1. Computational Algorithm-Driven Evaluation of Monocytic Myeloid-Derived Suppressor Cell Frequency for Prediction of Clinical Outcomes
- Author
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Teresa S. Rasalan, Phillip Wong, Katherine S. Panageas, Alexander M. Lesokhin, Czrina Cortez, Grégoire Altan-Bonnet, Michael A. Postow, Jedd D. Wolchok, Carly G. K. Ziegler, Deborah Kuk, Jianda Yuan, Shigehisa Kitano, and Matthew Adamow
- Subjects
Adult ,Male ,Oncology ,Cancer Research ,medicine.medical_specialty ,Cell type ,Immunology ,Lipopolysaccharide Receptors ,Antineoplastic Agents ,Ipilimumab ,Article ,Internal medicine ,medicine ,Humans ,Myeloid Cells ,Melanoma ,Aged ,Whole blood ,Aged, 80 and over ,biology ,business.industry ,Antibodies, Monoclonal ,HLA-DR Antigens ,Middle Aged ,medicine.disease ,biology.protein ,Myeloid-derived Suppressor Cell ,Biomarker (medicine) ,Female ,Antibody ,business ,Algorithms ,CD8 ,medicine.drug - Abstract
Evaluation of myeloid-derived suppressor cells (MDSC), a cell type implicated in T-cell suppression, may inform immune status. However, a uniform methodology is necessary for prospective testing as a biomarker. We report the use of a computational algorithm-driven analysis of whole blood and cryopreserved samples for monocytic MDSC (m-MDSC) quantity that removes variables related to blood processing and user definitions. Applying these methods to samples from patients with melanoma identifies differing frequency distribution of m-MDSC relative to that in healthy donors. Patients with a pretreatment m-MDSC frequency outside a preliminary definition of healthy donor range (
- Published
- 2014
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