Maihi Fujita
- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Cancer Genomics and Diagnostics
- Cancer Cells and Metastasis
- 3D Printing in Biomedical Research
- Immunotherapy and Immune Responses
- HER2/EGFR in Cancer Research
- Monoclonal and Polyclonal Antibodies Research
- Cancer Research and Treatments
- Cancer Treatment and Pharmacology
- Cell Image Analysis Techniques
- Radiopharmaceutical Chemistry and Applications
- Protein Degradation and Inhibitors
- Nutrition, Genetics, and Disease
- Macrophage Migration Inhibitory Factor
- Chemical Reactions and Isotopes
- Molecular Biology Techniques and Applications
- Adenosine and Purinergic Signaling
- Colorectal Cancer Treatments and Studies
- Digestive system and related health
- Biomedical Text Mining and Ontologies
- Cancer Immunotherapy and Biomarkers
- CRISPR and Genetic Engineering
- Microtubule and mitosis dynamics
University of Utah
2018-2025
Huntsman Cancer Institute
2016-2024
Models that recapitulate the complexity of human tumors are urgently needed to develop more effective cancer therapies. We report a bank patient-derived xenografts (PDXs) and matched organoid cultures from represent greatest unmet need: endocrine-resistant, treatment-refractory metastatic breast cancers. leverage PDXs PDX-derived organoids (PDxO) for drug screening is feasible cost-effective with in vivo validation. Moreover, we demonstrate feasibility using these models precision oncology...
Abstract 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 landscapes 536 patient-derived xenograft (PDX) models across 25 types, together mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared human tumors, PDXs typically higher purity fit dynamic driver events molecular properties via multiple...
Abstract Background Metastatic breast cancer (MBC) is incurable, with a 5-year survival rate of 28%. In the USA, more than 42,000 patients die from MBC every year. The most common type estrogen receptor-positive (ER+), and ER+ any other subtype. tumors can be successfully treated hormone therapy, but many acquire endocrine resistance, at which point treatment options are limited. There an urgent need for model systems that better represent human in vivo, where metastasize. Patient-derived...
Abstract Background Targeted therapies for triple-negative breast cancer (TNBC) are limited; however, the epidermal growth factor receptor (EGFR) represents a potential target, as majority of TNBC express EGFR. The purpose these studies was to evaluate effectiveness two EGFR-targeted antibody-drug conjugates (ADC: ABT-414; ABBV-321) in combination with navitoclax, an antagonist anti-apoptotic BCL-2 and BCL-X L proteins, order assess translational relevance combinations TNBC. Methods...
We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access National Cancer Institute-funded PDXNet consortium resources, facilitate collaboration among researchers and make these data easily available for research. The includes sections analysis results, metrics activities, processing protocols training materials data. Currently, contains model information resources from 334 new models across 33 cancer types. Tissue samples of were deposited in NCI's...
Abstract Model systems that recapitulate the complexity of human tumors and reality variable treatment responses are urgently needed to better understand cancer biology develop more effective therapies. Here we report development characterization a large bank patient-derived xenografts (PDX) matched organoid cultures from represent some greatest unmet needs in breast research treatment. These include endocrine-resistant, treatment-refractory, metastatic cancers and, cases, multiple tumor...
Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of intact tissue immunocompromised mice. Histologic imaging via hematoxylin eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies large clinical H&E image repositories have shown that deep learning analysis can identify intercellular morphologic signals correlated with disease phenotype therapeutic response. In this study,...
<div>Abstract<p>Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of intact tissue immunocompromised mice. Histologic imaging via hematoxylin eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies large clinical H&E image repositories have shown that deep learning analysis can identify intercellular morphologic signals correlated with disease phenotype...
<div>Abstract<p>Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of intact tissue immunocompromised mice. Histologic imaging via hematoxylin eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies large clinical H&E image repositories have shown that deep learning analysis can identify intercellular morphologic signals correlated with disease phenotype...
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