Project description:Combination of new therapeutics with trans-retinoic acid (ATRA) could improve efficiency of acute myeloid leukemia (AML) treatment. Modeling the process of ATRA-induced differentiation based on transcriptomic profile of leukemic cells allows us to identify key molecules that could be affected to enhance the therapeutic effect of ATRA. Moreover, transcriptome analysis reveals the earliest steps of molecular response to inducer treatment. Thus, the transcriptomic profile of leukemic cells under the ATRA treatment at the different time points is considered as input data for further upstream regulator search.

2024-10-17 | E-MTAB-13723 | biostudies-arrayexpress

Synergy from Gene Expression and Network Mining (SynGeNet) method predicts genotype-specific synergistic drug combinations in melanoma

Project description:Using our computational method SynGeNet to evaluate genomic and transcriptomic data characterizing four major genomic subtypes of melanoma, we selected the top ranked drug combination for BRAF-mutation melanoma for subsequent validaiton. Here we present drug-induced gene expression data from the BRAF-mutant A375 melanoma cell line in response to four treatment conditions: vehicle control (DMSO), vemurafenib alone, tretinoin (ATRA) alone and vemurafenib+tretinoin combination.

2018-07-01 | GSE109731 | GEO

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