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.
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Project description:Mus musculus Prcc, papillary renal cell carcinoma (translocation-associated) [Source:MGI Symbol;Acc:MGI:2137738], is differentially expressed in 54 experiment(s);
| ENSMUSG00000004895 | ExpressionAtlas
Project description:Mus musculus Prcc, papillary renal cell carcinoma (translocation-associated) [Source:MGI Symbol;Acc:MGI:2137738], is expressed in 37 baseline experiment(s);
| ENSMUSG00000004895 | ExpressionAtlas
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.
2024-09-02 | BIOMD0000000908 | BioModels