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  • 1
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    Abstract 2009: Flow cytometric analysis, sorting and molecular analysis of dissociated cells from human solid tumors derived from PDX mouse models
    American Association for Cancer Research (AACR) ; 2015
    In:  Cancer Research Vol. 75, No. 15_Supplement ( 2015-08-01), p. 2009-2009
    Details
    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
    URL: Article
    DOI: 10.1158/1538-7445.AM2015-2009
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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  • 2
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    Abstract 3949: Deep immunophenotyping using flow cytometry of dissociated cells from Barrett's esophagus and matched adjacent squamous epithelium defines distinct phenotypic clusters
    American Association for Cancer Research (AACR) ; 2017
    In:  Cancer Research Vol. 77, No. 13_Supplement ( 2017-07-01), p. 3949-3949
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 3949-3949
    Abstract: Barrett's esophagus (BE) is defined as metaplasia of the squamous epithelium to a specialized columnar epithelium with risk factors of gastroesophageal reflux and obesity and a predilection for middle-age and older white males. BE progresses through stages of dysplasia (low-grade and high-grade) before developing into esophageal adenocarcinoma. Challenges remain in early detection and predicting which patients may progress to dysplasia. Here we describe a method by which we compare human clinical IRB-approved BE biopsies and adjacent normal squamous epithelium using tissue dissociation and deep immunophenotyping by flow cytometric collection and analysis. A cassette of canonical epithelial or tumor stem cell-associated targets (EpCAM, CD24, CD44, CD49f, Her2/neu, CD133, CD90, CD166, and CD29), immune cell markers (CD3, CD45, CD127, HLA-DR, CD16, CD56, CD4, CD8, CD25, and CD19), as well as targets associated with myeloid derived suppressor cells (CD14, CD15, CD33, CD11b, HLA-DR, CD31 and CD86) were used to discern differences across subjects and between cellular compartments in normal and BE tissue. The Barrett’s samples show a majority population with a characteristic phenotype (EpCAM+CD133lowCD49fhigh) when compared with normal squamous tissue samples (EpCAM-CD133-CD49flow). The samples separate into two discrete groups using hierarchical clustering based on differential surface marker expression of combined epithelial and immune cell markers, but also reveal unexpected, shared phenotypes for some normal and BE samples. Principal component analysis supports this grouping and was used to identify more compelling targets for categorization, such as CD133 and CD49f. The resulting expression and distribution of targets offer a phenotypic fingerprint characterizing both the epithelial cell and immune cell compartment. Besides providing the potential for revealing clinically relevant differences between BE and normal tissue, as well as across subjects, the discovered surface immunophenotypes can be used to target specific subpopulations from dysplastic tissue for further molecular investigation. A deeper understanding of the role of such specific subpopulations should increase the prospects for more complete understanding of BE and its progression. Citation Format: Friedrich G. Hahn, Eileen Snowden, Warren Porter, Mitchell Ferguson, William S. Dillmore, Stephanie S. Yee, Taylor Black, Maureen DeMarshall, Aaron Middlebrook, Smita Ghanekar, Anil Rustgi, Erica L. Carpenter, Rainer Blaesius. Deep immunophenotyping using flow cytometry of dissociated cells from Barrett's esophagus and matched adjacent squamous epithelium defines distinct phenotypic clusters [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3949. doi:10.1158/1538-7445.AM2017-3949
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2017-3949
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 3
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    Abstract B11: Deep phenotyping of dissociated cells from PDX model solid tumors and human breast tumors using flow cytometry
    American Association for Cancer Research (AACR) ; 2015
    In:  Molecular Cancer Therapeutics Vol. 14, No. 12_Supplement_2 ( 2015-12-01), p. B11-B11
    Details
    In: Molecular Cancer Therapeutics, American Association for Cancer Research (AACR), Vol. 14, No. 12_Supplement_2 ( 2015-12-01), p. B11-B11
    Abstract: The model of solid tumors as monolithic entities under the control of a handful of driver genes which seemed to dominate the general perception of cancer for many years is increasingly being replaced by that of highly diverse ecosystems of cells. Multiple tumor subpopulations, as well as attending non-cancerous cells such as fibroblasts, endothelial cells, and cells from the immune compartment populate this ecosystem, communicate with each other and all influence clinically relevant decision points throughout tumorigenesis. Progress in analyzing and characterizing this highly heterogeneous, complex “society of cells” has been remarkably enhanced using the strengths of flow cytometry. A rather comprehensive characterization of individual cells within a population, known as deep phenotyping, is becoming possible with recent advances in multi-parametric staining, collection, and analysis of solid tissue derived cells. This technology is enabling researchers to identify multiple targets within a single sample more efficiently than with more traditional methods. We have developed a process whereby single cells are liberated from solid tumors through a combination of mechanical and enzymatic treatments and then interrogated by flow cytometry using deep phenotyping. Our chosen marker panels include targets (CD24, CD44, CD49f, EpCAM, CD166, CD133, CD184, HER2/Neu) which have been used to investigate properties relevant for cancer stem cells (CSC), Endothelial Mesenchymal Transition (EMT) and Tumor Microenvironmental (TME) processes but options are built into the design to accommodate less well characterized targets such as GD2, CD73, Notch receptors, EphB2, and c-Met. We have identified discrete subpopulations in breast cancer patient-derived xenograft (PDX) tumors in mice, demonstrating consistent and reproducible results which constitute a distinct immunophenotypic fingerprint for every model. Building on the experience with PDX derived biopsies and adding markers targeting the immune system we applied our work flow to clinical breast cancer tissue. Our results demonstrate that the multi-dimensional analyses enabled by a surface marker panel reveals differences in highly characterized subpopulations, some at less than 1% of the total population, that remain hidden by more conventional assessment methods. Citation Format: Friedrich Hahn, Eileen Snowden, Warren Porter, Mitchell Ferguson, Shannon Dillmore, Aaron Middlebrook, Shahryar Niknam, Peter Llontop, Smita Ghanekar, Rainer Blaesius. Deep phenotyping of dissociated cells from PDX model solid tumors and human breast tumors using flow cytometry. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr B11.
    Type of Medium: Online Resource
    ISSN: 1535-7163 , 1538-8514
    URL: Article
    DOI: 10.1158/1535-7163.TARG-15-B11
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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    SSG: 12
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  • 4
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    Immunophenotyping and Transcriptomic Outcomes in PDX-Derived TNBC Tissue
    American Association for Cancer Research (AACR) ; 2017
    In:  Molecular Cancer Research Vol. 15, No. 4 ( 2017-04-01), p. 429-438
    Details
    In: Molecular Cancer Research, American Association for Cancer Research (AACR), Vol. 15, No. 4 ( 2017-04-01), p. 429-438
    Abstract: Cancer tissue functions as an ecosystem of a diverse set of cells that interact in a complex tumor microenvironment. Genomic tools applied to biopsies in bulk fail to account for this tumor heterogeneity, whereas single-cell imaging methods limit the number of cells which can be assessed or are very resource intensive. The current study presents methods based on flow cytometric analysis and cell sorting using known cell surface markers (CXCR4/CD184, CD24, THY1/CD90) to identify and interrogate distinct groups of cells in triple-negative breast cancer clinical biopsy specimens from patient-derived xenograft (PDX) models. The results demonstrate that flow cytometric analysis allows a relevant subgrouping of cancer tissue and that sorting of these subgroups provides insights into cancer cell populations with unique, reproducible, and functionally divergent gene expression profiles. The discovery of a drug resistance signature implies that uncovering the functional interaction between these populations will lead to deeper understanding of cancer progression and drug response. Implications: PDX-derived human breast cancer tissue was investigated at the single-cell level, and cell subpopulations defined by surface markers were identified which suggest specific roles for distinct cellular compartments within a solid tumor. Mol Cancer Res; 15(4); 429–38. ©2016 AACR.
    Type of Medium: Online Resource
    ISSN: 1541-7786 , 1557-3125
    URL: Article
    DOI: 10.1158/1541-7786.MCR-16-0286-T
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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    SSG: 12
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  • 5
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    Abstract 2391: Flow cytometric sorting of subpopulations followed by RNASeq reveals distinct phenotypes in PDX model of basal breast cancer
    American Association for Cancer Research (AACR) ; 2016
    In:  Cancer Research Vol. 76, No. 14_Supplement ( 2016-07-15), p. 2391-2391
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 2391-2391
    Abstract: The recognition of tumor tissue as an interactive ecosystem of distinct cell types has recently emerged as a very promising basis for more successful treatment of cancer patients. While intratumor heterogeneity (ITH) as a phenomenon has been known for decades it is only recent that its functional significance can be investigated with effective tools. Starting with a correlation of cellular heterogeneity with aggressiveness, metastatic potential and drug susceptibility of a cancerous lesion the current focus on functional differences between various tumor cell compartments is revealing a number of distinct functions and interactions. The discovery of communication between various tumor cells through soluble factors as well as differences in implantation of homogeneous vs. heterogeneous cell populations into immune compromised mouse models suggest a “division of labor” among cell types within many tumor tissues. We have investigated the surface marker distribution of more than 8 different PDX tumor models by flow cytometry and detected extensive immunophenotypic heterogeneity. Using a range of markers associated with cancer stem cells, EMT and invasiveness (e.g. CD 24, 44, 133, 184, 326 (EpCAM), and CD45) we find heterogeneity with respect to many surface markers as well as individual immunophenotypic signatures for each model. Building on this characterization we chose several markers for sorting of subpopulations and performed gene expression analysis. Transcriptome analysis of a breast cancer model revealed two phenotypic signatures which suggest a strong proliferative population alongside a second population which is far less proliferative but much more active in angiogenesis, ECM organization and secretion of various soluble factors. This observation suggests a very clear example of distinct roles of multiple cell types to form a tumor tissue. Our findings could have implications for therapeutic strategies directed at more than one cell type as well as development of better diagnostic tools which take into account the presence of various phenotypically distinct cell populations. Citation Format: Warren Porter, Friedrich Hahn, Eileen Snowden, Mitchell Ferguson, Frances Tong, Shannon Dillmore, Joel S. Parker, Aaron Middlebrook, Smita Ghanekar, Rainer Blaesius. Flow cytometric sorting of subpopulations followed by RNASeq reveals distinct phenotypes in PDX model of basal breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2391.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2016-2391
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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  • 6
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    Abstract A198: Flow cytometric analysis and sorting of dissociated cells from human solid tumors derived from PDX mouse models.
    American Association for Cancer Research (AACR) ; 2013
    In:  Molecular Cancer Therapeutics Vol. 12, No. 11_Supplement ( 2013-11-01), p. A198-A198
    Details
    In: Molecular Cancer Therapeutics, American Association for Cancer Research (AACR), Vol. 12, No. 11_Supplement ( 2013-11-01), p. A198-A198
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1535-7163 , 1538-8514
    URL: Article
    DOI: 10.1158/1535-7163.TARG-13-A198
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2013
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    SSG: 12
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  • 7
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    Abstract B37: Phenotypic analysis of single cells dissociated from solid tumors
    American Association for Cancer Research (AACR) ; 2015
    In:  Cancer Research Vol. 75, No. 1_Supplement ( 2015-01-01), p. B37-B37
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 1_Supplement ( 2015-01-01), p. B37-B37
    Abstract: Current methods for solid tumor analysis may be inadequate for addressing both the heterogeneity of tumor cells and the components of the tumor microenvironment. Comprehensive analysis requires the ability to analyze tumor biopsy specimens at the single-cell level. A better understanding of how the tumors are behaving at a cellular level, in relation to the other cells within the tumor microenvironment, could lead to more accurate and specific treatment, and better patient prognosis. Evaluation of tumor derived single cells by flow cytometry could provide unique information that is not readily obtained from current methods. Here we demonstrate the single-cell analysis of solid tumors from breast and colorectal cancers. Since single-cell analysis of solid tumors may not occur at the collection site, it is important that tumors be preserved in order to retain their characteristics during transport. Using tumors from PDX mouse models, and human samples, different preservatives were evaluated for their effects on cellular viability and surface marker expression. Following shipment of the tumor samples in preservation solutions, the solid tumors were dissociated into single-cell suspensions using enzyme cocktails containing collagenase. Phenotypic evaluation was performed using flow cytometry after staining the single cells with monoclonal antibody panels specific for either tumor or immune cells. The results indicate that the dissociation method did not seem to adversely impact the expression of surface proteins. We demonstrate that it is feasible to analyze dissociated tumor cell populations with relevant surface markers. Analysis of the data revealed distinct phenotype patterns for single cells dissociated from breast and colorectal cancers. Further extensive evaluation of heterogeneity in these tumor types could reveal phenotypic signatures that may be clinically relevant. Citation Format: Joyce J. Ruitenberg, Aaron Middlebrook, Maria Suni, Friedrich Hahn, Eileen Snowden, Warren Porter, Mitchell Ferguson, Rainer Blaesius, Smita A. Ghanekar. Phenotypic analysis of single cells dissociated from solid tumors. [abstract]. In: Abstracts: AACR Special Conference on Cellular Heterogeneity in the Tumor Microenvironment; 2014 Feb 26-Mar 1; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(1 Suppl):Abstract nr B37. doi:10.1158/1538-7445.CHTME14-B37
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.CHTME14-B37
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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