Project description:Despite initial and often dramatic responses of epidermal growth factor receptor (EGFR)-addicted lung tumors to the EGFR-specific tyrosine kinase inhibitors (TKIs), gefitinib and erlotinib, nearly all develop resistance and relapse. To explore novel mechanisms mediating acquired resistance, we employed non-small-cell lung cancer (NSCLC) cell lines bearing activating mutations in EGFR and rendered them resistant to EGFR-specific TKIs through chronic adaptation in tissue culture. In addition to previously observed resistance mechanisms including EGFR-T790M 'gate-keeper' mutations and MET amplification, a subset of the seven chronically adapted NSCLC cell lines including HCC4006, HCC2279 and H1650 cells exhibited marked induction of fibroblast growth factor (FGF) 2 and FGF receptor 1 (FGFR1) mRNA and protein. Also, adaptation to EGFR-specific TKIs was accompanied by an epithelial to mesenchymal transition (EMT) as assessed by changes in CDH1, VIM, ZEB1 and ZEB2 expression and altered growth properties in Matrigel. In adapted cell lines exhibiting increased FGF2 and FGFR1 expression, measures of growth and signaling, but not EMT, were blocked by FGFR-specific TKIs, an FGF-ligand trap and FGFR1 silencing with RNAi. In parental HCC4006 cells, cell growth was strongly inhibited by gefitinib, although drug-resistant clones progress within 10 days. Combined treatment with gefitinib and AZD4547, an FGFR-specific TKI, prevented the outgrowth of drug-resistant clones. Thus, induction of FGF2 and FGFR1 following chronic adaptation to EGFR-specific TKIs provides a novel autocrine receptor tyrosine kinase-driven bypass pathway in a subset of lung cancer cell lines that are initially sensitive to EGFR-specific TKIs. The findings support FGFR-specific TKIs as potentially valuable additions to existing targeted therapeutic strategies with EGFR-specific TKIs to prevent or delay acquired resistance in EGFR-driven NSCLC. Examination of mRNA levels in DMSO and gefitinib-resistant cultures of HCC4006 and HCC827. Each group has two replicates.
Project description:Preclinical and clinical data implicate the transcriptional co-activator YAP1 in resistance to multiple targeted therapies, including BRAF and MEK inhibitors. However, tumor subtypes driven by YAP1 activity and associated vulnerabilities are poorly defined. Here, we show particularly high YAP1 activity in the MITFlow/AXLhigh subset of melanoma cell lines and patient tumors characterized by resistance to MAPK pathway inhibition and broad receptor tyrosine kinase activity. To uncover genetic dependencies of melanoma cells with high YAP1 activity, we used a genome-wide CRISPR/Cas9 functional screen and identified SLC35B2, the 3′-phosphoadenosine-5′-phosphosulfate transporter of the Golgi apparatus, as an essential gene for YAP1-mediated drug resistance. SLC35B2 expression correlates with tumor progression, and its loss decreases heparan sulfate expression, reduces receptor tyrosine kinase activity, and sensitizes resistant melanoma cells to BRAF inhibition in vitro and in vivo. Thus, SLC35B2 is a target in YAP1-driven BRAF mutant melanoma for overcoming drug resistance to MAPK pathway inhibitors.
Project description:Development of resistance causes failure of drugs targeting receptor tyrosine kinase (RTK) networks, and represents a critical challenge for precision medicine. Here we show that PHLDA1 down-regulation is critical to acquisition and maintenance of drug resistance in RTK-driven cancer. Using FGFR inhibition in endometrial cancer cells, we identify an Akt-driven compensatory mechanism underpinned by down-regulation of PHLDA1. We demonstrate broad clinical relevance of our findings, showing that PHLDA1 down-regulation also occurs in response to RTK-targeted therapy in breast and renal cancer patients, as well as following trastuzumab treatment in HER2+ breast cancer cells. Crucially, knockdown of PHLDA1 alone was sufficient to confer de novo resistance to RTK inhibitors, and induction of PHLDA1 expression re-sensitised drug resistant cancer cells to targeted therapies, identifying PHLDA1 as a biomarker for drug response and highlighting the potential of PHLDA1 reactivation as a means of circumventing drug resistance.
Project description:Drug resistance is a central problem in cancer therapy, yet the underlying mechanisms remain obscure. Cancer cells typically acquire resistance via genetic mutations, but may also adopt reversible epigenetic phenotypes that allow them to persist through drug exposure. In glioblastoma, poor efficacy of receptor tyrosine kinase (RTK) therapies has been alternatively ascribed to genetic heterogeneity or to epigenetic transitions that circumvent signaling blockade.
Project description:Receptor tyrosine kinase (RTK)-activated lung cancers are characterized by alterations in oncogenic drivers that induce kinase activation with resultant tyrosine kinase inhibitor (TKI) resistance through both on-target and off-target mechanisms.
Focusing on a subgroup of 93 EGFR-mutant lung cancers with paired osimertinib-naïve and osimertinib-resistant tumor samples, we find a significant enrichment of kataegis, chromothripsis and APOBEC mutagenesis among the cancers treated with targeted therapy.
APOBEC mutagenesis and structural rearrangements are pervasive mechanisms by which RTK-driven lung cancers may evolve and develop drug resistance.
Project description:Overexpression of the epidermal growth factor receptor family member Her-2/neu in breast cancer leads to autophosphorylation of the receptor, and induction of multiple downstream signaling pathways including Akt kinase to NF-kappaB cascade that is associated with poor prognosis. Previously, we demonstrated green tea polyhenol epigallocatechin 3-gallate (EGCG) inhibits growth of NF639 Her-2/neu-driven breast cancer cells via reducing receptor autophosphorylation, and downstream Akt and NF-kappaB activities (Pianetti et al., 2002). Interestingly, we noted that upon prolonged culture in the presence of EGCG some cells developed resistance to the polyphenol. Here we report that resistant cells have lost tyrosine phosphorylation on the Her-2/neu receptor. Surprisingly, they displayed elevated NF-kappaB activity, and inhibition of this activity sensitized cells to EGCG. Data from microarray analysis of the original and resistant NF639 populations of cells were subjected to Gene Set Enrichment Analysis (GSEA) pathway analysis, which revealed that the mitogen activated protein kinase (MAPK) pathway was activated in the resistant cells. Treatment of the resistant cells with a combination of EGCG and the MAPK inhibitor U0216 dramatically reduced colony growth and mesenchymal phenotype. Thus, activation of the MAPK pathway mediates resistance to EGCG. Our studies suggest that gene expression profiling of drug resistant cells may provide a mechanism of determining effective systemic therapies for treatment of these advanced cancers. Keywords: Drug resistance
Project description:Drug resistance is a major clinical challenge in achieving durable responses to targeted cancer therapeutics. Resistance mechanisms to new classes of epigenetic-targeted drugs entering the clinic remain largely unexplored. We used BET inhibition in MYCN-amplified neuroblastoma as a prototype to model innate and acquired resistance to chromatin remodeling inhibitors in cancer. Genome-scale, pooled lentiviral ORF and CRISPR knockout rescue screens nominated the PI3K pathway as a key signaling node that mediates resistance to BET inhibition. RNA-seq profiling of BET inhibitor resistant cells revealed that global enhancer and super-enhancer remodeling leads to differential cell state commitment and the upregulation of receptor tyrosine kinases upstream of PI3K signaling, engendering a vulnerability to receptor tyrosine kinase (RTK) and PI3K inhibition. Large-scale, unbiased, chemical combinatorial screening with BET inhibitors identified PI3K inhibitors among the most synergistic upfront combinations with JQ1, a finding validated in vivo. These studies provide a comprehensive roadmap to elucidate resistance to epigenetic-targeted cancer therapeutics and inform efficacious combination therapies for second-generation clinical trials.
Project description:Overexpression of the epidermal growth factor receptor family member Her-2/neu in breast cancer leads to autophosphorylation of the receptor, and induction of multiple downstream signaling pathways including Akt kinase to NF-ï«B cascade that is associated with poor prognosis. Previously, we demonstrated green tea polyhenol epigallocatechin 3-gallate (EGCG) inhibits growth of NF639 Her-2/neu-driven breast cancer cells via reducing receptor autophosphorylation, and downstream Akt and NF-ï«B activities (Pianetti et al., 2002). Interestingly, we noted that upon prolonged culture in the presence of EGCG some cells developed resistance to the polyphenol. Here we report that resistant cells have lost tyrosine phosphorylation on the Her-2/neu receptor. Surprisingly, they displayed elevated NF-ï«B activity, and inhibition of this activity sensitized cells to EGCG. Data from microarray analysis of the original and resistant NF639 populations of cells were subjected to Gene Set Enrichment Analysis (GSEA) pathway analysis, which revealed that the mitogen activated protein kinase (MAPK) pathway was activated in the resistant cells. Treatment of the resistant cells with a combination of EGCG and the MAPK inhibitor U0216 dramatically reduced colony growth and mesenchymal phenotype. Thus, activation of the MAPK pathway mediates resistance to EGCG. Our studies suggest that gene expression profiling of drug resistant cells may provide a mechanism of determining effective systemic therapies for treatment of these advanced cancers. Experiment Overall Design: Total RNA from original NF639 cells and EGCG resistant NF639 cells were harvested using the UltraspecII RNA isolation kit (Biotecx), following the manufacturerâs instruction. The RNA samples were submitted to Boston University Microarray Resource for microarray hybridization using Affymetrix Mouse 430A 2.0 chips. RNAs from two independent experiments were analyzed and data pooled for computational analysis.