Gene expression-based, treatment response analyses using Nanostring nCounter

Manneh, IL and Sutherland, CJORCID logo (2025). Gene expression-based, treatment response analyses using Nanostring nCounter. [Dataset]. Gene Expression Omnibus. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE295312
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Background: Despite availability of effective treatment regimens for drug-susceptible TB, some patients still experience poor treatment outcomes. Currently tools for monitoring treatment outcomes are dependent on detection of mycobacteria in sputum, which are slow, expensive and poor at predicting relapse and failure. This study aims to identify new blood-derived markers for predicting treatment response and outcomes. Methods: Whole blood was collected in PAXgene tubes from patients with microbiologically confirmed TB at diagnosis, week 2, and at month 2, 4 and 6. Treatment response and outcomes were determined by culture and gene expression was compared between slow and fast responders; and between patients with good (cured) and poor treatment outcomes (failure and recurrent TB) using targeted RNA gene expression. Gene signatures were developed using random forest classification models. Results: Significant changes in gene expression were detected over the course of the TB treatment. Notably, major gene expression differences were observed at diagnosis between subsequently cured patients and patients who experienced poor treatment outcomes while minimal changes were detected between slow and fast responders among cured patients at diagnosis. A 7-gene end of treatment signature distinguished patients with good outcomes from those with poor treatment outcomes with AUCs of 0.91, 0.98, and 1.0 at baseline, month 2 and month 6 respectively. Additionally, a 6-gene month 2 signature discriminates slow from fast responders with AUCs of 0.49, 0.57, and 0.93 at diagnosis, week 2 and month 2 respectively. Conclusion: The study identified genes signatures associated with TB treatment response and outcomes suggesting potential utility for treatment monitoring

Additional Information

The dataset analyzed for this study can be found in Gene expression Omnibus (GEO) (Accession number GSE295312).

Keywords

Mycobacterium tuberculosis disease; treatment response; gene expression; Tuberculosis

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