Project description:We devised a high-throughput, cell-based assay to identify novel therapeutic compounds to treat Group3 medulloblastoma (G3 MB). Mouse G3 MBs, grown as neurospheres, were screened against a library of approximately 7,000 compounds including FDA-approved drugs. We identified two FDA-approved drugs, pemetrexed and gemcitabine that preferentially inhibited tumor proliferation in vitro compared to control neurospheres, and substantially inhibited tumor proliferation in vivo. When combined, the two drugs significantly increased survival P7 Trp53-/-, Cdkn2c-/- neurospheres and MYC mouse cells were compared treated and untreated with drugs pemetrexed+gemcitabine
Project description:miR-17-92 mediates the MYC oncogene addiction in a conditional mouse lymphoma model. To identify targets of miR-17-92 in this model, miR-17-92 was expressed in the conditional lymphoma cell lines using MSCV-puro. Both control and miR-17-92-expressing conditional lymphoma cell lines were treated with doxycycline (DOX) (20ng/ml) for 48 hours to shut off MYC expression.
Project description:We devised a high-throughput, cell-based assay to identify novel therapeutic compounds to treat Group3 medulloblastoma (G3 MB). Mouse G3 MBs, grown as neurospheres, were screened against a library of approximately 7,000 compounds including FDA-approved drugs. We identified two FDA-approved drugs, pemetrexed and gemcitabine that preferentially inhibited tumor proliferation in vitro compared to control neurospheres, and substantially inhibited tumor proliferation in vivo. When combined, the two drugs significantly increased survival
Project description:Seventy-six FDA approved oncology drugs and emerging therapeutics were evaluated in 25 multiple myeloma (MM) and 15 non-Hodgkin’s lymphoma cell lines and in 113 primary MM samples. Ex vivo drug sensitivities were mined for associations with clinical phenotype, cytogenetic, genetic mutation and transcriptional profiles. We investigated the predictive value of anti-apoptotic BCL2 family member transcriptomic ratios as biomarkers of venetoclax sensitivity. RNA-seq analysis was available in 38 primary patient samples, from which we identified the 9 most (median AUC 0.09409) and least (median AUC 0.7195) sensitive samples to venetoclax.
Project description:miR-17-92 mediates the MYC oncogene addiction in a conditional mouse lymphoma model. To identify targets of miR-17-92 in this model, miR-17-92 was expressed in the conditional lymphoma cell lines using MSCV-puro.
Project description:Identifying the Mechanism of Action (MoA) of drugs is critical for the development of new drugs, understanding their side effects, and drug repositioning. However, identifying drug MoA has been challenging and has been traditionally attempted only though large experimental setups with little success. While advances in computational power offers the opportunity to achieve this in-silico, methods to exploit existing computational resources are still in their infancy. To overcome this, we developed a novel method to identify Drug Mechanism of Action using Network Dysregulation (DeMAND). The method is based on the realization that drugs affect the protein activity of their targets, but not necessarily their mRNA expression levels. In contrast, the change in protein activity directly affects the mRNA expression levels of downstream genes. Based on this hypothesis, DeMAND identifies drug MoA by comparing gene expression profiles following drug perturbation with control samples, and computing the change in the individual interactions within a pre-determined integrated transcriptional and post-translational regulatory model (interactome). This dataset includes GEPs in 3 different B-cell lymphoma cell lines (OCI-LY3, OCI-LY7 and U2932) at 6, 12, and 24hrs. 92 FDA approved compounds were used at a concentration of IC20 at 24h. DMSO was used as control at each time-point. A total of 828 samples and 29 control samples were available for analysis. Total RNA was isolated with the RNAqueous-96 Automated Kit (Ambion) on the Janus automated liquid handling system (Perkin Elmer Inc.), quantified by NanoDrop 6000 spectrophotometer and quality checked by Agilent Bioanalyzer. 300ng of each of the samples with RIN value >7 were converted to biotinylated cRNA with the Illumina TotalPrep-96 RNA Amplification Kit (Ambion) using a standard T7-based amplification protocol and hybridized on the Human Genome U219 96-Array Plate (Affymetrix). Hybridization, washing, staining and scanning of the array plates were performed on the GeneTitan Instrument (Affymetrix) according to manufacturer’s protocols.
Project description:Cancer cells are plastic, switching between signaling pathways to regulate growth under different conditions. In the tumor microenvironment this likely helps them evade therapies that target specific pathways. We must identify all possible signaling states and utilize them in drug screening programs to. One such state is characterized by expression of the transcription factor Hes3 and sensitivity to Hes3 knockdown and can be modeled in vitro by the use of defined culture conditions. Here we modeled this state in vitro, characterized it, and used it to identify drugs that target it. We cultured three primary human brain cancer cell lines, each from a different patient, under three different culture conditions (low, medium, and high Hes3 expression) and characterized gene regulation (RNA sequencing) and mechanical phenotype (real-time deformability assay). We also assessed gene expression regulation following Hes3 knockdown in conditions that maintain high Hes3 expression. We then employed a commonly used human brain tumor cell line to screen 1,600 FDA-approved compounds that specifically target the Hes3-high state in two different culture conditions (high and low Hes3). Cells from multiple patients behave similarly when placed under distinct culture conditions, in the assays described. We identified 37 FDA-approved compounds that specifically kill cancer cells in conditions characterized by high but not those characterized by low Hes3 expression. Our work reveals novel, potentially core signaling states in cancer, a strategy to identify treatments against them, and a set of putative drugs for potential repurposing.
Project description:We present paired ATAC and RNA-sequencing from EGFR-driven lung cancer cell lines genetically modified to lose tumor suppressors RB1 and/or PTEN, and study the acute response of these cell lines to FDA-approved chemical inhibitors of EGFR