Project description:Cancer is a heterogeneous disease, where multiple, phenotypically distinct subpopulations co-exist. Tumour evolution is a result of a complex interplay of genetic and epigenetic factors. To predict the molecular drivers of distinct cancer responses, we apply single-cell lineage tracing (scRNA-Seq of barcoded cells) on a triple-negative breast cancer model. We propose GALILEO, a framework providing lineage tracing, transcriptomic, and chromatin accessibility information simultaneously at single-cell resolution (Multiome ATAC + gene expression on barcoded cells). The combination of single-cell lineage tracing with phenotypic assays allows to link a cell state with its fate.
Project description:Rheumatoid arthritis (RA) is linked to depression and dementia in later life by inflammatory involvement of the central nervous system (CNS). Regional heterogeneity of brain immunophenotypes was described under homeostasis, but a topographical resolution of CNS immune responses in chronic peripheral inflammatory diseases like RA is missing. We demonstrate regional heterogeneity of CNS susceptibility to chronic peripheral inflammation in the human tumor necrosis factor α transgenic (TNFtg) mouse model of RA. TNFtg mice showed myeloid cell infiltration, microglial activation, and a mutual transcriptomic fingerprint of neuroinflammation in the cortex, striatum, and thalamus. Immune responses were minimal in the hippocampus and cerebellum. We demonstrate regional CNS immune responses to chronic peripheral inflammation, sparing the hippocampus and cerebellum and reversible by peripheral anti-inflammatory treatment. Targeting microenvironmental susceptibility or resilience of brain regions will help to prevent and treat RA-related neuropsychiatric comorbidity. RNA-sequencing was performed from five brain regions (cortex, striatum, thalamus, hippocampus, and cerebellum) from C57Bl6/J wild type mice and TNFtg mice (strain Tg197; kindly provided by George Kollias (Fleming Institute, Vari, Greece).
Project description:Cancer is a heterogeneous disease, where multiple, phenotypically distinct subpopulations co-exist. Tumour evolution is a result of a complex interplay of genetic and epigenetic factors. To predict the molecular drivers of distinct cancer responses, we apply single-cell lineage tracing (scRNA-Seq of barcoded cells) on a triple-negative breast cancer model. SUM159PT cells infected with a lentiviral barcode library (Perturb-seq Library) were sorted according to the presence of BFP signal, treated or not with paclitaxel (PTX), multiplexed with MULTI-Seq protocol, and then processed by scRNA-Seq.
Project description:Cancer is a heterogeneous disease, where multiple, phenotypically distinct subpopulations co-exist. Tumour evolution is a result of a complex interplay of genetic and epigenetic factors. To predict the molecular drivers of distinct cancer responses, we apply single-cell lineage tracing (scRNA-Seq of barcoded cells) on a triple-negative breast cancer model. SUM159PT cells infected with a lentiviral barcode library (Perturb-seq Library) were sorted according to the presence of BFP signal, treated or not with paclitaxel (PTX), and then processed by scRNA-Seq or Multiome.
Project description:To study the dynamics of GBM resistance and identify potential synergistic targets , we transfected PDGFR-amplified, patient-derived glioma neurospheres (TS543) with a barcoded lineage tracing library (CellTag), and treated the neurospheres with ispinesib. These genetically-modified, patient-derived neurospheres, which recapitulate key aspects of GBM heterogeneity, allow for surveillance of resistant phenotype on multiple timescales, and the barcode lineage tracing allows us to selectively analyze clones that are destined for resistance in the drug-naïve setting. We analyzed the phenotypes of the glioma cells during the long-term ispinesib treatment with single-cell RNAseq (scRNAseq), assess the stability and survival impact of drug-resistant phenotypes in the absence of drug and in orthotopic xenografts, and identified molecular markers of resistant clones in the drug-naïve setting to nominate effective drug combination.