4.3 Article

Serum levels of soluble programmed death ligand 1 predict treatment response and progression free survival in multiple myeloma

期刊

ONCOTARGET
卷 6, 期 38, 页码 41228-41236

出版社

IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.5682

关键词

multiple myeloma; programmed death-ligand 1; immune checkpoint; prognosis; biomarker

资金

  1. National Natural Science Foundation of China [81400159, 30471976, 81272620]
  2. Medical Research Foundation of Guangdong Province [B2014158]
  3. Young Teachers' Cultivation Project of Sun Yat-sen University [12ykpy54]
  4. Outstanding Young Talents Project of Sun Yat-sen University Cancer Center [04190101]
  5. Science and technology projects of Guangdong Province [2010B031600233, 2010A090200019]

向作者/读者索取更多资源

Immune checkpoint signaling plays an important role in immunosuppression in multiple myeloma (MM). Blood levels of soluble programmed death-ligand 1 (sPD-L1), a checkpoint-relevant protein, might predict treatment response and survival outcomes in MM patients. We used an enzyme-linked immunosorbent assay to measure serum sPD-L1 levels in 81 newly diagnosed MM patients. We found that myeloma patients had higher sPD-L1 concentrations than healthy controls. The best sPD-L1 cutoff value for predicting disease progression risk was 2.783 ng/mL. The overall response rate to treatment was higher in low sPD-L1 patients than in high sPD-L1 patients. The 3-year progression free survival (PFS) and overall survival (OS) rates for all patients were 16% and 64%, respectively. Multivariate survival analysis including Eastern Cooperative Oncology Group performance status score, treatment response, and sPD-L1 level showed that a less than partial treatment response (PR) and higher sPD-L1 levels (>2.783 ng/ml) were independent prognostic factors for shorter PFS; neither factor was predictive of OS. The serum sPD-L1 level is a valuable biomarker for predicting treatment response and an independent prognostic factor for PFS. PD-1/PD-L1 blockade may be a promising novel immune-based therapeutic strategy in MM.

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