Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

RNA-seq of CEACAM1- and CEACAM1+ regulatory T cells from tumor in patients with renal cell carcinoma

ABSTRACT: RNA-seq of CEACAM1- and CEACAM1+ regulatory T cells from tumor in patients with renal cell carcinoma

PROVIDER: PRJNA899835 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR22245447_1.fastq.gz	Fastqsanger.gz
	SRR22245447_2.fastq.gz	Fastqsanger.gz
	SRR22245448_1.fastq.gz	Fastqsanger.gz
	SRR22245448_2.fastq.gz	Fastqsanger.gz
	SRR22245449_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

RNA-seq of CEACAM1- and CEACAM1+ regulatory T cells from tumor in patients with renal cell carcinoma

Project description:We aimed to analyze the transcriptomic differences between CEACAM1- and CEACAM1+ regulatory T cells from tumor.

2023-01-25 | GSE217613 | GEO

dePillis2013 - Mathematical modeling of regulatory T cell effects on renal cell carcinoma treatment

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

Next Generation Sequencing from Tumor Tissues And Tumor-adjacent Tissues of Renal Cell Carcinoma

Project description:Tumor-adjacent tissues are very important for tumor research. This study aimed to identify hub genes in tumor-adjacent tissues of mice transplanted with 786-o renal cell carcinoma cells. 786-o cells were implanted in nude mice raised to 1 month of age, and normal tissues, tumor tissues, and adjacent tissues were obtained for RNA sequencing. All tissues were sequenced for transcriptome genes. This was the first systematic exploration of the hub genes in the tumor-adjacent tissues of mice transplanted with 786-o renal cell carcinoma cells, which provides a genetic basis for further in-depth study on the underlying regulatory mechanism of renal cell carcinoma.

2022-02-24 | GSE197100 | GEO

Renal papillary cell carcinoma

Project description:Renal papillary cell carcinoma

| PRJNA749556 | ENA

Genomic profiling of renal cell carcinoma in patients with end-stage renal disease

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

Renal cell carcinoma: a proteomic approach

Project description:The proteome of clinical tissue samples diagnosed with clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC) were evaluated analyzed along with the dataset identifier PXD022018 to establish a potential discriminative biomarker panel of proteins for these tumors subtypes.

2021-12-15 | PXD023296 | Pride

RNA-seq of regulatory T cells from peripheral blood and tumor in patients with renal cell carcinoma

Project description:RNA-seq of regulatory T cells from peripheral blood and tumor in patients with renal cell carcinoma

| PRJNA900570 | ENA

Genomic profiling of renal cell carcinoma in patients with end-stage renal disease

2012-03-24 | E-GEOD-28601 | biostudies-arrayexpress

Effect of ablation of CEACAM1 on gene expression in human regulatory T cells

Project description:To study the contribution of CEACAM1 in human Tregs, CEACAM1 was knocked out in ex-vivo expanded human Tregs by Crispr/Cas9. Tregs transfected with scramble gRNAs were used as controls. After electroporation, scramble or CEACAM1KO Tregs were subcultured with IL-2 for 7 days and RNA was isolated for genome-wide RNA-seq. Gene expression profiling analysis was performed using data obtained from RNA-seq of two replicates of CEACAM1KO and control cells.

2025-07-23 | GSE259322 | GEO

Genomic profiling of 19 renal cell carcinoma samples from patients with end-stage renal disease

Project description:In this study, 19 tumor samples from 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× Array.

2012-04-02 | GSE33117 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data