Ontology highlight
ABSTRACT:
PROVIDER: PRJNA869679 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Intra-tumor heterogeneity of tumor-initiating cell (TIC) activity drives colorectal cancer (CRC) progression and therapy resistance. Here, we used single-cell mRNA-sequencing (scRNA-seq) of patient-derived CRC models to decipher distinct cell subpopulations based on their transcriptional profiles. Cell type-specific expression modules of stem-like, transit amplifying-like, and differentiated CRC cells resemble differentiation states of normal intestinal epithelial cells. Strikingly, identified subpopulations differ in proliferative activity and metabolic state. In summary, we here show at single-cell resolution that transcriptional heterogeneity identifies functional states during TIC differentiation. Targeting transcriptional states associated to cancer cell differentiation might unravel vulnerabilities in human CRC.
2021-05-07 | PXD018230 | Pride
Project description:Interventions: Colon cancer group:Nil;Ulcerative colitis group:Nil;Colorectal Adenomas group:Nil
Primary outcome(s): Single-cell Sequencing
Study Design: Factorial
| 2702420 | ecrin-mdr-crc
Project description:KRAS-mutant pancreatic ductal adenocarcinoma (PDAC) is highly immunosuppressive and resistant to targeted therapies, immune checkpoint blockade and engineered T cells. Here, we performed a systematic high throughput combinatorial drug screen and identified a synergistic interaction between the MEK inhibitor trametinib and the multi-kinase inhibitor nintedanib. This interaction targets KRAS-directed oncogenic signaling in the aggressive and therapy resistant non-glandular mesenchymal subtype of PDAC, driven by an allelic imbalance, increased gene-dosage and expression of oncogenic KRAS. Mechanistically, the combinatorial treatment induces cell cycle arrest and cell death and initiates an interferon response. Using single cell RNA sequencing and immunophenotyping, we show that the combination therapy reprograms the immunosuppressive microenvironment and primes cytotoxic and memory T cells to infiltrate the tumors, thereby sensitizing mesenchymal PDAC to PD-L1 inhibition. This work opens new avenues to target the therapy refractory mesenchymal PDAC subtype.
2022-02-11 | PXD027877 | Pride
Project description:KRAS-mutant pancreatic ductal adenocarcinoma (PDAC) is highly immunosuppressive and resistant to targeted therapies, immune checkpoint blockade and engineered T cells. Here, we performed a systematic high throughput combinatorial drug screen and identified a synergistic interaction between the MEK inhibitor trametinib and the multi-kinase inhibitor nintedanib. This interaction targets KRAS-directed oncogenic signaling in the aggressive and therapy resistant non-glandular mesenchymal subtype of PDAC, driven by an allelic imbalance, increased gene-dosage and expression of oncogenic KRAS. Mechanistically, the combinatorial treatment induces cell cycle arrest and cell death and initiates an interferon response. Using single cell RNA sequencing and immunophenotyping, we show that the combination therapy reprograms the immunosuppressive microenvironment and primes cytotoxic and memory T cells to infiltrate the tumors, thereby sensitizing mesenchymal PDAC to PD-L1 inhibition. This work opens new avenues to target the therapy refractory mesenchymal PDAC subtype.
2022-02-23 | PXD023267 | Pride
Project description:DNA methylation and nucleosome positioning work together to generate chromatin structures that regulate gene expression. Nucleosomes are typically mapped using nuclease digestion requiring significant amounts of material and varying enzyme concentrations. We have developed a method (NOMe-seq) that uses a GpC methyltransferase (M.CviPI) and next generation sequencing to generate a high resolution footprint of nucleosome positioning genome-wide using less than 1 million cells while retaining endogenous DNA methylation information from the same DNA strand. Using a novel bioinformatics pipeline we show a striking anti-correlation between nucleosome occupancy and DNA methylation at CTCF regions, that is not present at promoters. We further show that the extent of nucleosome depletion at promoters is directly correlated to expression level and can accommodate multiple nucleosomes and provide genome-wide evidence that expressed non-CpG island promoters are nucleosome depleted. Importantly, NOMe-seq obtains DNA methylation and nucleosome positioning information from the same DNA molecule, giving the first genome-wide DNA methylation and nucleosome positioning correlation at the single molecule and thus, single cell level that can be used to monitor disease progression and response to therapy. Nucleosome Occupancy and Methylome-Sequencing (NOMe-Seq) on IMR90 cell line and 2 GBM cell lines
2012-09-12 | E-GEOD-40770 | biostudies-arrayexpress
Project description:Single-cell RNA sequencing of PBMCs and infusion products from 32 patients treated with CD19 CAR-T therapy
2022-07-13 | GSE197268 | GEO
Project description:A single cell atlas of human glioma under therapy
| PRJNA730532 | ENA
Project description:A novel anti-influenza combined therapy assessed by single cell RNA-sequencing
| PRJNA789923 | ENA
Project description:Cancer precision medicine largely relies on knowledge about genetic aberrations in tumors and next-generation-sequencing studies have shown a high mutational complexity in many cancers. Although a large number of the observed mutations is believed to be not causally linked with cancer, the functional effects of many rare mutations but also of combinations of driver mutations are often unknown. Here, we perform a systems analysis of a model of EGFR-mutated non-small cell lung cancer resistant to targeted therapy that integrates whole exome sequencing, global time-course discovery phosphoproteomics and computational modeling to identify functionally relevant molecular alterations. Our approach allows for a complexity reduction from over 2,000 genetic events potentially involved in mediating resistance to only 44 phosphoproteins and 35 topologically close genetic alterations. We perform single- and combination-drug testing against the predicted phosphoproteins and discovered that targeting of HSPB1, DBNL and AKT1 showed potent anti-proliferative effects overcoming resistance against EGFR-inhibitory therapy. Our approach may therefore be used to complement mutational profiling to identify functionally relevant molecular aberrations and propose combination therapies across cancers.
2018-07-02 | PXD009996 | Pride
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