Metabolic characteristics of programmed cell death-ligand 1-expressing lung cancer on 18F-fluorodeoxyglucose positron emission tomography/computed tomography

Kazuki Takada, Gouji Toyokawa, Tatsuro Okamoto, Shingo Baba, Yuka Kozuma, Taichi Matsubara, Naoki Haratake, Takaki Akamine, Shinkichi Takamori, Masakazu Katsura, Fumihiro Shoji, Hiroshi Honda, Yoshinao Oda, Yoshihiko Maehara

Research output: Contribution to journalArticlepeer-review

74 Citations (Scopus)

Abstract

Programmed cell death-1 (PD-1) and programmed cell death-ligand 1 (PD-L1) have been identified as novel targets of immunotherapy of lung cancer. In present study, we evaluated the metabolic characteristics of lung cancer by using 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) with regard to PD-L1 protein expression. PD-L1 protein expression was evaluated by immunohistochemistry with the antibody clone SP142 in 579 surgically resected primary lung cancer patients. Cases with less than 5% tumor membrane staining were considered negative. We examined the association between the frequency of PD-L1 protein expression and the maximum standardized uptake value (SUVmax) in preoperative 18F-FDG PET/CT. The cut-off values for SUVmax were determined by receiver operating characteristic curve analyses. The SUVmax was significantly higher in nonsmall cell lung cancer (NSCLC) patients with PD-L1 protein expression compared with those without PD-L1 protein expression (P < 0.0001). However, there was no correlation between SUVmax and PD-L1 protein expression in patients with neuroendocrine tumors (P = 0.6545). Multivariate analysis revealed that smoking, the presence of pleural invasion, and high SUVmax were independent predictors of PD-L1 positivity. PD-L1-expressing NSCLC had a high glucose metabolism. The SUVmax in preoperative 18F-FDG PET/CT was a predictor of PD-L1 protein expression in patients with NSCLC.

Original languageEnglish
Pages (from-to)2552-2561
Number of pages10
JournalCancer Medicine
Volume6
Issue number11
DOIs
Publication statusPublished - Nov 2017

All Science Journal Classification (ASJC) codes

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

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