Characterization of patient-derived xenograft models of myxoid liposarcoma either sentitive or resistant to trabectedin
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PROVIDER: EGAS00001003715 | EGA |
REPOSITORIES: EGA
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Project description:Transcriptional profiling of patient-derived xenograft models of myxoid liposarcoma with either FUS-CHOP type I, named as ML017, or FUS-CHOP type III, named as ML006. Both ML017 and ML006 are responsive to trabectedin treatment, while model ML017/ET has aquired resistance to the drug. Samples are either under untreated conditions, or treated either with trabectedin or pioglitazone or both.
2020-01-10 | E-MTAB-8632 | biostudies-arrayexpress
Project description:Myxoid liposarcoma (MLS) is the second most common type of liposarcoma, and today few model systems to study the disease exists. To be able to model the disease in vitro, cell-free scaffolds from MLS patient-derived xenograft (PDX) models were generated. The MLS scaffolds were then used as a 3D growth platform for MLS cell lines to study the cancer microenvironments impact on cellular heterogeneity using RNA sequencing. Key components in the microenvironment have also been shown to influence the fraction of cellular subpopulations, such as cancer stem cells and migratory cells but also to promote aggressive features of cancers. Therefore, to better understand and characterize these scaffolds, protein analyses were performed and links between scaffold compositions and the induced gene expression profiles of the cells grown therein could be made. This model system provides a better insight to the composition of the cell-free cancer microenvironment in a rare disease, which can lead to identification of novel malignancy inducing properties in MLS.
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Project description:Gastrointestinal stromal tumors (GISTs) with KIT or platelet-derived growth factor receptor alpha (PDGFRa) oncogenic driver gene mutations, respond to tyrosine kinase inhibitors (TKIs) including imatinib, sunitinib, and regorafenib. However, most patients develop TKI resistance; therefore, novel agents are required. We established three TKI-resistant GIST patient-derived xenograft (PDX) models for effective drug development. These were PDX models harboring primary and secondary KIT and additional mutations; KIT exon 11 (p.Y570_L576del), KIT exon 17 (p.D816E), and PTEN (p.T321fs) mutations in GIST-RX1 from a patient who was unresponsive to imatinib, sunitinib, and sorafenib, and KIT exon 11 (p.K550_splice) and KIT exon 14 (p.T670I) mutations in GIST-RX2 and KIT exon 9 (p.502_503insYA) and KIT exon 17 (p.D820E) mutations in GIST-RX4 from patients with imatinib and imatinib/sunitinib resistance, respectively. The histological features and mutation statuses of GIST PDXs were consistent with those of the original patient tumors, and the models showed TKI sensitivity comparable to clinical responses. Imatinib inhibited the KIT pathway in imatinib-sensitive GIST-T1 but not GIST-RX1, RX2, and RX4. These GIST PDX models will be useful for studying TKI resistance mechanisms and evaluating novel targeted agents in GIST.
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Project description:Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors.
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Project description:Testicular cancer (TC) is the most common solid tumour in young men. While cisplatin-based chemotherapy is highly effective in TC patients, chemoresistance still accounts for 10% of disease-related deaths. Pre-clinical models that faithfully reflect patient tumours are needed to assist in target discovery and drug development. Tumour pieces from eight TC patients were subcutaneously implanted in NOD scid gamma (NSG) mice. Three patient-derived xenograft (PDX) models of TC, including one chemoresistant model, were established containing yolk sac tumour and teratoma components. Whole-exome sequencing, copy number variation analysis and RNA-sequencing was performed on these TP53 wild type PDX tumours to assess the effects of passaging, showing high concordance of molecular features between passages.
2020-07-29 | GSE155262 | GEO
Project description:Testicular cancer (TC) is the most common solid tumour in young men. While cisplatin-based chemotherapy is highly effective in TC patients, chemoresistance still accounts for 10% of disease-related deaths. Pre-clinical models that faithfully reflect patient tumours are needed to assist in target discovery and drug development. Tumour pieces from eight TC patients were subcutaneously implanted in NOD scid gamma (NSG) mice. Three patient-derived xenograft (PDX) models of TC, including one chemoresistant model, were established containing yolk sac tumour and teratoma components. Whole-exome sequencing, copy number variation analysis and RNA-sequencing was performed on these TP53 wild type PDX tumours to assess the effects of passaging, showing high concordance of molecular features between passages.
2020-07-29 | GSE152270 | GEO
Project description:Osteosarcoma is a rare bone cancer in adolescents and young adults with a dismal prognosis because of metastatic disease and chemoresistance. Despite multiple clinical trials, no improvement in outcome has occurred in decades. There is an urgent need to better understand resistant and metastatic disease and to generate in vivo models from relapsed tumors. We developed eight new patient-derived xenograft (PDX) subcutaneous and orthotopic/paratibial models derived from patients with recurrent osteosarcoma and compared the genetic and transcriptomic landscapes of the disease progression at diagnosis and relapse with the matching PDX. Whole exome sequencing showed that driver and copy-number alterations are conserved from diagnosis to relapse, with the emergence of somatic alterations of genes mostly involved in DNA repair, cell cycle checkpoints, and chromosome organization. All PDX patients conserve most of the genetic alterations identified at relapse. At the transcriptomic level, tumor cells maintain their ossification, chondrocytic, and trans-differentiation programs during progression and implantation in PDX models, as identified at the radiological and histological levels. A more complex phenotype, like the interaction with immune cells and osteoclasts or cancer testis antigen expression, seemed conserved and was hardly identifiable by histology. Despite NSG mouse immunodeficiency, four of the PDX models partially reconstructed the vascular and immune-microenvironment observed in patients, among which the macrophagic TREM2/TYROBP axis expression, recently linked to immunosuppression. Our multimodal analysis of osteosarcoma progression and PDX models is a valuable resource to understand resistance and metastatic spread mechanisms, as well as for the exploration of novel therapeutic strategies for advanced osteosarcoma.
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Project description:Identify therapeutic vulnerabilities of palbociclib resistance in metastatic breast cancer patient-derived xenograft models and identify key biomarkers that correlate with development of resistance to inform new treatment directions
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Project description:Effective systemic treatment of cancer relies on the delivery of agents with optimal therapeutic potential. The molecular age of medicine has provided genomic tools that can identify a large number of potential therapeutic targets in individual patients, heralding the promise of personalized treatment. However, determining which potential targets actually drive tumor growth and should be prioritized for therapy is challenging. Indeed, reliable molecular matches of target and therapeutic agent have been stringently validated in the clinic for only a small number of targets. Patient-derived xenografts (PDXs) are tumor models developed in immunocompromised mice using tumor procured directly from the patient. As patient surrogates, PDX models represent a powerful tool for addressing individualized therapy. Challenges include humanizing the immune system of PDX models and ensuring high quality molecular annotation, in order to maximize insights for the clinic. Importantly, PDX can be sampled repeatedly and in parallel, to reveal clonal evolution, which may predict mechanisms of drug resistance and inform therapeutic strategy design.
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Project description:This SuperSeries is composed of the SubSeries listed below.
2020-07-29 | GSE155277 | GEO