Innate biosignature of treatment failure in human cutaneous leishmaniasis

María Adelaida Gómez (), Ashton Trey Belew, Deninson Alejandro Vargas, Lina Giraldo-Parra, Neal Alexander, David E. Rebellón-Sánchez, Theresa A. Alexander and Najib M. El-Sayed ()
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María Adelaida Gómez: Centro Internacional de Entrenamiento e Investigaciones Médicas (CIDEIM)
Ashton Trey Belew: University of Maryland
Deninson Alejandro Vargas: Centro Internacional de Entrenamiento e Investigaciones Médicas (CIDEIM)
Lina Giraldo-Parra: Centro Internacional de Entrenamiento e Investigaciones Médicas (CIDEIM)
Neal Alexander: Centro Internacional de Entrenamiento e Investigaciones Médicas (CIDEIM)
David E. Rebellón-Sánchez: Centro Internacional de Entrenamiento e Investigaciones Médicas (CIDEIM)
Theresa A. Alexander: University of Maryland
Najib M. El-Sayed: University of Maryland

Nature Communications, 2025, vol. 16, issue 1, 1-14

Abstract: Abstract The quality and magnitude of the immune and inflammatory responses determine the clinical outcome of Leishmania infection, and contribute to the efficacy of antileishmanial treatments. However, the precise immune mechanisms involved in healing or in the chronic immunopathology of human cutaneous leishmaniasis (CL) are not well understood. Through sequential transcriptomic profiling of blood monocytes, neutrophils, and eosinophils over the course of systemic treatment with meglumine antimoniate, we revealed that a heightened and sustained Type-I interferon response signature is a hallmark of treatment failure (TF) in CL patients infected with Leishmania (Viannia) panamensis and L.V. braziliensis. The transcriptomes of pre-treatment, mid-treatment and end-of-treatment samples were interrogated to identify predictive and prognostic biomarkers of TF. A composite score derived from the expression of 11 differentially expressed genes (common between monocytes, neutrophils and eosinophils) is predictive of TF. Similarly, machine learning models constructed using data from pre-treatment as well as post-treatment samples, accurately classify treatment outcome into cure and TF. Results from this study instigate the evaluation of Type-I interferon responses as immunological targets for host-directed therapies for the treatment of CL, and highlight the feasibility of using transcriptional signatures as predictive biomarkers of outcome for therapeutic decision making.

Date: 2025
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DOI: 10.1038/s41467-025-58330-3

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