Project description:In this study, 19 tumor samples from patients with renal cell carcinoma (RCC)-end-stage renal disease (ESRD) were analyzed by array comparative genomic hybridization (array CGH) using the Agilent Whole Human Genome 4× Array.
Project description:In this study, eighty tumor samples from 63 patients with renal cell carcinoma (RCC)-end-stage renal disease (ESRD) were analyzed by array comparative genomic hybridization (array CGH) using the Agilent Whole Human Genome 4×44K Oligo Micro Array.
Project description:In this study, 19 tumor samples from patients with renal cell carcinoma (RCC)-end-stage renal disease (ESRD) were analyzed by array comparative genomic hybridization (array CGH) using the Agilent Whole Human Genome 4× Array. 19 cystic disease samples from patients with RCC-ESRD
Project description:In this study, eighty tumor samples from 63 patients with renal cell carcinoma (RCC)-end-stage renal disease (ESRD) were analyzed by array comparative genomic hybridization (array CGH) using the Agilent Whole Human Genome 4×44K Oligo Micro Array. 79 tumor samples from 63 patients with RCC-ESRD
Project description:Mathematical modeling of regulatory T cell effects on renal cell carcinoma treatment
Lisette dePillis 1, , Trevor Caldwell 2, , Elizabeth Sarapata 2, and Heather Williams 2,
1.
Department of Mathematics, Harvey Mudd College, Claremont, CA 91711
2.
Harvey Mudd College, Claremont, CA 91711, United States, United States, United States
Abstract
We present a mathematical model to study the effects of the regulatory T cells (Treg) on Renal Cell Carcinoma (RCC) treatment with sunitinib. The drug sunitinib inhibits the natural self-regulation of the immune system, allowing the effector components of the immune system to function for longer periods of time. This mathematical model builds upon our non-linear ODE model by de Pillis et al. (2009) [13] to incorporate sunitinib treatment, regulatory T cell dynamics, and RCC-specific parameters. The model also elucidates the roles of certain RCC-specific parameters in determining key differences between in silico patients whose immune profiles allowed them to respond well to sunitinib treatment, and those whose profiles did not.
Simulations from our model are able to produce results that reflect clinical outcomes to sunitinib treatment such as: (1) sunitinib treatments following standard protocols led to improved tumor control (over no treatment) in about 40% of patients; (2) sunitinib treatments at double the standard dose led to a greater response rate in about 15% the patient population; (3) simulations of patient response indicated improved responses to sunitinib treatment when the patient's immune strength scaling and the immune system strength coefficients parameters were low, allowing for a slightly stronger natural immune response.
Keywords: Renal cell carcinoma, mathematical modeling., sunitinib, immune system, regulatory T cells.
Project description:We aim to identify profiling of circRNAs in renal tissue from renal cell carcinoma patients. In this study, seven paired frozen carcinoma tissues as well as normal tissues from patients with renal cell carcinoma were used for circRNA profiling by second generation of RNA sequencing.
Project description:Although renal cell carcinoma (RCC) is the sixth-leading cause of cancer death, the molecular events leading to disease onset and progression are not well understood. Genomic profiling of clear cell RCC (cRCC) patients indicated that loss of a negative regulator of the Wnt pathway, secreted frizzled-related protein 1 (sFRP1), occurred in the majority of more than 100 patients tested. To our knowledge, this is the first report of loss of sFRP1 expression in patients diagnosed with cRCC; this loss occurs in early stage cRCC, suggesting that it may be an important early event in renal carcinogenesis. Genomic profiling of patient matched normal and cRCC tissues identified Wnt regulated genes to be aberrantly increased in cRCC tissues suggesting sFRP1 suppresses Wnt signaling in cRCC. In order to test the hypothesis that sFRP1 acts as a tumor suppressor in cRCC, we have stably expressed sFRP1 in cRCC cells. sFRP1 expression in cRCC cells resulted in decreased growth in cell culture, inhibition of anchorage-independent growth, and decreased tumor volume in a nude mouse model. Together these data suggest an important role for sFRP1 as a tumor suppressor in cRCC. Keywords: Disease state analysis
