Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1178877 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31145562_1.fastq.gz | Fastqsanger.gz | |||
| SRR31145562_2.fastq.gz | Fastqsanger.gz | |||
| SRR31145563_1.fastq.gz | Fastqsanger.gz | |||
| SRR31145563_2.fastq.gz | Fastqsanger.gz | |||
| SRR31145564_1.fastq.gz | Fastqsanger.gz |
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Project description:Kilian2024 - Immune cell dynamics in Cue-Induced Extended Human Colitis Model
Single-cell technologies such as scRNA-seq and flow cytometry provide critical insights into immune cell behavior in inflammatory bowel disease (IBD). However, integrating these datasets into computational models for dynamic analysis remains challenging. Here, Kilian et al., (2024) developed a deterministic ODE-based model that incorporates these technologies to study immune cell population changes in murine colitis. The model parameters were optimized to fit experimental data, ensuring an accurate representation of immune cell behavior over time. It was then validated by comparing simulations with experimental data using Pearson’s correlation and further tested on independent datasets to confirm its robustness. Additionally, the model was applied to clinical bulk RNA-seq data from human IBD patients, providing valuable insights into immune system dynamics and potential therapeutic strategies.
Figure 4c, obtained from the simulation of human colitis model is highlighted here.
This model is described in the article:
Kilian, C., Ulrich, H., Zouboulis, V.A. et al. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. npj Syst Biol Appl 10, 69 (2024). https://doi.org/10.1038/s41540-024-00395-9
Abstract:
Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.
2025-03-07 | MODEL2502180001 | BioModels
Project description:Inflammatory breast cancer (IBC) is a difficult-to-treat disease with poor clinical outcomes due to high risk of metastasis and resistance to treatment. We previously described a CD44+CD24-pSTAT3+ cancer cell subpopulation with stem cell-like features in breast cancer that is dependent on JAK/STAT3 signaling. Here we report that CD44+CD24- cells are the most frequent cell-type in IBC and are commonly pSTAT3+. Combination of JAK/STAT3 inhibition with paclitaxel decreased IBC xenograft growth more than either agent alone. We developed and characterized IBC cell lines resistant to paclitaxel and doxorubicin to mimic therapeutic resistance in patients. Multi-omic profiling of parental and resistant cells revealed genes associated with lineage identity and inflammation were enriched in chemotherapy resistant derivatives. Integrated pSTAT3 ChIP-seq and RNA-seq analyses showed pSTAT3 regulates genes related to inflammation and epithelial to mesenchymal transition (EMT) in resistant cells, as well as PDE4A, a cAMP-specific phosphodiesterase. Metabolomic characterization identified elevated cAMP signaling and CREB as a candidate therapeutic target in IBC. We also investigated cellular dynamics and heterogeneity at the single cell level during chemotherapy and acquired resistance by CyTOF and single cell RNA-seq. We identified mechanisms of resistance including a shift from luminal to basal/mesenchymal cell states through selection for rare pre-existing subpopulations or an acquired change. Lastly, we showed that combination treatment with paclitaxel and JAK/STAT3 inhibition prevented the emergence of this more mesenchymal chemo-resistant subpopulation. Our results provide mechanistic rational for combination of chemotherapy with inhibition of JAK/STAT3 signaling as a new more effective therapeutic strategy in IBC.
2022-11-04 | MSV000090647 | GNPS
Project description:Single-cell RNA-seq of B cell polustion in breast cancer patients
| PRJNA559817 | ENA
Project description:Inflammatory breast cancer (IBC) is a difficult-to-treat disease with poor clinical outcomes due to high risk of metastasis and resistance to treatment. We previously described a CD44+CD24-pSTAT3+ cancer cell subpopulation with stem cell-like features in breast cancer that is dependent on JAK/STAT3 signaling. Here we report that CD44+CD24- cells are the most frequent cell-type in IBC and are commonly pSTAT3+. Combination of JAK/STAT3 inhibition with paclitaxel decreased IBC xenograft growth more than either agent alone. We developed and characterized IBC cell lines resistant to paclitaxel and doxorubicin to mimic therapeutic resistance in patients. Multi-omic profiling of parental and resistant cells revealed genes associated with lineage identity and inflammation were enriched in chemotherapy resistant derivatives. Integrated pSTAT3 ChIP-seq and RNA-seq analyses showed pSTAT3 regulates genes related to inflammation and epithelial to mesenchymal transition (EMT) in resistant cells, as well as PDE4A, a cAMP-specific phosphodiesterase. Metabolomic characterization identified elevated cAMP signaling and CREB as a candidate therapeutic target in IBC. We also investigated cellular dynamics and heterogeneity at the single cell level during chemotherapy and acquired resistance by CyTOF and single cell RNA-seq. We identified mechanisms of resistance including a shift from luminal to basal/mesenchymal cell states through selection for rare pre-existing subpopulations or an acquired change. Lastly, we showed that combination treatment with paclitaxel and JAK/STAT3 inhibition prevented the emergence of this more mesenchymal chemo-resistant subpopulation. Our results provide mechanistic rational for combination of chemotherapy with inhibition of JAK/STAT3 signaling as a new more effective therapeutic strategy in IBC.
2022-11-04 | MSV000090647 | MassIVE
Project description:Clusters of circulating tumor cells (CTC-clusters) are present in the blood of patients with cancer but their contribution to metastasis is not well defined. Here, we first use mouse models to demonstrate that breast cancer cells injected intravascularly as clusters are more prone to survive and colonize the lungs than single cells. Primary mammary tumors comprised of tagged cells give rise to oligoclonal CTC-clusters, with 50-fold increased metastatic potential, compared with single CTCs. Using intravital imaging and in vivo flow cytometry, CTC-clusters are visualized in the tumor circulation, and they demonstrate rapid clearance in peripheral vessels. In patients with breast cancer, presence of CTC-clusters is correlated with decreased progression-free survival. RNA sequencing identifies the cell junction protein plakoglobin as most differentially expressed between clusters and single human breast CTCs. Expression of plakoglobin is required for efficient CTC-cluster formation and breast cancer metastasis in mice, while its expression is associated with diminished metastasis-free survival in breast cancer patients. Together, these observations suggest that plakoglobin-enriched primary tumor cells break off into the vasculature as CTC-clusters, with greatly enhanced metastasis propensity. RNA-seq from 29 samples (15 pools of single CTCs and 14 CTC-clusters) isolated from 10 breast cancer patients
2014-07-11 | E-GEOD-51827 | biostudies-arrayexpress
Project description:We performed single cell RNA sequencing (RNA-seq) for 549 primary breast cancer cells and lymph node metastases from 11 patients with distinct molecular subtypes (BC01-BC02, estrogen receptor positive (ER+); BC03, double positive (ER+ and HER2+); BC03LN, lymph node metastasis of BC03; BC04-BC06, human epidermal growth factor receptor 2 positive (HER2+); BC07-BC11, triple-negative breast cancer (TNBC); BC07LN, lymph node metastasis of BC07) and matched bulk tumors. We separated these single cells into epithelial tumor and tumor-infiltrating immune cells using inferred CNVs from RNA-seq. The refined single cell profiles for the tumor and immune cells provide key expression signatures of breast cancer and the surrounding microenvironment.
2016-12-09 | GSE75688 | GEO
Project description:Extracellular Vesicles (EVs) are particles of different sizes, covered by a lipid bilayer membrane and containing highly heterogeneous cargo. Cancer cell-derived EVs have been the main object of an extensive investigation in the field because they carry cancer-specific molecular cargo and can promote cancer progression. Cancer-derived EVs include populations of atypically large EVs (L-EVs), which have been referred to as tumor microvesicles, large oncosomes, or simply L-EVs. While small EVs (S-EVs), which include exosomes, have been investigated by a plethora of reports, little is known about L-EVs. The paucity of studies comparing protein cargo of L- and S-EVs, of studies focused on protein coding RNA, and the absence of integrative analyses to compare the protein and gene expression in different EV fractions, prompted us to perform mass spectrometry to profile three different, size-based EV fractions generated by three cancer cell models (glioma, prostate and breast cancer). We identified protein signatures for L- and S-EVs either common to all cell types or specific to each of them individually. The proteins enriched in prostate cancer cell-derived L-EVs were also identified in L-EVs from patients with metastatic prostate cancer by a SWATH proteomic assay. We also performed RNA-Seq on the prostate cancer model and integrated proteomic and transcriptomic datasets. GSEA revealed that mitochondrial function was enriched in L-EVs versus S-EVs at both the RNA and protein level. The mitochondrial signature at the transcriptome level was confirmed by single cell RNA-Seq of L- EVs in vitro. The integrated L-EV proteomic and transcriptomic signature enabled distinction between benign and localized prostate cancer, as well as between localized cancer and metastatic castration-resistant cancer.
2025-04-16 | PXD038518 | Pride
Project description:RNA-seq was performed on breast cancer cell lines and primary tumors RNA-seq was performed on 28 breast cancer cell lines, 42 Triple Negative Breast Cancer (TNBC) primary tumors, and 42 Estrogen Receptor Positive (ER+) and HER2 Negative Breast Cancer primary tumors, 30 uninovlved breast tissue samples that were adjacent to ER+ primary tumors, 5 breast tissue samples from reduction mammoplasty procedures performed on patients with no known cancer, and 21 uninvolved breast tissue samples that were adjacent to TNBC primary tumors.
2014-06-11 | E-GEOD-58135 | biostudies-arrayexpress