Project description:TFEB has been recently reported to be a key molecule for lysosomal regulation. Renal cell carcinoma (RCC) with t(6;11) (p21;q12) is known to be the only tumor in which TFEB is upregulated. Transcriptome analysis using a whole-genome expression array and pathway analysis using upregulated genes in tumor tissue revealed that the lysosome-associated pathways were significantly deregulated. Total RNA was extracted from non-tumor and tumor in patient of renal cell carcinoma with t(6;11) (p21;q12) and subjected to gene expression microarray analysis.
Project description:TFEB has been recently reported to be a key molecule for lysosomal regulation. Renal cell carcinoma (RCC) with t(6;11) (p21;q12) is known to be the only tumor in which TFEB is upregulated. Transcriptome analysis using a whole-genome expression array and pathway analysis using upregulated genes in tumor tissue revealed that the lysosome-associated pathways were significantly deregulated.
Project description:We report a case of a 55 years old women who present a ALK associated renal cell carcinoma, with 3p deletion and measling of TFE3 expression. With CGH analysis and FISH we identify the rearrangment of ALK with TPM3
Project description:Renal Cell Carcinoma (RCC) associated with Xp11.2 translocation (TFE3-RCC) has been recently defined as a distinct subset of RCC. The Xp11 translocations involve the TFE3 transcription factor and produce chimeric TFE3 proteins retaining the basic helix-loop-helix leucine zipper structure for dimerization. To facilitate the development of molecular-based diagnostic tools and targeted therapies for TFE3-RCC, we generated a translocation RCC mouse model and performed DNA microarray analysis.
Project description:We performed a transcriptomic analysis in a cohort of 6 Collecting Duct Carcinoma, 5 Clear Cell Renal Cell Carcinoma and 4 non-matched normal renal tissues to unravel the underlying biological and molecular determinants and to identifiy specific genes and pathways of this rare tumor type.
Project description:Pluripotent embryonic stem cells have a unique cell cycle structure with a suppressed G1/S restriction point and little differential expression across the cell cycle phases. Here, we evaluate the link between G1/S restriction point activation, phasic gene expression, and cellular differentiation. Expression analysis reveals a gain in phasic gene expression across lineages between embryonic days E7.5 and E9.5. Genetic manipulation of the G1/S restriction point regulators miR-302 and P27 respectively accelerates or delays the onset of phasic gene expression in mouse embryos. Relief of miR-302-mediated p21 or p27 suppression expedites embryonic stem cell differentiation, while a constitutive Cyclin E mutant blocks it. Together, these findings uncover a causal relationship between emergence of the G1/S restriction point with a gain in phasic gene expression and cellular differentiation.
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.
