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61.
I Ahmad 《Annals of the Royal College of Surgeons of England》2015,97(7):481-486
Urothelial cell carcinoma (UCC) of the bladder is one of the most common malignancies, causing considerable morbidity and mortality worldwide. It is unique among the epithelial carcinomas as two distinct pathways to tumourigenesis appear to exist: low grade, recurring papillary tumours usually contain oncogenic mutations in FGFR3 or HRAS whereas high grade, muscle invasive tumours with metastatic potential generally have defects in the pathways controlled by the tumour suppressors p53 and retinoblastoma. Over the last two decades, a number of transgenic mouse models of UCC, containing deletions or mutations of key tumour suppressor genes or oncogenes, have helped us understand the mechanisms behind tumour development. In this summary, I present my work investigating the role of the WNT signalling cascade in UCC. 相似文献
62.
《Cancer cell》2021,39(11):1497-1518.e11
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Bimal Bhindi Christine M. Lohse Phillip J. Schulte Ross J. Mason John C. Cheville Stephen A. Boorjian Bradley C. Leibovich R. Houston Thompson 《European urology》2019,75(5):766-772
Background
Partial nephrectomy (PN) is generally favored for cT1 tumors over radical nephrectomy (RN) when technically feasible. However, it can be unclear whether the additional risks of PN are worth the magnitude of renal function benefit.Objective
To develop preoperative tools to predict long-term estimated glomerular filtration rate (eGFR) beyond 30 d following PN and RN, separately.Design, setting, and participants
In this retrospective cohort study, patients who underwent RN or PN for a single nonmetastatic renal tumor between 1997 and 2014 at our institution were identified. Exclusion criteria were venous tumor thrombus and preoperative eGFR <15 ml/min/1.73 m2.Intervention
RN and PN.Outcome measurements and statistical analysis
Hierarchical generalized linear mixed-effect models with backward selection of candidate preoperative features were used to predict long-term eGFR following RN and PN, separately. Predictive ability was summarized using marginal , which ranges from 0 to 1, with higher values indicating increased predictive ability.Results and limitations
The analysis included 1152 patients (13 206 eGFR observations) who underwent RN and 1920 patients (18 652 eGFR observations) who underwent PN, with mean preoperative eGFRs of 66 ml/min/1.73 m2 (standard deviation [SD] = 18) and 72 ml/min/1.73 m2 (SD = 20), respectively. The model to predict eGFR after RN included age, diabetes, preoperative eGFR, preoperative proteinuria, tumor size, time from surgery, and an interaction between time from surgery and age (marginal ). The model to predict eGFR after PN included age, presence of a solitary kidney, diabetes, hypertension, preoperative eGFR, preoperative proteinuria, surgical approach, time from surgery, and interaction terms between time from surgery and age, diabetes, preoperative eGFR, and preoperative proteinuria (marginal ). Limitations include the lack of data on renal tumor complexity and the single-center design; generalizability needs to be confirmed in external cohorts.Conclusions
We developed preoperative tools to predict renal function outcomes following RN and PN. Pending validation, these tools should be helpful for patient counseling and clinical decision-making.Patient summary
We developed models to predict kidney function outcomes after partial and radical nephrectomy based on preoperative features. This should help clinicians during patient counseling and decision-making in the management of kidney tumors. 相似文献67.
68.
Lara Feulner Hamed S. Najafabadi Simon Tanguay Janusz Rak Yasser Riazalhosseini 《Urologic oncology》2019,37(2):166-175
Background
Clear cell renal cell carcinoma (ccRCC) is known to occur across the adult lifetime traversing the spectrum of age-related organismal changes. Little is known as to how the aging process may affect the course of renal cell carcinoma (RCC) and the repertoire of genes involved.Methods
Using The Cancer Genome Atlas (n?=?436) and Cancer Genomics of the Kidney (n?=?89) datasets, we applied regression analysis to examine associations between patient age and gene expression profiles in ccRCC tumors and normal kidney tissues. Pathway enrichment analysis was performed to identify cellular process that is affected by aging in ccRCC. Moreover, connectivity mapping analysis was used to predict age-dependent response to drug treatments.Results
Our analysis revealed different age-dependent gene expression spectra in ccRCC and normal kidney tissues. These findings were significant and independently reproducible in both datasets examined. Age up-regulated genes, showing higher expression in older patients, were significantly enriched (false discovery rate <0.05) in normal tissues for pathways associated with immune response and extracellular matrix organization, whereas age up-regulated genes in tumors were enriched for metabolism and oxidation pathways. Strikingly, age down-regulated genes in normal cells were also enriched for metabolism and oxidation, while those in tumors were enriched for extracellular matrix organization. Further in silico analysis of potential drug targets predicted preferential efficacy of Phosphoinositide 3-kinase inhibitor or immunotherapy in association with age.Conclusion
We report on previously unrecognized associations between age and molecular underpinnings of RCC, including age-associated expression of genes implicated in RCC development or treatment. 相似文献69.
70.
《Journal of pharmaceutical sciences》2019,108(7):2500-2504
Accurately predicting the hepatic clearance of compounds using in vitro to in vivo extrapolation (IVIVE) is crucial within the pharmaceutical industry. However, several groups have recently highlighted the serious error in the process. Although empirical or regression-based scaling factors may be used to mitigate the common underprediction, they provide unsatisfying solutions because the reasoning behind the underlying error has yet to be determined. One previously noted trend was intrinsic clearance-dependent underprediction, highlighting the limitations of current in vitro systems. When applying these generated in vitro intrinsic clearance values during drug development and making first-in-human dose predictions for new chemical entities though, hepatic clearance is the parameter that must be estimated using a model of hepatic disposition, such as the well-stirred model. Here, we examine error across hepatic clearance ranges and find a similar hepatic clearance-dependent trend, with high clearance compounds not predicted to be so, demonstrating another gap in the field. 相似文献