Dennis A. Dean
A5003524455- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Cancer Genomics and Diagnostics
- Scientific Computing and Data Management
- Prostate Cancer Treatment and Research
- Cancer Cells and Metastasis
- 3D Printing in Biomedical Research
- Cancer, Hypoxia, and Metabolism
- Cancer Immunotherapy and Biomarkers
- Cell Image Analysis Techniques
- Research Data Management Practices
- Cancer Research and Treatments
- Genetics, Bioinformatics, and Biomedical Research
- Single-cell and spatial transcriptomics
- Molecular Biology Techniques and Applications
- Microtubule and mitosis dynamics
- Gastric Cancer Management and Outcomes
Seven Bridges Genomics (United States)
2020-2024
Abstract Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment propagation, affecting accuracy of modeling cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 matched patient (PT) samples from 509 models. CNA inferences based on DNA sequencing microarray data displayed substantially higher resolution...
Abstract Patient-derived xenografts (PDX) are tumor-in-mouse models for cancer. PDX collections, such as the NCI PDXNet, powerful resources preclinical therapeutic testing. However, variations in experimental and analysis procedures have limited interpretability. To determine robustness of studies, PDXNet tested temozolomide drug response three prevalidated (sensitive, resistant, intermediate) across four blinded Development Trial Centers using independently selected standard operating...
Abstract Although patient-derived xenografts (PDX) are commonly used for preclinical modeling in cancer research, a standard approach to vivo tumor growth analysis and assessment of antitumor activity is lacking, complicating the comparison different studies determination whether PDX experiment has produced evidence needed consider new therapy promising. We present consensus recommendations activity, providing public access suite tools analyses. expect that harmonizing study design assessing...
Developments in high-throughput sequencing (HTS) result an exponential increase the amount of data generated by experiments, complexity bioinformatics analysis reporting and types generated. These increases volume, diversity their expose necessity a structured standardized template. BioCompute Objects (BCOs) provide requisite support for communication HTS that includes workflow, as well data, curation, accessibility reproducibility communication. BCOs standardize how researchers report...
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,...
The BioCompute Object (BCO) standard is an IEEE (IEEE 2791-2020) designed to facilitate the communication of next-generation sequencing data analysis with applications across academia, government agencies, and industry. For example, Food Drug Administration (FDA) supports for regulatory submissions includes in their Data Standards Catalog submission HTS data. We created BCO App generation a range computational environments and, part, participate Advanced Track precisionFDA App-a-thon....
A Correction to this paper has been published: https://doi.org/10.1038/s41588-021-00811-4.
Abstract Background The field of bioinformatics has grown at such a rapid pace that gap in standardization exists when reporting an analysis. In response, the BioCompute project was created to standardize type and method information communicated describing bioinformatic Once became established, its goals shifted broadening awareness usage BioCompute, soliciting feedback from larger audience. To address these goals, collaborated with precisionFDA on crowdsourced challenge ran May 2019 October...
<div>Abstract<p>Although patient-derived xenografts (PDX) are commonly used for preclinical modeling in cancer research, a standard approach to <i>in vivo</i> tumor growth analysis and assessment of antitumor activity is lacking, complicating the comparison different studies determination whether PDX experiment has produced evidence needed consider new therapy promising. We present consensus recommendations activity, providing public access suite tools analyses....
<div>Abstract<p>Although patient-derived xenografts (PDX) are commonly used for preclinical modeling in cancer research, a standard approach to <i>in vivo</i> tumor growth analysis and assessment of antitumor activity is lacking, complicating the comparison different studies determination whether PDX experiment has produced evidence needed consider new therapy promising. We present consensus recommendations activity, providing public access suite tools analyses....
<p>Supplementary Figure 1 shows (A) spider plots of Log 2 individual tumor volumes, (B) growth curves representing average (C) proportional changes in volume, and (D) showing Log2 volume the data shown Figures 2.</p>
<p>Supplementary Figure 1 shows (A) spider plots of Log 2 individual tumor volumes, (B) growth curves representing average (C) proportional changes in volume, and (D) showing Log2 volume the data shown Figures 2.</p>
<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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