Thompson Ethan G, Du Ying, Malherbe Stephanus T, Shankar Smitha, Braun Jackie, Valvo Joe, Ronacher Katharina, Tromp Gerard, Tabb David L, Alland David, Shenai Shubhada, Via Laura E, Warwick James, Aderem Alan, Scriba Thomas J, Winter Jill, Walzl Gerhard, Zak Daniel E
The Center for Infectious Disease Research, Seattle, WA, USA.
Department of Science and Technology, National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa; South African Medical Research Council, Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Tuberculosis (Edinb). 2017 Dec;107:48-58. doi: 10.1016/j.tube.2017.08.004. Epub 2017 Aug 12.
Biomarkers for tuberculosis treatment outcome will assist in guiding individualized treatment and evaluation of new therapies. To identify candidate biomarkers, RNA sequencing of whole blood from a well-characterized TB treatment cohort was performed. Application of a validated transcriptional correlate of risk for TB revealed symmetry in host gene expression during progression from latent TB infection to active TB disease and resolution of disease during treatment, including return to control levels after drug therapy. The symmetry was also seen in a TB disease signature, constructed from the TB treatment cohort, that also functioned as a strong correlate of risk. Both signatures identified patients at risk of treatment failure 1-4 weeks after start of therapy. Further mining of the transcriptomes revealed an association between treatment failure and suppressed expression of mitochondrial genes before treatment initiation, leading to development of a novel baseline (pre-treatment) signature of treatment failure. These novel host responses to TB treatment were integrated into a five-gene real-time PCR-based signature that captures the clinically relevant responses to TB treatment and provides a convenient platform for stratifying patients according to their risk of treatment failure. Furthermore, this 5-gene signature is shown to correlate with the pulmonary inflammatory state (as measured by PET-CT) and can complement sputum-based Gene Xpert for patient stratification, providing a rapid and accurate alternative to current methods.
结核病治疗结果的生物标志物将有助于指导个体化治疗和新疗法的评估。为了确定候选生物标志物，对一个特征明确的结核病治疗队列的全血进行了RNA测序。应用经过验证的结核病风险转录相关指标，发现在从潜伏性结核感染进展到活动性结核病以及治疗期间疾病消退过程中，宿主基因表达存在对称性，包括药物治疗后恢复到对照水平。在由结核病治疗队列构建的结核病疾病特征中也观察到了这种对称性，该特征也与风险密切相关。这两种特征都能在治疗开始后1 - 4周识别出有治疗失败风险的患者。对转录组的进一步挖掘揭示了治疗失败与治疗开始前线粒体基因表达受抑制之间的关联，从而形成了一种新的治疗失败基线（治疗前）特征。这些对结核病治疗的新型宿主反应被整合到一个基于五基因实时PCR的特征中，该特征能够捕捉对结核病治疗的临床相关反应，并为根据患者治疗失败风险进行分层提供了一个便捷的平台。此外，这个五基因特征显示与肺部炎症状态（通过PET - CT测量）相关，并且可以补充基于痰液的Gene Xpert进行患者分层，为当前方法提供了一种快速准确的替代方法。
