Key regulators in two different colorectal cancer cell lines 1638N-T1 vs. CMT-93
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE78696 | GEO | 2016/12/02
SECONDARY ACCESSION(S): PRJNA313230
REPOSITORIES: GEO
Similar Datasets
Project description:We show here the transcriptional response in CMT-93 intestinal epithelial cells treated with Trichuris muris antigen and/or a garlic extract (40% PTSO-PTS).
2021-11-02 | GSE178655 | GEO
Project description:There are ~1.4 million cases of colorectal cancer (CRC) annually worldwide. Due to recent implementation of bowel cancer screening (BCS), incidence of diagnosis with stage I (T1/2, N0, M0) CRC has increased nearly four-fold; from approximately 12% pre-screening to approximately 42-45%. While survival rates for patients diagnosed with stage I CRC remains above 95%, and identification of patients at this early stage provides the best opportunity to improve in cancer survival rates, recent data has provided quantitative evidence that metastatic seeding can occur from disseminated cells at the very earliest stage of CRC development. The aim of study was to give an insight into aggressive “born-to-be-bad” biology through generation and transcriptional profiling of a novel case-controlled retrospective T1 CRC discovery cohort. We performed transcriptional and histological profiling to identify molecular pathology features of the high-risk metastatic phenotypes, discriminating between relapse and non-relapse T1 lesions and found that a cohort of aggressive early disseminating stage 1 CRC is associated with high cell intrinsic TGFB signalling and not stromal signalling.
2021-11-30 | GSE162667 | GEO
Project description:If we can more accurately predict the likelihood of regional lymph node metastasis (LNM) for endoscopically resected T1-stage colorectal cancers (CRC), the number of unnecessary additional surgeries can be reduced. We aimed of identify miRNA markers that can predict LNM-positive tumors among T1-stage CRCs and we also developed a miRNA classifier set for facilitating the accuracy and applicability.
2015-09-30 | GSE70574 | GEO
Project description:The NGS-aided mRNA-seq analysis was conducted to survey transcriptome changes by each of following mutations; bz1728, bz1728nobiro6, nbr6-t1 or taf12-t1.
2022-01-26 | GSE163911 | GEO
Project description:Here we studied the role of oxidized phospholipids in mediating phenotype switching of endothelial cells between quiescent and angiogenic states. Two oxPAPC datasets, a microRNA array and global run-on sequencing (GRO-seq), was combined with Nuclear factor erythroid 2-Related Factor 2 (NRF2) binding model to select candidate miRNAs for further studies. The pre-screening resulted in a selection of miR-106b~25 cluster for further studies. The cluster was shown to be both oxPAPC-responsive and NRF2-regulated, and its diagnostic and prognostic potential was investigated in pericardial fluid samples of heart failure and atherosclerosis patients. As the most abundant member of the cluster in both endothelial cells and pericardial fluid of atherosclerosis patients, miR-93-5p was selected for more detailed studies. RNA-seq from miR-93 overexpressing cells revealed significant changes in pathways related to angiogenesis. Together with NRF2, miR-93 was shown to control endothelial plasticity through regulation of the key players, namely Krüppel-like factor 2 (KLF2) for quiescence, 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) for glycolysis, and Vascular Endothelial Growth Factor A (VEGFA), Forkhead box protein O1 (FOXO1) and MYC proto-oncogene protein (MYC) for growth and proliferation.The findings show that NRF2 and miR-93 control the activity of endothelial cells and mediate the effects of oxPAPC on endothelial activation, collectively providing novel mechanisms for the control of endothelial plasticity and oxPAPC response.
2017-11-01 | GSE103530 | GEO
Project description:Acidovorax sp. T1 strain:T1 Genome sequencing and assembly
| PRJNA388301 | ENA
Project description:Stage T1 bladder cancers have the highest progression and recurrence rates of all non-muscle invasive bladder tumors. T1 tumors are heterogeneous; while most T1 patients are treated with BCG, many will progress and die from bladder cancer, and particularly aggressive tumors could be treated by early cystectomy. To better understand the molecular heterogeneity of T1 cancers, we performed transcriptome profiling and unsupervised clustering, identifying five consensus subtypes of T1 tumors treated with reTUR, induction and maintenance BCG. The T1-LumGU subtype was associated with CIS (6/13, 46% of all CIS), had high E2F1 and EZH2 expression, and enriched E2F target and G2M checkpoint Hallmarks. T1-Inflam was inflamed and infiltrated with immune cells. While most T1 tumors were classified as luminal papillary, the T1-TLum subtype had the highest median Luminal Papillary score and FGFR3 expression, no recurrence events, and the fewest copy number gains. T1-Myc and T1-Early subtypes had the most recurrences (14/30 within 24 months), highest median MYC expression, and, when combined, had significantly worse recurrence-free survival than the other three subtypes. T1-Early had 5 (38%) recurrences within the first 6 months of BCG, and repressed IFN-alpha and IFN-gamma Hallmarks and inflammation. We developed a single-patient T1 classifier and validated our subtype biology in a second cohort of T1 tumors. Future research will be necessary to validate the proposed T1 subtypes and to determine if therapies can be individualized for each subtype.
2020-07-13 | GSE154261 | GEO
Project description:The following CGH experiments were conducted on four sectors (S1-S4) from a single primary ductal carcinoma tumor (T1).
2009-07-10 | GSE16598 | GEO
Project description:Key regulators in two different colorectal cancer cell lines 1638N-T1 vs. CMT-93
| PRJNA313230 | ENA
Project description:The presence of lymph node metastasis (LNM) affects treatment strategy decisions in T1NxM0 colorectal cancer (CRC), but the currently used clinicopathological-based risk stratification cannot be used to accurately predict LNM. In this study, we established a model for predicting LNM and explored the mechanism of metastasis in T1 CRC.
2023-04-12 | PXD041476 | iProX