RT Journal Article
SR Electronic
T1 Computational Algorithm-Driven Evaluation of Monocytic Myeloid-Derived Suppressor Cell Frequency for Prediction of Clinical Outcomes
JF Cancer Immunology Research
JO Cancer Immunol Res
FD American Association for Cancer Research
SP 812
OP 821
DO 10.1158/2326-6066.CIR-14-0013
VO 2
IS 8
A1 Kitano, Shigehisa
A1 Postow, Michael A.
A1 Ziegler, Carly G.K.
A1 Kuk, Deborah
A1 Panageas, Katherine S.
A1 Cortez, Czrina
A1 Rasalan, Teresa
A1 Adamow, Mathew
A1 Yuan, Jianda
A1 Wong, Philip
A1 Altan-Bonnet, Gregoire
A1 Wolchok, Jedd D.
A1 Lesokhin, Alexander M.
YR 2014
UL http://cancerimmunolres.aacrjournals.org/content/2/8/812.abstract
AB 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 (<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 were inversely correlated with peripheral CD8+ T-cell expansion following ipilimumab. Algorithm-driven analysis may enable not only development of a novel pretreatment biomarker for ipilimumab therapy, but also prospective validation of peripheral blood m-MDSCs as a biomarker in multiple disease settings. Cancer Immunol Res; 2(8); 812–21. ©2014 AACR.