Person: Ficarro, Scott
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Ficarro
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Ficarro, Scott
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Publication Architecture of Autoinhibited and Active BRAF–MEK1–14-3-3 Complexes(Springer Science and Business Media LLC, 2019-10-03) Rawson, Shaun; Kim, Byeong-Won; Sharif, Humayun; Jeon, Hyesung; Park, Eunyoung; Li, Kunhua; Ficarro, Scott; Gonzalez-De Pino, Gonzalo; Marto, Jarrod; Eck, MichaelRAF family kinases are RAS-activated switches that initiate signaling through the MAP kinase cascade to control cellular proliferation, differentiation and survival1-3. RAF activity is tightly regulated and inappropriate activation is a frequent cause of cancer4-6. At present, the structural basis for RAF regulation is poorly understood. Here we describe autoinhibited and active state structures of full-length BRAF in complexes with MEK1 and a 14-3-3 dimer, determined using cryo electron microscopy (cryo-EM). A 4.1Å resolution cryo-EM reconstruction reveals an inactive BRAF/MEK1 complex restrained in a cradle formed by the 14-3-3 dimer, which binds the phosphorylated S365 and S729 sites that flank the BRAF kinase domain. The BRAF cysteine-rich domain (CRD) occupies a central position that stabilizes this assembly, but the adjacent RAS-binding domain (RBD) is poorly ordered and peripheral. The 14-3-3 cradle maintains autoinhibition by sequestering the membrane-binding CRD and blocking dimerization of the BRAF kinase domain. In the active state, these inhibitory interactions are released and a single 14-3-3 dimer rearranges to bridge the C-terminal pS729 binding sites of two BRAFs, driving formation of an active, back-to-back BRAF dimer. Our structural snapshots provide a foundation for understanding normal RAF regulation and its mutational disruption in cancer and developmental syndromes.Publication Genome-scale Proteome Quantification by DEEP SEQ Mass Spectrometry(2013) Zhou, Feng; Lu, Yu; Ficarro, Scott; Adelmant, Guillaume; Jiang, Wenyu; Luckey, C. John; Marto, JarrodAdvances in chemistry and massively parallel detection underlie DNA sequencing platforms that are poised for application in personalized medicine. In stark contrast, systematic generation of protein-level data lags well-behind genomics in virtually every aspect: depth of coverage, throughput, ease of sample preparation, and experimental time. Here, to bridge this gap, we develop an approach based on simple detergent lysis and single-enzyme digest, extreme, orthogonal separation of peptides, and true nanoflow LC-MS/MS that provides high peak capacity and ionization efficiency. This automated, deep efficient peptide sequencing and quantification (DEEP SEQ) mass spectrometry platform provides genome-scale proteome coverage equivalent to RNA-seq ribosomal profiling and accurate quantification for multiplexed isotope labels. In a model of the embryonic to epiblast transition in murine stem cells, we unambiguously quantify 11,352 gene products that span 70% of Swiss-Prot and capture protein regulation across the full detectable range of high-throughput gene expression and protein translation.Publication Structure of a pseudokinase domain switch that controls oncogenic activation of Jak kinases(2013) Toms, Angela V.; Deshpande, Anagha; McNally, Randall; Jeong, Youngjee; Rogers, Julia; Kim, Chae Un; Gruner, Sol M.; Ficarro, Scott; Marto, Jarrod; Sattler, Martin; Griffin, James; Eck, MichaelThe V617F mutation in the Jak2 pseudokinase domain causes myeloproliferative neoplasms, and the equivalent mutation in Jak1 (V658F) is found in T-cell leukemias. Crystal structures of wild type and V658F mutant human Jak1 pseudokinase reveal a conformational switch that remodels a linker segment encoded by exon 12, which is also a site of mutations in Jak2. This switch is required for V617F-mediated Jak2 activation, and possibly for physiologic Jak activation.Publication Targeting transcription regulation in cancer with a covalent CDK7 inhibitor(2014) Kwiatkowski, Nicholas; Zhang, Tinghu; Rahl, Peter B; Abraham, Brian J; Reddy, Jessica; Ficarro, Scott; Dastur, Anahita; Amzallag, Arnaud; Ramaswamy, Sridhar; Tesar, Bethany; Jenkins, Christopher R; Hannett, Nancy M; McMillin, Douglas; Sanda, Takaomi; Sim, Taebo; Kim, Nam Doo; Look, Thomas; Mitsiades, Constantine; Weng, Andrew P; Brown, Jennifer; Benes, Cyril; Marto, Jarrod; Young, Richard A; Gray, NathanaelTumor oncogenes include transcription factors that co-opt the general transcriptional machinery to sustain the oncogenic state1, but direct pharmacological inhibition of transcription factors has thus far proven difficult2. However, the transcriptional machinery contains various enzymatic co-factors that can be targeted for development of new therapeutic candidates3, including cyclin-dependent kinases (CDKs)4. Here we present the discovery and characterization of the first covalent CDK7 inhibitor, THZ1, which has the unprecedented ability to target a remote cysteine residue located outside of the canonical kinase domain, providing an unanticipated means of achieving selectivity for CDK7. Cancer cell line profiling indicates that a subset of cancer cell lines, including T-ALL, exhibit exceptional sensitivity to THZ1. Genome-wide analysis in Jurkat T-ALL shows that THZ1 disproportionally affects transcription of RUNX1 and suggests that sensitivity to THZ1 may be due to vulnerability conferred by the RUNX1 super-enhancer and this transcription factor’s key role in the core transcriptional regulatory circuitry of these tumor cells. Pharmacological modulation of CDK7 kinase activity may thus provide an approach to identify and treat tumor types exhibiting extreme dependencies on transcription for maintenance of the oncogenic state.Publication The Cyclophilin A-CD147 complex promotes bone marrow colonization of B-cell malignancies: implications for therapy(2015) Zhu, Di; Wang, Zhongqiu; Zhao, Jian-Jun; Calimeri, Teresa; Meng, Jiang; Hideshima, Teru; Fulciniti, Mariateresa; Kang, Yue; Ficarro, Scott; Tai, Yu-Tzu; Hunter, Zachary; McMilin, Douglas; Tong, Haoxuan; Mitsiades, Constantine; Wu, Catherine; Treon, Steven; Dorfman, David M.; Pinkus, Geraldine; Munshi, Nikhil; Tassone, Pierfrancesco; Marto, Jarrod; Anderson, Kenneth; Carrasco, RubenB-cell malignancies frequently colonizes the bone marrow (BM). The mechanisms responsible for this preferential homing are not entirely known. Using multiple myeloma (MM) as a model of a terminally differentiated B-cell malignancy that selectively colonizes the BM, we demonstrated that BM endothelial cells (BMECs), secrete cyclophilin A (eCyPA), which promotes migration, proliferation, and BM colonization of MM cells via binding to its receptor, CD147, on MM cells. The clinical and translational implications of this work are highlighted by the observation of significantly higher eCyPA levels in BM serum than in peripheral blood (PB) in MM persons, and that eCyPA-CD147 blockade supresses BM-homing and tumor growth in a mouse xenograft model of MM. eCyPA also promoted migration of CLL and LPL cells, two other B-cell malignancies that colonize the BM and express CD147. These findings offer a compelling rationale for exploring the eCyPA-CD147 axis as therapeutic target for these malignancies.Publication Elafin drives poor outcome in high grade serous ovarian cancers and basal-like breast tumors(2014) Labidi-Galy, S. Intidhar; Clauss, Adam; Ng, Vivian; Duraisamy, Sekhar; Elias, Kevin; Piao, Hui-Ying; Bilal, Erhan; Davidowitz, Rachel A.; Lu, Yiling; Badalian-Very, Gayane; Györffy, Balázs; Kang, Un-Beom; Ficarro, Scott; Ganesan, Shridar; Mills, Gordon B.; Marto, Jarrod; Drapkin, RonnyHigh grade serous ovarian carcinoma (HGSOC) and basal-like breast cancer (BLBC) share many features including TP53 mutations, genomic instability and poor prognosis. We recently reported that Elafin is overexpressed by HGSOC and is associated with poor overall survival. Here, we confirmed that Elafin overexpression is associated with shorter survival in 1000 HGSOC patients. Elafin confers a proliferative advantage to tumor cells through activation of the MAP kinase pathway. This mitogenic effect can be neutralized by RNA interference, specific antibodies, and a MEK inhibitor. Elafin expression in patient-derived samples was also associated with chemoresistance and strongly correlates with bcl-xL expression. We extended these findings into examination of 1100 primary breast tumors and six breast cancer cell lines. We observed that Elafin is overexpressed and secreted specifically by BLBC tumors and cell lines, leading to a similar mitogenic effect through activation of the MAP kinase pathway. Here too, Elafin overexpression is associated with poor overall survival, suggesting that it may serve as a biomarker and therapeutic target in this setting.Publication Pharmacological Targeting of the Pseudokinase Her3(2014) Xie, Ting; Lim, Sang Min; Westover, Kenneth D.; Dodge, Michael E.; Ercan, Dalia; Ficarro, Scott; Udayakumar, Durga; Gurbani, Deepak; Tae, Hyun Seop; Riddle, Steven M.; Sim, Taebo; Marto, Jarrod; Jänne, Pasi A.; Crews, Craig M.; Gray, NathanaelHer3 (ErbB3) belongs to the epidermal growth factor receptor tyrosine kinases and is well credentialed as an anti-cancer target but is thought to be “undruggable” using ATP-competitive small molecules because it lacks significant kinase activity. Here we report the first selective Her3 ligand, TX1-85-1, that forms a covalent bond with Cys721 located in the ATP-binding site of Her3. We demonstrate that covalent modification of Her3 inhibits Her3 signaling but not proliferation in some Her3 dependent cancer cell lines. Subsequent derivatization with a hydrophobic adamantane moiety demonstrates that the resultant bivalent ligand (TX2-121-1) enhances inhibition of Her3 dependent signaling. Treatment of cells with TX2-121-1 results in partial degradation of Her3 and serendipitously interferes with productive heterodimerization between Her3 with either Her2 or c-Met. These results suggest that small molecules will be capable of perturbing the biological function of Her3 and the approximately 60 other pseudokinases found in human cells.Publication Interpreting Cancer Genomes Using Systematic Host Perturbations by Tumour Virus Proteins(Nature Publishing Group, 2012) Rozenblatt-Rosen, Orit; Deo, Rahul C.; Dricot, Amélie; Askenazi, Manor; Tavares, Maria; Abderazzaq, Fieda; Byrdsong, Danielle; Correll, Mick; Fan, Changyu; Feltkamp, Mariet C.; Franchi, Rachel; Garg, Brijesh K.; Gulbahce, Natali; Hao, Tong; Korkhin, Anna; Litovchick, Larisa; Mar, Jessica C.; Pak, Theodore R.; Rabello, Sabrina; Rubio, Renee; Shen, Yun; Tasan, Murat; Wanamaker, Shelly; Roecklein-Canfield, Jennifer; Johannsen, Eric; Barabási, Albert-László; Padi, Megha; Adelmant, Guillaume; Calderwood, Michael; Rolland, Thomas; Grace, Miranda; Pevzner, Samuel; Carvunis, Anne-Ruxandra; Chen, Alyce; Cheng, Jingwei; Duarte, Melissa; Ficarro, Scott; Holthaus, Amy Marie; James, Robert; Singh, Saurav; Spangle, Jennifer; Webber, James T.; Beroukhim, Rameen; Kieff, Elliott; Cusick, Michael; Hill, David; Munger, Karl; Marto, Jarrod; Quackenbush, John; Roth, Fritz; DeCaprio, James; Vidal, MarcGenotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer.Publication multiplierz: An Extensible API Based Desktop Environment for Proteomics Data Analysis(BioMed Central, 2009) Parikh, Jignesh R; Askenazi, Manor; Ficarro, Scott; Cashorali, Tanya; Webber, James T; Blank, Nathaniel C; Zhang, Yi; Marto, JarrodBackground: Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge. Results: We describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a "zero infrastructure" philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines. Conclusion: Collectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research.Publication mzStudio: A Dynamic Digital Canvas for User-Driven Interrogation of Mass Spectrometry Data(MDPI, 2017) Ficarro, Scott; Alexander, William M.; Marto, JarrodAlthough not yet truly ‘comprehensive’, modern mass spectrometry-based experiments can generate quantitative data for a meaningful fraction of the human proteome. Importantly for large-scale protein expression analysis, robust data pipelines are in place for identification of un-modified peptide sequences and aggregation of these data to protein-level quantification. However, interoperable software tools that enable scientists to computationally explore and document novel hypotheses for peptide sequence, modification status, or fragmentation behavior are not well-developed. Here, we introduce mzStudio, an open-source Python module built on our multiplierz project. This desktop application provides a highly-interactive graphical user interface (GUI) through which scientists can examine and annotate spectral features, re-search existing PSMs to test different modifications or new spectral matching algorithms, share results with colleagues, integrate other domain-specific software tools, and finally create publication-quality graphics. mzStudio leverages our common application programming interface (mzAPI) for access to native data files from multiple instrument platforms, including ion trap, quadrupole time-of-flight, Orbitrap, matrix-assisted laser desorption ionization, and triple quadrupole mass spectrometers and is compatible with several popular search engines including Mascot, Proteome Discoverer, X!Tandem, and Comet. The mzStudio toolkit enables researchers to create a digital provenance of data analytics and other evidence that support specific peptide sequence assignments.