68Ga-PSMA-11 PET/CT Parameter Correlates with Pathological VEGFR-2/PDGFR-β Expression in Renal Cell Carcinoma Patients.

Abstract

Response prediction is necessary for renal cell carcinoma (RCC) tumors. We aim to evaluate parameters derived from 68Ga-PSMA-11 PET/CT images for prediction of pathological VEGFR-2/PDGFR-β expression of primary RCC tumors. Forty-eight RCC patients were retrospectively enrolled with preoperative 68Ga-PSMA-11 PET/CT scan and surgical specimen. Radiological parameters including tumor diameter, mean CT value, and maximal standard uptake value (SUVmax) were derived from PET/CT images and pathological VEGFR-2/PDGFR-β/PSMA expression were identified with immunohistochemistry. Mann-Whitney U test was performed for continuous variables and the chi-square test for categorical variables. ROC was used for determining the effectiveness of preoperative parameters in differentiating VEGFR-2/PDGFR-β expression. Univariate and multivariate logistic regression analyses were performed for significant parameters to predict VEGFR-2 & PDGFR-β co-expression. Of the 48 tumors, 25 (52.1%) harbored positive VEGFR-2 expression, 28 (58.3%) harbored positive PDGFR-β expression, and 24 (50%) were both VEGFR-2 positive and PDGFR-β positive. SUVmax significantly differed by subgroups of VEGFR-2/PDGFR-β expression (both P < 0.001). SUVmax demonstrated superior performance for differentiating VEGFR-2 & PDGFR-β co-expression (positive vs. negative), with area under the curve 0.87 (95% CI 0.78-0.96, P < 0.001), sensitivity 93% and specificity 78%. Moreover, SUVmax was identified as the significant predictor for VEGFR-2 & PDGFR-β co-expression (odds ratio 4.01, 95% CI 1.99-8.08, P < 0.001). Concordant with radiological findings with 68Ga-PSMA-11 PET/CT, pathological PSMA staining intensity was significantly higher in both VEGFR-2-positive tumor and PDGFR-β-positive tumor (P = 0.009 and P < 0.001, respectively). 68Ga-PSMA-11 PET/CT could effectively identify pathological VEGFR-2/PDGFR-β expression of primary RCC tumors, which may help with selection of mRCC patients suitable for TKIs treatment.