Radiomic features of renal cell carcinoma primary and metastatic sites as predictors of TERT and BAP1 mutations.

Abstract

282 Background: TERT and BAP1 mutations are associated with poor clinical outcome in patients (pts) with metastatic renal cell carcinoma (mRCC) (Dizman et al JITC 2020; Joseph et al J Urol 2016). In this study we explore radiogenomics as a non-invasive method to identify these alterations. Methods: Pts with mRCC who had genomic testing in the course of routine clinical care were included in the current analysis. Pts were assessed with the GEM Extra assay, a CAP-accredited, CLIA-certified test encompassing paired tumor-normal whole exome sequencing (WES) and tumor whole transcriptome sequencing (TGen; Phoenix, AZ). Pts underwent CT imaging; radiomic analysis was performed on the segmented metastatic and primary lesions. Features were independently correlated with TERT and BAP1 mutation status to generate Pearson correlation values (PCVs). Results: 92 pts (65:27 M: F) were included in the analysis; of these, the majority of pts (84%) had clear cell histology. Alterations in the TERT gene were seen in 12 pts. In these pts 1,325 radiomic features of the primary tissue were examined and 251 features correlated with a PCV ≥ |0.2|. Of these, 42 features were correlated with a PCV ≥ |0.3|. Highest correlation with TERT mutation was seen with Gray Level Cooccurrence Matrix (GLCM) and First Order Features (FOF). 9 pts had BAP1 mutation with 5 detected in primary tumor and 4 in metastatic sites. Analysis of primary tumor imaging yielded no significant associations between radiomic features and BAP1 mutation. However, out of approximately 1,500 radiomic features noted in metastatic sites, 111 features correlated with BAP1 mutation with a PCV ≥ 0.2. Of these, 15 features correlated with a PCV ≥ 0.3. The radiomic features with the highest correlation with BAP1mt were Gray Level Dependence Matrix (GLDM) and GLCM. Conclusions: By identifying a correlation between radiomic features of TERT mutation in primary tumors and BAP1 mutation in metastatic sites, our work may ultimately yield a non-invasive method of discerning mutational status in patents with mRCC. Efforts are ongoing to validate our findings within The Cancer Imaging Archive.