Project description:In this study we want present a bank of metastatic colorectal cancer (mCRC) Patient Derived Organoids (PDOs) obtained from Patient Derived Xenografts (PDXs). These models are annotated with different omics to advance our understanding of CRC. We wanted to create a resource for the scientific community to assess the predictive reliability of these preclinical models. We performed comparative analyses between PDOs and matched PDXs to assess the similarities of these two platforms regarding molecular profiles and transcriptional classification. Moreover, we analyzed how these models respond to Cetuximab, a chimeric monoclonal antibody, normally given to patients after chemotherapy, that inhibits EGFR. After having assessed models’ reliability with Cetuximab, we aimed at identifying potential synergistic drugs to individuate new possible therapeutic prospects.
Project description:Colorectal cancer (CRC) is one of the most lethal cancers when it progresses to the advanced/metastatic stage. Treatment options for refractory metastatic colorectal cancer (mCRC) are limited. Therefore, there is an urgent need to develop effective treatment methods for metastatic colorectal cancer. In this study, we screened a library of small molecules for inhibitors of CRC recurrence using CRC cell lines and patient-derived organoids (PDOs) from metastatic, heavily pretreated CRC. The in vivo efficacy of LS-1-2 was evaluated in the HCT116 and the resistant HCT8 cell lines, patient-derived xenografts(PDXs) including refractory mCRC, and a liver metastasis mouse model. Biotin pull-down and liquid chromatography tandem-mass spectrometry (LC-MS/MS) were performed to identify proteins that interact with LS-1-2. The genome-wide gene expression and quantitative phosphoproteomic analyses were performed to determine the signaling pathway involved in LS-1-2. Molecular docking, molecular dynamics analysis and cellular thermal shift assays were used to predict and validate the binding sites of LS-1-2 on non-muscle Myosin IIA (NMHC IIA). Our results showed that LS-1-2 exhibited broad antiproliferative effects on a series of CRC cell lines and PDOs. The in vivo anti-tumor efficacy of LS-1-2 was demonstrated across cell line- and patient-derived xenografts and in the liver metastatic CRC model. NMHC IIA was identified as a direct target of LS-1-2, and LS-1-2 competitively inhibited the phosphorylation of NMHC IIA at S1943 and S1714 by CK2. NMHC IIA phosphorylation promoted CRC cell proliferation and invasion, which was reduced by LS-1-2. NMHC IIA phosphorylation-mediated YAP activity induced activation of AKT and inactivation of FOXO3a and was suppressed by LS-1-2. In conclusion, our findings suggest that NMHC IIA phosphorylation can be used as a potential molecular target in CRC metastasis, and that targeting NMHC IIA phosphorylation by LS-1-2 may be a promising strategy for the treatment and prevention of CRC metastasis.
Project description:We performed in-vivo selection of human patient derived colorectal cancer xenografts. 4 independent highly-liver metastatic sub-lines (lvm PDXs) were generated. Those lvm PDXs were harvested with the corresponding parental PDX tumors from mice and then we performed MACS mice cell depletion followed by FACS sorting to obtain human EpCAM positive and mice MHC negatitve populations. total RNA was extracted from those ex-vivo tumors and high-throuput sequencing was performed
Project description:Metastatic colorectal cancer (mCRC) is associated with multiple somatic copy number alterations (SCNAs). We analyzed SCNAs to estimate overall survival (OS) and progression free suvival (PFS) for mCRC patients treated with bevacizumab in combination with oxaliplatin or irinotecan.
Project description:Patient derived xenografts (PDXs) of human EGFR-mutant lung cancer were propagated in mice and treated with osimertinib or control to investigate the transcriptional adaption resposne.
Project description:Multiple samples of Patient Derived Xenografts (PDX) of a EGFR-resistant colorectal cancer are recovered at different times and profiled by scGET-seq.