A5084957178- Cancer Genomics and Diagnostics
- Lung Cancer Treatments and Mutations
- Advanced Breast Cancer Therapies
- Pancreatic and Hepatic Oncology Research
- Cancer, Stress, Anesthesia, and Immune Response
- Cancer Cells and Metastasis
- Computational Drug Discovery Methods
- Pancreatic function and diabetes
- Fibroblast Growth Factor Research
- Diabetes and associated disorders
- 3D Printing in Biomedical Research
- Diabetes Management and Research
- Colorectal Cancer Treatments and Studies
- Comparative constitutional jurisprudence studies
- Protein Degradation and Inhibitors
- Immune cells in cancer
- Hemoglobin structure and function
- Conflict, Peace, and Violence in Colombia
- CAR-T cell therapy research
- Glioma Diagnosis and Treatment
- Cytokine Signaling Pathways and Interactions
- Phagocytosis and Immune Regulation
- Criminal Justice and Penology
- Neonatal Health and Biochemistry
- Melanoma and MAPK Pathways
California Pacific Medical Center
2019-2023
Université de Strasbourg
2015-2016
Glioblastoma’s (GBM) aggressive growth is driven by redundant activation of a myriad signaling pathways and genomic alterations in tyrosine kinase receptors, such as epidermal factor receptor (EGFR), which altered over 50% cases. Single agents targeting EGFR have not proven effective against GBM. In this study, we aimed to identify an anti-tumor regimen using pharmacogenomic testing patient-derived GBM samples, culture vivo. High-throughput pharmacological screens ten EGFR-driven samples...
Transplantation of encapsulated islets in a bioartificial pancreas is promising alternative to free islet cell therapy avoid immunosuppressive regimens. However, hypoxia, which can induce rapid loss islets, major limiting factor. The efficiency oxygen delivery an vitro model involving hypoxia and confined conditions has never been investigated. Oxygen carriers such as perfluorocarbons hemoglobin might improve oxygenation. To verify this hypothesis, study aimed identify the best candidate...
In bioartificial pancreases (BP), the number of islets needed to restore normoglycaemia in diabetic patient is critical. However, confinement a high quantity limited space may impact islet survival, particularly regard low oxygen partial pressure (PO2) such environments. The aim present study was evaluate confined under hypoxia on cell survival. Rat were seeded at three different concentrations (150, 300, and 600 Islet Equivalents (IEQ)/cm(2)) cultured normal atmospheric (160 mmHg) as well...
Abstract Background Patient-derived xenograft (PDX) mouse tumour models can predict response to therapy in patients. Predictions made from PDX cultures (PDXC) would allow for more rapid and comprehensive evaluation of potential treatment options patients, including drug combinations. Methods We developed a library BRAF-mutant metastatic melanoma, high-throughput drug-screening (HTDS) platform utilising clinically relevant exposures. then evaluated 34 antitumor agents across eight melanoma...
<p>Supplementary Table 8 FGFR mutations</p>
<p>Supplementary Table 7 gene_importance_t0.1_limit4_ew</p>
<p>Supplementary Table 5 LOBICO data</p>
<p>Text of Supplementary Figure Legends</p>
<p>Figure S3</p>
<p>Supplementary Table 6 ROC formulae training and test</p>
<p>Supplementary Table 3 binarization sensitivity 19 drugs</p>
<div>Abstract<p>As a result of tumor heterogeneity and solid cancers harboring multiple molecular defects, precision medicine platforms in oncology are most effective when both genetic pharmacological determinants evaluated. Expandable patient-derived xenograft (PDX) mouse corresponding PDX culture (PDXC) models recapitulate many the biological characteristics original patient tumor, allowing for comprehensive pharmacogenomic analysis. Here, somatic mutations 23 matched samples...
<p>Supplementary Table 1 drug concentrations</p>
<p>Supplementary Table 4 LOBICO PDXC % sens vs insens</p>
<p>Supplementary Table 2 pancancer clinical info</p>
<p>Text of Supplementary Figure Legends</p>
<p>Supplementary Table 8 FGFR mutations</p>
<p>Figure S1</p>
<p>Supplementary Table 7 gene_importance_t0.1_limit4_ew</p>
<p>Supplementary Table 5 LOBICO data</p>
<p>Supplementary Table 6 ROC formulae training and test</p>
<p>Supplementary Table 4 LOBICO PDXC % sens vs insens</p>
<p>Figure S2</p>
<p>Figure S2</p>
<p>Figure S1</p>