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Cancer immunotherapies have the potential to induce durable anti-tumor immune responses; however the efficacy of these treatments varies among patients and partially depends on the complex interplay between malignant cells and non-malignant cells within the tumor microenvironment. In the tumor microenvironment, T cells play a crucial role in eliminating tumor cells and orchestrating anti-tumor immune responses; in contrast immunosuppressive cell types such as myeloid-derived suppressor cells can support tumor progression. Here we harnessed recent advances in single-cell multiomics that allow high-resolution functional characterization of intratumoral immune cells to improve our understanding of their dynamic relationships. Specifically, we utilized a One Solution Workflow to dissociate a solid tumor followed by in-depth dissection of the immune composition of the tumor microenvironment using both flow cytometry and the BD Rhapsody™ Single-Cell Analysis System. We characterized the cellular composition of tumor microenvironment using flow cytometry analysis. Importantly, by examining the expression of mRNA and surface protein markers at single-cell resolution, we unraveled the complexities of the tumor microenvironment, elucidated cellular heterogeneity and identified cell-type specific gene signatures. We propose this One Solution Workflow can be adopted to understand the transcriptional and proteomic phenotypes of tumor infiltrating leukocytes for development of novel immune therapeutic strategies for cancer. For Research Use Only. Not for use in diagnostic or therapeutic procedures. Class 1 Laser Product.BD-23279 (v1.0) 1120BD, the BD Logo and Rhapsody are trademarks of Becton, Dickinson and Company or its affiliates. © 2020 BD. All rights reserved. Citation Format: Xiaoshan Shi, Margaret Nakamoto, Aaron Middlebrook, Wei Huang, Evelyn Lo, Patrick T. Neuhoefer, Scott Bornheimer, Smita Ghanekar. Deep characterization of tumor infiltrating leukocytes using a combination of flow cytometry and single-cell multiomics [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 2788.

Hematopoietic stem and progenitor cells (HSPCs) can generate a diversity of blood cells throughout the human lifespan. Although these cells have been evaluated using both sorted (Corces et al. Nat. Genet. 2016) and single cell assays (Pellin et al Nat. Commun. 2019), there remains uncertainty in the degree of heterogeneity within HSPC subpopulations and their associated differentiation trajectories. The phenotypic diversity within HSPCs needs to be better characterized in order to understand the pathogenesis of blood disorders including hematologic malignancies. To address this need, we characterized healthy bone marrow mononuclear cells (BMMCs) with whole transcriptome analysis (WTA) and surface marker evaluation. We hypothesized that by utilizing concurrent RNA and surface marker analysis (n=35), we can improve HSPC clustering and characterize specific phenotypic states along unique hematopoietic differentiation trajectories. Three healthy BMMC samples were stained with antibody conjugated oligonucleotides (BD® Abseq) and analyzed using BD Rhapsody™. We filtered 8,070 high quality cells for 2,508 HSPCs, myeloid cells, and lymphocyte precursors. The antibody-derived tags (ADTs) obtained from BD® Abseq comprised 33 of the most informative features (n=2000) and resulted in more stable clustering as determined by within sum of squares (WSS = 898 verses 934 for WTA alone for 20 clusters). Additionally, we designed a targeted HSPC panel (n=500 genes) with BD® Abseq which identified similar cell clusters compared to the WTA alone and WTA plus ADT data (rand index = 0.88). HSPC clustering identified putative hematopoietic stem cell (HSC), common myeloid progenitor (CMP), and megakaryocyte-erythroid progenitor (MEP) clusters that expressed canonical surface markers. Of interest, we identified candidate novel myeloid, T-cell, and B-cell primed precursors and new surface marker expression gradients that align with specific differentiation trajectories. The results of this analysis will be presented. The HSPC clusters were converted into a signature matrix using Cibersortx (Newman et al. Nat. Biotechnol. 2019), and bulk acute myeloid leukemia (AML) and healthy samples were deconvolved into respective healthy cell clusters. We subsequently performed multivariate Cox proportional hazard analysis, and observed that high levels of healthy cluster 8 (H8; HR 3.40, 95% confidence interval 1.24-9.34), the candidate lymphoid-primed multipotent progenitor (LMPP), and low levels of healthy cluster 6 (H6; HR 0.26, 95% confidence interval 0.12-0.58), a candidate erythrocyte precursor, at diagnosis were associated with worse overall survival. Deconvolution using sorted healthy sub-populations (Corces et al. Nat. Genet. 2016) only identified erythrocyte precursors as statistically relevant (HR 0.27, 95% confidence interval 0.12-0.61). Of note, H8 had a distinct gene expression profile compared to that identified for the sorted LMPP sub-population using differential gene expression analysis. In summary, we identified novel cell type clusters and surface marker associations using combined single cell WTA and surface marker analysis (BD® Abseq). We were able to correlate cell types with both canonical and novel surface markers, and deconvolution analysis provided preliminary insights into their clinical relevance in AML. Citation Format: Asiri Ediriwickrema, Sreejith Ramakrishnan, Margaret Nakamoto, Smita Ghanekar, Bogdan Luca, Aaron Newman, Andrew Gentles, Ravindra Majeti. Multiomic single cell analysis of normal human bone marrow identifies a unique stem and progenitor population that expands in AML [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3779.

Cancer treatment has been revolutionized with the development of immunomodulatory therapies. These therapies have primarily focused on enhancing T-cell responses: whether it is unleashing T cells through blockade of regulatory checkpoint inhibitors or generation of chimeric antigen receptor (CAR) T cells. However, there has been recent interest in harnessing the immunotherapeutic potential of other cytotoxic cells such as Natural Killer (NK) cells. Similar to NK cells, innate lymphoid cells (ILCs) may offer another target of these immunotherapy approaches. Before the potential of these cells can be realized, there is a need for better understanding of these recently described cell populations. ILCs act as the immune system's first responders and have been shown to play a key role in tissue homeostasis, chronic inflammation and cancer. Three main groups of non-cytotoxic ILCs (ILC1, ILC2 and ILC3) have been broadly defined based on developmental trajectories and function, driven by expression of specific transcription factors. Deeper characterization of these cells through either high parameter protein analysis or single-cell RNA sequencing has revealed a more complex and heterogeneous nature of ILCs across different tissues and donors. Therefore, the identity of ILCs is still elusive and controversial. In this study, we developed a comprehensive approach to further refine the signatures of human circulating ILC subsets. Total ILCs (Lineage- CD127+ cells) were enriched from 4 normal donors by flow sorting using the BD FACSAria™ Fusion cell sorter and processed for downstream single-cell multiomic characterization. BD® AbSeq reagents and a targeted BD Rhapsody™ Immune Response Panel were used to enable simultaneous detection of 42 proteins and 399 genes using the BD Rhapsody™ Single-Cell Analysis System. Differential protein and gene expression analysis in addition to combinatorial expression of CD294 and CD117 confirmed 3 conventional ILC populations as well as the signatures of three distinct subsets within ILC1. This discovery approach provided information about relative expression of a small selection of proteins or surface marker-coding genes that enable the discrimination of these ILC subsets. These data were used to design high-parameter flow cytometry panels for high-throughput analysis of different healthy donors. ILC subsets differentially distributed across donors were detected and defined using unsupervised computational analysis confirming the result of multiomic analysis, while the functional and biological relevance of the identified subsets remains to be assessed. For Research Use Only. Not for use in diagnostic or therapeutic procedures. Class 1 laser product. BD, the BD Logo, FACSymphony and Rhapsody are trademarks of Becton, Dickinson and Company or its affiliates. © 2019 BD. All rights reserved. Citation Format: Aaron J. Tyznik, Mirko Corselli, Gisle V. Baracho, Chip Lomas, Silin Sa, Stephanie Widmann, Suraj Saksena, Smita Ghanekar. Resolving the heterogeneity of human circulating innate lymphoid cells via simultaneous, high-dimensional analysis of protein and gene expression [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3310.

Single cell multiomic (scM) methods are powerful tools to characterize patient-specific tumor-immune microenvironment, but current methods of sample handling and preparation can introduce bias. Obtaining non-biased results is particularly important in studies to identify new biomarkers for patient stratification of responders versus non-responders for immunotherapies in oncology. This problem is becoming acute as the number of immune-therapy modalities and combinations in clinical trials and in medical practice continue to expand. Current methodologies used to analyze patient specimens in routine pathology are not adequate to address heterogeneity and complexity of immune cell ecosystem of individuals. SCM analysis of immune cells from tumor microenvironment using technologies that allow high parameter analysis of genes and proteins will allow a comprehensive atlas of immune cells in the tumor tissue, however the quality of single cell sample preparation is critical. Here, we report evaluation of several available solid tumor dissociation methods, including mechanical dissociation by scalpel, BD™ Medimachine System, Miltenyi gentleMACS™ dissociator. Mechanical dissociation was followed by enzymatic dissociation using BD Horizon™ Dri Tumor & Tissue Dissociation Reagent or, in the case of gentleMACS™, the Miltenyi Tumor Dissociation Kit. Metrics evaluated were cell recovery, viability, and proportion of various cell lineage populations using flow cytometry; and expression of 399 mRNA transcripts and 31 proteins using single cell multiomics (BD Rhapsody™, BD Rhapsody™ Immune Response Targeted Panel, and BD™ AbSeq). Tumor tissues were from a mouse a pancreatic (PDAC) tumor model and humanized Patient-Derived Xenograft (PDX; from Onco-hu® mice) models of colon and lung cancer. Method dependent differences in viable cell yield and proportions of immune vs. tumor cells were observed. SCM analysis of FACS sorted CD45+ tumor-infiltrating lymphocytes (TILs) showed differences in gene and protein expression profiles, particularly for expression of rare vs. abundant genes depending on the dissociation method. Our data identify protocols to interrogate tumor immune microenvironment starting from tumor tissue specimen through scM all the way to informatics analysis with consistent results. Similar studies and further optimization are recommended for other tumor types. Consistent adoption of standardized protocols will enable robust findings in research and clinical trials, with the ultimate goal of improved therapies, biomarkers and outcomes. For Research Use Only. Not for use in diagnostic or therapeutic procedures. GentleMACS™ is trademark of Miltenyi Biotec. Onco-hu® is a registered trademark of The Jackson Laboratory. BD, the BD Logo, Horizon, Medimachine, and Rhapsody are trademarks of Becton, Dickinson and Company or its affiliates. © 2019 BD. All rights reserved. Citation Format: Aaron J. Middlebrook, Wei Huang, Margaret Nakamoto, Xiaoshan Shi, Evelyn Lo, Patrick Neuhoefer, Scott Bornheimer, Smita Ghanekar. Improving sample preparation workflows for single cell multiomic analysis of infiltrating leukocytes from solid tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6197.

e15245 Background: Single cell multiomics analysis of tumor cells and tumor infiltrating immune cells using high parameter flow cytometry and single cell genomics technologies is a powerful approach in the investigation of tumor biology and in the discovery of new drug targets and biomarkers. The preparation of single cells from solid tumor samples often involves a physical dissociation step in combination with an enzymatic digestion step. Methods: The effect of the tumor cell dissociation process on the phenotypic properties of single cells isolated from solid tumor samples were analyzed using a 12-color reagent panel on the BD FACSLyric flow cytometer. Specifically, spontaneous pancreatic tumor samples from genetically modified mice were processed using a manual dissociation process with a scalpel blade as well as an integrated tumor sample dissociation process with the prototype Singulator instrument with various protocol settings. The BD Horizon Dri Tumor & Tissue Dissociation Reagent (TTDR) reagent was used for the enzymatic step in all sample preparations. The yield, viability, and frequency of tumor cells and different subsets of leukocytes were measured for each tumor-derived single cell sample preparation. On the Singulator system, cell yield reached a plateau with highest viability at the 30-min process time and a higher percentage of tumor cells was obtained compared to the manual sample processing method. Results: The relative frequencies of T cells, B cells, myeloid cells and macrophages also changed in different sample preparation methods. However, the spatial heterogeneity in the tumor section and cell composition may contribute to these differences and would require more in-depth analysis. In summary, these results suggest that there are many variables in the tumor sample single cell dissociation process that could impact the downstream study results, particularly for multiomics studies. Conclusions: This study highlights the need for optimization and standardization of the sample processing methodologies for downstream analysis. Disclaimers: For Research Use Only. Not for use in diagnostic or therapeutic procedures. Class 1 Laser Product. BD, the BD Logo, FACSLyric, and Horizon are trademarks of Becton, Dickinson and Company. © 2020 BD and its subsidiaries. All rights reserved.

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.

The heterogeneous nature of solid tumors, coupled with the relatively small sample size of available biopsies, has led to an emerging need to glean as much information as possible from these valuable specimens. Current approaches to solid tumor analysis fail to completely reveal the diverse range of cellular compartments that comprise the tumor microenvironment. A comprehensive approach to tumor interrogation requires efficient tissue dissociation to facilitate analysis at the single-cell level. In contrast to current methods, single-cell analysis of tumor derived cell suspensions by flow cytometry has the potential to provide a more complete understanding of the many subpopulations within the tumor microenvironment and the cell to cell interactions that govern this space. In order to prepare a cell suspension from solid tumor tissue, most investigators subject the tumor sample to a combination of mechanical and enzymatic dissociation modalities. Regardless of the combination of enzymes used for dissociation, there exists a degree of non-specific proteolytic cleavage. In the work presented here, we set out to quantify the non-specific cleavage associated with a proprietary enzyme mixture developed for tumor dissociation. Using a mixed sample that included peripheral blood mononuclear cells and several cell lines, we were able to generate a sample that expressed approximately 90% of our current antibody catalog. By staining our sample with a rudimentary 3 color panel, we were able to identify 10 individual cell populations based on marker expression and/or scatter. This composite sample was left untreated or exposed to our propriety mixture of dissociation enzymes and then subsequently screened for all 251 antigens in our catalog. The impact of non-specific proteolytic cleavage on surface marker detection was gauged in terms of median fluorescence intensity of positive population and stain index. Our results indicate that of the 251 surface markers tested in our experimental series, less than 10 percent were significantly affected by enzymatic digestion. Of those markers that were affected only a fraction of them were affected to such an extent that it was impossible to detect positive expression. These results underscore the importance of understanding the factors that can influence surface marker detection and bolster our confidence that this particular mixture of enzymes is imparting minimal impact on surface marker detection. Citation Format: Aaron J. Middlebrook, Caitlin Austin, Daniel Santos, Eileen Snowden, Warren Porter, Friedrich Hahn, Mitchell Ferguson, Rainer Blaesius, Smita Ghanekar. The effects of enzymatic digestion on epitope detection by flow cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2113.

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

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.

Cell migration occurs during physiological and pathological processes, which include wound healing and tumor metastasis. In vitro migration assays are necessary to understand the mechanism underlying cell migration and also to identify inhibitory or stimulatory molecules. The Boyden chamber assay is commonly used to measure cell motility in vitro where the number of cells that migrate through the transwell membrane is quantitated manually using an inverted microscope. Alternatively, cells can be detached from the membrane and stained with a fluorescent probe, prior to counting cells using a plate reader. These conventional assays are limited by an inability to simultaneously characterize individual cells while monitoring migration. To address this, we have developed a multi-parameter flow cytometry-based migration assay for the quantitative measurement of cell migration and simultaneous immunophenotypic analysis of the migrated cells. Invasive HT-1080 and non-invasive MCF-7 cancer cell lines were plated in the upper layer of a cell permeable membrane, as per the standard Boyden chamber assay. BD Horizon™ Fixable Viability Stain (FVS) was used to determine the optimal detachment conditions providing maximum yield with minimal impact on cell viability. Migrated cells were also co-stained with multiple conjugated antibodies to assess cell surface marker expression. Cells were analyzed on BD Accuri™ flow cytometer for rapid quantitation of migrated cells and analysis of up to 4 parameters. Alternatively, BD FACSCelesta™ flow cytometer was used for higher parameter analysis. Migrated cells were identified based on light scatter properties and viability staining with FVS, while immunophenotype was assessed in live cells. Our results demonstrate that this flow cytometric assay can be used to rapidly quantify changes in the migratory ability of different cell lines in the presence of inhibitors or stimulators. Additionally, we were able to assess the expression of hallmark cancer cell markers (CD44, CD24, CD326 (EpCAM)) before and after migration. The ability to quantify the number of migrating cells in response to specific stimuli and to simultaneously define cell immunophenotype represents a significant advancement, as compared to conventional cell motility assays. Our results demonstrate that this novel approach allows for a deeper analysis of cell migration that could enable complex drug discovery studies and the discovery of new cell signatures associated with metastatic progression. Citation Format: Mirko Corselli, Xiao Wang, Lissette Wilensky, Aaron Middlebrook, Smita Ghanekar, Jacob Rabenstein, Nil Emre. A quantitative and multi-parameter flow cytometry assay to simultaneously assess cell migration and immunophenotype. [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 5082.

Exploring tumor heterogeneity with the goal of improving outcome has led to the need to glean as much information as possible at an individual cell level from these valuable specimens. Traditional approaches to solid tumor analyses fail to reveal the diverse range of cellular compartments beyond tumor cells that comprise the tumor microenvironment. A comprehensive approach to tumor interrogation requires efficient tissue dissociation to facilitate analysis at the single-cell level. Compared to current methods, single-cell analysis of tumor derived cell suspensions by flow cytometry has the potential to provide a more thorough understanding of the many subpopulations within the tumor microenvironment and the cell-to-cell interactions that govern this space. Here, we demonstrate an efficient workflow that enables comprehensive cell analysis of solid tumors from breast cancers. After dissociating human breast cancer biopsies from primary tumors into cell suspension, we analyzed the immune compartment and the cancer/stromal cell compartment by multicolor flow cytometry, using 26 markers. A comprehensive analysis of this data set reveals the heterogeneity within the tumor microenvironment on a phenotypic level, which might have potentially significant correlations to the clinical status and molecular phenotype of the cancer. These results encourage the expansion of the use of flow cytometry as a means of solid tumor biopsy analysis, highlighting the potential clinical value of this approach in disease management. Citation Format: Aaron J. Middlebrook, Peter Llontop, Mary Beth Hanley, Warren Porter, Friedrich Hahn, Eileen Snowden, Rainer Blaesius, Smita Ghanekar. Deep phenotyping of dissociated solid tumor cells from breast cancer specimens. [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 2423.

Purpose: We aim to characterize VTX-2337, a novel Toll-like receptor (TLR) 8 agonist in clinical development, and investigate its potential to improve monoclonal antibody–based immunotherapy that includes the activation of natural killer (NK) cells. Experimental Design: HEK-TLR transfectants were used to compare the selectivity and potency of VTX-2337, imiquimod, CpG ODN2006, and CL075. The ability of VTX-2337 to induce cytokine and chemokine production from human peripheral blood mononuclear cells (PBMC) and activation of specific immune cell subsets was examined. The potential for VTX-2337 to activate NK cell activity through direct and indirect mechanisms was also investigated. Finally, we tested the potential for VTX-2337 to augment antibody-dependent cell-mediated cytotoxicity (ADCC), especially in individuals with low-affinity FcγR3A single-nucleotide polymorphism (SNP). Results: VTX-2337 selectively activates TLR8 with an EC50 of about 100 nmol/L and stimulates production of TNFα and interleukin (IL)-12 from monocytes and myeloid dendritic cells (mDC). VTX-2337 stimulates IFNγ production from NK cells and increases the cytotoxicity of NK cells against K562 and ADCC by rituximab and trastuzumab. Effects of VTX-2337 on NK cells were, in part, from direct activation as increased IFNγ production and cytotoxic activity were seen with purified NK cells. Finally, VTX-2337 augments ADCC by rituximab in PBMCs with different FcγR3A genotypes (V/V, V/F, and F/F at position 158). Conclusions: VTX-2337 is a novel small-molecule TLR8 agonist that activates monocytes, DCs, and NK cells. Through the activation of NK cells, it has the potential to augment the effectiveness of monoclonal antibody treatments where a polymorphism in FcγR3A limits clinical efficacy. Clin Cancer Res; 18(2); 499–509. ©2011 AACR.

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.

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

The heterogeneous nature of solid tumors, coupled with the relatively small sample size of available biopsies, has led to an emerging need to glean as much information as possible from these valuable specimens. Current approaches to solid tumor analysis fail to completely reveal the diverse range of cellular compartments that comprise the tumor microenvironment. A comprehensive approach to tumor interrogation requires efficient tissue dissociation to facilitate analysis at the single-cell level. In contrast to current methods, single-cell analysis of tumor derived cell suspensions by flow cytometry has the potential to provide a more complete understanding of the many subpopulations within the tumor microenvironment and the cell to cell interactions that govern this space. Here we demonstrate an efficient workflow that enables comprehensive single-cell analysis of solid tumors from breast cancers. Using tumors from clinical samples and mouse models, we evaluated different dissociation and processing techniques for their effects on cellular viability and surface marker expression. Solid tumors were dissociated into single-cell suspensions using a combination of mechanical dissociation and enzymatic digestion. Phenotypic distribution and morphology of cells within the tumor microenvironment was evaluated using flow cytometry. As this approach evolves, and a knowledge base of relevant surface markers is established, this technology has the potential to significantly impact how tumor biopsies are processed to get multiparametric information at a single cell level. Citation Format: Aaron J. Middlebrook, Shahryar Niknam, Joyce Ruitenberg, Albert J. Mach, Maria Suni, Warren Porter, Friedrich Hahn, Eileen Snowden, Rainer Blaesius, Smita Ghanekar. Characterization of single cells from dissociated solid tumors. [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 227. doi:10.1158/1538-7445.AM2015-227

More precise quantitation of cellular immune responses has become possible with the advent of single-cell assays of immune function, such as cytokine flow cytometry, enzyme-linked immunospot (ELISPOT), and MHC-peptide multimers. Cytokine flow cytometry is an attractive technique because it allows the detection of responses to whole antigens without regard to MHC restriction, while also collecting additional information on responding cells via multiparameter flow cytometry. In this review, we compare cytokine flow cytometry with other assays of immune function, summarize some of that data that have been collected in various disease states using cytokine flow cytometry, and describe some methodological improvements designed to increase the robustness, throughput, and information content of this technique. We hypothesize that a new generation of automated cytokine flow cytometry assays will allow elucidation of the correlates of protection for diseases involving cellular immunity, through application of these assays in more and large clinical trials.

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

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.