Columbia University and Sloan Kettering Institute For Cancer Research | Date: 2016-11-18
Yeshiva University and Sloan Kettering Institute For Cancer Research | Date: 2016-08-31
Methods are provided for treating metastatic cancer in patients having metastatic cancer or for preventing metastasis in cancer patients at risk for metastasis comprising administering to the patient an antibody to B7x, or an active antibody fragment that binds B7x, in an amount effective to treat or prevent metastasis.
Sloan Kettering Institute For Cancer Research | Date: 2016-12-06
A novel synthesis of the anti-androgen, A52, which has been found to be useful in the treatment of prostate cancer, is provided. A52 as well as structurally related analogs may be prepared via the inventive route. This new synthetic scheme may be used to prepare kilogram scale quantities of pure A52.
Sloan Kettering Institute For Cancer Research | Date: 2017-01-18
An isolated, heteroclitic WT1 peptide, wherein the isolated peptide comprises the amino acid sequence SGQAYMFPNAPYLPSCLES (SEQ ID No: 41) and has one or more point mutations in a primary or secondary anchor residue of an HLA class I or class II binding motif, or the isolated peptide has at least 83% sequence identity with the amino acid sequence SEQ ID NO:41, or the isolated peptide is 20-26 amino acids in length and comprises the amino acid sequence SGQAYMFPNAPYLPSCLES (SEQ ID NO:41), or the isolated peptide is 17 or 18 amino acids in length and comprises a fragment of the amino acid sequence SGQAYMFPNAPYLPSCLES (SEQ ID NO:41). The peptide may be for use in treating a WT1-expressing cancer in asubject.
Agency: NSF | Branch: Standard Grant | Program: | Phase: Biomechanics & Mechanobiology | Award Amount: 535.00K | Year: 2016
Cytotoxic T cells function by selectively destroying virally infected or cancerous target cells. In recent years, this targeted killing capacity has emerged as a core component of several promising immunotherapeutic strategies to fight cancer. A better understanding of how cytotoxic T cells operate is therefore not only of biological interest but also of potential clinical relevance. T cells kill by first forming a close cell-cell interface, called an immunological synapse, with their targets. They then secrete a mixture of toxic proteins into the synapse, which damage the targets plasma membrane and intracellular contents. Recent biophysical studies have indicated that T cells exert a substantial amount of mechanical force across the synapse, which could potentially alter the shape and physical properties of the target cell. The experiments in this research will investigate the hypothesis that these forces boost killing by enhancing the activity of the toxic proteins secreted into the synapse. The idea that mechanical force and chemical signals cooperate in this manner is quite unappreciated and could represent an important new concept in the understanding of intercellular communication and immune function. The principal investigator will also develop a paid summer internship program in mechanobiology targeting female students at both the high school and university levels to provide them an entryway into a research career.
The studies will focus on potential synergy between synaptic forces and the secreted cytolytic molecule perforin, which forms proteinaceous pores on the target cell membrane. Preliminary results suggest that synapse formation increases target cell membrane tension, thereby potentiating perforin pore formation. Biophysical methods will be merged with immunological assays in order to investigate this hypothesis. Polyacrylamide hydrogel substrates will be used to explore the relationship between target cell tension and perforin pore formation. Optical trap methodology will be used to quantify the effects of synapse formation on membrane tension. Finally, polydimethylsiloxine micropillar arrays will be used to examine the spatiotemporal coordination of force exertion and perforin secretion. The successful completion of these research goals could establish mechanopotentiation (i.e. the synergy between physical and chemical signals) as an important avenue for intercellular communication, which would broadly influence current conceptions and future studies of cell-cell interactions and mechanobiology.
Agency: NSF | Branch: Continuing grant | Program: | Phase: OFFICE OF MULTIDISCIPLINARY AC | Award Amount: 200.00K | Year: 2016
This award is part of the NSF effort to promote significant advances in the fundamental understanding of cancer biology made possible through multidisciplinary research that involves experts in theoretical physics, applied mathematics, and computer science.
Achieving durable control of metastatic solid tumors will require high-order targeted therapeutic combinations, because single-agent therapeutics eventually become thwarted by the development of tumor drug resistance. However, design of combinatorial regimens cannot be done by empirical trial and error in the clinical setting. The goal of the project is to blend a systems biology network-based theoretical framework with an integrated experimental and analytical program in order to address the combinatorial regimen challenge in oncology. Based on areas of exemplary clinical need, investigator expertise, and the availability of patient-derived tumor tissue, the project will focus on BRAF-mutant melanoma and PIK3CA-mutant, estrogen receptor positive (ER+) breast cancer as initial tumor types in which to pilot the approach. In addition the project will offer interdisciplinary training and research experience to postdoctoral and clinical fellows, graduate students, and indirectly to all members of the groups who participate. Professional development of all trainees will be enhanced by yearly meetings of the whole project team which will include tutorials on modeling and experimental methodologies. A symposium on the quantitative science of cancer will be organized at the Dana Farber Cancer Institute during the third year of this project. Team members are also committed to broadening the participation of women and under-represented minorities in STEM fields by pro-active recruitment and mentoring.
The project will integrate dynamic modeling of signal transduction pathways relevant to cell proliferation and apoptosis, genomic and evolutionary analyses of tumor cells, and systematic cell death and therapeutic resistance studies. The dynamic models will be informed, tested, and iterated using experimental approaches applied to relevant cancer model systems. The experiments leverage emerging technologies such as pooled genome-wide open reading frame screens, dynamic BH3 profiling of cancer cells closeness to the apoptotic threshold, whole exome sequencing and single cell RNA-seq analysis. The models will recapitulate steady state signaling network activation, acute adaptive effects of treatment (e.g., feedback dysregulation) and the range of drug-resistant states that may emerge following longer-term drug exposure. Tumor cell heterogeneity will be represented by the implementation of different initial configurations or state overrides of network components. Using newly developed systems control methodologies, the models will be used to prioritize drug combinations and dosing/scheduling principles for in vitro and in vivo testing. The final result will be a theoretical and experimentally validated approach that can be generalized across many other cancer types. This project develops a new framework to address cancer as a deregulated complex dynamical system and it will lead to an improved understanding of adaptive and acquired drug resistance mechanisms. The project will make a significant contribution toward a major goal of cancer precision medicine, namely the identification of optimal high-order combinations for individual cancer patients. The project will also establish new connections between evolutionary theory and dynamical systems theory. The theoretical and methodological advances will be applicable or adaptable to other cancers and diseases in general, leading to potentially transformative impacts on human health.
This proposal is cofunded by the Physics of Living Systems Program in the Physics Division and the Systems and Synthetic Biology Program in the Molecular and Cellular Biosciences Division.
Agency: NSF | Branch: Standard Grant | Program: | Phase: Systems and Synthetic Biology | Award Amount: 887.52K | Year: 2015
Many biological functions are cooperative in nature and depend on interactions, both physical and chemical, between cells. This project will investigate the organizing principles of multicellular assemblies using systems biology approaches and the social bacterium Pseudomonas aeruginosa as a model. This project will test the hypothesis that social bacteria have evolved molecular mechanisms that confer robustness to their multicellular traits. Multidisciplinary approaches that combine mathematical modeling, microbial genetics and comparative genomics will be used to dissect the multiple factors that affect biofilm formation and swarming motility. Graduate student training includes extensive research experience in genomic and systems biology. Education outreach programs will train summer undergraduate student interns and local scientific community workshop participants in evolutionary genomics and systems biology analyses including the use of computational tools. The outreach program is partnered with Hunter College of the City University of New York, a neighboring large, urban, and public institution.
This project will use swarming as a model of microbial cooperation. Swarming is a collective form of surface motility that enables bacteria to migrate over surfaces. Swarming requires the production and secretion of rhamnolipid biosurfactants by individual bacteria: biosurfactant production requires significant resources that can be exploited by cheaters who do not produce the surfactant but take advantage of surfactant production by others. Cooperative behavior can also be disrupted by mutants with many flagella that take over the population and disrupt swarming at the cost of being unable to form biofilms. This project will: 1) dissect the spatial-temporal dynamics of metabolic prudence, a mechanism regulating the synthesis of rhamnolipids required for swarming; 2) investigate the evolutionary and molecular mechanisms of hyperswarming evolution; and 3) dissect the trade-off between two collective traits: swarming and biofilms in natural bacterial populations. In addition this project will develop a bioinformatics infrastructure and database to investigate the genomic correlates of phenotypic diversity in environmental strains of P. aeruginosa. Specifically, this project will develop novel methods of comparative genomics based on evolutionary analysis of whole genome sequencing data using ancestral character reconstruction of both genotypes and phenotypes. The novel methods will be applicable to other social bacteria.
Aragon Pharmaceuticals Inc. and Sloan Kettering Institute For Cancer Research | Date: 2016-09-12
Described herein are amorphous and crystalline forms of the androgen receptor modulator 4-[7-(6-cyano-5-trifluoromethylpyridin-3-yl)-8-oxo-6-thioxo-5,7-diazaspiro[3.4]oct-5-yl]-2-fluoro-N-methylbenzamide. Also described are pharmaceutical compositions suitable for administration to a mammal that include the androgen receptor modulator, and methods of using the androgen receptor modulator, alone and in combination with other compounds, for treating diseases or conditions that are associated with androgen receptor activity.
Sloan Kettering Institute For Cancer Research | Date: 2016-01-14
This invention provides peptides, immunogenic compositions and vaccines comprising same, and methods of treating, reducing the incidence of, and inducing immune responses to a WT1-expressing cancer, comprising same.
Sloan Kettering Institute For Cancer Research | Date: 2016-11-09
The present application provides substituted purine derivatives (I) and related compounds of the formulas shown. These compounds are useful as inhibitors of HSP90, and hence in the treatment of related diseases. (Formulae) Z_(1)-Z_(3), X_(a)-X_(c), X_(2), X_(4), Y and R are as defined in the specification.