An array of possibilities in cancer research using cytokine antibody arrays

Colorectal Cancer and Immunity: From the Wet Lab to Individuals

Simple Summary

Tackling the current dilemma of colorectal cancer resistance to immunotherapy is puzzling and requires novel therapeutic strategies to emerge. However, characterizing the intricate interactions between cancer and immune cells remains difficult because of the complexity and heterogeneity of both compartments. Developing rationales is intellectually feasible but testing them can be experimentally challenging and requires the development of innovative procedures and protocols. In this review, we delineated useful in vitro and in vivo models used for research in the field of immunotherapy that are or could be applied to colorectal cancer management and lead to major breakthroughs in the coming years.

Abstract

Immunotherapy is a very promising field of research and application for treating cancers, in particular for those that are resistant to chemotherapeutics. Immunotherapy aims at enhancing immune cell activation to increase tumor cells recognition and killing. However, some specific cancer types, such as colorectal cancer (CRC), are less responsive than others to the current immunotherapies. Intrinsic resistance can be mediated by the development of an immuno-suppressive environment in CRC. The mutational status of cancer cells also plays a role in this process. CRC can indeed be distinguished in two main subtypes. Microsatellite instable (MSI) tumors show a hyper-mutable phenotype caused by the deficiency of the DNA mismatch repair machinery (MMR) while microsatellite stable (MSS) tumors show a comparatively more “stable” mutational phenotype. Several studies demonstrated that MSI CRC generally display good prognoses for patients and immunotherapy is considered as a therapeutic option for this type of tumors. On the contrary, MSS metastatic CRC usually presents a worse prognosis and is not responsive to immunotherapy. According to this, developing new and innovative models for studying CRC response towards immune targeted therapies has become essential in the last years. Herein, we review the in vitro and in vivo models used for research in the field of immunotherapy applied to colorectal cancer.

Plasma protein-based signature predicts distant metastasis and induction chemotherapy benefit in Nasopharyngeal Carcinoma

Rationale: Currently, for locoregionally advanced nasopharyngeal carcinoma (LA-NPC), there is no effective blood-based method to predict distant metastasis. We aimed to detect plasma protein profiles to identify biomarkers that could distinguish patients with NPC who are at high risk of posttreatment distant metastasis.

Methods: A high-throughput antibody array was initially applied to detect 1000 proteins in pretreatment plasma from 16 matched LA-NPC patients with or without distant metastasis after radical treatment. Differentially expressed proteins were further examined using a low-throughput array to construct a plasma protein-based signature for distant metastasis (PSDM) in a cohort of 226 patients.

Results: Fifty circulating proteins were differentially expressed between metastatic and non-metastatic patients and 18 were proven to be strongly correlated with distant metastasis-free survival (DMFS) in NPC. A PSDM signature consisting of five proteins (SLAMF5, ESM-1, MMP-8, INSR, and Serpin A5) was established to assign patients with NPC into a high-risk group and a low-risk group. Patients in the high-risk group had shorter DMFS (P < 0.001), disease-free survival (DFS) (P < 0.001) and overall survival (OS) (P < 0.001). Moreover, the PSDM performed better than N stage and Epstein-Barr virus (EBV) DNA load at effectively identifying patients with NPC at high risk of metastasis. For patients in the high-risk group, induction chemotherapy significantly improved DMFS, DFS, and OS.

Conclusions: The PSDM could be a useful liquid biopsy tool to effectively predict distant metastasis and the benefit of induction chemotherapy in patients with LA-NPC.

Developing a periodontal disease antibody array for the prediction of severe periodontal disease using machine learning classifiers

BACKGROUND

The aim of this study was to simultaneously and quantitatively assess the expression levels of 20 periodontal disease-related proteins in gingival crevicular fluid (GCF) from normal controls (NOR) and severe periodontitis (SP) patients with an antibody array.

METHODS

Antibodies against 20 periodontal disease-related proteins were spotted onto a glass slide to create a periodontal disease antibody array (PDD). The array was then incubated with GCF samples collected from 25 NOR and 25 SP patients. Differentially expressed proteins between NOR and SP patients were then used to build receiver operator characteristic (ROC) curves and compare five classification models, including support vector machine, random forest, k nearest neighbor, linear discriminant analysis, and Classification and Regression Trees.

RESULTS

Seven proteins (C-reactive protein, interleukin [IL]-1α, interleukin-1β, interleukin-8, matrix metalloproteinase-13, osteoprotegerin, and osteoactivin) were significantly upregulated in SP patients compared with NOR, while receptor activator of nuclear factor-kappa was significantly downregulated. The highest diagnostic accuracy using a ROC curve was observed for IL-1β with an area under the curve of 0.984. Five of the proteins (IL-1β, IL-8, MMP-13, osteoprotegerin, and osteoactivin) were identified as important features for classification. Linear discriminant analysis had the highest classification accuracy across the five classification models that were tested.

CONCLUSION

This study highlights the potential of antibody arrays to diagnose periodontal disease.

Protein array profiling of circulating angiogenesis-related factors during bevacizumab containing treatment in metastatic colorectal cancer

BACKGROUND

Prolonged angiogenesis inhibition may improve treatment outcome in metastatic colorectal cancer (mCRC) patients. However, due to the complexity of the angiogenic pathways there is a lack of valid predictive biomarkers for anti-angiogenic agents. Here, we describe and optimize a procedure for simultaneous dynamic profiling of multiple angiogenesis related proteins in patient serum to explore associations with the response and acquired resistance to anti-angiogenic therapy.

MATERIALS AND METHODS

Patients (n=22) were selected from a clinical trial investigating maintenance treatment with bevacizumab alone after response to induction chemotherapy + bevacizumab in mCRC. Serum samples were analysed for 55 unique angiogenesis related proteins using a commercial proteome profiler array and a publicly available image analysis program for quantification. Samples were collected at baseline before induction treatment start, at start of maintenance treatment, and at end of treatment after tumour progression.

MAIN RESULTS AND CONCLUSION

For eight proteins, the antibody array signals were below detection range in all patient samples. None of the proteins showed levels at baseline or at start of maintenance with strong evidence for correlation to time to progression (lowest nominal p-value 0.03). The dynamic ranges of protein levels measured during the induction treatment period and during the maintenance period were analysed separately for time trends. Evidence for changing trends (up/down) in the levels of MMP-8, TIMP-4 and EGF was observed both during response to induction treatment and at progressive disease, respectively. For three of the proteins (IL-8, Activin A and IGFBP-2), weak evidence for correlation between increasing protein levels during induction with chemotherapy and bevacizumab and time to progression was observed. In conclusion, semi-quantitative profiling of angiogenesis related proteins in patient serum may be a versatile tool to screen for protein patterns aiming at identifying resistance mechanisms of anti-angiogenic treatment in patients with mCRC.

New Insights into the Tumor Microenvironment Utilizing Protein Array Technology

The tumor microenvironment (TME) is a considerably heterogeneous niche, which is created by tumor cells, the surrounding tumor stroma, blood vessels, infiltrating immune cells, and a variety of associated stromal cells. Intercellular communication within this niche is driven by soluble proteins synthesized by local tumor and stromal cells and include chemokines, growth factors, interferons, interleukins, and angiogenic factors. The interaction of tumor cells with their microenvironment is essential for tumorigenesis, tumor progression, growth, and metastasis, and resistance to drug therapy. Protein arrays enable the parallel detection of hundreds of proteins in a small amount of biological sample. Recent data have demonstrated that the application of protein arrays may yield valuable information regarding the structure and functional mechanisms of the TME. In this review, we will discuss protein array technologies and their applications in TME analysis to discern pathways involved in promoting the tumorigenic phenotype.

Identification of Basic Fibroblast Growth Factor as the Dominant Protector of Laminar Shear Medium from the Modified Shear Device in Tumor Necrosis Factor-α Induced Endothelial Dysfunction

Background and Aims: Endothelial dysfunction is a hallmark of cardiovascular diseases. The straight region of an artery is protected from atherosclerosis via its laminar blood flow and high shear stress. This study investigated the cytoprotective effects of a new laminar shear medium (LSM) derived from a modified cone-and-plate shear device and identified basic fibroblast growth factor (bFGF) secreted by human aortic endothelial cells (HAECs) as the dominant protective factor in the LSM.

Methods: Based on a modified cone-and-plate shear device system, HAECs were exposed to laminar shear (15 dynes/cm²) and static control for 24 h to produce a new supernatant LSM and static medium (SM). Evaluation of the protective effects of LSM and SM on endothelial dysfunction induced by tumor necrosis factor (TNF)-α (10 ng/mL), which leads to production of reactive oxygen species (ROS), inflammatory monocyte adhesion, and tissue factor activity. ROS induction-, inflammation-, and thrombosis-related genes and protein expression were evaluated by quantitative-PCR and western blotting. To identify the cytokines that played a key role in the cytoprotective action of the LSM, we used cytokine antibody arrays, selected an abundant marker cytokine, bFGF, and validated the different cytoprotective effects of recombinant bFGF (rbFGF) and neutralization by monoclonal antibody (rbFGF+Ab) co-treatment. Aortic and lung tissues from different groups of C57BL/6J mice were examined by immunohistochemistry. SB203580 (specific inhibitor of p38) and BIX02189 (specific inhibitor of MEK5) were used to identify bFGF as the main cytoprotective factor acting via p38/MAPK and MEK5-KLF2 pathways.

Results: Compared with traditional LSM, the new LSM not only significantly decreased TNF-α-induced intracellular adhesion molecule 1 and plasminogen activator inhibitor type 1 gene expression, but also significantly increased heme oxygenase 1 gene expression. The new LSM and bFGF attenuated TNF-α-induced ROS induction, inflammation, and tissue factor activity and inhibited the inflammatory- and thrombosis-related gene/protein overexpression both in vitro and in vivo. Mechanistically, the cytoprotective action of bFGF was mediated via the p38/MAPK and MEK5-KLF2 pathways.

Conclusion: bFGF was identified as the critical factor mediating the cytoprotective effects of LSM derived from the modified laminar shear system.

High baseline levels of interleukin-8 in leukocytes and urine predict tumor recurrence in non-muscle invasive bladder cancer patients receiving bacillus Calmette-Guerin therapy: A long-term survival analysis

Bacillus Calmette-Guerin (BCG) therapy for non-muscle invasive bladder cancer (NMIBC) can significantly reduce the risk of recurrence and progression. However, BCG therapy may fail in up to a half of treated patients and may also cause toxicities. Biomarkers to predict the effectiveness of BCG therapy are desired to pre-select patients for BCG therapy to maximize efficacy while avoid unnecessary toxicity. Twelve cytokines were measured in 100 blood and 112 urine samples using cytokine antibody array and correlated with recurrence-free survival in overall and BCG-treated NMIBC patients. Of the 12 cytokines, interleukin (IL) -2, IL-8, IL-10, tumor necrosis factor (TNF)-α, granulocyte-macrophage colony-stimulating factor (GM-CSF) and interferon (IFN)-γ were measurable in more than 30% of peripheral blood leukocyte (PBL) samples. Only IL-8 in PBL was found to be significantly associated with tumor recurrence, especially in those who receiving BCG therapy (hazard ratio [HR] = 4.24; 95% confidence interval [95%CI] = 1.65-10.88; p = 0.003). The median recurrence-free survival time for BCG-treated patients with high baseline IL-8 levels were much shorter than those with low IL-8 levels (7.9 vs. >78.4 mo, p = 0.004). Furthermore, consistent associations between urinary IL-8 levels and tumor recurrence in patients receiving BCG therapy were observed in 58 pre-BCG and 54 long-term post-BCG-treated urine samples (both p ≤ 0.005). High urinary baseline IL-8 level also predicted shorter time to tumor recurrence in NMIBC patients (both p ≤ 0.004). By using antibody array-based technology in two separate cohorts of NMIBC patients, we found that PBL and urinary baseline IL-8 levels were significantly associated with tumor recurrence after BCG therapy.

HIV microarray for the mapping and characterization of HIV-specific antibody responses

We used the microarray technology to develop chips containing a comprehensive set of proteins and peptides covering the proteome of HIV-1 clade C, which is the HIV-1 subtype that causes the majority of infections worldwide. We demonstrate that the HIV microarray allows simultaneous, sensitive and specific detection of antibody responses for the major immunoglobulin classes (IgG, IgA, IgM, IgE) and subclasses (IgG1-4) with minute amounts of serum samples towards a large number of HIV antigens and peptides. Furthermore, we show that the HIV chip can be used for the monitoring of antibody responses during the course of the disease and during treatment. The HIV microarray should be useful to study antibody responses to multiple HIV antigens and epitopes in HIV-infected patients to explore pathomechanisms of the disease, for diagnosis and for monitoring of treatment and of vaccine trials.

Tumor-induced perturbations of cytokines and immune cell networks

Until recently, the intrinsically high level of cross-talk between immune cells, the complexity of immune cell development, and the pleiotropic nature of cytokine signaling have hampered progress in understanding the mechanisms of immunosuppression by which tumor cells circumvent native and adaptive immune responses. One technology that has helped to shed light on this complex signaling network is the cytokine antibody array, which facilitates simultaneous screening of dozens to hundreds of secreted signal proteins in complex biological samples. The combined applications of traditional methods of molecular and cell biology with the high-content, high-throughput screening capabilities of cytokine antibody arrays and other multiplexed immunoassays have revealed a complex mechanism that involves multiple cytokine signals contributed not just by tumor cells but by stromal cells and a wide spectrum of immune cell types. This review will summarize the interactions among cancerous and immune cell types, as well as the key cytokine signals that are required for tumors to survive immunoediting in a dormant state or to grow and spread by escaping it. Additionally, it will present examples of how probing secreted cell-cell signal networks in the tumor microenvironment (TME) with cytokine screens have contributed to our current understanding of these processes and discuss the implications of this understanding to antitumor therapies.

High-throughput proteomics using antibody microarrays: an update

Antibody-based microarrays are a rapidly emerging technology that has advanced from the first proof-of-concept studies to demanding serum protein profiling applications during recent years, displaying great promise within disease proteomics. Miniaturized micro- and nanoarrays can be fabricated with an almost infinite number of antibodies carrying the desired specificities. While consuming only minute amounts of reagents, multiplexed and ultrasensitive assays can be performed targeting high- as well as low-abundance analytes in complex nonfractionated proteomes. The microarray images generated can then be converted into protein expression profiles or protein atlases, revealing a detailed composition of the sample. The technology will provide unique opportunities for fields such as disease diagnostics, biomarker discovery, patient stratification, predicting disease recurrence and drug target discovery. This review describes an update of high-throughput proteomics, using antibody-based microarrays, focusing on key technological advances and novel applications that have emerged over the last 3 years.

The Use of High-Throughput Technologies to Investigate Vascular Inflammation and Atherosclerosis

The greatest challenge of scientific research is to understand the causes and consequences of disease. In recent years, great efforts have been devoted to unraveling the basic mechanisms of atherosclerosis (the underlying pathology of cardiovascular disease), which remains a major cause of morbidity and mortality worldwide. Because of the complex and multifactorial pathophysiology of cardiovascular disease, different research techniques have increasingly been combined to unravel genetic aspects, molecular pathways, and cellular functions involved in atherogenesis, vascular inflammation, and dyslipidemia to gain a multifaceted picture addressing this complexity. Thanks to the rapid evolution of high-throughput technologies, we are now able to generate large-scale data on the DNA, RNA, and protein levels. With the help of sophisticated computational tools, these data sets are integrated to enhance information extraction and are being increasingly used in a systems biology approach to model biological processes as interconnected and regulated networks. This review exemplifies the use of high-throughput technologies—such as genomics, transcriptomics, proteomics, and epigenomics—and systems biology to explore pathomechanisms of vascular inflammation and atherosclerosis.

µFBI: a microfluidic bead-based immunoassay for multiplexed detection of proteins from a µL sample volume

Background

Over the last ten years, miniaturized multiplexed immunoassays have become robust, reliable research tools that enable researchers to simultaneously determine a multitude of parameters. Among the numerous analytical protein arrays available, bead-based assay systems have evolved into a key technology that enables the quantitative protein profiling of biological samples whilst requiring only a minimal amount of sample material.

Methodology/Principal Findings

A microfluidic bead-based immunoassay, µFBI, was developed to perform bead-based multiplexed sandwich immunoassays in a capillary. This setup allows the simultaneous detection of several parameters and only requires 200 ng of tissue lysate in a 1 µL assay volume. In addition, only 1 µL of detection antibodies and 1 µL of the reporter molecule Streptavidin-Phycoerythrin were required. The µFBI was used to compare the expression of seven receptor tyrosine kinases and their degree of tyrosine phosphorylation in breast cancer tissue and in normal tissue lysates. The total amount of HER-2, as well the degree of tyrosine phosphorylation was much higher in breast cancer tissue than in normal tissue. µFBI and a standard bead-based assay led to identical protein expression data. Moreover, it was possible to reduce the quantity of sample material required by a factor of 100 and the quantity of reagents by a factor of 30.

Conclusions/Significance

The µFBI, microfluidic bead-based immunoassay, allows the analysis of multiple parameters from a very small amount of sample material, such as tumor biopsies or tissue sections.

Protein microarrays for personalized medicine

BACKGROUND

Over the last 10 years, DNA microarrays have achieved a robust analytical performance, enabling their use for analyzing the whole transcriptome or for screening thousands of single-nucleotide polymorphisms in a single experiment. DNA microarrays allow scientists to correlate gene expression signatures with disease progression, to screen for disease-specific mutations, and to treat patients according to their individual genetic profiles; however, the real key is proteins and their manifold functions. It is necessary to achieve a greater understanding of not only protein function and abundance but also their role in the development of diseases. Protein concentrations have been shown to reflect the physiological and pathologic state of an organ, tissue, or cells far more directly than DNA, and proteins can be profiled effectively with protein microarrays, which require only a small amount of sample material.

CONTENT

Protein microarrays have become well-established tools in basic and applied research, and the first products have already entered the in vitro diagnostics market. This review focuses on protein microarray applications for biomarker discovery and validation, disease diagnosis, and use within the area of personalized medicine.

SUMMARY

Protein microarrays have proved to be reliable research tools in screening for a multitude of parameters with only a minimal quantity of sample and have enormous potential in applications for diagnostic and personalized medicine.

Antibody array platform to monitor protein tyrosine phosphorylation in mammalian cells

Protein tyrosine phosphorylation plays a central role in cell-signaling and is a focus of biomedical studies and cancer therapy. However, it is still challenging to identify or characterize the coordinated changes of many candidate proteins of one particular pathway or multiple pathways simultaneously. Antibody array is a recently developed approach applied for differential analysis of multiple protein posttranslational modification events in mammalian cells. It is based on the highly specific recognition between the immobilized antibodies on the array and their specific target proteins in a high-throughput screening format. Here we have described in detail two methods for differential analysis of protein tyrosine phosphorylation in cells by (1) using a single fluorescent protein capture format on membrane array and (2) a competitive protein capture method on glass surface array.

Bioengineering a humanized acne microenvironment model: proteomics analysis of host responses to Propionibacterium acnes infection in vivo

Acne is a human disease of the sebaceous hair follicle. Unlike humans, most animals produce little or no triglycerides in hair follicles to harbor Propionibacterium acnes a fact that has encumbered the development of novel treatments for acne lesions. Although genetic mutant mice with acne-like skins have been used for screening anti-acne drugs, the mice generally have deficits in immune system that turns out to be inappropriate to generate antibodies for developing acne vaccines. Here, we employed a bioengineering approach using a tissue chamber integrated with a dermis-based cell-trapped system (DBCTS) to mimic the in vivo microenvironment of acne lesions. Human sebocyte cell lines were grown in DBCTS as a scaffold and inserted into a perforated tissue chamber. After implantation of a tissue chamber bearing human sebocytes into ICR mice, P. acnes or PBS was injected into a tissue chamber to induce host immune response. Infiltrated cells such as neutrophils and macrophages were detectable in tissue chamber fluids. In addition, a proinflammatory cytokine macrophage-inflammatory protein-2 (MIP-2) was elevated after P. acnes injection. In tissue chamber fluids, 13 proteins including secreted proteins and cell matrix derived from mouse, human cells or P. acnes were identified by proteomics using isotope-coded protein label (ICPL) coupled to nano-LC-MS analysis. After P. acnes infection, four proteins including fibrinogen, alpha polypeptide, fibrinogen beta chain, S100A9, and serine protease inhibitor A3K showed altered concentrations in the mimicked acne microenvironment. The bioengineered acne model thus provides an in vivo microenvironment to study the interaction of host with P. acnes and offers a unique set-up for screening novel anti-acne drugs and vaccines.

Use of genome-wide high-throughput technologies in biomarker development

In recent years, the usage of high-throughput technologies in the fields of genomics, transcriptomics, proteomics and metabolomics for biomarker discovery has expanded enormously. Biomarkers can be applied for many purposes, including diagnosis, prognosis, staging and selecting appropriate patient therapy. In addition, biomarkers can provide information on disease mechanism or progression. Biomarker development for clinical application encompasses phases for their discovery and characterization, assay development and, finally, implementation using automated platforms employed in clinical laboratories. However, translation from bench to bedside outside a research-oriented environment has proven to be more difficult. This is reflected by only few new biomarkers being integrated into clinical application in the last years. This article reviews currently used high-throughput technologies for the identification of biomarkers, as well as present approaches to increase the percentage of biomarkers that pass the barriers for clinical application.

Fundamentals of protein separations: 50 years of nanotechnology, and growing

The separation of proteins in biology samples has long been recognized as an important and daunting endeavor that continues to have enormous impact on human health. Today's technology for protein separations has its origins in the early nanotechnology of the 1950s and 1960s, and the methods include immunoassays and other affinity extractions, electrophoresis, and chromatography. What is different today is the need to resolve and identify many low-abundance proteins within complex biological matrices. Multidimensional separations are the rule, high speed is needed, and the separations must be able to work with mass spectrometry for protein identification. Hybrid approaches that combine disparate separation tools (including recognition, electrophoresis, and chromatography) take advantage of the fact that no single class of separation can resolve the proteins in a biological matrix. Protein separations represent a developing area technologically, and understanding the principles of protein separations from a molecular and nanoscale viewpoint will enable today's researchers to invent tomorrow's technology.