Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Deep transcriptional profiling of the two cancer stem cell populations present in the SW480 cell line as presented in "Colorectal Cancer Stem Cell Subtypes Orchestrate Distinct Tumor Microenvironments" [bulk RNA-seq]

ABSTRACT: Tumor heterogeneity derives from diverse populations of cancer cells that contribute unique properties to the microenvironment and tumor progression. While multiple classification systems have been developed to define tumor subtypes in colorectal cancer (CRC), the lack of single cell resolution has prohibited a better understanding of how these distinct cancer cell subtypes influence the overall tumor phenotype. Here were report that two cancer stem cell subtypes that are oncogenic versions of the intestinal Crypt Base Columnar (CBC) and Regenerative Stem Cell (RSC) populations, are commonly co-present in human CRC. We develop subtype-specific xenograft models utilizing a heterogeneous patient cell line (SW480) that contains CBCs and RSCs, and we define their tumor microenvironments at high resolution via single cell RNA sequencing. RSCs create differentiated, inflammatory, slow growing tumors. CBCs create proliferative, immune-suppressive, invasive tumors. With this enhanced resolution, we unify current CRC patient classification schema with TME phenotypes and organization.

ORGANISM(S): Homo sapiens

PROVIDER: GSE254891 | GEO | 2024/04/25

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Single cell profiling of SW480 subtype-specific subcutaneous and orthotopic xenografts (SW480-CBC and SW480-RSC) as presented in "Colorectal Cancer Stem Cell Subtypes Orchestrate Distinct Tumor Microenvironments" [scRNA-seq]

Project description:Tumor heterogeneity derives from diverse populations of cancer cells that contribute unique properties to the microenvironment and tumor progression. While multiple classification systems have been developed to define tumor subtypes in colorectal cancer (CRC), the lack of single cell resolution has prohibited a better understanding of how these distinct cancer cell subtypes influence the overall tumor phenotype. Here were report that two cancer stem cell subtypes that are oncogenic versions of the intestinal Crypt Base Columnar (CBC) and Regenerative Stem Cell (RSC) populations, are commonly co-present in human CRC. We develop subtype-specific xenograft models utilizing a heterogeneous patient cell line (SW480) that contains CBCs and RSCs, and we define their tumor microenvironments at high resolution via single cell RNA sequencing. RSCs create differentiated, inflammatory, slow growing tumors. CBCs create proliferative, immune-suppressive, invasive tumors. With this enhanced resolution, we unify current CRC patient classification schema with TME phenotypes and organization.

2024-04-25 | GSE254890 | GEO

Single-Cell Transcriptomes of the Regenerating Intestine Reveal a Revival Stem Cell [part 1]

Project description:The weekly turnover of the intestinal epithelium is driven by multipotent, Lgr5+, crypt base columnar cells (CBCs). In response to injury, however, Lgr5+ cells are lost but then re-emerge and are required for successful recovery. How these resurgent Lgr5+ stem cells arise is unclear. We transcriptionally profiled single cells from regenerating intestinal epithelia and identified a unique cell type we term the revival stem cell (rSC). rSCs are mutually exclusive to CBCs and are distinguished by elevated expression of cell survival and DNA repair genes. In homeostasis, rSCs are extremely rare, but nevertheless give rise to all the major cell types of the intestine including crypt-villus axes. After damage rSCs display a 20-fold, Yap-dependent, transient expansion, reconstitute the Lgr5+ CBC compartment and are required to regenerate a functional intestine. These studies define a unique stem cell phenotype that is mobilized by damage to reconstitute the intestinal epithelium.

2019-02-28 | GSE117783 | GEO

Single-Cell Transcriptomes of the Regenerating Intestine Reveal a Revival Stem Cell [part 2]

2019-02-28 | GSE123515 | GEO

Consensus Molecular Subtype predicts differential vulnerability of colorectal cancer to the survivin suppressant YM155 II

Project description:Tumor heterogeneity is a major challenge to the treatment of colorectal cancer (CRC). Recently, a transcriptome-based classification was developed, segregating CRC into four consensus molecular subtypes (CMS) with distinct biological and clinical characteristics. Here, we applied the CMS classification on CRC cell lines to identify novel subtype-specific drug vulnerabilities. We combined publicly available transcriptome data from multiple resources to assign 159 CRC cell lines to CMS. By integrating results from large scale drug screens, we discovered that CMS1 cancer is highly vulnerable to the survivin suppressor YM155. We confirmed our results using an independent panel of CRC cell lines and demonstrate a 100-fold higher sensitivity of CMS1 lines. This vulnerability was specific to YM155 and not observed for commonly used chemotherapeutic agents. In CMS1 cancer, low concentrations of YM155 induced apoptosis and expression signatures associated with NFkappaB and ER stress mediated apoptosis signaling. Using a genome-wide CRISPR/Cas9 screen, we discovered a novel role of genes involved in LDL-receptor recycling as modulators of YM155 response in CMS1 CRC. Our work shows that combining drug response data with CMS classification in cell lines can reveal specific vulnerabilities and propose YM155 as novel CMS1 specific drug. We performed expression profiling experiments in order to validate molecular subtypes for selected cell lines

2018-07-03 | GSE116528 | GEO

AKT dependent Notch3 activation drives tumor progression in a model of mesenchymal colorectal cancer subtype

Project description:Recently a consensus molecular subtype (CMS) classification of colorectal cancer (CRC) has been established that is based on the transcriptional rather than the genetic profile of an individual tumor and which may ultimately help to individualize CRC therapy. So far, however, the lack of appropriate animal models that faithfully recapitulate the different molecular subtypes impedes adequate preclinical testing of stratified therapeutic concepts. Here we demonstrate that constitutive AKT activation in intestinal epithelial cells markedly enhances colonic tumor invasion and metastasis in Trp53DIEC mice (Trp53ΔIECAktE17K) upon challenge with the carcinogen azoxymethane (AOM). Gene-expression profiling indicates that Trp53ΔIECAktE17K tumors closely resemble the human mesenchymal colorectal cancer subtype (CMS4), which is characterized by the poorest survival rate among the four consensus molecular subtypes of CRC. Trp53ΔIECAktE17K tumors are further characterized by a NOTCH pathway gene signature and a distinct cell autonomous upregulation of Notch3 in tumor epithelia while treatment of Trp53ΔIECAktE17K mice with a NOTCH3-inhibiting antibody reduces invasion and metastasis. Conversely, selective activation of NOTCH3 by overexpression of NOTCH3-IC in Akt wt tumor organoids strongly promotes development of metastasis in an orthotopic transplantation model. In CRC patients NOTCH3 expression correlates positively with tumor grading and the presence of lymph node as well as distant metastases and is specifically upregulated in CMS4 tumors. Therefore, we suggest NOTCH3 as a putative target for advanced CMS4 CRC patients.

2021-09-08 | PXD014778 | Pride

Colorectal cancer classification based on gene expression is not associated with FOLFIRI response

Project description:Sadanandam et al. (2013) recently published a study based on the use of microarray data to classify colorectal cancer (CRC) samples. The classification claimed to have strong clinical implications, as reflected in the paper title: “A colorectal cancer classification system that associates cellular phenotype and responses to therapy”. They defined five subtypes: (i) inflammatory; (ii) goblet-like; (iii) enterocyte; (iv) transit-amplifying; and (v) stem-like. Based on drug sensitivity data from 21 patients, they also reported that the so-called stem-like subtype show differential sensitivity to FOLFIRI. This is the key result in their publication, since it implies a direct relation between the subtype and the choice of CRC therapy (i.e. FOLFIRI response). However, our analyses using the same drug sensitivity data and results from additional patients showed that the CRC classification reported by Sadanandam et al. is not predictive of FOLFIRI response. We used the classification algorithm to obtain CRC subtypes from our samples. Then we tested the subtype-drug response association performing a retrospective study.

2014-09-10 | E-GEOD-54483 | biostudies-arrayexpress

Consensus Molecular Subtype predicts differential vulnerability of colorectal cancer to the survivin suppressant YM155 I

2018-07-03 | GSE116529 | GEO

CRIS, a superior predictive and prognostic classification system of colorectal cancer based on high-resolution analysis of cancer cell-autonomous traits

Project description:Recent work built on published transcriptional subtypes of colorectal cancer (CRC) has shown that tumor stromal content impacts CRC classification, with both clinical and biological implications. To Tackle the issue of intrinsic epithelial gene profiles, we assembled a dataset of matched liver metastatic colorectal cancer and Patients Derived Xenografts. in which the stroma of the original tumor is substituted by murine tissue, we deployed a molecularly annotated collection of 515 PDXs from 244 patients as a resource for species (human)-specific assessment of cancer-cell intrinsic transcriptional features. We identified five ColoRectal cancer Intrinsic Subtypes (CRIS) endowed with functional and phenotypic characteristics related to specific genetic traits, most of which were not evidenced in the transcriptional subgroups reported in previous studies.

2017-06-19 | GSE73255 | GEO

CRIS, a superior predictive and prognostic classification system of colorectal cancer based on high-resolution analysis of cancer cell-autonomous traits II

2017-06-19 | GSE76402 | GEO

Super-SILAC Allows Classification of Diffuse Large B-cell Lymphoma Subtypes by Their Protein Expression Profiles

Project description:Correct classification of cancer patients into subtypes is a prerequisite for acute diagnosis and effective treatment. Currently this classification relies mainly on histological assessment, but gene expression analysis bymicroarrays has shown great promise. Here we show that high accuracy, quantitative proteomics can robustly segregate cancer subtypes directly at the level of expressed proteins. We investigated two histologically indistinguishable subtypes of diffuse large B-cell lymphoma (DLBCL): activated Bcell- like (ABC) and germinal-center B-cell-like (GCB) subtypes, by first developing a general lymphoma stable isotope labeling with amino acids in cell culture (SILAC) mix from heavy stable isotope-labeled cell lines. This super- SILAC mix was combined with cell lysates from five ABCDLBCL and five GCB-DLBCL cell lines. Shotgun proteomic analysis on a linear ion trap Orbitrap mass spectrometer with high mass accuracy at the MS and MS/MS levels yielded a proteome of more than 7,500 identified proteins. High accuracy of quantification allowed robust separation of subtypes by principal component analysis. The main contributors to the classification included proteins known to be differentially expressed between the subtypes such as the transcription factors IRF4 and SPI1/ PU.1, cell surface markers CD44 and CD27, as well as novel candidates. We extracted a signature of 55 proteins that segregated subtypes and contained proteins connected to functional differences between the ABC and GCB-DLBCL subtypes, including many NF-kappa B-regulated genes. Shortening the analysis time to single-shot analysis combined with use of the new linear quadrupole Orbitrap analyzer (Q Exactive) also clearly differentiated between the subtypes. These results show that high resolution shotgun proteomics combined with super-SILAC-based quantification is a promising new technology for tumor characterization and classification.

2016-03-10 | MSV000079572 | MassIVE

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