Abstract 4834: Single cell multiplex gene expression analysis to unravel heterogeneity of PDX samples established from tumors of breast cancer patients with different ethnicity

Abstract

Abstract Intra-tumor heterogeneity represents one of the main challenges in cancer therapeutics. This heterogeneity is generated at the genetic level primarily by genomic alterations and clonal selection and at the epigenetic level by tumor cell differentiation. In addition, inter-tumor heterogeneities may also be related to differences in tumor biology in different ethnic populations. To explore the cell heterogeneity in breast cancer, we studied patient derived xenograft (PDX) models generated from African (Ghana), African-American, and Caucasian breast cancer patients. Gene expression of a selected panel of cancer associated genes was determined in single cells using C1 and BioMark HD platforms. Analyzed multiplex RT-qPCR data revealed significant heterogeneity in mRNA expression within and between studied PDX samples at single cell resolution. We observed a significantly different mRNA expression profile within each ethnic group of breast cancer PDX samples. In addition, distinct gene expression signatures were observed between the PDX samples of different ethnic origin. ALDH1a1, ALDH1a3, CD44, CD24, and CD133 were among the CSC markers that were differentially expressed in different PDX single cell samples. Vimentin, EpCAM, HER2, CDH1, CDH2, TGFb1, cytokeratins, GATA3 and MKI67 genes related to the epithelial to mesenchymal (EMT) and mesenchymal to epithelial (MET) phenotypes also demonstrated significantly variable expression in the studied PDX samples. YAP1, TM4SF1, TSPAN6, AMOTL2, STAP2 and ANXA3 genes were differentially expressed in the PDX samples. These candidate biomarkers represent a collection of genes that may warrant further investigation for their potential involvement in cancer initiation, promotion and progression to metastasis, and drug resistance. These data emphasize the importance of studying tumors at single cell resolution to unravel gene expression variation. Upon validation in clinical tumor specimens, this approach could help to identify cellular subpopulations within tumors and possibly identify novel targets for cancer therapy. Citation Format: Ebrahim Azizi, Evelyn M. Jiagge, Shamileh Fouladdel, Shukmei Wong, Michele L. Dziubinski, Mary Sehl, Anahita Kyani, Jun Li, Hui Jiang, Tahra K. Luther, Shawn G. Clouthier, Sean P. McDermott, John Carpten, Lisa A. Newman, Sofia D. Merajver, Max S. Wicha. Single cell multiplex gene expression analysis to unravel heterogeneity of PDX samples established from tumors of breast cancer patients with different ethnicity. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4834. doi:10.1158/1538-7445.AM2015-4834