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1.
Cell ; 160(5): 977-989, 2015 Feb 26.
Artigo em Inglês | MEDLINE | ID: mdl-25723171

RESUMO

There is a lack of effective predictive biomarkers to precisely assign optimal therapy to cancer patients. While most efforts are directed at inferring drug response phenotype based on genotype, there is very focused and useful phenotypic information to be gained from directly perturbing the patient's living cancer cell with the drug(s) in question. To satisfy this unmet need, we developed the Dynamic BH3 Profiling technique to measure early changes in net pro-apoptotic signaling at the mitochondrion ("priming") induced by chemotherapeutic agents in cancer cells, not requiring prolonged ex vivo culture. We find in cell line and clinical experiments that early drug-induced death signaling measured by Dynamic BH3 Profiling predicts chemotherapy response across many cancer types and many agents, including combinations of chemotherapies. We propose that Dynamic BH3 Profiling can be used as a broadly applicable predictive biomarker to predict cytotoxic response of cancers to chemotherapeutics in vivo.


Assuntos
Morte Celular , Neoplasias/tratamento farmacológico , Transdução de Sinais , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Carcinoma Pulmonar de Células não Pequenas/patologia , Linhagem Celular , Feminino , Humanos , Leucemia Mielogênica Crônica BCR-ABL Positiva/tratamento farmacológico , Leucemia Mielogênica Crônica BCR-ABL Positiva/patologia , Mitocôndrias/metabolismo , Neoplasias/patologia , Neoplasias Ovarianas/tratamento farmacológico , Neoplasias Ovarianas/patologia , Medicina de Precisão
2.
Proc Natl Acad Sci U S A ; 114(17): E3434-E3443, 2017 04 25.
Artigo em Inglês | MEDLINE | ID: mdl-28396387

RESUMO

Oncogenic PIK3CA mutations are found in a significant fraction of human cancers, but therapeutic inhibition of PI3K has only shown limited success in clinical trials. To understand how mutant PIK3CA contributes to cancer cell proliferation, we used genome scale loss-of-function screening in a large number of genomically annotated cancer cell lines. As expected, we found that PIK3CA mutant cancer cells require PIK3CA but also require the expression of the TCA cycle enzyme 2-oxoglutarate dehydrogenase (OGDH). To understand the relationship between oncogenic PIK3CA and OGDH function, we interrogated metabolic requirements and found an increased reliance on glucose metabolism to sustain PIK3CA mutant cell proliferation. Functional metabolic studies revealed that OGDH suppression increased levels of the metabolite 2-oxoglutarate (2OG). We found that this increase in 2OG levels, either by OGDH suppression or exogenous 2OG treatment, resulted in aspartate depletion that was specifically manifested as auxotrophy within PIK3CA mutant cells. Reduced levels of aspartate deregulated the malate-aspartate shuttle, which is important for cytoplasmic NAD+ regeneration that sustains rapid glucose breakdown through glycolysis. Consequently, because PIK3CA mutant cells exhibit a profound reliance on glucose metabolism, malate-aspartate shuttle deregulation leads to a specific proliferative block due to the inability to maintain NAD+/NADH homeostasis. Together these observations define a precise metabolic vulnerability imposed by a recurrently mutated oncogene.


Assuntos
Classe I de Fosfatidilinositol 3-Quinases , Complexo Cetoglutarato Desidrogenase , Mutação , Proteínas de Neoplasias , Neoplasias , Animais , Linhagem Celular Tumoral , Ciclo do Ácido Cítrico/genética , Classe I de Fosfatidilinositol 3-Quinases/genética , Classe I de Fosfatidilinositol 3-Quinases/metabolismo , Glicólise/genética , Humanos , Complexo Cetoglutarato Desidrogenase/biossíntese , Complexo Cetoglutarato Desidrogenase/genética , Camundongos , Camundongos Nus , Proteínas de Neoplasias/genética , Proteínas de Neoplasias/metabolismo , Neoplasias/enzimologia , Neoplasias/genética , Neoplasias/patologia
3.
iScience ; 24(9): 102971, 2021 Sep 24.
Artigo em Inglês | MEDLINE | ID: mdl-34505004

RESUMO

Protein arginine methyltransferases (PRMTs) catalyze the post-translational monomethylation (Rme1), asymmetric (Rme2a), or symmetric (Rme2s) dimethylation of arginine. To determine the cellular consequences of type I (Rme2a) and II (Rme2s) PRMTs, we developed and integrated multiple approaches. First, we determined total cellular dimethylarginine levels, revealing that Rme2s was ∼3% of total Rme2 and that this percentage was dependent upon cell type and PRMT inhibition status. Second, we quantitatively characterized in vitro substrates of the major enzymes and expanded upon PRMT substrate recognition motifs. We also compiled our data with publicly available methylarginine-modified residues into a comprehensive database. Third, we inhibited type I and II PRMTs and performed proteomic and transcriptomic analyses to reveal their phenotypic consequences. These experiments revealed both overlapping and independent PRMT substrates and cellular functions. Overall, this study expands upon PRMT substrate diversity, the arginine methylome, and the complex interplay of type I and II PRMTs.

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