RESUMO
The aberrant regulation of protein expression and function can drastically alter cellular physiology and lead to numerous pathophysiological conditions such as cancer, inflammatory diseases, and neurodegeneration. The steady-state expression levels of endogenous proteins are controlled by a balance of de novo synthesis rates and degradation rates. Moreover, the levels of activated proteins in signaling cascades can be further modulated by a variety of posttranslational modifications and protein-protein interactions. The field of targeted protein degradation is an emerging area for drug discovery in which small molecules are used to recruit E3 ubiquitin ligases to catalyze the ubiquitination and subsequent degradation of disease-causing target proteins by the proteasome in both a dose- and time-dependent manner. Traditional approaches for quantifying protein level changes in cells, such as Western blots, are typically low throughput with limited quantification, making it hard to drive the rapid development of therapeutics that induce selective, rapid, and sustained protein degradation. In the last decade, a number of techniques and technologies have emerged that have helped to accelerate targeted protein degradation drug discovery efforts, including the use of fluorescent protein fusions and reporter tags, flow cytometry, time-resolved fluorescence energy transfer (TR-FRET), and split luciferase systems. Here we discuss the advantages and disadvantages associated with these technologies and their application to the development and optimization of degraders as therapeutics.
Assuntos
Descoberta de Drogas/métodos , Ensaios de Triagem em Larga Escala , Terapia de Alvo Molecular/métodos , Complexo de Endopeptidases do Proteassoma/metabolismo , Processamento de Proteína Pós-Traducional , Bibliotecas de Moléculas Pequenas/farmacologia , Ubiquitina-Proteína Ligases/metabolismo , Células Eucarióticas/citologia , Células Eucarióticas/efeitos dos fármacos , Células Eucarióticas/metabolismo , Citometria de Fluxo/métodos , Humanos , Ligantes , Ligação Proteica , Proteólise/efeitos dos fármacos , Proteínas Recombinantes de Fusão/genética , Proteínas Recombinantes de Fusão/metabolismo , Bibliotecas de Moléculas Pequenas/química , Espectrometria de Fluorescência/métodos , Coloração e Rotulagem/métodos , Ubiquitina-Proteína Ligases/genética , Ubiquitinação/efeitos dos fármacosRESUMO
PURPOSE: Chronic lymphocytic leukemia (CLL) with 17p deletion typically progresses quickly and is refractory to most conventional therapies. However, some del(17p) patients do not progress for years, suggesting that del(17p) is not the only driving event in CLL progression. We hypothesize that other concomitant genetic abnormalities underlie the clinical heterogeneity of del(17p) CLL. EXPERIMENTAL DESIGN: We profiled the somatic mutations and copy number alterations (CNA) in a large group of del(17p) CLLs as well as wild-type CLL and analyzed the genetic basis of their clinical heterogeneity. RESULTS: We found that increased somatic mutation number associates with poor overall survival independent of 17p deletion (P = 0.003). TP53 mutation was present in 81% of del(17p) CLL, mostly clonal (82%), and clonal mutations with del(17p) exhibit shorter overall survival than subclonal mutations with del(17p) (P = 0.019). Del(17p) CLL has a unique driver mutation profile, including NOTCH1 (15%), RPS15 (12%), DDX3X (8%), and GPS2 (6%). We found that about half of del(17p) CLL cases have recurrent deletions at 3p, 4p, or 9p and that any of these deletions significantly predicts shorter overall survival. In addition, the number of CNAs, but not somatic mutations, predicts shorter time to treatment among patients untreated at sampling. Indolent del(17p) CLLs were characterized by absent or subclonal TP53 mutation and few CNAs, with no difference in somatic mutation number. CONCLUSIONS: We conclude that del(17p) has a unique genomic profile and that clonal TP53 mutations, 3p, 4p, or 9p deletions, and genomic complexity are associated with shorter overall survival. Clin Cancer Res; 23(3); 735-45. ©2016 AACR.