An automated analysis of highly complex flow cytometry-based proteomic data

Addressing current challenges and future directions in immuno-oncology: expert perspectives from the 2017 NIBIT Foundation Think Tank, Siena, Italy

A collaborative think tank involving panellists from immuno-oncology networks, clinical/translational investigators and the pharmaceutical industry was held in Siena, Italy, in October 2017 to discuss the evolving immune-oncology landscape, identify selected key challenges, and provide a perspective on the next steps required in the translation of current research and knowledge to clinical reality. While there is a trend of combining new agents (e.g., co-stimulator agonists) with a PD-1/PD-L1 treatment backbone, use of alternative combination therapy approaches should also be considered. While the rapid evolution in systems biology provides a deeper understanding of tumor and tumor microenvironment heterogeneity, there remains the need to identify and define genuinely predictive biomarkers to guide treatment and patient selection. Cross-specialty and cross-sector collaboration, along with a broader collective data-sharing approach are key to optimizing immuno-oncology therapy in clinical practice. Continued support of younger research-clinicians is essential for future success in clinical, translational and basic science investigations.

High-resolution antibody array analysis of proteins from primary human keratinocytes and leukocytes

Antibody array analysis of labeled proteomes has high throughput and is simple to perform, but validation remains challenging. Here, we used differential detergent fractionation and size exclusion chromatography in sequence for high-resolution separation of biotinylated proteins from human primary keratinocytes and leukocytes. Ninety-six sample fractions from each cell type were analyzed with microsphere-based antibody arrays and flow cytometry (microsphere affinity proteomics; MAP). Monomeric proteins and multi-molecular complexes in the cytosol, cytoplasmic organelles, membranes and nuclei were resolved as discrete peaks of antibody reactivity across the fractions. The fractionation also provided a two-dimensional matrix for assessment of specificity. Thus, antibody reactivity peaks were considered to represent specific binding if the position in the matrix was in agreement with published information about i) subcellular location, ii) size of the intended target, and iii) cell type-dependent variation in protein expression. Similarities in the reactivity patterns of either different antibodies to the same protein or antibodies to similar proteins were used as additional supporting evidence. This approach provided validation of several hundred proteins and identification of monomeric proteins and protein complexes. High-resolution MAP solves many of the problems associated with obtaining specificity with immobilized antibodies and a protein label. Thus, laboratories with access to chromatography and flow cytometry can perform large-scale protein analysis on a daily basis. This opens new possibilities for cell biology research in dermatology and validation of antibodies.

A high-throughput pipeline for validation of antibodies

Western blotting (WB) is widely used to test antibody specificity, but the assay has low throughput and precision. Here we used preparative gel electrophoresis to develop a capture format for WB. Fractions with soluble, size-separated proteins facilitated parallel readout with antibody arrays, shotgun mass spectrometry (MS) and immunoprecipitation followed by MS (IP-MS). This pipeline provided the means for large-scale implementation of antibody validation concepts proposed by an international working group on antibody validation (IWGAV).

Ensemble multicolour FRET model enables barcoding at extreme FRET levels

Quantitative models of Förster resonance energy transfer (FRET)-pioneered by Förster-define our understanding of FRET and underpin its widespread use. However, multicolour FRET (mFRET), which arises between multiple, stochastically distributed fluorophores, lacks a mechanistic model and remains intractable. mFRET notably arises in fluorescently barcoded microparticles, resulting in a complex, non-orthogonal fluorescence response that impedes their encoding and decoding. Here, we introduce an ensemble mFRET (emFRET) model, and apply it to guide barcoding into regimes with extreme FRET. We further introduce a facile, proportional multicolour labelling method using oligonucleotides as homogeneous linkers. A total of 580 barcodes were rapidly designed and validated using four dyes-with FRET efficiencies reaching 76%-and used for multiplexed immunoassays with cytometric readout and fully automated decoding. The emFRET model helps to expand the barcoding capacity of barcoded microparticles using common organic dyes and will benefit other applications subject to stochastic mFRET.

Novel serum and bile protein markers predict primary sclerosing cholangitis disease severity and prognosis

BACKGROUND & AIMS

Prognostic biomarkers are lacking in primary sclerosing cholangitis, hampering patient care and the development of therapy. We aimed to identify novel protein biomarkers of disease severity and prognosis in primary sclerosing cholangitis (PSC).

METHODS

Using a bead-based array targeting 63 proteins, we profiled a derivation panel of Norwegian endoscopic retrograde cholangiography bile samples (55 PSC, 20 disease controls) and a Finnish validation panel (34 PSC, 10 disease controls). Selected identified proteins were measured in serum from two Norwegian PSC cohorts (n=167 [1992-2006] and n=138 [2008-2012]), inflammatory bowel disease (n=96) and healthy controls (n=100).

RESULTS

In the bile derivation panel, the levels of 14 proteins were different between PSC patients and controls (p<0.05); all were confirmed in the validation panel. Twenty-four proteins in the bile derivation panel were significantly (p<0.05) different between PSC patients with mild compared to severe cholangiographic changes (modified Amsterdam criteria); this was replicated for 18 proteins in the validation panel. Interleukin (IL)-8, matrix metallopeptidase (MMP)9/lipocalin (LCN)2-complex, S100A8/9, S100A12 and tryptophan hydroxylase (TPH)2 in the bile were associated with both a PSC diagnosis and grade of cholangiographic changes. Stratifying PSC patients according to tertiles of serum IL-8, but not MMP9/LCN2 and S100A12, provided excellent discrimination for transplant-free survival both in the serum derivation and validation cohort. Furthermore, IL-8 was associated with transplant-free survival in multivariable analyses in both serum panels independently of age and disease duration, indicating an independent influence on PSC progression. However, the Enhanced Liver Fibrosis (ELF®) test and Mayo risk score proved to be stronger predictors of transplant-free survival.

CONCLUSIONS

Based on assaying of biliary proteins, we have identified novel biliary and serum biomarkers as indicators of severity and prognosis in PSC.

LAY SUMMARY

Prognostic biomarkers are lacking in primary sclerosing cholangitis, hampering patient care and the development of therapy. We have identified inflammatory proteins including calprotectin and IL-8 as important indicators of disease severity and prognosis in bile and serum from patients with primary sclerosing cholangitis.

High-resolution Antibody Array Analysis of Childhood Acute Leukemia Cells

Acute leukemia is a disease pathologically manifested at both genomic and proteomic levels. Molecular genetic technologies are currently widely used in clinical research. In contrast, sensitive and high-throughput proteomic techniques for performing protein analyses in patient samples are still lacking. Here, we used a technology based on size exclusion chromatography followed by immunoprecipitation of target proteins with an antibody bead array (Size Exclusion Chromatography-Microsphere-based Affinity Proteomics, SEC-MAP) to detect hundreds of proteins from a single sample. In addition, we developed semi-automatic bioinformatics tools to adapt this technology for high-content proteomic screening of pediatric acute leukemia patients.To confirm the utility of SEC-MAP in leukemia immunophenotyping, we tested 31 leukemia diagnostic markers in parallel by SEC-MAP and flow cytometry. We identified 28 antibodies suitable for both techniques. Eighteen of them provided excellent quantitative correlation between SEC-MAP and flow cytometry (p< 0.05). Next, SEC-MAP was applied to examine 57 diagnostic samples from patients with acute leukemia. In this assay, we used 632 different antibodies and detected 501 targets. Of those, 47 targets were differentially expressed between at least two of the three acute leukemia subgroups. The CD markers correlated with immunophenotypic categories as expected. From non-CD markers, we found DBN1, PAX5, or PTK2 overexpressed in B-cell precursor acute lymphoblastic leukemias, LAT, SH2D1A, or STAT5A overexpressed in T-cell acute lymphoblastic leukemias, and HCK, GLUD1, or SYK overexpressed in acute myeloid leukemias. In addition, OPAL1 overexpression corresponded to ETV6-RUNX1 chromosomal translocation.In summary, we demonstrated that SEC-MAP technology is a powerful tool for detecting hundreds of proteins in clinical samples obtained from pediatric acute leukemia patients. It provides information about protein size and reveals differences in protein expression between particular leukemia subgroups. Forty-seven of SEC-MAP identified targets were validated by other conventional method in this study.

Data Analysis Strategies for Protein Microarrays

Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation.