A multiplexed assay for quantifying immunomodulatory proteins supports correlative studies in immunotherapy clinical trials Article Swipe
Jeffrey R. Whiteaker
,
Lei Zhao
,
Regine M. Schoenherr
,
Dongqing Huang
,
Rachel A. Lundeen
,
Ulianna Voytovich
,
Jacob J. Kennedy
,
Richard G. Ivey
,
Chenwei Lin
,
Oscar Murillo
,
Travis D. Lorentzen
,
Simona Colantonio
,
Tessa W. Caceres
,
Rhonda R. Roberts
,
Joseph G. Knotts
,
Joshua J. Reading
,
Candice Perry
,
Christopher W. Richardson
,
Sandra S. Garcia-Buntley
,
William Bocik
,
Stephen M. Hewitt
,
Shrabanti Chowdhury
,
Jackie Vandermeer
,
Stephen D. Smith
,
Ajay K. Gopal
,
Nirasha Ramchurren
,
Steven P. Fling
,
Pei Wang
,
Amanda G. Paulovich
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fonc.2023.1168710
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fonc.2023.1168710
Introduction Immunotherapy is an effective treatment for a subset of cancer patients, and expanding the benefits of immunotherapy to all cancer patients will require predictive biomarkers of response and immune-related adverse events (irAEs). To support correlative studies in immunotherapy clinical trials, we are developing highly validated assays for quantifying immunomodulatory proteins in human biospecimens. Methods Here, we developed a panel of novel monoclonal antibodies and incorporated them into a novel, multiplexed, immuno-multiple reaction monitoring mass spectrometry (MRM-MS)-based proteomic assay targeting 49 proteotypic peptides representing 43 immunomodulatory proteins. Results and discussion The multiplex assay was validated in human tissue and plasma matrices, where the linearity of quantification was >3 orders of magnitude with median interday CVs of 8.7% (tissue) and 10.1% (plasma). Proof-of-principle demonstration of the assay was conducted in plasma samples collected in clinical trials from lymphoma patients receiving an immune checkpoint inhibitor. We provide the assays and novel monoclonal antibodies as a publicly available resource for the biomedical community.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fonc.2023.1168710
- https://www.frontiersin.org/articles/10.3389/fonc.2023.1168710/pdf
- OA Status
- gold
- Cited By
- 5
- References
- 48
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4367853637
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4367853637Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fonc.2023.1168710Digital Object Identifier
- Title
-
A multiplexed assay for quantifying immunomodulatory proteins supports correlative studies in immunotherapy clinical trialsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-05-02Full publication date if available
- Authors
-
Jeffrey R. Whiteaker, Lei Zhao, Regine M. Schoenherr, Dongqing Huang, Rachel A. Lundeen, Ulianna Voytovich, Jacob J. Kennedy, Richard G. Ivey, Chenwei Lin, Oscar Murillo, Travis D. Lorentzen, Simona Colantonio, Tessa W. Caceres, Rhonda R. Roberts, Joseph G. Knotts, Joshua J. Reading, Candice Perry, Christopher W. Richardson, Sandra S. Garcia-Buntley, William Bocik, Stephen M. Hewitt, Shrabanti Chowdhury, Jackie Vandermeer, Stephen D. Smith, Ajay K. Gopal, Nirasha Ramchurren, Steven P. Fling, Pei Wang, Amanda G. PaulovichList of authors in order
- Landing page
-
https://doi.org/10.3389/fonc.2023.1168710Publisher landing page
- PDF URL
-
https://www.frontiersin.org/articles/10.3389/fonc.2023.1168710/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.frontiersin.org/articles/10.3389/fonc.2023.1168710/pdfDirect OA link when available
- Concepts
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Correlative, Immunotherapy, Clinical trial, Medicine, Computational biology, Immunology, Bioinformatics, Immune system, Biology, Pathology, Philosophy, LinguisticsTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2024: 5Per-year citation counts (last 5 years)
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48Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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