18F-RGD PET/CT and Systemic Inflammatory Biomarkers Predict Outcomes of Patients With Advanced NSCLC Receiving Combined Antiangiogenic Treatment

Jie Liu; Leilei Wu; Zhiguo Liu; Samuel Seery; Jianing Li; Zhenhua Gao; Jinming Yu; Xue Meng

doi:10.3389/fonc.2021.671912

¹⁸F-RGD PET/CT and Systemic Inflammatory Biomarkers Predict Outcomes of Patients With Advanced NSCLC Receiving Combined Antiangiogenic Treatment

Front Oncol. 2021 Jun 4:11:671912. doi: 10.3389/fonc.2021.671912. eCollection 2021.

Authors

Jie Liu¹, Leilei Wu^{1

2}, Zhiguo Liu¹, Samuel Seery^{3

4}, Jianing Li¹, Zhenhua Gao¹, Jinming Yu¹, Xue Meng¹

Affiliations

¹ Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
² Department of Medical Oncology, Cancer Center, Qilu Hospital of Shandong University, Jinan, China.
³ Department of Humanities and Social Sciences, Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
⁴ Faculty of Health and Medicine, Division of Health Research, Lancaster University, Lancaster, United Kingdom.

Abstract

Background: The aim of this study was to evaluate ¹⁸F-AlF-NOTA-PRGD2 positron emission tomography/computed tomography (¹⁸F-RGD PET/CT) and serum inflammation biomarkers for predicting outcomes of patients receiving combined antiangiogenic treatment for advanced non-small cell lung cancer (NSCLC).

Methods: Patients with advanced NSCLC underwent ¹⁸F-RGD PET/CT examination and provided blood samples before treatments commenced. PET/CT parameters included maximum standard uptake value (SUVmax) and mean standard uptake value (SUVmean), peak standard uptake value (SUVpeak) and metabolic tumor volume (MTV) for all contoured lesions. Biomarkers for inflammation included pretreatment neutrophil-to-lymphocyte ratio (PreNLR), pretreatment platelet-to-lymphocyte ratio (PrePLR), and pretreatment lymphocyte-to-monocyte ratio (PreLMR). Receiver operating characteristic (ROC) curve analysis was used to describe response prediction accuracy. Logistic regression and Cox's regression analysis was implemented to identify independent factors for short-term responses and progression-free survival (PFS).

Results: This study included 23 patients. According to ROC curve analysis, there were significant correlations between the SUVmax, SUVmean, and ¹⁸F-RGD PET/CT MTV and short-term responses (p<0.05). SUVmax was identified using logistic regression analysis as a significant predictor of treatment sensitivity (p=0.008). Cox's multivariate regression analysis suggested that high SUVpeak (p=0.021) and high PreLMR (p=0.03) were independent PFS predictors. Combining SUVpeak and PreLMR may also increase the prognostic value for PFS, enabling us to identify a subgroup of patients with intermediate PFS.

Conclusion: ¹⁸F-RGD uptake on PET/CT and serum inflammation biomarker pretreatment may predict outcomes for combined antiangiogenic treatments for advanced NSCLC patients. Higher ¹⁸F-RGD uptake and higher PreLMR also appear to predict improved short-term responses and PFS. Combining biomarkers may therefore provide a basis for risk stratification, although further research is required.

Keywords: 18F-RGD PET/CT; NSCLC; combined antiangiogenic therapy; inflammatory biomarkers; outcome prediction.