99%

Drug discovery in spinal cord injury-induced osteoporosis: a text mining-based study

Wang¹,

Xu²,

Han³

et al. 2022

Ann Transl Med

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Background Spinal cord injury (SCI) and osteoporosis (OP) are common diseases in spine surgery, and OP could be the complication of SCI. However, SCI-induced OP is a complex pathologic process and drug discovery is limited, which restricts the study in the mechanism and treatment of the disease. This study aims to identify the genes and molecular pathways related to SCI-induced OP through computational tools and public datasets, and to explore drug targeting therapy, ultimately preventing the occurrence of OP after SCI. Methods In this study, common genes related to SCI and OP were obtained by text mining, then which conducted the functional analysis. Protein-protein interaction (PPI) networks were constructed by STRING online and Cytoscape software. Finally, core genes and potential drugs were performed after undergoing drug-gene interaction analysis which also completed functional analysis. Results A total of 371 genes common to ‘SCI’ and ‘OP’ were identified by text mining. After functional analysis, 207 significant genes were screened out. Subsequently, PPI analysis yielded 23 genes targetable by 13 drugs which were the candidate to treat SCI-induced OP. Conclusions Taken together, siltuximab, olokizumab, clazakizumab and BAN2401 were first discovered to become the potential drugs for the treatment of SCI-induced OP. Drug discovery using text mining and pathway analysis is a significant way to investigate the pathomechanism of the disease while exploring existing drugs to treat the disease.

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Identification of Potential Biomarkers and Related Transcription Factors in Peripheral Blood of Tuberculosis Patients

Cited by 11 publications

References 29 publications

A Combined Long Noncoding RNA Signature as a Candidate Prognostic Biomarker for Ovarian Cancer

A Combined Long Noncoding RNA Signature as a Candidate Prognostic Biomarker for Ovarian Cancer

cis-eQTL mapping of TB-T2D comorbidity elucidates the involvement of African ancestry in TB susceptibility

Drug discovery in spinal cord injury-induced osteoporosis: a text mining-based study

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