Background: We aimed to determine the most common mutations in endometrial cancers (EC) of patients enrolled in UNCSeq and to discern if there was any correlation between the detected mutations and the patients' BMI as well as tumor histology and stage. Methods: Snap-frozen and FFPE tissue samples were collected from EC patients enrolled on UNCSeq (NCT01457196). Illumina libraries were prepared separately from tumor and a matched normal sample from each patient. Relevant targets were enriched by a custom designed Agilent SureSelect hybrid capture enrichment library using standard protocols. Samples were sequenced on Illumina HiSeq machines in a variety of formats. Mutations with a quality score < 100 were filtered from the data set and only mutations rated to have a moderate to high impact were retained. Patient Mutational Counts were associated with clinical correlates via negative binomial regression, and the heterogeneity of mutational counts between groups was assessed via the Fligner-Killeen Test. Results: Data was collected from 126 EC patients. We found 591 mutations that appeared in at least 1 individual. The five most common mutations detected in endometrioid tumors were of PTEN, PIK3CA, ARID1A, PIK3R1 and CTNNB1. The most common mutations in serous tumors were of TP53, PIK3CA, FBXW7, MML2 and MLH1. After limiting the analysis to the 104 patients with endometrioid histology, we did not observe a correlation between BMI and mutation frequency. However, patients with Stage 1 and 2 disease (early) tended to have a much higher mutation frequency than patients with Stage 3 and 4 disease (advanced) (p = 0.004). Similarly, Grade 1 EC also exhibited greater mutational heterogeneity in terms of total number of mutations observed per patient relative to other grades (p = 0.037). Conclusions: We did not find a relationship between BMI and mutated genes in endometrioid EC. Further collection of EC through UNCseq is ongoing. However, mutation heterogeneity appears to be common in low stage and grade tumors. These findings suggest that mutation heterogeneity may be relatively indolent until sub-clonal populations eventually arise as a result of acquired driver mutations, such that one subpopulation predominates, resulting in higher grade and stage EC.