Introduction: Endometrial cancer (EC) is the most common gynecological malignancy among women in developed countries. In the United States, it is estimated that 66,570 new cases and 12,940 deaths will occur in 2021. EC is more common in white women, but black women have a worse prognosis with higher mortality rates. Molecular characteristics in tumor tissue have been reported for potential clinical utility. Integrated genomic characterization efforts have shown common molecular alterations occurring in oncogenic pathways from bulk molecular profiling of EC tumors. However, little is known about the tumor heterogeneity in endometrial cancer. Thus, using high resolution single cell technologies, we assessed tumor heterogeneity in endometrial cancers. Our preliminary study includes endometrial tumors from five (3 African Americans, 1 Hispanic/Latino, 1 Caucasian) cases. We utilize bulk whole exome sequencing and single cell whole genome sequencing copy number variation to study tumor heterogeneity. Frozen tumor sections were used to collect and sequence single nuclei utilizing the 10x ChromiumTM single cell copy number variation (scCNV). Illumina NovasEQ600 was used to sequence the single cell libraries. Results: 1,546 cells were sequenced across five tumors. Each tumor was visually inspected through hierarchical clustering from the scCNV data. Beyond describing the heterogeneity through chromosome or chromosome arm level gains and losses in samples that included single and mixed histology tumors, we assessed clonal populations suggesting apparently different clonal evolution within samples. Mutations in cancer related genes such as TP53, PTEN and PIK3CA among others suggested a clonal tumor cell stratification. The single cell whole genome data was compared to bulk exome sequencing data to determine the power of scCNV to detect clonal populations of tumor cells. Conclusions: Using varied histologies in five EC tumors, we performed DNA-CNV analysis using single cell sequencing. This level of resolution enhanced our analysis to provide clear evidence of heterogeneity in all tumors that were assessed in our study. We plan to further expand our sample size to study the degree of heterogeneity in endometrial cancer. Citation Format: Enrique Velazquez Villarreal, Lee D. Gibbs, Dana Mahinbakht, Diane M. Da Silva, Lynda D. Roman, David W. Craig, John D. Carpten. Single cell whole genome sequencing to assess tumor heterogeneity in endometrial cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 772.

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Introduction: CRC is the second leading cause of cancer mortality in the United States. Clinical factors and molecular characteristics may impact therapeutics and prognosis. Scientific studies have uncovered significant aberrations, including critical genes and pathways. Despite these efforts, few studies have utilized similar sample sizes to TCGA, heterogeneous populations and integrative clinical data to compare their reported genomic changes, even though little is known about the tumor microenvironment and its significance for colorectal tumorigenesis. Methods: Clinical and DNA genomic data from 262 colorectal tumor/normal DNA samples were obtained for whole exome sequencing analysis from the Oncology Research Information Exchange Network and two colorectal tissue samples for Spatial Transcriptomics profiling from the USC colorectal cancer Moonshot project. Whole Exome Sequencing data analysis was used for identifying genetic alterations. Samples were stratified based on microsatellite instability, age group, anatomical subsites, and histological subtypes. Emphasis was given to comparing molecular characteristics among Hispanic/Latino patients since their reported higher mortality and cancer disparities. Mutation frequencies from our cohort were compared to those from the TCGA. An ongoing spatial transcriptomics analysis consists in processing two fresh-frozen tissue samples through the visium spatial gene expression library using standard short-read sequencing. Results: Tumor molecular profiling revealed 20 genes significantly mutated. We found differences in gene mutation frequencies among our samples, highlighting APC (60%), TP53 (56%), TTN (49%), and KRAS (44%) gene mutations. In comparison with TCGA data, in addition to the expected APC, TP53, PIK3CA, and KRAS mutations, we found frequent mutations in POLE and TTN. To assess the basis for the considerably different mutation rates, we evaluated MSI. Among the 262 tumors, 41 (16%) had high levels of MSI, 2 (1%) had low levels of MSI (MSI-L), and 215 (82%) were microsatellite stable (MSS). Cancer heterogeneity was reported among tumors with different characteristics such as age group, anatomical subsite, and histological subtypes. The ongoing spatial transcriptomics analysis that will be ready before the annual meeting will identify cellular populations and map immunological and inflammatory signals in the microenvironment. Conclusions: Our study reveals the impact of molecularly profiling tumors using considerable sample sizes and stratified samples in several subgroups. Our study adds important information about tumor heterogeneity and the tumor microenvironment in colorectal cancer by including our spatial transcriptomics data analysis. Citation Format: Enrique Velazquez Villarreal, Seeta Rajpara, Yuxin Jin, Jing Qian, Bohan Zhang, Brigette Waldrup, Donna Loza, Heinz-Josef Lenz, David W. Craig, John D. Carpten. Tumor molecular profiling and spatial transcriptomics to assess colorectal cancer heterogeneity and microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1515.