Project description:Proneural-mesenchymal transition (PMT) is a phenotypic alteration and contributes to therapeutic resistance and recurrence of glioblastoma (GBM). Macrophages, as a main infiltrating component of tumor immune microenvironment (TIM), can regulate the biological processes of PMT. However, the mechanisms driving this process remain largely unknown. Here, We performed single-cell RNA sequencing (scRNA-seq) (3V3) and Spatial transcriptomics RNA sequencing(stRNA-seq)(1V1) from tumor core and matching tumor periphery samples to discripe the overall landscape of tumor and nontumor cells in gliomas.
Project description:Glioblastoma is the most common type of malignant brain tumor among adults. We used single-cell RNA sequencing (scRNA-seq) to analyze the diversity of glioblastoma cells.
Project description:Proneural-mesenchymal transition (PMT) is a phenotypic alteration and contributes to therapeutic resistance and recurrence of glioblastoma (GBM). Macrophages, as a main infiltrating component of tumor immune microenvironment (TIM), can regulate the biological processes of PMT. However, the mechanisms driving this process remain largely unknown. Here, We performed single-cell RNA sequencing (scRNA-seq) (3V3) and Spatial transcriptomics RNA sequencing(stRNA-seq)(1V1) from tumor core and matching tumor periphery samples to discripe the overall landscape of tumor and nontumor cells in gliomas.
Project description:Vortioxetine is the neuroactive drug with the highest ex vivo anti-glioblastoma efficacy across patients measured in our study. We used single-cell RNA sequencing (scRNA-seq) to analyze the transcriptomic response to Vortioxetine treatment.
Project description:To study developmental trajectories in brain organoids, we conducted scRNA-seq and scATAC-seq in parallel on a dense timecourse of early development.
Project description:Sample multiplexed scRNA-seq is a promising strategy to overcome current barriers in high cost and potential technical variations by multiple scRNA-seq tests. In this study, we developed a highly efficienct novel sample barcode labeling method using DNA-encoded Lipid Nanoparticles ('Nanocoding') that could label cells with minimal dependence on their type or sample conditions. This method provids a roubust and general protocol for sample barcoding and multiplexing in scRNA-seq. We demonstrated the performance of Nanocoding through three scRNA-seq studies, which include: 1. mouse spleen cells mix (one dataset including 6 mouse spleen tissues samples); 2. HeLa-mouse Stromal Vascular Fraction(SVF) cells mix (one dataset containing mixed HeLa cell and SVF cell); 3. Aged-Young SVF cells mix (one dataset containing two SVF samples) tests. These studies showcased the biomodal distribution of barcode counts in different models with high signal-to-background ratio, as well as pan-cell labeling activity for efficient and accurate sample-multiplexing. By using Nanocoding, we profiled obsity and age related change in lipid metabolism associated genes or inflammatory related features, in various cell types from spleen or adipose tissues.