Abstract 772: Single cell whole genome sequencing to assess tumor heterogeneity in endometrial cancer

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.

Abstract 2199: Identifying genomic heterogeneity at single-cell resolution in endometrial cancer

Introduction: Endometrial cancer accounts for ~76,000 deaths amongst women worldwide. In the United States, it is estimated 65,620 new cases and 12,590 deaths occurring in 2020, being the fourth most common gynecologic malignancy in the country. It has been reported that specific molecular characteristics in tissues are associated with poorer prognosis. Publicly available data generated from bulk molecular profiling of tumors has provided a molecular taxonomy of endometrial cancers with common alterations occurring in a number of known oncogenic pathways. However, little is known about the degree of heterogeneity in endometrial cancer. Thus, we have set out to utilize single cell technologies to assess tumor heterogeneity in endometrial cancers. Methods: Our preliminary study includes serous and mixed lineage endometrial tumors from five (3 African Americans, 1 Hispanic/Latino, 1 Caucasian) cases. In addition to bulk whole exome sequencing, we utilized single cell whole genome sequencing to assess global copy number heterogeneity. OCT-embedded frozen tumor sections were dissociated to collect nuclei, which were subjected to single nuclei sequencing using the 10x ChromiumTM single cell copy number variation (scCNV) assay targeting 500 cells per sample. Single cell libraries were quality assessed and sequenced using the Illumina NovaSeq6000 system. Data were processed using the 10X Genomics CellRanger pipeline for assessment of copy number heterogeneity. Results: We generated scCNV data on a total of 1,546 cells across five tumors. Hierarchical clustering and visual inspection of scCNV data reveals obvious somatic copy number tumor cell heterogeneity in all samples, including single and mixed histology tumors. Heterogeneity was mostly distinguished by whole chromosome or chromosome arm level gains or losses. Clonal focal amplifications were detected at 5p, 8p, 8q, and 17q encompassing known oncogenes. As we are able to identify clustered diploid populations of normal cells, we are using these data to perform segregation analysis for CGH analysis and the identification of somatic mutations in clonal populations of cells. These data are being compared to bulk exome sequencing data to determine the power of scCNV for detecting clonal populations of tumor cells. Conclusions: This project used high resolution single cell sequencing in five endometrial cancers with varying histologies. scCNV analysis provided clear evidence of heterogeneity in all tumors that were assessed in our study. This single cell whole genome data is being further analyzed for the presence of focal events, breakpoints and mutations that further stratify clonal tumor cell components in these cases. We plan to further expand this cohort to establish additional evidence for heterogeneity in endometrial cancer.

Citation Format: Enrique I. Velazquez Villarreal, Lee D. Gibbs, Dana Mahinbakht, Diane M. Da Silva, Lynda D. Roman, David W. Craig, John D. Carpten. Identifying genomic heterogeneity at single-cell resolution in endometrial cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2199.

Incidence of diabetes and prediabetes unmasked by dexamethasone in women undergoing (neo) adjuvant taxane therapy

e12526

Background: Women with early stage breast cancer receive premedication with dexamethasone prior to administration of paclitaxel and docetaxel. We undertook a retrospective chart review to determine the frequency of steroid-induced hyperglycemia in women receiving steroid premedication with paclitaxel and docetaxel. Methods: Women who were receiving paclitaxel or taxotere chemotherapy as (neo)adjuvant therapy were identified from pharmacy records. Patients were excluded if they were currently receiving insulin or hypoglycemic agents for diabetes. A Comprehensive Metabolic Panel (CMP) was performed prior to chemotherapy and the random glucose level was recorded. The highest random glucose level recorded during all cycles of treatment was used in the analysis. The threshold for diabetes is a random glucose of 200 mg/dL and levels > 150 mg/dL, but less than 200 mg/dL is considered prediabetes. Between August 2017 to December 2019, 131 patients were identified and 100 met the criteria for inclusion. The study was approved by the Institutional Review Board. A single individual abstracted the data which included demographic data, BMI, comorbidities, random glucose levels prior to therapy and whether they received treatment for the elevations in blood glucose. Results: A total of 131 charts were reviewed, but 31 were excluded because 2 were male, 13 had type 2 diabetes at diagnosis, and 16 had metastatic disease. The median age of the 100 patients was 53 years (range 31 to 82 years); 45% were White/Non-Hispanic, 28% Hispanic, 18% Asian, 5% African American, 1% were Native Hawaiian or other Pacific Islander, 2% were unknown, and 1% were of mixed race. Prediabetic random glucose levels were recorded in 30% of patients and 23% had levels consistent with a diagnosis of diabetes. Out of the patients who exhibited a blood glucose above 200, 16 out of the 23 patients were White, 6 of them were Hispanic and 1 was Asian. The average BMI was 27.7. The average BMI of patients who exhibited a blood glucose of over 200 mg/dL was 28.85 and the average of those who had a blood glucose of over 150 mg/dL was 27.56. Conclusions: Diabetes and prediabetes were unmasked by taking the premedication with dexamethasone in 53% of women undergoing (neo)adjuvant docetaxel or paclitaxel. Current guidelines do not recommend additional blood work after completion of active treatment. Given our results, it is important that medical oncologist ensure that patients with elevations in random glucose be referred for appropriate endocrine workup and therapy, including lifestyle modifications.