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1.
Genetics ; 226(4)2024 04 03.
Artigo em Inglês | MEDLINE | ID: mdl-38290049

RESUMO

Mutations in SETD2 are among the most prevalent drivers of renal cell carcinoma (RCC). We identified a novel single nucleotide polymorphism (SNP) in SETD2, E902Q, within a subset of RCC patients, which manifests as both an inherited or tumor-associated somatic mutation. To determine if the SNP is biologically functional, we used CRISPR-based genome editing to generate the orthologous mutation within the Drosophila melanogaster Set2 gene. In Drosophila, the homologous amino acid substitution, E741Q, reduces H3K36me3 levels comparable to Set2 knockdown, and this loss is rescued by reintroduction of a wild-type Set2 transgene. We similarly uncovered significant defects in spindle morphogenesis, consistent with the established role of SETD2 in methylating α-Tubulin during mitosis to regulate microtubule dynamics and maintain genome stability. These data indicate the Set2 E741Q SNP affects both histone methylation and spindle integrity. Moreover, this work further suggests the SETD2 E902Q SNP may hold clinical relevance.


Assuntos
Carcinoma de Células Renais , Proteínas de Drosophila , Neoplasias Renais , Animais , Humanos , Carcinoma de Células Renais/genética , Carcinoma de Células Renais/metabolismo , Carcinoma de Células Renais/patologia , Histonas/genética , Histonas/metabolismo , Drosophila/metabolismo , Drosophila melanogaster/genética , Drosophila melanogaster/metabolismo , Polimorfismo de Nucleotídeo Único , Neoplasias Renais/genética , Neoplasias Renais/metabolismo , Neoplasias Renais/patologia , Fuso Acromático/genética , Fuso Acromático/metabolismo , Histona-Lisina N-Metiltransferase/genética , Histona-Lisina N-Metiltransferase/metabolismo , Proteínas de Drosophila/genética , Proteínas de Drosophila/metabolismo
2.
Invest Radiol ; 59(8): 569-576, 2024 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-38265058

RESUMO

OBJECTIVES: The Centers for Medicare and Medicaid Services funded the development of a computed tomography (CT) quality measure for use in pay-for-performance programs, which balances automated assessments of radiation dose with image quality to incentivize dose reduction without compromising the diagnostic utility of the tests. However, no existing quantitative method for assessing CT image quality has been validated against radiologists' image quality assessments on a large number of CT examinations. Thus to develop an automated measure of image quality, we tested the relationship between radiologists' subjective ratings of image quality with measurements of radiation dose and image noise. MATERIALS AND METHODS: Board-certified, posttraining, clinically active radiologists rated the image quality of 200 diagnostic CT examinations from a set of 734, representing 14 CT categories. Examinations with significant distractions, motion, or artifact were excluded. Radiologists rated diagnostic image quality as excellent, adequate, marginally acceptable, or poor; the latter 2 were considered unacceptable for rendering diagnoses. We quantified the relationship between ratings and image noise and radiation dose, by category, by analyzing the odds of an acceptable rating per standard deviation (SD) increase in noise or geometric SD (gSD) in dose. RESULTS: One hundred twenty-five radiologists contributed 24,800 ratings. Most (89%) were acceptable. The odds of an examination being rated acceptable statistically significantly increased per gSD increase in dose and decreased per SD increase in noise for most categories, including routine dose head, chest, and abdomen-pelvis, which together comprise 60% of examinations performed in routine practice. For routine dose abdomen-pelvis, the most common category, each gSD increase in dose raised the odds of an acceptable rating (2.33; 95% confidence interval, 1.98-3.24), whereas each SD increase in noise decreased the odds (0.90; 0.79-0.99). For only 2 CT categories, high-dose head and neck/cervical spine, neither dose nor noise was associated with ratings. CONCLUSIONS: Radiation dose and image noise correlate with radiologists' image quality assessments for most CT categories, making them suitable as automated metrics in quality programs incentivizing reduction of excessive radiation doses.


Assuntos
Doses de Radiação , Tomografia Computadorizada por Raios X , Humanos , Tomografia Computadorizada por Raios X/métodos , Radiologistas , Estados Unidos , Melhoria de Qualidade
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