Related Experiment Video
Updated: Aug 16, 2026
Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor
Published on: August 25, 2023
Identifying candidate therapeutic targets in amyotrophic lateral sclerosis through a transcriptome-wide
Enrique J de Andrés-Galiana1, Juan Luis Fernández-Martínez2, Germán Morís3
1Group of Inverse Problems, Optimization and Machine Learning, Department of Mathematics, University of Oviedo, Oviedo, Spain; Department of Computer Science, University of Oviedo, Oviedo, Spain.
None:
Amyotrophic lateral sclerosis (ALS) is a heterogeneous neurodegenerative disease for which effective disease-modifying therapies remain limited. This study aimed to derive internally recurrent ALS-associated transcriptional signatures and generate directionally interpretable drug-repositioning hypotheses using a consensus machine-learning framework. Two publicly available transcriptomic datasets from motor cortex (E-MTAB-2325) and blood (E-TABM-940) were analyzed using four feature-selection methods within 100 repetitions of 4-fold cross-validation. Probes recurrently selected in models achieving an accuracy of at least 0.90 were prioritized and examined using COGENA pathway enrichment and Connectivity Map drug-signature analysis. Fifteen qualifying models were obtained for the motor-cortex dataset and 55 for the blood dataset. No exact prioritized gene or probe identifier was shared between the two top-100 signatures, but pathway-level integration identified complementary evidence involving glial and immune regulation, proteostasis and vesicle trafficking, MAPK-related stress signaling, cytoskeletal and extracellular remodeling, and RNA-related processes. The motor-cortex dataset additionally emphasized astroglial support, glutamate handling, and inclusion-body regulation, whereas the blood dataset highlighted cytokine regulation and directionally heterogeneous immune, mitochondrial, and metabolic signals. Deferoxamine and disulfiram showed the clearest reversal-compatible profiles in motor cortex, whereas yohimbic acid and atovaquone showed reversal-compatible profiles in blood. Ciprofloxacin, prochlorperazine, and a compound group led by androsterone instead showed concordant connectivity. The results provide transparent, hypothesis-generating gene, pathway, and compound priorities, but they do not establish biomarkers, therapeutic efficacy, or clinical suitability and require validation in independent cohorts and experimental ALS models.
