Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

ABSTRACT: Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

PROVIDER: EGAS00001004335 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

Functional Subclone Profiling for Prediction of Treatment-Induced Intratumor Population Shifts and Discovery of Rational Drug Combinations in Human Glioblastoma [SNP]

Project description:Purpose: Investigation of clonal heterogeneity may be key to understanding mechanisms of therapeutic failure in human cancer. However, little is known on the consequences of therapeutic intervention on the clonal composition of solid tumors. Experimental Design: Here, we used 33 single cell–derived subclones generated from five clinical glioblastoma specimens for exploring intra- and interindividual spectra of drug resistance profiles in vitro. In a personalized setting, we explored whether differences in pharmacologic sensitivity among subclones could be employed to predict drug-dependent changes to the clonal composition of tumors. Results: Subclones from individual tumors exhibited a remarkable heterogeneity of drug resistance to a library of potential antiglioblastoma compounds. A more comprehensive intratumoral analysis revealed that stable genetic and phenotypic characteristics of coexisting subclones could be correlated with distinct drug sensitivity profiles. The data obtained from differential drug response analysis could be employed to predict clonal population shifts within the naïve parental tumor in vitro and in orthotopic xenografts. Furthermore, the value of pharmacologic profiles could be shown for establishing rational strategies for individualized secondary lines of treatment. Conclusions: Our data provide a previously unrecognized strategy for revealing functional consequences of intratumor heterogeneity by enabling predictive modeling of treatment-related subclone dynamics in human glioblastoma

2016-12-19 | GSE72732 | GEO

Functional Subclone Profiling for Prediction of Treatment-Induced Intratumor Population Shifts and Discovery of Rational Drug Combinations in Human Glioblastoma [expression]

2016-12-19 | GSE72927 | GEO

PRC2 Heterogeneity Drives Tumor Growth in Medulloblastoma [mouse]

Project description:Intratumor epigenetic heterogeneity is emerging as a key mechanism underlying tumor evolution and drug resistance. Epigenetic abnormalities frequently occur in medulloblastoma, the most common childhood malignant brain tumor. Medulloblastoma is classified into four subtypes including SHH medulloblastoma, which is characterized by elevated SHH signaling and a cerebellum granule neuron precursor (CGNP) cell-of-origin. Here we report that the histone H3K27 methyltransferase polycomb repressor complex 2 (PRC2) is often heterogeneous within individual SHH medulloblastoma tumors. In mouse models, complete deletion of the PRC2 core subunit EED inhibited medulloblastoma growth, while a mosaic deletion of EED significantly enhanced tumor growth. EED is intrinsically required for CGNP maintenance by inhibiting both neural differentiation and cell death. Complete deletion of EED led to CGNP depletion and reduced occurrence of medulloblastoma. Surprisingly, medulloblastomas with mosaic EED levels grew faster than control wildtype tumors and expressed increased levels of oncogenes such as Igf2, which is directly repressed by PRC2 and has been demonstrated to be both necessary and sufficient for SHH medulloblastoma progression. IGF2 mediated the oncogenic effects of PRC2 heterogeneity in tumor growth. Assessing clones of a human medulloblastoma cell line with different EED levels confirmed that EEDlow cells can stimulate the growth of EEDhigh cells through paracrine IGF2 signaling. Thus, PRC2 heterogeneity plays an oncogenic role in medulloblastoma through both intrinsic growth competence and non-cell autonomous mechanisms in distinct tumor subclones.

2022-06-18 | GSE206003 | GEO

PRC2 Heterogeneity Drives Tumor Growth in Medulloblastoma [Human]

2022-06-18 | GSE206000 | GEO

Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis

Project description:Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.

2023-08-01 | GSE235783 | GEO

Methylome profiling of glioblastoma biopsies obtained by neuro-navigation in four distinct areas for 10 patients (necrotic zone, tumor zone, interface, and peripheral brain zone).

Project description:We classified samples and deciphered a key genes signature of intratumor heterogeneity by Principal Component Analysis and Weighted Gene Co-expression Network Analysis. We provide a signature of key cancer-heterogeneity genes highly associated with the intratumor spatial gradient and show that it is enriched in genes with correlation between methylation and expression levels.

2016-09-19 | E-MTAB-5109 | biostudies-arrayexpress

Methylation dataset of multi regional colorectal carcinoma.

Project description:Understanding intratumor heterogeneity is clinically important because it could cause therapeutic failure by fostering evolutionary adaptation. To this end, we profiled the genome and epigenome in multiple regions within each of eight colorectal tumors. Extensive intertumor heterogeneity is observed, from which we inferred the evolutionary history of the tumors. First, clonally shared alterations appeared, in which C>T transitions at CpG site and CpG island hypermethylation were relatively enriched. Correlation between mutation counts and patients’ ages suggests that the early-acquired alterations resulted from aging. In the late phase, a parental clone was branched into numerous subclones. Known driver alterations were observed frequently in the early-acquired alterations, but rarely in the late-acquired alterations. Consistently, our computational simulation of the branching evolution suggests that extensive intratumor heterogeneity could be generated by neutral evolution. Collectively, we propose a new model of colorectal cancer evolution, which is useful for understanding and confronting this heterogeneous disease.

2016-10-18 | GSE88821 | GEO

Expression data of multi regional colorectal carcinoma

Project description:Understanding intratumor heterogeneity is clinically important because it could cause therapeutic failure by fostering evolutionary adaptation. To this end, we profiled the genome and epigenome in multiple regions within each of nine colorectal tumors. Extensive intertumor heterogeneity is observed, from which we inferred the evolutionary history of the tumors. First, clonally shared alterations appeared, in which C>T transitions at CpG site and CpG island hypermethylation were relatively enriched. Correlation between mutation counts and patients’ ages suggests that the early-acquired alterations resulted from aging. In the late phase, a parental clone was branched into numerous subclones. Known driver alterations were observed frequently in the early-acquired alterations, but rarely in the late-acquired alterations. Consistently, our computational simulation of the branching evolution suggests that extensive intratumor heterogeneity could be generated by neutral evolution. Collectively, we propose a new model of colorectal cancer evolution, which is useful for understanding and confronting this heterogeneous disease.

2016-12-01 | GSE90708 | GEO

SNP array data of multi regional colorectal carcinoma

Project description:Understanding intratumor heterogeneity is clinically important because it could cause therapeutic failure by fostering evolutionary adaptation. To this end, we profiled the genome and epigenome in multiple regions within each of nine colorectal tumors. Extensive intertumor heterogeneity is observed, from which we inferred the evolutionary history of the tumors. First, clonally shared alterations appeared, in which C>T transitions at CpG site and CpG island hypermethylation were relatively enriched. Correlation between mutation counts and patients’ ages suggests that the early-acquired alterations resulted from aging. In the late phase, a parental clone was branched into numerous subclones. Known driver alterations were observed frequently in the early-acquired alterations, but rarely in the late-acquired alterations. Consistently, our computational simulation of the branching evolution suggests that extensive intratumor heterogeneity could be generated by neutral evolution. Collectively, we propose a new model of colorectal cancer evolution, which is useful for understanding and confronting this heterogeneous disease.

2017-05-01 | GSE98385 | GEO

Transcriptome profiling of glioblastoma biopsies obtained by neuro-navigation in four distinct areas for 10 patients (necrotic zone, tumor zone, interface, and peripheral brain zone).

Project description:We classified samples and deciphered a key genes signature of intratumor heterogeneity by Principal Component Analysis and Weighted Gene Co-expression Network Analysis. Transcriptome analysis highlighted a pronounced intratumor architecture reflecting the surgical sampling plan of the study and identified gene modules associated with hallmarks of cancer.

2016-09-19 | E-MTAB-5092 | biostudies-arrayexpress

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