Showing papers by "Pablo Tamayo published in 2014"

A Melanoma Cell State Distinction Influences Sensitivity to MAPK Pathway Inhibitors

Abstract: Most melanomas harbor oncogenic BRAFV600 mutations, which constitutively activate the MAP kinase (MAPK) pathway. Although MAPK pathway inhibitors show clinical benefit in BRAFV600-mutant melanoma, it remains incompletely understood why 10-20% of patients fail to respond. Here, we show that RAF inhibitor sensitive and resistant BRAFV600-mutant melanomas display distinct transcriptional profiles. Whereas most drug-sensitive cell lines and patient biopsies showed high expression and activity of the melanocytic lineage transcription factor MITF, intrinsically resistant cell lines and biopsies displayed low MITF expression but higher levels of NF-κB signaling and the receptor tyrosine kinase AXL. In vitro, these MITF-low/NF-κB-high melanomas were resistant to inhibition of RAF and MEK, singly or in combination, and ERK. Moreover, in cell lines, NF-κB activation antagonized MITF expression and induced both resistance marker genes and drug resistance. Thus, distinct cell states characterized by MITF or NF-κB activity may influence intrinsic resistance to MAPK pathway inhibitors in BRAFV600-mutant melanoma.

Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies

Abstract: Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing. All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines. When combined with genomic characterization of these cell lines, this dataset facilitates the linkage of genetic dependencies with specific cellular contexts (e.g., gene mutations or cell lineage). To enable such comparisons, we developed and provided a bioinformatics tool to identify linear and nonlinear correlations between these features.

Erratum: Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies

Abstract: Scientific Data 1:140035 doi: 10.1038/sdata.2014.35 (2014); Published 30 September 2014; Updated 11 November 2014 The original version of this Data Descriptor contained a typographical error in the spelling of the author Terence C. Wong, which was incorrectly given as Terrence C. Wong. This has now been corrected in the PDF and HTML versions of the Data Descriptor.

Inhibition of KRAS-driven tumorigenicity by interruption of an autocrine cytokine circuit

Abstract: Although the roles of mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3 kinase (PI3K) signaling in KRAS-driven tumorigenesis are well established, KRAS activates additional pathways required for tumor maintenance, inhibition of which are likely to be necessary for effective KRAS-directed therapy. Here we show that the IKK-related kinases TBK1 and IKKe promote KRAS-driven tumorigenesis by regulating autocrine CCL5 and IL-6 and identify CYT387 as a potent JAK/TBK1/IKKe inhibitor. CYT387 treatment ablates RAS-associated cytokine signaling and impairs Kras-driven murine lung cancer growth. Combined CYT387 and MEK inhibitor therapy induces regression of aggressive murine lung adenocarcinomas driven by Kras mutation and p53 loss. These observations reveal that TBK1/IKKe promote tumor survival by activating CCL5 and IL-6 and identify concurrent inhibition of TBK1/IKKe, JAK, and MEK signaling as an effective approach to inhibit the actions of oncogenic KRAS.

Targeting an IKBKE cytokine network impairs triple-negative breast cancer growth

Abstract: Triple-negative breast cancers (TNBCs) are a heterogeneous set of cancers that are defined by the absence of hormone receptor expression and HER2 amplification. Here, we found that inducible IκB kinase-related (IKK-related) kinase IKBKE expression and JAK/STAT pathway activation compose a cytokine signaling network in the immune-activated subset of TNBC. We found that treatment of cultured IKBKE-driven breast cancer cells with CYT387, a potent inhibitor of TBK1/IKBKE and JAK signaling, impairs proliferation, while inhibition of JAK alone does not. CYT387 treatment inhibited activation of both NF-κB and STAT and disrupted expression of the protumorigenic cytokines CCL5 and IL-6 in these IKBKE-driven breast cancer cells. Moreover, in 3D culture models, the addition of CCL5 and IL-6 to the media not only promoted tumor spheroid dispersal but also stimulated proliferation and migration of endothelial cells. Interruption of cytokine signaling by CYT387 in vivo impaired the growth of an IKBKE-driven TNBC cell line and patient-derived xenografts (PDXs). A combination of CYT387 therapy with a MEK inhibitor was particularly effective, abrogating tumor growth and angiogenesis in an aggressive PDX model of TNBC. Together, these findings reveal that IKBKE-associated cytokine signaling promotes tumorigenicity of immune-driven TNBC and identify a potential therapeutic strategy using clinically available compounds.

Gene signatures related to B cell proliferation predict influenza vaccine-induced antibody response

Abstract: Vaccines are very effective at preventing infectious disease but not all recipients mount a protective immune response to vaccination. Recently, gene expression profiles of PBMC samples in vaccinated individuals have been used to predict the development of protective immunity. However, the magnitude of change in gene expression that separates vaccine responders and nonresponders is likely to be small and distributed across networks of genes, making the selection of predictive and biologically relevant genes difficult. Here we apply a new approach to predicting vaccine response based on coordinated upregulation of sets of biologically informative genes in postvaccination gene expression profiles. We found that enrichment of gene sets related to proliferation and immunoglobulin genes accurately segregated high responders to influenza vaccination from low responders and achieved a prediction accuracy of 88% in an independent clinical trial. Many of the genes in these gene sets would not have been identified using conventional, single-gene level approaches because of their subtle upregulation in vaccine responders. Our results demonstrate that gene set enrichment method can capture subtle transcriptional changes and may be a generally useful approach for developing and interpreting predictive models of the human immune response.

Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data.

Abstract: In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template – used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts. Software for fitting the JCM models have been implemented in an R package EMMIX-JCM, available from http://www.maths.uq.edu.au/~gjm/mix_soft/EMMIX-JCM/.

Integrative Radiogenomic Profiling Identifies BRAF Mutations as Novel Radiotherapeutic Targets in Adenocarcinomas of the Lung

Abstract: Purpose/Objective(s): Advances in treatment planning and delivery have made it possible to safely deliver a small number of high radiation doses to tumors through a treatment modality termed stereotactic body radiation therapy (SBRT). SBRT has been shown to increase local control of many tumors, leading some to propose that high dose radiation therapy may engage new mechanisms of tumor eradication. Human cancers develop in a complex environment composed of blood vessels, fibroblasts, and immune cells. However, it remains controversial whether stromal cells, such as endothelial cells, or tumor cells are the critical targets that regulate tumor eradication by SBRT. Genetically engineered mouse models of cancer develop within a native tumor microenvironment in immunocompetent mice and may more faithfully recapitulate the tumor microenvironment of human cancer than transplanted models. To determine the critical target(s) in primary tumors that mediate local control by SBRT, we used dual recombinase technology to selectively manipulate the radiosensitivity of endothelial cells or tumors cells in primary mouse soft tissue sarcomas. Materials/Methods: Using novel dual recombinase technology, we initiated primary soft tissue sarcomas in FSF-Kras; p53 mice by intramuscular injection of an adenovirus expressing FlpO recombinase and deleted floxed alleles of Bax or Atm in endothelial cells using the tissue-specific Cre-driver VE-Cadherin-Cre. We also deleted Atm in tumor cells by intramuscular injection of 4-hydroxytamoxifen into Pax7-CreER; LSLKras; p53; Atm mice. Following tumor development, mice were treated with 20 Gy or 50 Gy focal sarcoma irradiation using an X-RAD 225Cx small animal image-guided irradiator, and sarcoma growth delay and local control were monitored by caliper measurement. Results: Deletion of Bax in endothelial cells did not affect endothelial cell death or tumor response to radiation therapy. Deletion of Atm in endothelial cells increased radiation-induced cell death of tumor endothelial cells and prolonged tumor growth delay following a non-curative dose of radiation. However, following a curative dose of radiation, Atm deletion in endothelial cells did not affect growth delay and failed to increase local control. In contrast, deletion of Atm specifically in tumor cells increased local control of primary tumors by radiation therapy. Conclusions: Tumor cells rather than endothelial cells are the critical targets that regulate primary tumor eradication by SBRT.