Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA353118 | ENA |
REPOSITORIES: ENA
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Project description:Autophagy plays important roles in malignant pathogenesis and drug resistance. We used medicinal chemistry approaches to generate a series of novel agents that inhibit autophagic degradation. ROC-325 was selected as a lead compound for further evaluation. Comprehensive in vitro and in vivo studies were conducted to evaluate the selectivity, tolerability, and efficacy of ROC-325 in preclinical models of renal cell carcinoma (RCC). ROC-325 exhibited superior in vitro anticancer effects than the existing autophagy inhibitor hydroxychloroquine in 12 different tumor models with diverse genetic backgrounds. Focused studies of the mechanism of action and efficacy of ROC-325 in RCC cells showed that drug treatment induced hallmark characteristics of autophagy inhibition including accumulation of autophagosomes with undegraded cargo, lysosomal deacidification, p62 stabilization, and disruption of autophagic flux. Subsequent experiments showed that ROC-325 antagonized RCC growth and survival in an ATG5/7-dependent manner, induced apoptosis, and exhibited favorable selectivity. Oral administration of ROC-325 to mice bearing 786-0 RCC xenografts was well tolerated, significantly more effective at inhibiting tumor progression than HCQ, and inhibited autophagy in vivo. We used microarrays to determine gene expression changes following 24 h treatment with ROC-325 in RCC cell lines and identified differentially expressed genes.
2018-02-16 | GSE89766 | GEO
Project description:Aneuploidy-induced cellular stresses limit autophagic degradation.
| PRJNA258554 | ENA
Project description:Peroxisome proliferator-activated receptor-gamma (PPARg) regulates the interface between cellular lipid metabolism, redox status and organelle differentiation. Following conditional prostatic epithelial knockout of PPARg in mice we observed focal hyperplasia of the epithelium which developed to mouse prostatic intraepithelial neoplasia (mPIN), becoming progressively more severe with time. We selectively knocked down PPARg2 isoform in wild-type mouse prostatic epithelial cells and examined the consequences of this in a tissue recombination model. Histopathologically the results resembled the conditional PPARg KO mouse prostates. Electron microscopy showed accumulated defective lysosomes and autophagic vacuoles in both of PPARg- and g2- deficient cells. Gene expression profiling indicated a major dysregulation of cell cycle control and metabolic signaling networks related to peroxisomal and lysosomal maturation, lipid oxidation and degradation. We conclude that PPARg maintains the maturation and turnover of peroxisomes and lysosomes in prostate epithelium. Disruption of PPARg signaling results in autophagy and oxidative stress during mPIN pathogenesis. The mPrE-PPARg knockout and mPrE-PPARg2 shRNA cells were compared to wildtype mPrE cells. Time (3 days culture) and cell types (x 4) were tested.
2010-05-18 | E-GEOD-13867 | biostudies-arrayexpress
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.
2020-01-06 | BIOMD0000000908 | BioModels
Project description:Genome-wide maps of H3K36me3 in metastatic renal cell carcinoma and isogenic renal cell carcinoma cell lines
| PRJNA278169 | ENA
Project description:LncRNA from metastatic clear cell renal cell carcinoma (ccRCC) compared with non-metastatic clear cell renal carcinoma
| PRJNA349174 | ENA