Abstract A198: Flow cytometric analysis and sorting of dissociated cells from human solid tumors derived from PDX mouse models.
Authors: Blaesius Rainer , Hahn Friedrich , Snowden Eileen , Porter Warren , Ferguson Mitchell , Marmura Tina , Tong Frances , Dillmore Shannon , Middlebrook Aaron , Ruitenberg Joyce , Suni Maria , Ghanekar Smita 
Published: August 2014

Functional and genetic heterogeneity in tumor tissue was first observed over 50 years ago. Today, tumor heterogeneity is frequently evoked in describing the pathway from pre-cancerous lesions to aggressive, metastatic cancer. During this progression, multiple clonal lineages are thought to arise, leading to subpopulations of the tumor showing different metastatic profiles and susceptibility to anti-cancer therapy. In addition, the role of the tumor microenvironment became recognized and infiltrating leukocytes or tumor associated fibroblasts are no longer viewed as mere contaminants of a solid tumor biopsy. The emerging picture is increasingly compared to macroscopic ecosystems and a detailed understanding of the interactions between numerous cell subgroups seems necessary for the complete understanding of cancer pathogenesis. Scarcity of appropriate tools and model systems are an obstacle to the investigation of this heterogeneity at a molecular level but advances over the last few years have led to a significant acceleration in this field. More sensitive and far cheaper methods for collection of genomic and transcriptomic data have revealed a complex picture of the evolution of individual solid tumors. To turn this deeper understanding of tumorigenesis into improved clinical outcomes, routine methods are required to separate complex tumors into subpopulations. This stratification will provide a more comprehensive characterization of the tumor and enable more detailed prediction of disease progression and resistance development.

We have developed dissociation methods for solid tumor tissue which allows flow cytometric analysis as well as sorting to provide cells for multiple downstream analysis modalities. Using patient derived xenograft (PDX) mouse models derived from primary human breast, colorectal and lung cancer biopsies we have demonstrated efficient dissociation, surface marker analysis and nucleic acid purification from sorted populations. Conditions have been optimized for a range of relevant surface markers (e.g. CD 24, 44, 133, 184, 326 (EpCAM), and CD45) which are suitable to identify cells predicted to have stem cell, endothelial, epithelial or immune cell functions, respectively. Through sequencing of subpopulations identified by their phenotype we have demonstrated the compatibility of our workflow with downstream analysis methods such as Next Generation Sequencing (NGS). Our RNA stability measurements suggest that gene expression analysis is equally feasible. Our data provide a standardized basis for in depth investigation of subpopulations of cells from solid tumors with various molecular techniques.

Citation Information: Mol Cancer Ther 2013;12(11 Suppl):A198.

Citation Format: Rainer Blaesius, Friedrich Hahn, Eileen Snowden, Warren Porter, Mitchell Ferguson, Tina Marmura, Frances Tong, Shannon Dillmore, Aaron Middlebrook, Joyce Ruitenberg, Maria Suni, Smita Ghanekar. Flow cytometric analysis and sorting of dissociated cells from human solid tumors derived from PDX mouse models. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr A198.