Background: Neoantigen-based personalized cancer vaccines carry significant promise in treating solid malignancies. For the purpose of neoantigen prediction, questions remain on the suitability of the primary versus the metastatic tumor of an individual patient (pt). Here we performed an in-depth analysis of somatic variants of 45 pts with paired primary and metastatic solid tumors. Methods: Pts were enrolled in the Total Cancer Care protocol across the Oncology Research Information Exchange Network (ORIEN). Whole-exome sequencing (WES) of primary and metastatic tumor pairs was performed for 45 pts. These included head and neck (n = 8), renal cell carcinoma (n = 7), non-small cell lung cancer (n = 6), melanoma (n = 5), bladder (n = 3), sarcoma (n = 3), ovary (n = 3), esophageal (n = 2), colorectal (n = 2) and other singletons (n = 5). The data was analyzed through the ORIEN AVATAR Molecular Analysis Pipeline, which consisted of adapter trimming, single sample variant detection, somatic mutation detection and filtering, variant annotation, and filtering of variants from a panel of normal samples. In this analysis, we focused on somatic events that result in an in-frame alteration (such as missense, in-frame insertion/deletion) and out-of-frame protein-altering mutations (such as frameshifts, de novo start and nonstop gain). To assign the clones based on the variant allele frequency, we performed complete linkage clustering. Each cluster was then assigned based on the identified oncogenic driver variant. Results: For in-frame events, we noticed that bladder cancer, melanoma, and gynecological cancers shared close to 75% of the mutations between paired primary and metastatic cases. In contrast, esophageal, brain, and endometrial cancers had a low overlap (< 25%) of variants. For out-of-frame events, we found that these events tend to have a lower proportion of shared somatic variants between primary and metastasis than in-frame variants. Through a closer evaluation of the variant allele frequency in variants shared between primary and metastatic disease, we were able to track several cancer drivers, such as oncogenic drivers of BRAF V600E, RB1 R358*, NRAS G13R, KRAS G12A, and TP53 loss-of-function that were consistently present in paired primary and metastatic tumors. Here, we were able to assign the putative clone based on the driver event in 39 out of 45 pts. Conclusions: Our analysis demonstrates genetic variations that exist when comparing paired primary and metastatic tumors that appear to vary by histology. Variants are potentially undergoing negative selection supported by the preferential loss of out-of-frame events in metastatic tumors. Understanding the clonal structure will be key to neoantigen prediction for effective neoantigen-based vaccines. Additional steps in variant prioritization are ongoing and will be reported at the meeting.