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Inhibiting the interaction of cMET and IGF-1R with FAK effectively reduces growth of pancreatic cancer cells in vitro and in vivo.

ABSTRACT: Pancreatic cancer is one of the most lethal diseases with no effective treatment. Previously, we have shown that FAK is overexpressed in pancreatic cancer and plays a key role in cancer cell survival and proliferation. FAK has been shown to interact with growth factor receptors including cMET and IGF-1R. As a novel therapeutic approach, we targeted the protein interaction of FAK with growth factor receptors to block tumor growth, alter signaling pathways and sensitize cells to chemotherapy. We have selected a small molecule compound (INT2-31) that decreases phosphorylation of AKT via disrupting interaction of FAK with cMET and IGF-1R. Our results demonstrate that interaction of a small molecule compound with FAK decreases phosphorylation of FAK Y397 while increasing FAK Y407 phosphorylation, without inhibiting the kinase activity of FAK and dramatically reduces downstream signaling to AKT. Our lead compound, INT2-31, demonstrates significant inhibition of tumor cell growth in two orthotopic models of pancreatic cancer. In addition, INT2-31 increases sensitivity to gemcitabine chemotherapy in a direct fresh biopsy xenograft model of pancreatic cancer growth.

SUBMITTER: Ucar DA

PROVIDER: S-EPMC4052463 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Inhibiting the interaction of cMET and IGF-1R with FAK effectively reduces growth of pancreatic cancer cells in vitro and in vivo.

Ucar Deniz A DA Magis Andrew T AT He Di-Hua DH Lawrence Nicholas J NJ Sebti Said M SM Kurenova Elena E Zajac-Kaye Maria M Zhang Jianliang J Hochwald Steven N SN

Anti-cancer agents in medicinal chemistry 20130501 4

Pancreatic cancer is one of the most lethal diseases with no effective treatment. Previously, we have shown that FAK is overexpressed in pancreatic cancer and plays a key role in cancer cell survival and proliferation. FAK has been shown to interact with growth factor receptors including cMET and IGF-1R. As a novel therapeutic approach, we targeted the protein interaction of FAK with growth factor receptors to block tumor growth, alter signaling pathways and sensitize cells to chemotherapy. We h ...[more]

PMID: 23272972

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Project description:Ewing Sarcoma is caused by a pathognomonic genomic translocation that places an N-terminal EWSR1 gene in approximation with one of several ETS genes (typically FLI1). This aberration, in turn, alters the transcriptional regulation of more than five hundred genes and perturbs a number of critical pathways that promote oncogenesis, cell growth, invasion, and metastasis. Among them, translocation-mediated up-regulation of the insulin-like growth factor receptor 1 (IGF-1R) and mammalian target of rapamycin (mTOR) are of particular importance since they work in concert to facilitate IGF-1R expression and ligand-induced activation, respectively, of proven importance in ES transformation. When used as a single agent in Ewing sarcoma therapy, IGF-1R or mTOR inhibition leads to rapid counter-regulatory effects that blunt the intended therapeutic purpose. Therefore, identify new mechanisms of resistance that are used by Ewing sarcoma to evade cell death to single-agent IGF-1R inhibition might suggest a number of therapeutic combinations that could improve its clinical activity. TC32 and TC71 ES clones with acquired resistance to OSI-906 or NVP-ADW-742 were generated by maintaining the corresponding parental cell lines with increasing concentrations of the agents (up to 2.3 Î¼M for OSI-906, 1.5 Î¼M for NVP-ADW-742) for 7 months. All parental and acquired drug resistant cell lines were tested twice per year for mycoplasma contamination using the MycoAlert Detection Kit (Lonza Group Ltd.) according to the manufacturerâs protocol and validated using short-tandem repeat fingerprinting with an AmpFLSTR Identifier kit as previously described. Herein, we determine subtle differences in acquired mechanism of resistance by two promising small molecule inhibitors of IGF-1R/IR-Î±. OSI-906, which inhibits IGF-1R and IR, and NVP-ADW-742, which inhibits only IGF-1R, were evaluated using in vitro assays to decipher the mechanism(s) by which IGF-1R inhibition induces drug resistance in Ewing sarcoma cells. The preparation of extracted proteins from sensitive and acquired resistant Ewing sarcoma cells to OSI-906 and NVP-ADW-742 for reverse-phase protein lysate array (RPPA) analysis were prepared using the same array. Lysates were processed, spotted onto nitrocellulose-coated FAST slides, probed with 115 validated primary antibodies, and detected using a DakoCytomation-catalyzed system with secondary antibodies. MicroVigene software program (VigeneTech) was used for automated spot identification, background correction, and individual spot-intensity determination. Expression data was normalized for possible unequal protein loading, taking into account the signal intensity for each sample for all antibodies tested. Log2 values were media-centered by protein to account for variability in signal intensity by time and were calculated using the formula log2 signal â log2 median. Principal component analysis was used to check for a batch effect and feature-by-feature two-sample t-tests were used to assess differences between sensitive and resistant cell lines to drug treatments. We also used feature-by-feature one-way analysis of variance (ANOVA) followed by the Tukey test to perform pair comparisons for all groups. Beta-uniform mixture models were used to fit the resulting p value distributions to adjust for multiple comparisons. The cutoff p values and number of significant proteins were computed for several different false discovery rates (FDRs). Biostatistical analyses comparing two groups were performed using an unpaired t-test with Gaussian distribution followed by the Welch correction. To distinguish between treatment groups, we used one-way ANOVA with the Geisser-Greenhouse correction. Differences with p values <0.05 were considered significant. Within clustered image maps (CIM), unsupervised double hierarchical clustering used the Pearson correlation distance and Wardâs linkage method as the clustering algorithm to link entities (proteins) and samples.

Dataset Information

Inhibiting the interaction of cMET and IGF-1R with FAK effectively reduces growth of pancreatic cancer cells in vitro and in vivo.

Publications

Inhibiting the interaction of cMET and IGF-1R with FAK effectively reduces growth of pancreatic cancer cells in vitro and in vivo.

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