Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Bioprinted spatially defined breast tumor microenvironment models of intratumoral heterogeneity and drug resistance

ABSTRACT: Bioprinted spatially defined breast tumor microenvironment models of intratumoral heterogeneity and drug resistance

PROVIDER: PRJNA1121410 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Bioprinted spatially defined breast tumor microenvironment models of intratumoral heterogeneity and drug resistance

Project description:Cellular extracellular matrix (ECM) and spatial heterogeneity of tumor microenvironments (TME) regulate disease progression and treatment efficacy. Developing in vitro models that recapitulate the TME promises to accelerate studies of tumor biology and identify new targets for therapy. Here, we employed extrusion-based, multi-nozzle three-dimensional (3D) bioprinting to spatially pattern triple-negative MDA-MB-231 breast cancer cells, endothelial cells, and human mammary cancer-associated fibroblasts with biomimetic ECM inks. Bioprinted models captured key features of the spatial architecture of human breast tumors, including varying-sized dense regions of cancer cells and surrounding microvessel-rich stroma. Angiogenesis and ECM stiffening occurred in the stromal area but not the cancer cell rich regions, mimicking pathological changes in patient samples. Transcriptomic analyses revealed upregulation of angiogenesis-related and ECM remodeling-related signatures in the stroma region and identified potential ligand-receptor mediators of these processes. Breast cancer cells in distinct parts of the bioprinted TME showed differing sensitivities to chemotherapy, highlighting environmentally mediated drug resistance. In summary, our 3D bioprinted tumor model will act as a platform to discover integrated functions of the TME in cancer biology and therapy.

2024-06-13 | GSE269415 | GEO

Epigenomic tomography for probing spatially-defined chromatin state in the brain

Project description:Epigenomic tomography for probing spatially-defined chromatin state in the brain

| PRJNA891616 | ENA

LCM-Seq analysis of microscopically defined human embryo HSC microenvironment

Project description:This dataset contains RNA-Seq data for cells within spatially defined subdomains of the human embryo dorsal aorta, subdissected from tissue sections using laser capture microdissection. This dataset explores dorsal-ventral polarisation across the dorsal aorta, the site of hematopoietic stem cell emergence.

2020-09-17 | GSE151875 | GEO

Micro-engineered perfusable 3D-bioprinted glioblastoma model for in-vivo mimicry of tumor microenvironment

Project description:Micro-engineered perfusable 3D-bioprinted glioblastoma model for in-vivo mimicry of tumor microenvironment

| PRJNA738713 | ENA

Single cell RNA-seq of bioprinted human kidney organoid

Project description:These files represent single cell RNA-Seq data generated on a 10x Chromium genomics platform from bioprinted iPSC-derived human kidney organoids differentiated according to our published protocol (Takasato et al., Nature Protocols 2016). The data contains >2000 cells that passed our QC. Data was used to confirm that bioprinted organoids contain a similar cellular composition as standard manually produced organoids - See https://www.biorxiv.org/content/10.1101/505396v1.

2020-09-01 | GSE138835 | GEO

Intratumoral heterogeneity, cell of origin and microenvironment in retinoblastoma [scRNA-seq]

Project description:Intratumoral heterogeneity, cell of origin and microenvironment in retinoblastoma [scRNA-seq]

| PRJNA707413 | ENA

Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface

Project description:Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface

| PRJNA670235 | ENA

LCM-Seq analysis of microscopically defined human embryo HSC microenvironment

Project description:LCM-Seq analysis of microscopically defined human embryo HSC microenvironment

| PRJNA637577 | ENA

Spatially resolved whole-transcriptomic and proteomic profiling of lung cancer and immune-microenvironment according to PD-L1 expression

Project description:The expression of PD-L1 on tumor cells (TCs) is used as an immunotherapy biomarker in lung cancer, but heterogeneous intratumoral expression is often observed. Using a Digital Spatial Profiler, we performed proteomic and whole-transcriptomic analyses of TCs and immune cells (ICs) in spatially matched areas according to tumor PD-L1 expression and the status of the immune microenvironment. Several findings were validated using immunohistochemistry, The Cancer Genome Atlas, and immunotherapy cohorts. ICs in areas with high PD-L1 expression showed more features indicative of immunosuppression and exhaustion than ICs in areas with low PD-L1 expression. TCs highly expressing PD-L1 within immune-inflamed (IF) areas show up-regulation of pro-inflammatory processes, whereas TCs highly expressing PD-L1 within immune-deficient (ID) areas show up-regulation of various metabolic processes. Using differentially expressed genes of TCs between the IF and ID areas, we identified a novel prognostic gene signature for lung cancer. In addition, the high ratio of CD8+ cells to M2 macrophages was found to predict favorable outcomes in patients with PD-L1-expressing lung cancer after immune checkpoint inhibitor therapy. This study demonstrates that TCs and ICs have distinct spatial features within the tumor microenvironment that are related to tumoral PD-L1 expression and IC infiltration.

2024-08-21 | GSE265899 | GEO

Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface

Project description:Cancer cells interact with a wide variety of other cell types, but our understanding of microenvironmental heterogeneity and how it influences tumor phenotypes is limited. While single-cell RNA-seq (scRNA-seq) has helped define these TME cell types, it provides limited information on the mechanisms that define how individual tumor cells interact with TME. Here, we integrate spatial transcriptomics with scRNA-seq to define the architecture and nature of nascent tumor and surrounding microenvironment cells as they come into contact through the process of invasion. Using a well-defined transgenic zebrafish model of BRAFV600E-driven melanoma, we identify a transcriptionally unique “interface” cluster localized at the boundary between tumor cells and surrounding tissues. Using an unbiased, data-driven approach, we identify spatially-patterned gene modules specific to the interface and show that the interface is a distinct transcriptional entity that histologically resembles the microenvironment but transcriptionally resembles the tumor. By complementing ST with scRNA-seq, we demonstrate that the interface is composed of specialized tumor and microenvironment cells. Both cell types in the interface upregulate a common set of cilia genes, and we find enrichment of cilia proteins only where the tumor meets the TME. Cilia gene expression is regulated by ETS-family transcription factors, which normally act to suppress their expression outside of this region. This unique ETS-driven interface transcriptional state is conserved across ten different human patient samples, suggesting this is a conserved feature of human melanoma. Taken together, our results demonstrate the power of spatial and single-cell transcriptomics techniques in uncovering novel biological mechanisms that drive tumor invasion into new tissues.

2021-09-21 | GSE159709 | 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