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.
Project description:Tumor metastasis accounts for the majority of cancer-related deaths; it is therefore important to develop preclinical models that faithfully recapitulate disease progression. Here, we generated paired organoids derived from primary tumors and matched liver metastases in the same colorectal cancer patients (CRC). Despite the fact that paired organoids exhibit comparable gene expression and cell morphology. organoids from metastatic lesions demonstrate more aggressive phenotypes, tumorigenesis, and metastatic capacity than those from primary lesions. Transcriptional analyses of the paired organoids reveal signature genes and pathways altered during the progression of CRC. including SOX2, altered during the progression of CRC. Further study shows that inducible knockdown of SOX2 attenuated invasion, proliferation, and liver metastasis outgrowth. Taken together, we use patient-derived organoids to model cancer metastasis. Our data propose that SOX2 is not only a critical biomarker for the development and metastasis of CRC, but also a potent target for the disease treatment.
Project description:We generated 3D tumour organoids from colorectal cancer patients and tested their responses to inhibitors of Tankyrase (TNKSi) which are known to modulate Wnt signalling. Complex 3D models provide a challenging platform for the quantitative analysis of drug responses of therapies that have differential effects on tumour cell subpopulations. We demonstrated that morphometric analyses can capture subtle alterations in organoid responses to Wnt inhibitors that are consistent with activity against a cancer stem cell subpopulation, highlighting the value of phenotypic readouts as a quantitative method to assess drug-induced effects in a relevant preclinical model.
Project description:We have performed gene expression profiling of patient-derived tumor organoids (PDOs) and tissue samples of resected liver metastases from patients with metastatic colorectal cancer.
Project description:The therapeutic regimens of adjuvant and neoadjuvant chemotherapy for colorectal cancer (CRC) remain largely relied on clinical experience, and thus preclinical models are needed to guide individualized medicine. The investigators are going to establish 3D bioprinted CRC models and organoids from surgically resected tumor tissues of CRC patients with or without liver metastases. In vitro 3D models and organoids will be treated with the same chemotherapy drugs with the corresponding patients from whom the models are derived. The sensitivity of chemotherapy drugs will be tested in these two types of in vitro models, and the actual response to chemotherapy in patients will be evaluated. The predictive ability of 3D models for chemotherapy sensitivity in CRC patients will be compared with that of the organoids. This observational study will validate the potential value of 3D bioprinted tumor models in predicting the response to chemotherapy in CRC.
Project description:Here, we generated bulk RNA-seq data on colon organoids derived from both healthy and familial adenomatous polyposis patients. We related findings observed within this dataset to differential expression findings from a publicly available colorectal cancer cohort.