Project description:The mTOR (mammalian Target of Rapamycin) pathway is constitutively activated in Diffuse Large B-Cell Lymphoma (DLBCL). mTOR inhibition has been shown to have clinical activity in patients with DLBCL, although overall response rates remain low. We therefore evaluated differences in the transcriptome between DLBCL cell lines with differential sensitivity to the mTOR inhibitor Rapamycin, to (A) identify gene-expression patterns(GEP) capable of identifying sensitivity to Rapamycin, (B) understand the underlying mechanisms of resistance to Rapamycin in DLBCL and (C) identify bioactive molecules likely to synergize with mTOR inhibitors. Using Affymetrix HuGene ST 1.0 microarrays, we were able to identify a gene expression signature capable of accurately predicting sensitivity and resistance to Rapamycin in DLBCL cell lines. Pathway analysis identified the serine/threonine kinase Akt as central to the differentially-expressed gene network. Connectivity mapping of our datasets identified compounds targeting the AKT pathway with a high likelihood of reversing the GEP associated with resistance to Rapamycin. Specifically, we evaluated the HIV protease inhibitor (PI) Nelfinavir, which is known to have anti-cancer and Akt-inhibitory properties, as well as the small molecule Akt inhibitor MK-2206, for their potential to synergize with to Rapamycin in DLBCL. Nelfinavir and MK-2206 caused profound inhibition of cell viability in combination with Rapamycin in DLBCL cell lines. Low nanomolar concentrations of Rapamycin inhibited phosphorylation of Akt and also downstream targets of activated mTOR when used in combination with these Akt inhibitors. These findings have the potential to significantly improve patient selection for mTOR inhibitor therapy, and to improve rates and depths of response. More broadly, they support the use of global RNA expression and connectivity mapping to improve patient selection and identify synergistic drug combinations for cancer therapy. DLBCL cell lines were tested for Rapamycin sensitivity and classified as "sensitive" or "resistant." Genome-wide analysis of all cell lines were performed using the Affymetrix HuGene ST 1.0 Array Platform. Genes with differential expression between sensitive and resistant cell lines were analyzed using Statistical Analysis of Microarrays (SAM) software, and a signature of genes determnined. This signature was found to accurately predict sensitivity or resistance of other DLBCL cell lines, and to identify the protein kinase Akt as central to resistance.

Project description:The mTOR (mammalian Target of Rapamycin) pathway is constitutively activated in Diffuse Large B-Cell Lymphoma (DLBCL). mTOR inhibition has been shown to have clinical activity in patients with DLBCL, although overall response rates remain low. We therefore evaluated differences in the transcriptome between DLBCL cell lines with differential sensitivity to the mTOR inhibitor Rapamycin, to (A) identify gene-expression patterns(GEP) capable of identifying sensitivity to Rapamycin, (B) understand the underlying mechanisms of resistance to Rapamycin in DLBCL and (C) identify bioactive molecules likely to synergize with mTOR inhibitors. Using Affymetrix HuGene ST 1.0 microarrays, we were able to identify a gene expression signature capable of accurately predicting sensitivity and resistance to Rapamycin in DLBCL cell lines. Pathway analysis identified the serine/threonine kinase Akt as central to the differentially-expressed gene network. Connectivity mapping of our datasets identified compounds targeting the AKT pathway with a high likelihood of reversing the GEP associated with resistance to Rapamycin. Specifically, we evaluated the HIV protease inhibitor (PI) Nelfinavir, which is known to have anti-cancer and Akt-inhibitory properties, as well as the small molecule Akt inhibitor MK-2206, for their potential to synergize with to Rapamycin in DLBCL. Nelfinavir and MK-2206 caused profound inhibition of cell viability in combination with Rapamycin in DLBCL cell lines. Low nanomolar concentrations of Rapamycin inhibited phosphorylation of Akt and also downstream targets of activated mTOR when used in combination with these Akt inhibitors. These findings have the potential to significantly improve patient selection for mTOR inhibitor therapy, and to improve rates and depths of response. More broadly, they support the use of global RNA expression and connectivity mapping to improve patient selection and identify synergistic drug combinations for cancer therapy.

			Action	DRS
	BIOMD0000000823?filename=Varusai2018-biopax2.owl	Owl
	BIOMD0000000823?filename=Varusai2018-biopax3.owl	Owl
	BIOMD0000000823?filename=Varusai2018-matlab.m	Other
	BIOMD0000000823?filename=Varusai2018.cps	Other
	BIOMD0000000823?filename=Varusai2018.ode	Other

Dataset Information

Varusai2018 - Dynamic modelling of the mTOR signalling network reveals complex emergent behaviours conferred by DEPTOR

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Dynamic modelling of the mTOR signalling network reveals complex emergent behaviours conferred by DEPTOR.

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