Oncotarget

Research Papers:

Soluble PD-L1: A biomarker to predict progression of autologous transplantation in patients with multiple myeloma

Shang-Yi Huang _, Hsiu-Hsia Lin, Chung-Wu Lin, Chi-Cheng Li, Ming Yao, Jih-Luh Tang, Hsin-An Hou, Woei Tsay, Sheng-Je Chou, Chieh-Lung Cheng and Hwei-Fang Tien

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Oncotarget. 2016; 7:62490-62502. https://doi.org/10.18632/oncotarget.11519

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Abstract

Shang-Yi Huang1,*, Hsiu-Hsia Lin1,*, Chung-Wu Lin2, Chi-Cheng Li3, Ming Yao1, Jih-Luh Tang1,3, Hsin-An Hou1, Woei Tsay1, Sheng-Je Chou1, Chieh-Lung Cheng1, Hwei-Fang Tien1

1Department of Internal Medicine, National Taiwan University, Medical College and Hospital, Taipei, Taiwan

2Department of Pathology, National Taiwan University, Medical College and Hospital, Taipei, Taiwan

3Tai-Cheng Stem Cell Therapy Center, National Taiwan University, Taipei, Taiwan

*These authors have contributed equally to this work

Correspondence to:

Shang-Yi Huang, email: [email protected]

Keywords: soluble PD-L1, bone marrow plasma, multiple myeloma, autologous transplantation, prognosis

Received: April 25, 2016    Accepted: August 11, 2016    Published: August 23, 2016

ABSTRACT

Autologous hematopoietic stem cell transplantation (AuHSCT) is standard in treating eligible multiple myeloma (MM) patients. However, the outcome after treatment is highly variable. We used ELISA to analyze the levels of soluble PD-L1 (suPD-L1) in bone marrow (BM) plasma from 61 patients with MM at 100 days after AuHSCT. Patients were classified into high (H) and normal-to-low (NL) groups depending on their suPD-L1 levels. Among patients who had a very good partial response (VGPR) or better after AuHSCT, those in the H-group had a shorter response period (RpSCT) as well as shorter overall survival (OS) than those in the NL-group. Multivariate analyses confirmed that a high suPD-L1 level and high-risk cytogenetic abnormalities are independent factors for RpSCT. Our data suggest that suPD-L1 in the BM plasma of MM patients who have VGPR or better after AuHSCT could be used as a biomarker to predict outcome.


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