Project description:Treatment of established lines and primary ovarian cancer cultures with Src and MEK inhibitors, saracatinib and selumetinib, respectively, showed target kinase inhibition and synergistic induction of apoptosis and cell cycle arrest in vitro and tumor inhibition in xenografts.
Project description:We identified IGF2BP1 as a marker of the C5 molecular subtype of high-grade ovarian carcinoma (HG-SOC). IGF2BP1 promotes SRC activity and ERK2 expression enhancing the tolerance towards SRC- and MEK-directed inhibitors saracatinib and selumetib. Combination treatment overcomes IGF2BP1-promoted resistance.
Project description:A major component of the cardiac stress response is the simultaneous activation of several gene regulatory networks. Interestingly, the transcriptional regulator steroid receptor coactivator-2, SRC-2 is often decreased during cardiac failure in humans. We postulated that SRC-2 suppression plays a mechanistic role in the stress response and that SRC-2 activity is an important regulator of the adult heart gene expression profile. Genome-wide microarray analysis, confirmed with targeted gene expression analyses revealed that genetic ablation of SRC-2 activates the “fetal gene program” in adult mice as manifested by shifts in expression of a) metabolic and b) sarcomeric genes, as well as associated modulating transcription factors. While these gene expression changes were not accompanied by changes in left ventricular weight or cardiac function, imposition of transverse aortic constriction (TAC) predisposed SRC-2 knockout (KO) mice to stress-induced cardiac dysfunction. In addition, SRC-2 KO mice lacked the normal ventricular hypertrophic response as indicated through heart weight, left ventricular wall thickness, and blunted molecular signaling known to activate hypertrophy. Our results indicate that SRC-2 is involved in maintenance of the steady-state adult heart transcriptional profile, with its ablation inducing transcriptional changes that mimic a stressed heart. These results further suggest that SRC-2 deletion interferes with the timing and integration needed to respond efficiently to stress through disruption of metabolic and sarcomeric gene expression and hypertrophic signaling, the three key stress responsive pathways.
Project description:We sought to detect predictive markers related to a Src kinase inhibitor (saracatinib) sensitivity in ovarian cancer. Cell proliferation assays assigned 18 ovarian cancer cell lines to sensitive or resistant to this drug. Using baseline gene expression data from these 18 cell lines, we sought to identify differentially expressed genes correlated with saracatinib sensitivity. We also used SNP array data from 7 cell lines to detect differentically affected genomic locations.
Project description:A major component of the cardiac stress response is the simultaneous activation of several gene regulatory networks. Interestingly, the transcriptional regulator steroid receptor coactivator-2, SRC-2 is often decreased during cardiac failure in humans. We postulated that SRC-2 suppression plays a mechanistic role in the stress response and that SRC-2 activity is an important regulator of the adult heart gene expression profile. Genome-wide microarray analysis, confirmed with targeted gene expression analyses revealed that genetic ablation of SRC-2 activates the M-bM-^@M-^\fetal gene programM-bM-^@M-^] in adult mice as manifested by shifts in expression of a) metabolic and b) sarcomeric genes, as well as associated modulating transcription factors. While these gene expression changes were not accompanied by changes in left ventricular weight or cardiac function, imposition of transverse aortic constriction (TAC) predisposed SRC-2 knockout (KO) mice to stress-induced cardiac dysfunction. In addition, SRC-2 KO mice lacked the normal ventricular hypertrophic response as indicated through heart weight, left ventricular wall thickness, and blunted molecular signaling known to activate hypertrophy. Our results indicate that SRC-2 is involved in maintenance of the steady-state adult heart transcriptional profile, with its ablation inducing transcriptional changes that mimic a stressed heart. These results further suggest that SRC-2 deletion interferes with the timing and integration needed to respond efficiently to stress through disruption of metabolic and sarcomeric gene expression and hypertrophic signaling, the three key stress responsive pathways. For microarray analysis, 250ng of RNA isolated from total heart (RNeasy kit, Qiagen) for each sample was labeled using the new standard Affymetrix linear amplification protocol using the 3' IVT Express Kit. This was reverse-transcribed and cRNA was produced and biotinylated via in vitro transcription. A hybridization cocktail containing Affymetrix spike-in controls and 15 M-NM-<g fragmented, labeled cRNA was loaded onto a GeneChipM-BM-. Mouse 430 2.0 array. The array was hybridized for 16 hours at 45M-BM-0C with rotation at 60 rpm then washed and stained with a strepavidin, R-phycoerythrin conjugate stain using the FS 450_0001 Fluidics protocol setting. Signal amplification was done using biotinylated antistreptavidin. The stained array was scanned on the Affymetrix GeneChipM-BM-. Scanner 3000. The images were analyzed and quality control metrics recorded using Affymetrix Command Console v3. Experiments were run using Affymetrix MG 430 2.0 chip with 45,101 probesets representing 20,757 unique genes. There were 8 experiments in 2 groups: WT-unstressed M-bM-^@M-^S 4 experiments, and KO-unstressed M-bM-^@M-^S 4 experiments. QC parameters for all experiments were within the acceptable limits. We used the following software packages for data QC, statistical analysis and presentation of the results: Affymetrix Expression Console (www.affymetrix.com), Partek (www.partek.com), BRB Array Tools (linus.nci.nih.gov/BRB-ArrayTools.html), and dChip (biosun1.harvard.edu/complab/dchip). Expressions were estimated using the RMA (Multi-Array Analysis) method [38] with Partek software. Differentially expressed genes were found using the RVM (Random Variance Model) t-test, which is designed for small sample size experiments [39]. We used BRB Array Tools software, developed by Dr. Richard Simon and the BRB-ArrayTools Development Team. All genes were included in the comparison. For the genes represented by more than one probeset, we used the most highly expressed probeset. The cutoffs for differentially expressed genes were False Discovery Rate (FDR) = 0.05 [40].