Predictive value of 18F‐FDG PET/CT and serum tumor markers for tumor mutational burden in patients with non‐small cell lung cancer

Author:

Zhang Qian1ORCID,Tao Xiuli2,Yuan Pei3,Zhang Zewei2,Ying Jianming3,Guo Lei3,Li Ning4ORCID,Wang Shuhang4,Li Jing12,Liu Ying2,Guo Wei5ORCID,Zhao Shijun1,Wu Ning12

Affiliation:

1. Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China

2. Department of Nuclear Medicine (PET‐CT Center) National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China

3. Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China

4. Department of Clinical Trial Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China

5. Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China

Abstract

AbstractPurposeTo investigate the correlations between metabolic parameters (MPs) of 18F‐fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT), serum tumor markers (STMs), and tumor mutational burden (TMB) in patients with non‐small cell lung cancer (NSCLC).Materials and MethodsIn this retrospective study, we enrolled 129 patients with NSCLC (males, 78; females, 51) who underwent baseline TMB and STM tests and 18F‐FDG PET/CT scans before treatment between March 2018 and September 2022. Patients were categorized into TMB‐high (TMB ≥10 mutations/Mb; n = 27 [20.9%]) and non‐TMB‐high (TMB <10 mutations/Mb; n = 102 [79.1%]) groups. Binary logistic regression analyses were performed to determine independent predictors of TMB‐high. Univariate and multivariate linear regression analyses were performed to determine independent predictors of TMB level on a log scale. Subgroup analyses for adenocarcinoma (ADC), ADC with EGFR+, ADC with EGFR−, and squamous cell carcinoma (SCC) were performed.ResultsFor ADC, all MPs (SULpeak, SULmax, SULmean, MTV, and TLG) were significantly higher in the TMB‐high group than the non‐TMB‐high group; smoker (odds ratio [OR] = 27.08, p = 0.018), EGFR+ (OR = 0.03, p = 0.033), KRAS+ (OR = 7.98, p = 0.083), high CEA (OR = 33.56, p = 0.029), and high CA125 (OR = 13.68, p = 0.030) were independent predictors of TMB‐high; and all MPs showed significant positive linear correlations with TMB on a log scale, with SULpeak as an independent predictor. However, no significant correlation was observed for SCC.ConclusionMPs and STMs can predict the TMB level for patients with ADC, and may serve as potential substitutes for TMB with increased value and easy implementation in guiding immunotherapy through noninvasive methods.

Publisher

Wiley

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology

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