In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 15_Supplement ( 2015-08-01), p. 2009-2009
Abstract:
Functional and genetic heterogeneity in tumor tissue has been a well described phenomenon for many decades but only recently emerged as a potentially crucial contributor to cancer development and progression. The correlation between cellular heterogeneity and aggressiveness, metastatic potential and drug susceptibility of a cancerous lesion have led to models in which the existence of multiple clonal cell lineages is a central feature enabling a neoplastic lesion to overcome selective pressures caused by the surrounding tissues’ defensive capabilities as well as therapeutic interventions. In addition, the role of the tumor microenvironment as an integral part of tumorigenesis was recognized and infiltrating leukocytes or tumor associated fibroblasts are no longer viewed as mere contaminants of a solid tumor biopsy. The emerging picture is 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 an integrated workflow for dissociation and flow cytometric analysis and sorting for multiple downstream analysis modalities. Using patient derived xenograft (PDX) mouse models derived from primary human breast cancer biopsies we have demonstrated the ability to identify distinct immunophenotypes for each model and use this analysis to isolate distinct subpopulations. Our successful optimization of a variety of well characterized surface markers (e.g. CD 24, 44, 133, 184, 326 (EpCAM), and CD45) provides a basis for effective fingerprinting of cancer cells from a variety of sources. In an effort to demonstrate the potential of FACS sorting of solid tumor derived cell populations we have interrogated sorted fractions by NGS as well as RT-PCR array analysis and show distinct genotypic as well as gene expression signatures for each subgroup. The evidence provided by our data suggests that the single cell focused approach flow cytometry has traditionally enabled in hematological cancers is accessible for solid tumors as well and may unlock valuable biological insights. Citation Format: Rainer Blaesius, Friedrich Hahn, Eileen Snowden, Warren Porter, Mitchell Ferguson, Frances Tong, Stewart Jurgensen, Chang Chen, Daphne Clancy, Jamal Sirriyah, John Alianti, Perry Haaland, Shannon Dillmore, Jeff Baker, Aaron Middlebrook, Joyce Ruitenberg, Maria Suni, Smita Ghanekar. Flow cytometric analysis, sorting and molecular analysis of dissociated cells from human solid tumors derived from PDX mouse models. [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 2009. doi:10.1158/1538-7445.AM2015-2009
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2015-2009
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2015
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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