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dc.contributor.authorToro Domínguez, Daniel
dc.contributor.authorCarmona Sáez, Pedro
dc.identifier.citationToro-Domínguez, D., Lopez-Domínguez, R., García Moreno, A. et al. Differential Treatments Based on Drug-induced Gene Expression Signatures and Longitudinal Systemic Lupus Erythematosus Stratification. Sci Rep 9, 15502 (2019). []es_ES
dc.descriptionDaniel Toro is at present supported by structural funds to MEAR from the Fundación Pública Andaluza Progreso y Salud of the Junta de Andalucíaes_ES
dc.descriptionSupplementary information is available for this paper at
dc.description.abstractSystemic lupus erythematosus (SLE) is a heterogeneous disease with unpredictable patterns of activity. Patients with similar activity levels may have different prognosis and molecular abnormalities. In this study, we aimed to measure the main differences in drug-induced gene expression signatures across SLE patients and to evaluate the potential for clinical data to build a machine learning classifier able to predict the SLE subset for individual patients. SLE transcriptomic data from two cohorts were compared with drug-induced gene signatures from the CLUE database to compute a connectivity score that reflects the capability of a drug to revert the patient signatures. Patient stratification based on drug connectivity scores revealed robust clusters of SLE patients identical to the clusters previously obtained through longitudinal gene expression data, implying that differential treatment depends on the cluster to which patients belongs. The best drug candidates found, mTOR inhibitors or those reducing oxidative stress, showed stronger cluster specificity. We report that drug patterns for reverting disease gene expression follow the cell-specificity of the disease clusters. We used 2 cohorts to train and test a logistic regression model that we employed to classify patients from 3 independent cohorts into the SLE subsets and provide a clinically useful model to predict subset assignment and drug efficacy.es_ES
dc.description.sponsorshipThis work has been partially supported by Junta de Andalucía through grant PI-0173–2017. The Hopkins Lupus Cohort is supported by NIH AR RO1069572.es_ES
dc.publisherNature Researches_ES
dc.rightsAtribución 3.0 España*
dc.titleDifferential Treatments Based on Drug-induced Gene Expression Signatures and Longitudinal Systemic Lupus Erythematosus Stratificationes_ES

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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España