The research progress of 3-gene host transcriptional biomarkers (GBP5, DUSP3 and KLF2)

doi:10.19982/j.issn.1000-6621.20210660

Abstract

Abstract:

Tuberculosis remains a major public health problem in the world. Especially in developing countries, there has a serious threat to human health. Further achieving the WHO’s goal of “End TB” by 2035, there urgently need new, fast, accurate and affordable detecting techniques for diagnosing TB and monitoring treatment responses. There have researches that shown to improve the tuberculosis clinical diagnosis and treatment monitoring with a 3-gene transcriptional biomarkers including guanylate binding protein5 (GBP5), dual specificity phosphatase3 (DUSP3) and Krüppel-like transcription factor2 (KLF2). To better understanding its clinical value, we have briefly summarized the finding, development, clinical importance and limitations of 3-gene host transcriptional biomarkers.

Key words: Tuberculosis, Guanylate binding protein5 (GBP5), Dual specificity phosphatase3 (DUSP3), Krüppel-like transcription factor2 (KLF2)

CLC Number:

R521
R786

HAN Ting-ting, CHEN Qiu-qi, DENG Guo-fang. The research progress of 3-gene host transcriptional biomarkers (GBP5, DUSP3 and KLF2)[J]. Chinese Journal of Antituberculosis, 2022, 44(2): 193-196. doi: 10.19982/j.issn.1000-6621.20210660

References 27

[1]	Singhania A, Wilkinson RJ, Rodrigue M, et al. The value of transcriptomics in advancing knowledge of the immune response and diagnosis in tuberculosis. Nat Immunol, 2018, 19(11):1159-1168. doi: 10.1038/s41590-018-0225-9. doi: 10.1038/s41590-018-0225-9 pmid: 30333612
[2]	Denkinger CM, Kik SV, Cirillo DM, et al. Defining the Needs for Next Generation Assays for Tuberculosis. J Infect Dis, 2015, 211(suppl_2):S29-S38. doi: 10.1093/infdis/jiu821. doi: 10.1093/infdis/jiu821 URL
[3]	World Health Organization. Global Tuberculosis Report 2021. Geneva: World Health Organization, 2021.
[4]	Tan Y, Tan Y, Li J, et al. Combined IFN-γ and IL-2 release assay for detect active pulmonary tuberculosis: a prospective multicentre diagnostic study in China. J Transl Med, 2021, 19(1):289. doi: 10.1186/s12967-021-02970-8. doi: 10.1186/s12967-021-02970-8 URL
[5]	Hoang LT, Jain P, Pillay TD, et al. Transcriptomic signatures for diagnosing tuberculosis in clinical practice: a prospective, multicentre cohort study. Lancet Infect Dis, 2021, 21(3):366-375. doi: 10.1016/S1473-3099(20)30928-2. doi: 10.1016/S1473-3099(20)30928-2 pmid: 33508221
[6]	Roe JK, Thomas N, Gil E, et al. Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis. JCI Insight, 2016, 1(16):e87238. doi: 10.1172/jci.insight.87238. doi: 10.1172/jci.insight.87238
[7]	Sweeney TE, Braviak L, Tato CM, et al. Genome-wide expression for diagnosis of pulmonary tuberculosis: a multicohort analysis. Lancet Respir Med, 2016, 4(3):213-224. doi: 10.1016/S2213-2600(16)00048-5. doi: 10.1016/S2213-2600(16)00048-5 URL
[8]	Blankley S, Berry MP, Graham CM, et al. The application of transcriptional blood signatures to enhance our understanding of the host response to infection: the example of tuberculosis. Philos Trans R Soc Lond B Biol Sci, 2014, 369(1645):20130427. doi: 10.1098/rstb.2013.0427. doi: 10.1098/rstb.2013.0427 URL
[9]	Zak DE, Penn-Nicholson A, Scriba TJ, et al. A blood RNA signature for tuberculosis disease risk: a prospective cohort study. Lancet, 2016, 387(10035):2312-2322. doi: 10.1016/S0140-6736(15)01316-1. doi: 10.1016/S0140-6736(15)01316-1 URL
[10]	Warsinske H, Vashisht R, Khatri P. Host-response-based gene signatures for tuberculosis diagnosis: A systematic comparison of 16 signatures. PLoS Med, 2019, 16(4):e1002786. doi: 10.1371/journal.pmed.1002786. doi: 10.1371/journal.pmed.1002786 URL
[11]	Thompson EG, Du Y, Malherbe ST, et al. Host blood RNA signatures predict the outcome of tuberculosis treatment. Tuberculosis (Edinb), 2017, 107:48-58. doi: 10.1016/j.tube.2017.08.004. doi: 10.1016/j.tube.2017.08.004 URL
[12]	Chen JX, Han YS, Zhang SQ, et al. Novel therapeutic evaluation biomarkers of lipid metabolism targets in uncomplicated pulmonary tuberculosis patients. Signal Transduct Target Ther, 2021, 6(1):22. doi: 10.1038/s41392-020-00427-w. doi: 10.1038/s41392-020-00427-w URL
[13]	Bloom CI, Graham CM, Berry MPR, et al. Detectable Changes in The Blood Transcriptome Are Present after Two Weeks of Antituberculosis Therapy. PLoS One, 2012, 7(10):e46191. doi: 10.1371/journal.pone.0046191. doi: 10.1371/journal.pone.0046191 URL
[14]	Satproedprai N, Wichukchinda N, Suphankong S, et al. Diagnostic value of blood gene expression signatures in active tuberculosis in Thais: a pilot study. Genes Immun, 2015, 16(4):253-260. doi: 10.1038/gene.2015.4. doi: 10.1038/gene.2015.4 pmid: 25764116
[15]	O’Garra A, Berry MPR, Graham CM, et al. An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis. Nature, 2010, 466(7309):973-977. doi: 10.1038/nature09247. doi: 10.1038/nature09247 URL
[16]	Bayaa R, Ndiaye M, Chedid C, et al. Multi-country evaluation of RISK6, a 6-gene blood transcriptomic signature, for tuberculosis diagnosis and treatment monitoring. Sci Rep, 2021, 11(1):13646. doi: 10.1038/s41598-021-93059-1. doi: 10.1038/s41598-021-93059-1 pmid: 34211042
[17]	Sambarey A, Devaprasad A, Mohan A, et al. Unbiased Identification of Blood-based Biomarkers for Pulmonary Tuberculosis by Modeling and Mining Molecular Interaction Networks. EBioMedicine, 2017, 15:112-126. doi: 10.1016/j.ebiom.2016.12.009. doi: S2352-3964(16)30588-6 pmid: 28065665
[18]	MacLean E, Broger T. A 10-Gene Signature for the Diagnosis and Treatment Monitoring of Active Tuberculosis Using a Molecular Interaction Network Approach. EBioMedicine, 2017, 16(C):22-23. doi: 10.1016/j.ebiom.2017.01.017. doi: 10.1016/j.ebiom.2017.01.017 URL
[19]	Heyckendorf J, Marwitz S, Reimann M, et al. Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model. Eur Respir J, 2021, 58(3):2003492. doi: 10.1183/13993003.03492-2020. doi: 10.1183/13993003.03492-2020 URL
[20]	Sivakumaran D, Jenum S, Vaz M, et al. Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes. Commun Biol, 2020, 3(1):359. doi: 10.1038/s42003-020-1087-x. doi: 10.1038/s42003-020-1087-x URL
[21]	Francisco NM, Fang YM, Ding L, et al. Diagnostic accuracy of a selected signature gene set that discriminates active pulmonary tuberculosis and other pulmonary diseases. J Infect, 2017, 75(6):499-510. doi: 10.1016/j.jinf.2017.09.012. doi: 10.1016/j.jinf.2017.09.012 URL
[22]	Warsinske HC, Rao AM, Moreira F, et al. Assessment of Validity of a Blood-Based 3-Gene Signature Score for Progression and Diagnosis of Tuberculosis, Disease Severity, and Treatment Response. JAMA Netw Open, 2018, 1(6):e183779. doi: 10.1001/jamanetworkopen.2018.3779. doi: 10.1001/jamanetworkopen.2018.3779 URL
[23]	Zimmer AJ, Schumacher SG, Sodersten E, et al. A novel blood-based assay for treatment monitoring of tuberculosis. BMC Res Notes, 2021, 14(1):247. doi: 10.1186/s13104-021-05663-z. doi: 10.1186/s13104-021-05663-z URL
[24]	Suárez I, Fünger SM, Kröger S, et al. The Diagnosis and Treatment of Tuberculosis. Dtsch Arztebl Int, 2019, 116(43):729-735. doi: 10.3238/arztebl.2019.0729. doi: 10.3238/arztebl.2019.0729
[25]	Koo H, Min J, Kim HW, et al. Prediction of treatment failure and compliance in patients with tuberculosis. BMC Infect Dis, 2020, 20(1):622. doi: 10.1186/s12879-020-05350-7. doi: 10.1186/s12879-020-05350-7 URL
[26]	Södersten E, Ongarello S, Mantsoki A, et al. Diagnostic Accuracy Study of a Novel Blood-Based Assay for Identification of Tuberculosis in People Living with HIV. J Clin Microbiol, 2021, 59(3). doi: 10.1128/JCM.01643-20. doi: 10.1128/JCM.01643-20
[27]	Turner CT, Gupta RK, Tsaliki E, et al. Blood transcriptional biomarkers for active pulmonary tuberculosis in a high-burden setting: a prospective, observational, diagnostic accuracy study. Lancet Respir Med, 2020, 8(4):407-419. doi: 10.1016/S2213-2600(19)30469-2. doi: 10.1016/S2213-2600(19)30469-2 URL