Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [Bulk-RNA-seq]

ABSTRACT: We subject multiple versions and single cell-derived sublines of an archetypal non-small cell lung cancer cell line to experimental scrutiny at the genomic, transcriptomic, and cell population levels. We find evidence of genetic variability among cell line versions and one subline. Additional sublines show no genetic variation but epigenetic differences are detected at the transcriptomic level. Stochastic simulations of subline growth dynamics confirm that one subline likely contains at least two genetic states while all others are isogenic. Overall, our results substantiate a view of intratumoral heterogeneity in which different genetic states give rise to multiple epigenetic “basins of attraction,” across which cells can transition driven by stochastic factors such as gene expression noise and asymmetric cell division. Deconvolving intratumoral heterogeneity into genetic, epigenetic, and stochastic components provides a lens through which to view tumor drug response and acquired treatment resistance that may lead to novel therapeutic strategies in the future.

ORGANISM(S): Homo sapiens

PROVIDER: GSE150025 | GEO | 2020/05/08

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [scRNA-seq]

Project description:We subject multiple versions and single cell-derived sublines of an archetypal non-small cell lung cancer cell line to experimental scrutiny at the genomic, transcriptomic, and cell population levels. We find evidence of genetic variability among cell line versions and one subline. Additional sublines show no genetic variation but epigenetic differences are detected at the transcriptomic level. Stochastic simulations of subline growth dynamics confirm that one subline likely contains at least two genetic states while all others are isogenic. Overall, our results substantiate a view of intratumoral heterogeneity in which different genetic states give rise to multiple epigenetic “basins of attraction,” across which cells can transition driven by stochastic factors such as gene expression noise and asymmetric cell division. Deconvolving intratumoral heterogeneity into genetic, epigenetic, and stochastic components provides a lens through which to view tumor drug response and acquired treatment resistance that may lead to novel therapeutic strategies in the future.

2020-05-08 | GSE150083 | GEO

Human Embryonic Stem Cell Sublines

Project description:Human embryonic stem (ES) cell lines acquire recurrent karyotypic abnormalities that may promote growth and survival in long-term culture. Cells with these abnormalities are often present at low levels in human ES cell cultures, requiring subcloning for isolation and analyses. We have developed a rapid method to isolate either abnormal or normal clones from karyotypically mosaic human ES cell cultures that we call Genetic Diagnosis at Passage (G-DAP). We have used this technique to isolate three distinct abnormal sublines from H9 human ES cells in continuous culture. These sublines were characterized by G-banding, fluorescence in situ hybridization (FISH), spectral karyotyping (SKY), and array comparative genomic hybridization (aCGH). One subline (H9.DT) has, as it’s only abnormality, a duplication of 12p capped by a 5q subtelomere. A related subline (H9.TSF) has an additional copy of the derivative chromosome 12, partial trisomy of 17q, and trisomy 14. The third subline (H9.DE) has an interstitial deletion of 18q as the sole anomaly. Despite these karyotypic abnormalities, all three sublines retain markers of the undifferentiated state. The subline H9.TSF demonstrated the ability to form embryoid bodies consisting of all three germ layers. Significantly, H9.DT and H9.TSF sublines show a classic karyotype progression that mirrors that seen in both hematopoietic and solid tumors. This progression was accompanied by an impressive increase in growth potential. The isolation of human ES cell sublines with clonal cytogenetic abnormalities provides a valuable tool for study of factors that promote in vitro genetic changes and for analysis of mechanisms of aneuploidy related to genetic progression found in human cancers.

2008-07-18 | GSE12119 | GEO

Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities

Project description:Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities

| PRJNA631050 | ENA

Enhancement of metastasis by spontaneous ploidy doubling of breast cancer cell MDA-MB-231.

Project description:MDA-MB-231 bone-metastatic subline 1833 and lung metastatic subline 4175 underwent spontaneous ploidy doubling in culture, i.e. the genome approximately duplicated itself gradually. The modal- and hyper-ploid subpopulations during the ploidy transition were sorted into two separate sublines, 1833-Modal and 1833-Hyper for 1833, 4175-Modal and 4175-Hyper for 4175. Their expresssion patterns were compared to each other as well as to other MDA-MB-231 sublines isolated previously by Kang et al. 2003 and Minn et al. 2005. Keywords: Cell type comparison 19 cell lines were analyzed, including the parental line MDA-MB-231, modal-ploid sublines 1833-Modal and 4175-Modal, hyper-ploid sublines 1833-Hyper and 4175-Hyper, strongly bone-metastatic lines 1833 (the original subline after short culture), 2274, 2268 and 2269, weakly bone-metastatic lines 2293, 2295 and 2297, strongly lung-metastaic lines 4142, 4173, 4175 (the original subline after short culture) and 4180, and weakly lung-metastatic lines SCP6, SCP21 and SCP26. Single sample for each line.

2010-06-08 | E-GEOD-16554 | biostudies-arrayexpress

Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues

Project description:This SuperSeries is composed of the following subset Series: GSE41048: Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues (ChIP-Seq and MeDIP-Seq) GSE41049: Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues (Gene Expression data) Refer to individual Series

2012-09-24 | E-GEOD-41050 | biostudies-arrayexpress

Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [scRNA-seq]

Project description:Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [scRNA-seq]

| PRJNA631051 | ENA

Expression profiling of invasion associated molecules in head and neck cancer cells

Project description:Three isogenic HNC cell sublines with highly invasive properties were established. Invasion-associated genes were identified by comparison of transcriptomic profiles between HNC parental cell lines and the invasive sublines via Affymetrix cDNA microarrays. We used cDNA microarray to compare gene expression of invasion subline cells and parental cells in head and neck cancer.

2023-01-15 | GSE143689 | GEO

Enhancement of metastasis by spontaneous ploidy doubling of breast cancer cell MDA-MB-231.

2010-06-01 | GSE16554 | GEO

Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [Bulk-RNA-seq]

Project description:Multi-omics data and stochastic simulations support a cancer heterogeneity framework unifying genetic, epigenetic, and stochastic variabilities [Bulk-RNA-seq]

| PRJNA630953 | ENA

Identification of chemoresistant genes in hepatocellular carcinoma (HCC)

Project description:The aim of this study was to identify chemoresistance-associated genes in hepatocellular carcinoma (HCC). cDNA microarray analysis was performed to compare the mRNA expression profiles of a human metastatic HCC cell line (named MHCC97Low) and its derived chemoresistant sublines including cisplatin resistant subline (named MHCC97L/CisR or C8) and doxorubicin resistant subline (named MHCC97L/DoxR or D5).

2014-01-17 | GSE54175 | 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