Background: Clear cell carcinomas (CCC) are rare histologies outside of the kidney and are typically less sensitive to standard treatments. Genomic alterations in chromatin remodeling pathways involving ARID1A or the intracellular PI3K-mTOR signaling pathway are found in both renal and ovarian CCC. It is unclear whether CCCs originating from different anatomic sites share a common genomic landscape. This CARIS Precision Oncology Alliance project sought to determine whether CCC of different organs shared similar genomic signatures and to identify potential pathways that could be targeted in a tumor-agnostic clinical trial. Methods: CCCs (N = 861) from multiple primary tumor sites, including kidney (30.5%), ovary (39%), endometrium (23.9%), other gynecologic sites (e.g., cervix, fallopian tube, 3.3%), and miscellaneous (non-kidney or gynecologic sites, 3.3%) were analyzed at the Caris Life Sciences Laboratory (Phoenix, AZ). Using hierarchical clustering (HC) and principal component analysis (PCA), the samples were compared across 648 total genes from five metabolic gene sets consisting of angiogenesis, glycolysis, hypoxia, oxidative phosphorylation, and fatty acid metabolism. Gene Set Enrichment Analysis (GSEA) was further conducted on the samples across fifty hallmark gene sets representing specific biologic processes and expression. Samples were also analyzed for individual genomic alterations and immune-oncology associated biomarkers. PD-L1 (SP142) expression was evaluated by immunohistochemistry (positive threshold: 2+ stain intensity and ≥ 5% tumor cells). Results: HC and PCA demonstrated that renal CCC formed distinct clusters compared to non-renal CCC. Tumors from gynecologic sites could not be separated into distinct clusters. GSEA showed that the hypoxia gene set was significantly upregulated in the renal but not in non-renal CCCs. Mutations involving TP53, ARID1A, PIK3CA were found to be the most altered genes in endometrial (62%, 26%, 31%), ovarian (13%, 55%, 48%), other gynecological sites (33%, 38%, 44%), and non-gynecologic CCC (13%, 17%, 12%) respectively. PD-L1 expression, high tumor mutational burden (≥10 mutations/Mb), and deficient mismatch repair/microsatellite instability rates across sites were: kidney (11%, 2%, 2%), endometrium (13%, 12%, 7%), ovary (9%, 4%, 3%), other gynecological sites (31%, 11%, 11%), and miscellaneous sites (11%, 19%, 4%). Conclusions: Initial metabolic gene expression clustering analysis shows that CCCs do not separate by organ of origin beyond renal versus extra-renal. TP53, ARID1A, and PIK3CA were the most frequently altered genes in non-renal CCC. Out of fifty hallmark gene sets, only two were statistically significantly different among gynecological CCCs. This similarity between gynecological CCC can be leveraged by targeting pathways such as PI3K-AKT-mTOR, DNA repair, and MYC targets in a site agnostic manner. Furthermore, high PD-L1 expression is found in other gynecological sites.