Iva Monique T. Gramatikov

ORCID: 0000-0001-5789-7961
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About
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Research Areas
  • Bioinformatics and Genomic Networks
  • Cancer, Hypoxia, and Metabolism
  • Microbial Metabolic Engineering and Bioproduction
  • Prostate Cancer Treatment and Research
  • Cell death mechanisms and regulation
  • Cancer Genomics and Diagnostics
  • Protein Degradation and Inhibitors
  • Ubiquitin and proteasome pathways
  • Cancer Cells and Metastasis

AstraZeneca (United States)
2024

Beth Israel Deaconess Medical Center
2023

Massachusetts Institute of Technology
2023

A challenge for screening new candidate drugs to treat cancer is that efficacy in cell culture models not always predictive of patients. One limitation standard a reliance on non-physiological nutrient levels propagate cells. Which nutrients are available can influence how cells use metabolism proliferate and impact sensitivity some drugs, but general assessment physiological affect response small molecule therapies lacking. To enable compounds determine the environment impacts drug...

10.1101/2023.02.25.529972 preprint EN cc-by-nc bioRxiv (Cold Spring Harbor Laboratory) 2023-02-27

Abstract Background Genetically engineered mouse models (GEMMs) of cancer are powerful tools to study mechanisms disease progression and therapy response, yet little is known about how these respond multimodality used in patients. Radiation (RT) frequently treat localized cancers with curative intent, delay oligometastases, palliate symptoms metastatic disease. Methods Here we report the development, testing, validation a platform immobilize target tumors mice stereotactic ablative RT...

10.1038/s43856-023-00336-3 article EN cc-by Communications Medicine 2023-08-09

BFL1, a member of the antiapoptotic BCL2 family, has been relatively understudied compared to its counterparts despite evidence overexpression in various hematological malignancies. Across two articles, we describe development BFL1 vivo tools. The first article describes hit identification from covalent fragment library and subsequent evolution compound 6.22 This work reports structure-based optimization 6 into series inhibitors selective over other family members, with low nanomolar...

10.1021/acs.jmedchem.4c01995 article EN Journal of Medicinal Chemistry 2024-12-06
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