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Current · Arkansas
Last published
2026
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OpenAlex · ORCID
Refreshed
2026-08-15
Christopher P. Wardell
High Impact
Assistant Professor
Also affiliated: BMW (Germany) (2015); University of Leeds (2011); Institute of Cancer Research (2010–2023); BAE Systems (Sweden) (2007); University of Arkansas Medical Center (2018–2025); Oxford University Press (United Kingdom) (2020); Wessex Regional Genetics Laboratory (2011); Winthrop Rockefeller Foundation (2020–2023); RIKEN Center for Integrative Medical Sciences (2015–2018); University of Southampton (2011); Newcastle University (2011)
Faculty Researcher
Biomedical Informatics, College of Medicine
37 h-index
165 pubs
7,727 cited
Research Areas
Biomedical Subjects
Biography and Research Information
OverviewAI-generated summary
Christopher P. Wardell's research focuses on the molecular underpinnings of cancer, particularly multiple myeloma and glioblastoma. His work investigates the genomic and transcriptomic alterations that drive disease progression and influence patient outcomes. Wardell has explored the role of structural variants and specific gene mutations, such as those in the CRBN pathway, in the development of resistance to cancer therapies.
His research also encompasses the development and application of computational pipelines for precision medicine. This includes methods for analyzing next-generation sequencing data to identify actionable mutations and for combining transcriptomics with organoid modeling to tailor treatment strategies. Wardell collaborates with researchers at the University of Arkansas for Medical Sciences, including Michael Bauer, Cody Ashby, Michael Rutherford, and Murat Gökden, with whom he has co-authored multiple publications.
With an h-index of 37 and over 7,600 citations across 165 publications, Wardell is recognized as a highly cited researcher. His work contributes to understanding disease mechanisms and advancing therapeutic approaches in oncology.
Metrics
- h-index: 37
- Publications: 165
- Citations: 7,727
Selected Publications
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Longitudinal multi-omics characterization of the malignant evolution in multirelapsing glioblastoma (2026)
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Applying computational modelling to a high-risk multiple myeloma data set to create novel risk stratification groupings (2025)
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Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition (2025)
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Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images (2025)
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Long-read sequencing for brain tumors (2024)
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Abstract 953: Integration of functional precision medicine assay for high grade glioma management: A single institution experience (2024)
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Intracranial hematolymphoid malignancies: A case series with molecular characterization (2023)
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Science and Tools of Radiomics for Radiation Oncology (2023)
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An advanced molecular medicine case report of a rare human tumor using genomics, pathomics, and radiomics (2023)
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The Impact of Autologous Stem Cell Transplantation on the Genetics of High-Risk Relapsed Multiple Myeloma (2022)
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Identification of novel long noncoding RNA with distinct expression patterns in different subtypes of multiple myeloma (2022)
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Structural variants shape the genomic landscape and clinical outcome of multiple myeloma (2022)
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323 Generation of a functional precision medicine pipeline which combines comparative transcriptomics and tumor organoid modeling to identify bespoke treatment strategies for glioblastoma (2022)
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Oncogenic Mutation BRAF V600E Changes Phenotypic Behavior of THLE-2 Liver Cells through Alteration of Gene Expression (2022)
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A Functional Precision Medicine Pipeline Combines Comparative Transcriptomics and Tumor Organoid Modeling to Identify Bespoke Treatment Strategies for Glioblastoma (2021)
Grants & Funding
As listed on this researcher's institutional profile.
- TCIA Sustainment and Scalability - Platforms for Quantitative Imaging Informatics in Precision Medicine NIH Co-Investigator
- TCIA Sustainment and Scalability - Platforms for Quantitative Imaging Informatics in Precision Medicine - Year 4 - Continuation NIH/Nat. Cancer Institute Co-Investigator
Collaboration Network
Top Collaborators
Cody Ashby
University of Arkansas for Medical Sciences
10 shared publications
In database
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- Structural variants shape the genomic landscape and clinical outcome of multiple myeloma
- Mutations in CRBN and other cereblon pathway genes are infrequently associated with acquired resistance to immunomodulatory drugs
- FiNGS: high quality somatic mutations using filters for next generation sequencing
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
Showing 5 of 10 shared publications
Faith E. Davies
NYU Langone Health (US)
8 shared publications
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- Structural variants shape the genomic landscape and clinical outcome of multiple myeloma
- Mutations in CRBN and other cereblon pathway genes are infrequently associated with acquired resistance to immunomodulatory drugs
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
Showing 5 of 8 shared publications
Brian A. Walker
Sylvester Comprehensive Cancer Center (US)
8 shared publications
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- Structural variants shape the genomic landscape and clinical outcome of multiple myeloma
- Mutations in CRBN and other cereblon pathway genes are infrequently associated with acquired resistance to immunomodulatory drugs
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
Showing 5 of 8 shared publications
Gareth J. Morgan
NYU Langone Health (US)
7 shared publications
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- Structural variants shape the genomic landscape and clinical outcome of multiple myeloma
- Mutations in CRBN and other cereblon pathway genes are infrequently associated with acquired resistance to immunomodulatory drugs
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
Showing 5 of 7 shared publications
Analiz Rodriguez
University of Arkansas for Medical Sciences
7 shared publications
In database
- A Functional Precision Medicine Pipeline Combines Comparative Transcriptomics and Tumor Organoid Modeling to Identify Bespoke Treatment Strategies for Glioblastoma
- Genomic and Transcriptomic Profiling of Brain Metastases
- Primary glioblastoma of the cauda equina with molecular and histopathological characterization: Case report
- Long-read sequencing for brain tumors
- 323 Generation of a functional precision medicine pipeline which combines comparative transcriptomics and tumor organoid modeling to identify bespoke treatment strategies for glioblastoma
Showing 5 of 7 shared publications
Michael Bauer
University of Arkansas for Medical Sciences
6 shared publications
In database
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- Structural variants shape the genomic landscape and clinical outcome of multiple myeloma
- FiNGS: high quality somatic mutations using filters for next generation sequencing
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
Showing 5 of 6 shared publications
Frits van Rhee
University of Arkansas for Medical Sciences
5 shared publications
In database
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
- Identification of novel long noncoding RNA with distinct expression patterns in different subtypes of multiple myeloma
Murat Gökden
University of Arkansas for Medical Sciences
5 shared publications
In database
- A Functional Precision Medicine Pipeline Combines Comparative Transcriptomics and Tumor Organoid Modeling to Identify Bespoke Treatment Strategies for Glioblastoma
- Genomic and Transcriptomic Profiling of Brain Metastases
- Primary glioblastoma of the cauda equina with molecular and histopathological characterization: Case report
- Long-read sequencing for brain tumors
- Intracranial hematolymphoid malignancies: A case series with molecular characterization
Eileen M. Boyle
NYU Langone Health (US)
4 shared publications
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- Structural variants shape the genomic landscape and clinical outcome of multiple myeloma
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
Maurizio Zangari
Winthrop Rockefeller Foundation
4 shared publications
In database
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
Carolina Schinke
University of Arkansas for Medical Sciences
4 shared publications
In database
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
- Healing of lytic lesions and restoration of bone health in multiple myeloma through sclerostin inhibition
Niels Weinhold
Heidelberg University (DE)
4 shared publications
- Mutations in CRBN and other cereblon pathway genes are infrequently associated with acquired resistance to immunomodulatory drugs
- The Impact of gain1q on Mutational Structure and Clonal Evolution in a Uniformly Treated High-Risk Series of Patients at First Relapse
- The Impact of Autologous Stem Cell Transplantation on the Genetics of High-Risk Relapsed Multiple Myeloma
- Applying computational modelling to a high-risk multiple myeloma data set to create novel risk stratification groupings
Martin Kaiser
Royal Marsden NHS Foundation Trust (GB)
4 shared publications
- Mutations in CRBN and other cereblon pathway genes are infrequently associated with acquired resistance to immunomodulatory drugs
- The Impact of gain1q on Mutational Structure and Clonal Evolution in a Uniformly Treated High-Risk Series of Patients at First Relapse
- The Impact of Autologous Stem Cell Transplantation on the Genetics of High-Risk Relapsed Multiple Myeloma
- Applying computational modelling to a high-risk multiple myeloma data set to create novel risk stratification groupings
Charlotte Pawlyn
Royal Marsden NHS Foundation Trust (GB)
4 shared publications
- Mutations in CRBN and other cereblon pathway genes are infrequently associated with acquired resistance to immunomodulatory drugs
- The Impact of gain1q on Mutational Structure and Clonal Evolution in a Uniformly Treated High-Risk Series of Patients at First Relapse
- The Impact of Autologous Stem Cell Transplantation on the Genetics of High-Risk Relapsed Multiple Myeloma
- Applying computational modelling to a high-risk multiple myeloma data set to create novel risk stratification groupings
Yan Wang
NYU Langone Health (US)
3 shared publications
- The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma
- High‐risk transcriptional profiles in multiple myeloma are an acquired feature that can occur in any subtype and more frequently with each subsequent relapse
- Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups
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