The development of flow cytometric biomarkers in human studies and clinical trials has been slowed by inconsistent sample processing, use of cell surface markers, and reporting of immunophenotypes. Additionally, the function(s) of distinct cell types as biomarkers cannot be accurately defined without the proper identification of homogeneous populations. As such, we developed a method for the identification and analysis of human leukocyte populations by the use of eight 10-color flow cytometric protocols in combination with novel software analyses. This method utilizes un-manipulated biological sample preparation that allows for the direct quantitation of leukocytes and non-overlapping immunophenotypes. We specifically designed myeloid protocols that enable us to define distinct phenotypes that include mature monocytes, granulocytes, circulating dendritic cells, immature myeloid cells, and myeloid derived suppressor cells (MDSCs). We also identified CD123 as an additional distinguishing marker for the phenotypic characterization of immature LIN-CD33+HLA-DR- MDSCs. Our approach permits the comprehensive analysis of all peripheral blood leukocytes and yields data that is highly amenable for standardization across inter-laboratory comparisons for human studies.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a median lifespan of 2–3 years after diagnosis. There are few meaningful treatments that alter progression in this disease. Preclinical and clinical studies have demonstrated that neuroinflammation may play a key role in the progression rate of ALS. Despite this, there are no validated biomarkers of neuroinflammation for use in clinical practice or clinical trials. Biomarkers of neuroinflammation could improve patient management, provide new therapeutic targets, and possibly help stratify clinical trial selection and monitoring. However, attempts to identify a singular cause of neuroinflammation have not been successful. Here, we performed multi-parameter flow cytometry to comprehensively assess 116 leukocyte populations and phenotypes from lymphocytes, monocytes, and granulocytes in a cohort of 80 ALS patients. We identified 32 leukocyte phenotypes that were altered in ALS patients compared to age and gender matched healthy volunteers (HV) that included phenotypes of both inflammation and immune suppression. Unsupervised hierarchical clustering and principle component analysis of ALS and HV immunophenotypes revealed two distinct immune profiles of ALS patients. ALS patients were clustered into a profile distinct from HVs primarily due to differences in a multiple T cell phenotypes, CD3+CD56+ T cells and HLA-DR on monocytes. Patients clustered into an abnormal immune profile were younger, more likely to have a familial form of the disease, and survived longer than those patients who clustered similarly with healthy volunteers (344 weeks versus 184 weeks; p = 0.012). The data set generated from this study establishes an extensive accounting of immunophenotypic changes readily suitable for biomarker validation studies. The extensive immune system changes measured in this study indicate that normal immune homeostatic mechanisms are disrupted in ALS patients, and that multiple immune states likely exist within a population of patients with ALS.

SummaryIt was hypothesized that contact between chronic lymphocytic leukaemia (CLL) B-cells and marrow stromal cells impact both cell types. To test this hypothesis, we utilized a long-term primary culture system from bone biopsies that reliably generates a mesenchymal stem cell (MSC). Co-culture of MSC with CLL B-cells protected the latter from both spontaneous apoptosis and drug-induced apoptosis. The CD38 expression in previously CD38 positive CLL B-cells was up-regulated with MSC co-culture. Upregulation of CD71, CD25, CD69 and CD70 in CLL B-cells was found in the co-culture. CD71 upregulation was more significantly associated with high-risk CLL, implicating CD71 regulation in the microenvironment predicting disease progression. In MSC, rapid ERK and AKT phosphorylation (within 30 min) were detected when CLL B-cells and MSC were separated by transwell; indicating that activation of MSC was mediated by soluble factors. These findings support a bi-directional activation between bone marrow stromal cells and CLL B-cells.

BackgroundWe have developed a novel approach to categorize immunity in patients that uses a combination of whole blood flow cytometry and hierarchical clustering.MethodsOur approach was based on determining the number (cells/μl) of the major leukocyte subsets in unfractionated, whole blood using quantitative flow cytometry. These measurements were performed in 40 healthy volunteers and 120 patients with glioblastoma, renal cell carcinoma, non-Hodgkin lymphoma, ovarian cancer or acute lung injury. After normalization, we used unsupervised hierarchical clustering to sort individuals by similarity into discreet groups we call immune profiles.ResultsFive immune profiles were identified. Four of the diseases tested had patients distributed across at least four of the profiles. Cancer patients found in immune profiles dominated by healthy volunteers showed improved survival (p < 0.01). Clustering objectively identified relationships between immune markers. We found a positive correlation between the number of granulocytes and immunosuppressive CD14+HLA-DRlo/neg monocytes and no correlation between CD14+HLA-DRlo/neg monocytes and Lin-CD33+HLA-DR- myeloid derived suppressor cells. Clustering analysis identified a potential biomarker predictive of survival across cancer types consisting of the ratio of CD4+ T cells/μl to CD14+HLA-DRlo/neg monocytes/μL of blood.ConclusionsComprehensive multi-factorial immune analysis resulting in immune profiles were prognostic, uncovered relationships among immune markers and identified a potential biomarker for the prognosis of cancer. Immune profiles may be useful to streamline evaluation of immune modulating therapies and continue to identify immune based biomarkers.

BackgroundThere is little information regarding the composition of peripheral blood immunity in sarcoma patients and even less in the context of pediatric sarcomas. We describe the immune status using flow cytometry of peripheral blood in patients with osteosarcoma and Ewing sarcoma and demonstrate excessive CD14 in tumor tissues.MethodsPeripheral blood from patients with OS and ES was collected at diagnosis or relapse, and used for immune phenotyping of 74 different leukocyte phenotypes. Blood from young adult healthy volunteers was collected as controls. Tumor tissues were analyzed by immunohistochemistry.ResultsNineteen patients (average age = 14 y) and 16 controls (average age = 25y) were enrolled on study. Of the 74 phenotypes, 14 were different between sarcoma patients and HV. Sarcoma patients’ leukocytes contained a higher percentage of granulocytes (67 % sarcoma vs. 58 % HV; p = 0.003) and fewer lymphocytes (20 % sarcoma vs. 27 % HV; p = 0.001). Increased expression of CTLA-4 was seen in both T cells in sarcoma patients as compared to HV (p = 0.05). Increased CD14+ HLA-DRlo/neg immunosuppressive monocytes were seen in sarcoma patients (p = 0.03); primarily seen in OS. Increased tumor necrosis factor receptor II expression was seen on CD14+ cells derived from sarcoma patients as compared to HV (p = 0.01). Massive infiltration of CD14+ cells was seen in OS (>50 % of cells in the majority of tumors) compared to ES (<10-25 % of cells). In contrast, both OS and ES had limited T cell infiltration (generally <10 % of cells).ConclusionsPediatric sarcoma patients exhibit several immune phenotypic differences that were exacerbated in more severe disease. These phenotypes have the potential to contribute to immune suppression and may indicate potential targets for immune therapies.Electronic supplementary materialThe online version of this article (doi:10.1186/s40425-015-0082-0) contains supplementary material, which is available to authorized users.