Abstract
To evaluate the efficacy of parameters derived from [68Ga]Ga-PSMA-11 PET/CT images in predicting pathological HIF-2α expression in primary tumors among patients with renal cell carcinoma (RCC). Fifty-three RCC patients with preoperative [68Ga]Ga-PSMA-11 PET/CT scans and complete surgical specimens were retrospectively enrolled in this study. Radiographic parameters were obtained from PET/CT images, and immunohistochemistry was used to measure the expression of HIF-2α and PSMA. Continuous variables and categorical variables were analyzed by the Mann-Whitney U test and chi-square test, respectively. ROC analysis was used to test the efficacy of several preoperative parameters in identifying pathological HIF-2α expression. Univariable logistic regression analyses were performed for significant parameters to predict pathological HIF-2α expression in RCC. Of the 53 tumors, 29 (54.7%) had high expression of HIF-2α. The SUVmax was significantly different in the HIF-2α expression subgroups (p < 0.001). SUVmax emerged as the most significant parameter to differentiate HIF-2α expression subgroups (high vs. low), with the AUC of 0.93 (95% CI 0.85-1.00, p < 0.001), sensitivity of 90%, and specificity of 88%. Furthermore, SUVmax was confirmed as the most significant predictor of HIF-2α expression level by univariable logistic regression model analysis (odds ratio 1.39, 95% CI 1.17-1.65, p < 0.001). Consistent with the radiographic results of [68Ga]Ga-PSMA-11 PET/CT, the staining intensity of pathological PSMA was significantly higher in HIF-2α-high-expressing tumors (p = 0.003). [68Ga]Ga-PSMA-11 PET/CT was superior in identifying pathological HIF-2α expression in primary tumors of RCC patients, demonstrating its potential application in predicting responses to HIF-2α antagonists. • [68Ga]Ga-PSMA-11 PET/CT could potentially predict the HIF-2α expression of primary tumors among patients with RCC. • SUVmaxof [68Ga]Ga-PSMA-11 PET/CT was the most significant predictor of HIF-2α expression level. • This probability could help predict the therapeutic response of patients with RCC to HIF-2α antagonists.
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