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Cancer Immunology Research
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Research Article

Computational Algorithm Driven Evaluation of Monocytic Myeloid Derived Suppressor Cell Frequency For Prediction of Clinical Outcomes

Shigehisa Kitano, Michael A. Postow, Carly G. K. Ziegler, Deborah Kuk, Katherine Panageas, Czrina Cortez, Teresa S Rasalan, Matthew Adamow, Jianda Yuan, Phillip Wong, Grégoire Altan-Bonnet, Jedd D Wolchok and Alexander M Lesokhin
Shigehisa Kitano
1Immunology Program, National Cancer Center Hospital
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Michael A. Postow
2Melanoma and Sarcoma Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center
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Carly G. K. Ziegler
3Center Cancer Systems Biology, Memorial Sloan-Kettering Cancer Center
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Deborah Kuk
4Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center
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Katherine Panageas
5Biostatistics, Memorial Sloan-Kettering Cancer Center
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Czrina Cortez
6Immunology, Memorial Sloan-Kettering Cancer Center
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Teresa S Rasalan
7Medicine, Memorial Sloan-Kettering Cancer Center
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Matthew Adamow
7Medicine, Memorial Sloan-Kettering Cancer Center
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Jianda Yuan
8Ludwig Center for Cancer Immunotherapy, Memorial Sloan-Kettering Cancer Center
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Phillip Wong
9Immunology Program, Memorial Sloan Kettering Cancer Center
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Grégoire Altan-Bonnet
10Division of Hematology, Memorial Sloan-Kettering Cancer Center
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Jedd D Wolchok
6Immunology, Memorial Sloan-Kettering Cancer Center
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Alexander M Lesokhin
7Medicine, Memorial Sloan-Kettering Cancer Center
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  • For correspondence: lesokhia@mskcc.org
DOI: 10.1158/2326-6066.CIR-14-0013
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Abstract

Evaluation of myeloid derived suppressor cells (MDSC), a cell type implicated in T cell suppression, may inform immune status. However, uniform methodology is necessary for prospective testing as a biomarker. We report 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 melanoma patients identifies differing frequency distribution of m-MDSC relative to healthy donors (HD). Patients with a pre-treatment m-MDSC frequency outside a preliminary definition of HD range (<14.9%) were significantly more likely to achieve prolonged overall survival following treatment with ipilimumab, an antibody that promotes T cell activation and proliferation. m-MDSC frequencies inversely correlated with peripheral CD8+ T cell expansion following ipilimumab. Algorithm driven analysis may enable not only development of a novel pre-treatment biomarker for ipilimumab therapy, but also prospective validation of peripheral blood m-MDSC as a biomarker in multiple disease settings.

  • Received January 20, 2014.
  • Revision received April 22, 2014.
  • Accepted May 12, 2014.
  • Copyright © 2014, American Association for Cancer Research.
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This OnlineFirst version was published on May 20, 2014
doi: 10.1158/2326-6066.CIR-14-0013

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Computational Algorithm Driven Evaluation of Monocytic Myeloid Derived Suppressor Cell Frequency For Prediction of Clinical Outcomes
Shigehisa Kitano, Michael A. Postow, Carly G. K. Ziegler, Deborah Kuk, Katherine Panageas, Czrina Cortez, Teresa S Rasalan, Matthew Adamow, Jianda Yuan, Phillip Wong, Grégoire Altan-Bonnet, Jedd D Wolchok and Alexander M Lesokhin
Cancer Immunol Res May 20 2014 DOI: 10.1158/2326-6066.CIR-14-0013

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Computational Algorithm Driven Evaluation of Monocytic Myeloid Derived Suppressor Cell Frequency For Prediction of Clinical Outcomes
Shigehisa Kitano, Michael A. Postow, Carly G. K. Ziegler, Deborah Kuk, Katherine Panageas, Czrina Cortez, Teresa S Rasalan, Matthew Adamow, Jianda Yuan, Phillip Wong, Grégoire Altan-Bonnet, Jedd D Wolchok and Alexander M Lesokhin
Cancer Immunol Res May 20 2014 DOI: 10.1158/2326-6066.CIR-14-0013
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