Whole-Transcriptomic Profiling of Sorted Human Renal Cell Carcinoma Immune Populations
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PROVIDER: EGAS00001006593 | EGA |
REPOSITORIES: EGA
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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
2012-03-24 | E-GEOD-28601 | biostudies-arrayexpress
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.
2012-03-24 | GSE28601 | GEO
Project description:The advent of micro-physiological systems (MPS) in biomedical research has enabled the introduction of more complex and relevant physiological into in vitro models. The recreation of complex morphological features in three-dimensional environments can recapitulate otherwise absent dynamic interactions in conventional models. In this study we developed an advanced in vitro Renal Cell Carcinoma (RCC) that mimics the interplay between healthy and malignant renal tissue. Based on the TissUse Humimic platform our model combines healthy renal proximal tubule epithelial cells (RPTEC) and RCC. Co-culturing reconstructed RPTEC tubules with RCC spheroids in a closed micro-perfused circuit resulted in significant phenotypical changes to the tubules. Expression of immune factors revealed that interleukin-8 (IL-8) and tumor necrosis factor-alfa (TNF-α) were upregulated in the non-malignant cells while neutrophil gelatinase-associated lipocalin (NGAL) was downregulated in both RCC and RPTEC. Metabolic analysis revealed that RCC prompted a shift in the energy production of RPTEC tubules, inducing glycolysis, in a metabolic adaptation that likely supports RCC growth and immunogenicity. In contrast, RCC maintained stable metabolic activity, emphasizing their resilience to external factors. RNA-seq and biological process analysis of primary RTPTEC tubules demonstrated that the 3D tubular architecture and MPS conditions reverted cells to a predominant oxidative phosphorylate state, a departure from the glycolytic metabolism observed in 2D culture. This dynamic RCC co-culture model, approximates the physiology of healthy renal tubules to that of RCC, providing new insights into tumor-host interactions. Our approach can show that an RCC-MPS can expand the complexity and scope of pathophysiology and biomarker studies in kidney cancer research.
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Project description:Renal cell carcinoma (RCC) is among the top 8 most diagnosed cancer in United States, which 79,000 patients newly were diagnosed and 13,920 deaths [1]. The clear-cell RCC (ccRCC) is the most common histopathological subtype representing approximately 85~90% in all diagnosed case [2]. In renal cancer treatment, metastasis is considered the most serious problem. Metastatic RCC (mRCC) is a fetal disease. It is known that about 25~30% of patients diagnosed with early kidney cancer have metastasized [3, 4]. The 5-year survival rate of patients with mRCC is 11.7%, and the prognosis is very poor [5]. Approximately 30% of patients have recurrence despite removal of the primary tumor, including 10-15% of patients found in T1 and clinically removed [4]. The mRCC patients show poor response to chemotherapy and radiotherapy, the rate of disappointing for treatment is increased from 15% to 25% [6, 7]. The common sites of RCC metastasis is known to the lung (40%), bone (30%), lymph node (22%) and liver (20%) [8].
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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
Project description:In order to clarify the molecular mechanism involved in renal carcinogenesis, and identify molecular targets for diagnosis and treatment, we analyzed genome-wide gene expression profiles of 15 surgical specimens of clear cell renal cell carcinoma (RCC), compared to normal renal cortex, using a combination of laser microbeam microdissection (LMM) with a cDNA microarray representing 27,648 genes.
2012-07-16 | GSE39364 | GEO
Project description:Renal cell carcinoma (RCC) represents about 2-3% of all cancers with over 400,000 new cases per year. Sunitinib, a vascular endothelial growth factor tyrosine kinase receptor inhibitor, has been used mainly for first-line treatment of metastatic clear-cell RCC with good or intermediate prognosis. However, about one third of metastatic RCC patients do not respond to sunitinib, leading to disease progression. Here we aim to find and characterize proteins associated with poor sunitinib response in a pilot proteomics study. 16 RCC tumors from patients responding (8) vs. non-responding (8) to sunitinib in 3 months after treatment initiation, together with their adjacent non-cancerous tissues, were analyzed using data independent acquisition mass spectrometry. Proteomics analysis quantified 1996 protein groups (q<0.01) and revealed 27 proteins deregulated between tumors non-responding vs. responding to sunitinib, representing a pattern of deregulated proteins potentially contributing to sunitinib resistance. Gene set enrichment analysis showed up-regulation of epithelial-to-mesenchymal transition with transgelin as one of the most significantly abundant protein. Transgelin expression was silenced by CRISPR/Cas9 and RNA interference, and the cells with reduced transgelin level exhibited significantly slower proliferation. Our data indicate that transgelin is an essential protein supporting RCC cell proliferation which could contribute to intrinsic sunitinib resistance.
2021-11-03 | PXD027065 | Pride
Project description:The tumor microenvironment (TME) in renal cell carcinomas (RCC) is marked by substantial immunosuppression and immune resistance though highly infiltrated by T cells. There is an urgent need to elucidate tumor immune evasion and to develop novel therapeutic target to boost the efficacy of immune checkpoint blockade (ICB) in RCC. Our study uncovers a mechanism wherein the polyadenylate-binding protein PABPC1L modulates indoleamine2, 3dioxygenase1 (IDO1), a prospective candidate for immunotherapy. PABPC1L, markedly upregulated in RCC, correlates with unfavorable prognosis and resistance to ICB. Overexpressed PABPC1L bolsters tryptophan metabolism and induces T-cell dysfunction by stabilizing IDO1. Conversely, silencing PABPC1L diminishes IDO1 expression, mitigates cytotoxic T-cell suppression, and enhances responsiveness to anti-PD-1 therapy. Our findings underscore PABPC1L's crucial role in facilitating immune evasion in RCC, making it a potential addition to ICB therapy.
2024-02-14 | GSE241871 | GEO
Project description:An analysis of the biphasic epithelioid (E-) and sarcomatoid(S-) components of sarcomatoid RCC and advanced stage non-sarcomatoid RCC (E*) showed that: the E- and S- components shared a similar transcriptomic signature, despite morphologic differences; and that the transcriptome of sarcomatoid RCC was sharply distinct from non-sarcomatoid RCC. The E- and R- components of rhabdoid RCC were also transcriptomically similar but distinct from RCC lacking rhabdoid/sarcomatoid features (E*). Total RNA processed and spotted on Illumina microarrays from the following patient samples: 38 sarcomatoid RCC (37 paired E- and S and 1 unpaired S-), 4 rhabdoid RCC (paired E- and R-) and 56 non-sarcomatoid RCC. There are 8 replicate samples (7 sarcomatoid RCC and 1 rhabdoid RCC).
2015-06-18 | E-GEOD-59264 | biostudies-arrayexpress