Flow Cytometry

最近的突破在癌症研究nd treatment have been in the field of immuno-oncology, using novel immunotherapies to bolster the host’s immune system to more effectively target and destroy tumor cells. Among the list of FDA-approved therapeutics with immunoregulatory activity are antibody and cytokine-based immunotherapies, small molecule drugs, and cell-based therapy. The success that these and other therapies have had at prolonging survival has placed emphasis on the development of new single agent and combination therapies with greater efficacy at treating cancer.

Productive development of immunotherapies requires high-throughput and robust quantitative analysis of the immune system in the tumor micro-environment, peripheral blood, and other host tissues.

To meet this need, our contract flow cytometry service, provides you with an advanced, state-of-the-art analytical flow cytometry resource to support all aspects of your drug development needs. Run your sample generation studies with us or overnight-ship us your preclinical or non-CLIA regulated clinical samples and we’ll take care of the flow cytometry for you.

Basic to Comprehensive Immune Profiling

With over 50 years of combined expertise, our full-service analytical team can add anex vivo流式细胞术臂到任何in vivostudy. Our list of standardized antibody panels (see below) have been validated in multiplein vivocancer models and provide basic to comprehensive analysis of a wide range of lymphoid and myeloid lineage immune subsets to capture shifts that occur in the immune response triggered byin vivotest agent treatment. See a list of our panels below.

Basic T Cell Panel

Tumor-infiltrating CD4+ and CD8+ T cell analysis in a murine 4T1 breast carcinoma model.

Quantitative measurement of tumor-infiltrating T cells can be crucial when evaluating the immune-modulating effects of new immunotherapies. The Basic T Cell Panel provides T cell subset measurement and has been validated in multiple tissue types. In the above study, T cell subsets in a mammary fat pad implanted 4T1 mammary carcinoma were analyzed ex vivo. CD3+ T cells were first identified by gating on CD45+ hematopoietic cells. T cell populations were further analyzed based on CD4 and CD8 lineage marker expression.

Tumor-infiltrating CD4+ and CD8+ T cell analysis in a murine 4T1 breast carcinoma model.
Basic T & B Cell Panel

T cell and B cell subset analysis in murine spleen.

The Basic T & B Cell Panel can be utilized to quantify CD4+ and CD8+ T cells as well as B cells fractions in heterogeneous samples. Only 6 fluorescence channels are occupied by this panel, which leaves several channels available for further cell characterization by dropping in additional antibodies. In the study above, CD3+ T cells and CD19+ B cells were analyzed in the Live Cell gate. T cells were further subdivided into CD4+ and CD8+ populations.

Regulatory T Cell Panel

Regulatory T cell analysis in the murine CT.26 colorectal tumor model

调节性T细胞抑制了几种疾病模型中的抗肿瘤反应,是新免疫治疗的有吸引力的目标。调节性T细胞面板是基本T细胞面板的膨胀,可用于评估靶向调节T细胞的新治疗方法的影响。在上述研究中,从CT.26腺癌宿主中分析了调节性T细胞的脾体内。首先通过在CD45 + CD3 +细胞上鉴定CD4 + T细胞。基于CD25和FoxP3的共表达进一步分化调节性T细胞。
Regulatory T cell analysis in the murine CT.26 colorectal tumor model
T Cell Activation/Exhaustion Panel

Analysis of T cell activation in the murine A20 B cell lymphoma model

One challenge faced during the development of new immunotherapies is overcoming the loss of anti-tumor activity that occurs in T cells within the tumor microenvironment. A state referred to as T cell exhaustion, which can be identified based on the relative expression of different immune checkpoints and activation markers. The T Cell Activation/Exhaustion panel is an expansion of the Basic T Cell panel and can be used to measure expression for select key biomarkers in different tissues. In the study above, expression of immune checkpoint proteins CTLA-4 and PD-1 as well as the surrogate proliferation marker Ki-67 were measured in T cell subsets within A20 cell line-derived tumors.

Comprehensive T Cell Panel

CD4+, CD8+, and regulatory T cell analysis combined with immune checkpoint/activation marker interrogation using the T Cell Panel

结合了utilit综合T细胞面板y of the Basic, Regulatory, and T Cell Activation/Exhaustion panels into one comprehensive analysis of the T cell profile within tissues. The data above displays (A) CD4+/CD8+ T cell subset analysis in murine tumors using a 4T1 breast carcinoma model, (B) regulatory T cell analysis in spleens from CT.26 colorectal adenocarcinoma bearing mice, and (C) CTLA-4, PD-1, and Ki-67 expression levels in T cell subsets from A20 (B cell lymphoma) cell line-derived tumors.
Natural Killer Cell Panel

Natural Killer (NK) cell and Dendritic Cell (DC) subset analysis in CT.26 colorectal adenocarcinoma model

NK细胞群众所周知,均可用于其抗肿瘤活性和控制许多肿瘤生长的能力。DCS具有抗肿瘤功能,是疫苗的免疫治疗靶标。已显示NKDC(AKA IKDC)对NK细胞和DCS的功能特征。自然杀手单元面板可用于识别亚群。进行上述研究以定量肿瘤衍生的Ly6G-Ly6C-Immune细胞内的NK细胞,DC和NKDC子集的百分比。

Myeloid-Derived Suppressor Cell Panel

Myeloid-Derived Suppressor Cell (MDSC) analysis in a murine CT.26 colorectal oncology model

MDSC subsets can influence several pro-tumor responses including the suppression of immune function, and are an attractive target for immunotherapy. They are a heterogeneic cell population. The phenotype of which can be shaped by signals in the tumor microenvironment. The data above demonstrates how the MDSC panel can be used for basic identification of granulocytic (G-) and monocytic (M-) MDSC subsets in CT.26-derived tumors. CD11b+ myeloid cells were first identified in the CD45+ gate after CD3+CD19+ lymphocyte exclusion. G-MDSC and M-MDSC were further differentiated based on expression of Ly-6G and Ly-6C surface receptors.

Expanded Myeloid Panel

Analysis of myeloid-derived suppressor cell (MDSC), natural killer (NK) cell, and dendritic cell (DC) subsets in a murine CT.26 colorectal tumor model.

The Expanded Myeloid panel is an expansion of the basic MDSC panel to enable analysis of NK and DC subsets in addition to MDSC populations. In the data shown, these subsets were analyzed in CT.26-derived tumors. Monocytic (M-) and Granulocytic (G-) MDSCs express high levels of Ly-6C and Ly-6G protein respectively (Bright) and co-expressed the CD11b marker. NK and DCs were analyzed in the MDSC exclusion gate and further differentiated based on pan-NK markers (CD49b and CD335) vs DC-specific CD11c protein expression. Red and grey peaks represent CD11b stained and unstained cells respectively.

Comprehensive Myeloid Panel

Myeloid Cell Analysis in tumors using the MI Bioresearch Comprehensive Myeloid Panel

The Comprehensive Myeloid Panel builds on the Basic Myeloid-Derived Suppressor Cell Panel for a more in depth analysis of myeloid cell populations. It also enables the analysis of the immune inhibitory receptor PD-L1 on both tumor and immune cell subsets. The data above demonstrates how the Comprehensive Myeloid Panel can be used to A) measure PD-L1 expression on tumor and immune cells (4T1 breast carcinoma model), B) Quantify macrophage and dendritic cell subsets (CT.26 colorectal tumor model), and C) characterize MDSC subsets for expression of CD115, which is a receptor that has been shown to directly correlate with suppressive activity (CT.26 colorectal tumor model). This panel can also be helpful in the analysis of neutrophils and monocyte populations (not shown). Red and grey peaks represent cells stained for target antigen and unstained cells respectively.

M1 & M2 Tumor-Associated Macrophage Panel

Analysis of classically (M1) and alternatively (M2) activated tumor-associated macrophages in a CT.26 colorectal adenocarcinoma model

M1 and M2 macrophages are the two major macrophage groups that reside within the tumor microenvironment. They have opposing functions with regard to cancer progression and are therefore targets for new immunotherapies. The study above demonstrates how the M1 and M2 Tumor-Associated Macrophage panel can be used to profile the ratios of these two groups. To this end, MDSC subsets were excluded so that CD11b+/F480+ macrophages could be identified. This fraction was analyzed for M2 macrophages (CD206+) and M2 macrophages (CD206-MHCII+).