Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA394831 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Eleven TC-RCC cases were selected on the basis of the criteria defined by the 2012 Vancouver Classification of Renal Neoplasia and WHO 2016 classification criteria, and re-reviewed by a panel of expert renal pathologists. Two of these cases, TC-RCC#9 and #10, had a mixed tubulocystic and papillary histology and were macro-dissected into separate PRCC and TC-RCC components. The molecular basis of TC-RCC, and miRNA expression profile, is unknown. We therefore used Affymetrix miRNA v.2. arrays to elucidate the expression of these samples
2017-07-19 | GSE101563 | GEO
Project description:Renal cell carcinoma is the most common neoplasm of the adult kidney. A few subtypes of RCC include papillary RCC (pRCC), chromophobe RCC (chRCC) and the benign oncocytoma tumor. In some cases, distinguishing between the RCC subyptes is difficult. We performed a mircroRNA (miRNA) microarray to determine differential miRNA expression between pRCC, chRCC, and oncocytoma. We performed a miRNA microarray on 10 tumor samples of each papillary renal cell carcinoma (pRCC), chromophobe renal cell carcinoma (chRCC), and oncocytoma.
2012-08-13 | E-GEOD-39790 | biostudies-arrayexpress
Project description:Renal cell carcinoma is the most common neoplasm of the adult kidney. A few subtypes of RCC include papillary RCC (pRCC), chromophobe RCC (chRCC) and the benign oncocytoma tumor. In some cases, distinguishing between the RCC subyptes is difficult. We performed a mircroRNA (miRNA) microarray to determine differential miRNA expression between pRCC, chRCC, and oncocytoma.
2012-08-14 | GSE39790 | GEO
Project description:Between 80% and 90% of renal carcinomas are either clear cell renal cell carcinoma or papillary RCC although there are at least 20 other distinct forms of RCC recognised by the World Health Organization (WHO). Emerging or provisional entities have been considered as variants of PRCC, including papillary renal neoplasm with reversed polarity (PRNRP). However, the molecular basis of PRNRP, and miRNA expression profile, is unknown. We used microarray analysis to elucidate the non-coding RNA (ncRNA) profiles of 10 PRNRP cases and compared them with other renal neoplasms. Cases were only considered for this study after fulfilment of strict inclusive histological and immunohistochemical criteria. We used Affymetrix miRNA v.4.0 arrays to elucidate the expression of these samples.
2024-02-18 | GSE255707 | GEO
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:Renal cell carcinoma (RCC) is one of the most common cancers worldwide with nearly non-symptomatic course till advanced stage of disease. RCC can be distinguished into three subtypes: papillary (pRCC), chromophobe (chRCC) and clear cell renal cell carcinoma (ccRCC) representing up to 75% of all RCC cases. Detection and RCC monitoring tools are limited to standard imaging techniques, in combination with non-RCC specific morphological and biochemical read-outs. RCC subtype identification relays mainly on results of pathological examination of tumor slides. Molecular, clinically applicable and ideally non-invasive tools aiding RCC management are still non-existent, although molecular characterization of RCC is relatively advanced. Hence many research efforts concentrate on identification of molecular markers that will assist with RCC sub-classification and monitoring. Due to stability and tissue-specificity miRNAs are promising candidates for such biomarkers. Here we performed a meta-analysis study, utilized seven available NGS and seven microarray RCC studies in order to identify subtype-specific expression of miRNAs. We concentrated on four potentially oncocytoma-specific miRNAs (miRNA-424-5p, miRNA-146b-5p, miRNA-183-5p, miRNA-218-5p), two pRCC (miRNA-127-3p, miRNA-139-5p) and eight ccRCC specific miRNAs (miRNA-200c-3p, miRNA-362-5p, miRNA-363-3p and miRNA-204-5p, 21-5p, miRNA-224-5p, miRNA-155-5p, miRNA-210-3p) and validated their expression in an independent sample set. Additionally, we found ccRCC-specific miRNAs to be differentially expressed in ccRCC Fuhrman grades and identified alterations in their isoform composition in tumor tissue. Our results revealed that changes in expression of selected miRNA might be potentially utilized as a tool aiding ccRCC subclass discrimination and propose a miRNA panel aiding RCC subtype distinction.
2021-02-01 | GSE151423 | GEO
Project description:Renal cell carcinoma (RCC) is one of the most common cancers worldwide with nearly non-symptomatic course till advanced stage of disease. RCC can be distinguished into three subtypes: papillary (pRCC), chromophobe (chRCC) and clear cell renal cell carcinoma (ccRCC) representing up to 75% of all RCC cases. Detection and RCC monitoring tools are limited to standard imaging techniques, in combination with non-RCC specific morphological and biochemical read-outs. RCC subtype identification relays mainly on results of pathological examination of tumor slides. Molecular, clinically applicable and ideally non-invasive tools aiding RCC management are still non-existent, although molecular characterization of RCC is relatively advanced. Hence many research efforts concentrate on identification of molecular markers that will assist with RCC sub-classification and monitoring. Due to stability and tissue-specificity miRNAs are promising candidates for such biomarkers. Here we performed a meta-analysis study, utilized seven available NGS and seven microarray RCC studies in order to identify subtype-specific expression of miRNAs. We concentrated on four potentially oncocytoma-specific miRNAs (miRNA-424-5p, miRNA-146b-5p, miRNA-183-5p, miRNA-218-5p), two pRCC (miRNA-127-3p, miRNA-139-5p) and eight ccRCC specific miRNAs (miRNA-200c-3p, miRNA-362-5p, miRNA-363-3p and miRNA-204-5p, 21-5p, miRNA-224-5p, miRNA-155-5p, miRNA-210-3p) and validated their expression in an independent sample set. Additionally, we found ccRCC-specific miRNAs to be differentially expressed in ccRCC Fuhrman grades and identified alterations in their isoform composition in tumor tissue. Our results revealed that changes in expression of selected miRNA might be potentially utilized as a tool aiding ccRCC subclass discrimination and propose a miRNA panel aiding RCC subtype distinction.
2021-02-01 | GSE151419 | GEO
Project description:We performed a microRNA (miRNA) microarray on 10 metastatic RCC tumors and compared differential miRNA expresison to 19 primary clear cell renal cell carcinomas (ccRCC). We found there were 65 significantly dysregulated miRNAs; 9 miRNAs were significantly upregulated and 56 miRNAs were significantly downregulated in metastatic RCC when compared to primary clear cell renal cell carcinoma. miRNA microarray was performed on 10 metastatic RCC tumors
2012-08-13 | E-GEOD-39440 | biostudies-arrayexpress
Project description:We performed a microRNA (miRNA) microarray on 10 metastatic RCC tumors and compared differential miRNA expresison to 19 primary clear cell renal cell carcinomas (ccRCC). We found there were 65 significantly dysregulated miRNAs; 9 miRNAs were significantly upregulated and 56 miRNAs were significantly downregulated in metastatic RCC when compared to primary clear cell renal cell carcinoma.
2012-08-14 | GSE39440 | GEO
Project description:Purpose: Renal cell carcinoma (RCC) is often diagnosed incidentally as an early-stage small renal mass (SRM; pT1a, ≤ 4 cm). Increasing concerns surrounding the overtreatment of patients with benign or clinically indolent tumors has led to a shift in current treatment recommendations, especially for elderly and infirm patients. There are currently no available biomarkers to accurately stratify patients according to risk. Therefore, we set out to identify early biomarkers of RCC progression. Experimental Design: We employed label-free LC-MS/MS and targeted parallel-reaction monitoring (PRM) to identify early, non-invasive diagnostic and prognostic biomarkers for early-stage RCC-SRMs. In total, we evaluated 115 urine samples, including 33 renal oncocytoma (≤ 4 cm) cases, 30 progressive and 26 non-progressive clear cell RCC-SRM (ccRCC-SRM) cases, in addition to 26 healthy controls. Results: We identified nine endogenous peptides which displayed significantly elevated expression in ccRCC-SRMs relative to healthy controls. Peptides NVINGGSHAGNKLAMQEF, VNVDEVGGEALGRL, and VVAGVANALAHKYH showed significantly elevated expression in ccRCC-SRMs relative to renal oncocytoma. Additionally, peptides SHTSDSDVPSGVTEVVVKL and IVDNNILFLGKVNRP displayed significantly elevated expression in progressive relative to non-progressive ccRCC-SRMs. Peptide SHTSDSDVPSGVTEVVVKL showed the most significant discriminatory ability (AUC: 0.76, 95% CI: 0.62 to 0.90, p = 0.0027). Patients with elevated SHTSDSDVPSGVTEVVVKL expression had significantly shorter overall survival (HR: 4.13, 95% CI: 1.09 to 15.65, p = 0.024) compared to patients with lower expression. Conclusions: Our in-depth peptidomic analysis identified novel biomarkers for early-stage RCC-SRMs. Characterization of urinary peptides may provide insight into early RCC progression and could potentially help assign patients to appropriate management programs.
2019-08-08 | PXD013111 | Pride