Project description:Using 5' droplet-based single cell sequencing, we profiled single cells dervied from human colorectal cancer organoids carrying either APC mutation or RSPO fusion, and paired normal colon organoids for the later.
Project description:We report the first use of genome-edited human kidney organoids, combined with single-cell transcriptomics, to study APOL1 risk variants at the native genomic locus in different nephron cell types. This approach captures interferon-mediated induction of APOL1 gene expression and cellular dedifferentiation with a secondary insult“second hit” of endoplasmic reticulum stress.
Project description:We performed quantitative mass spectrometry based proteomic analysis and comparative transcriptomics analysis of 7 individual patient-derived human colorectal tumor and healthy organoids, the latter acquired from adjacent healthy tissue.
Project description:Use of single-cell transcriptomics to test early HD selective vulnerability by comparing CTRL and HD telencephalic organoids at day 45 and 120 of differentiation. To test the influence and the interactions between healthy and HD cells, chimeric organoids composed of CTRL and HD cells juxtaposed within the same organoid were grown and analyzed by scRNAseq at day 120.
Project description:As metabolic rewiring is crucial for cancer cell proliferation, metabolic phenotyping of patient-derived organoids is desirable to identify drug-induced changes and trace metabolic vulnerabilities of tumor subtypes. We established a novel protocol for metabolomic and lipidomic profiling of colorectal cancer organoids by LC-QTOF-MS facing the challenge of capturing metabolic information from minimal sample amount (< 500 cells/injection) in the presence of extracellular matrix (ECM). The best procedure of the tested protocols included ultrasonic metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v/v) without ECM removal. To eliminate ECM-derived background signals, we implemented a data filtering procedure based on p-value and fold change cut-offs which retained features with signal intensities >120% compared to matrix-derived signals present in blank samples. As a proof-of-concept, the method was applied to examine the early metabolic response of colorectal cancer organoids to 5-fluorouracil treatment. Statistical analysis revealed dose-dependent changes in the metabolic profiles of treated organoids including elevated levels of 2'-deoxyuridine, 2'-O-methylcytidin, inosine and 1-methyladenosine and depletion of 2'-deoxyadenosine and specific phospholipids. In accordance with the mechanism of action of 5-fluorouracil, changed metabolites are mainly involved in purine and pyrimidine metabolism. The novel protocol provides a first basis for the assessment of metabolic drug response phenotypes in 3D organoid models.