Antibody array generation and use

Protein profiling of mechanically processed lipoaspirates: discovering wound healing and anti-fibrotic biomarkers in nanofat

BACKGROUND

Nanofat is an injectable oily emulsion, rich in adipose derived stem cells (ADSCs) and growth factors. It is prepared from lipoaspirates through mechanical emulsification and filtration. Despite being successfully used in several procedures in regenerative medicine such as scar attenuation, skin rejuvenation and treatment of chronic wounds, little is known about exactly how nanofat induces regeneration in treated skin at the molecular level.

METHODS

Microfat and nanofat samples were isolated from 18 healthy patients. Proteomic profiling was performed through untargeted mass spectrometry proteomics and multiplex antibody arrays. Pathway enrichment analysis of differentially expressed proteins between microfat and nanofat was performed using Gene Ontology, Reactome and KEGG as reference databases.

RESULTS

Untargeted proteomics showed that upregulated genes in nanofat are involved in innate immunity responses, coagulation and wound healing, while downregulated genes were linked to cellular migration and extracellular matrix (ECM) production. Secretome array screening of microfat and nanofat samples showed no significantly different expression, which strongly suggests that the mechanical emulsification step does not affect the concentration of tissue regeneration biomarkers. The identified proteins are involved in wound healing, cellular migration, extracellular matrix remodelling, angiogenesis, stress response and immune response.

CONCLUSIONS

Mechanical processing of lipoaspirates into nanofat significantly influences the proteome profile by enhancing inflammation, antimicrobial and wound healing pathways. Nanofat is extremely rich in tissue repair and tissue remodelling factors.

CLINICAL RELEVANCE STATEMENT

This study shows that the effects of Micro- and Nanofat treatment are based on upregulated inflammation, antimicrobial and wound healing pathways. Mechanical emulsification does not alter the concentration of tissue regeneration biomarkers.

Spatial Bias in Antibody Microarrays May Be an Underappreciated Source of Variability

Antibody microarrays enable multiplexed protein detection with minimal reagent consumption, but they continue to be plagued by lack of reproducibility. Chemically functionalized glass slides are used as substrates, yet antibody binding spatial inhomogeneity across the slide has not been analyzed in antibody microarrays. Here, we characterize spatial bias across five commercial slides patterned with nine overlapping dense arrays (by combining three buffers and three different antibodies), and we measure signal variation for both antibody immobilization and the assay signal, generating 270 heatmaps. Spatial bias varied across models, and the coefficient of variation ranged from 4.6 to 50%, which was unexpectedly large. Next, we evaluated three layouts of spot replicates-local, random, and structured random-for their capacity to predict assay variation. Local replicates are widely used but systematically underestimate the whole-slide variation by up to seven times; structured random replicates gave the most accurate estimation. Our results highlight the risk and consequences of using local replicates: the underappreciation of spatial bias as a source of variability, poor assay reproducibility, and possible overconfidence in assay results. We recommend the detailed characterization of spatial bias for antibody microarrays and the description and use of distributed positive replicates for research and clinical applications.

Apoptosis regulation in the penumbra after ischemic stroke: expression of pro- and antiapoptotic proteins

Ischemic stroke is the leading cause of human disability and mortality in the world. The main problem in stroke therapy is the search of efficient neuroprotector capable to rescue neurons in the potentially salvageable transition zone (penumbra), which is expanding after brain damage. The data on molecular mechanisms of penumbra formation and expression of diverse signaling proteins in the penumbra during first 24 h after ischemic stroke are discussed. Two basic features of cell death regulation in the ischemic penumbra were observed: (1) both apoptotic and anti-apoptotic proteins are simultaneously over-expressed in the penumbra, so that the fate of individual cells is determined by the balance between these opposite tendencies. (2) Similtaneous and concerted up-regulation in the ischemic penumbra of proteins that execute apoptosis (caspases 3, 6, 7; Bcl-10, SMAC/DIABLO, AIF, PSR), signaling proteins that regulate different apoptosis pathways (p38, JNK, DYRK1A, neurotrophin receptor p75); transcription factors that control expression of various apoptosis regulation proteins (E2F1, p53, c-Myc, GADD153); and proteins, which are normally involved in diverse cellular functions, but stimulate apoptosis in specific situations (NMDAR2a, Par4, GAD65/67, caspase 11). Hence, diverse apoptosis initiation and regulation pathways are induced simultaneously in penumbra from very different initial positions. Similarly, various anti-apoptotic proteins (Bcl-x, p21/WAF-1, MDM2, p63, PKBα, ERK1, RAF1, ERK5, MAKAPK2, protein phosphatases 1α and MKP-1, estrogen and EGF receptors, calmodulin, CaMKII, CaMKIV) are upregulated. These data provide an integral view of neurodegeneration and neuroprotection in penumbra. Some discussed proteins may serve as potential targets for anti-stroke therapy.

Serum interleukin-8 as a potential diagnostic biomarker in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) has poor prognosis mainly due to the difficulty of making early diagnosis. Therefore, novel biomarkers are critically needed.

OBJECTIVE

We aimed to investigate the diagnostic value of serum interleukin-8 (IL-8) in ESCC.

METHODS

Data mining of TCGA was used to analyze expression level of IL-8 mRNA in esophageal carcinoma. Serum levels of IL-8 were measured in 103 ESCC patients and 86 normal controls by ELISA. Receiver operating characteristic (ROC) curve was used to evaluate its diagnostic accuracy.

RESULTS

IL-8 mRNA expression level and serum IL-8 concentration were both statistically higher in patients than normal controls (P< 0.001). ROC curve demonstrated that the optimum diagnostic cut-off for serum IL-8 was 80.082 pg/mL, providing an area under the curve (AUC) of 0.694 (95% CI: 0.620-0.768), with specificity of 86.0% and sensitivity of 42.7%. The AUC for early-stage ESCC was 0.618 (95% CI: 0.499-0.737), with sensitivity of 35.3% and specificity of 86.0%. Kaplan-Meier analysis and the log-rank test indicated that IL-8 may not be a prognostic predictor for ESCC.

CONCLUSIONS

Serum IL-8 was highly expressed in ESCC patients and may be a potential marker for early diagnosis of ESCC.

The Interaction of the Gut Microbiota with the Mucus Barrier in Health and Disease in Human

Glycoproteins are major players in the mucus protective barrier in the gastrointestinal and other mucosal surfaces. In particular the mucus glycoproteins, or mucins, are responsible for the protective gel barrier. They are characterized by their high carbohydrate content, present in their variable number, tandem repeat domains. Throughout evolution the mucins have been maintained as integral components of the mucosal barrier, emphasizing their essential biological status. The glycosylation of the mucins is achieved through a series of biosynthetic pathways processes, which generate the wide range of glycans found in these molecules. Thus mucins are decorated with molecules having information in the form of a glycocode. The enteric microbiota interacts with the mucosal mucus barrier in a variety of ways in order to fulfill its many normal processes. How bacteria read the glycocode and link to normal and pathological processes is outlined in the review.

Advances in the development of human protein microarrays

INTRODUCTION

High-content protein microarrays in principle enable the functional interrogation of the human proteome in a broad range of applications, including biomarker discovery, profiling of immune responses, identification of enzyme substrates, and quantifying protein-small molecule, protein-protein and protein-DNA/RNA interactions. As with other microarrays, the underlying proteomic platforms are under active technological development and a range of different protein microarrays are now commercially available. However, deciphering the differences between these platforms to identify the most suitable protein microarray for the specific research question is not always straightforward. Areas covered: This review provides an overview of the technological basis, applications and limitations of some of the most commonly used full-length, recombinant protein and protein fragment microarray platforms, including ProtoArray Human Protein Microarrays, HuProt Human Proteome Microarrays, Human Protein Atlas Protein Fragment Arrays, Nucleic Acid Programmable Arrays and Immunome Protein Arrays. Expert commentary: The choice of appropriate protein microarray platform depends on the specific biological application in hand, with both more focused, lower density and higher density arrays having distinct advantages. Full-length protein arrays offer advantages in biomarker discovery profiling applications, although care is required in ensuring that the protein production and array fabrication methodology is compatible with the required downstream functionality.

Tumor tissue protein signatures reflect histological grade of breast cancer

Histological grade is one of the most commonly used prognostic factors for patients diagnosed with breast cancer. However, conventional grading has proven technically challenging, and up to 60% of the tumors are classified as histological grade 2, which represents a heterogeneous cohort less informative for clinical decision making. In an attempt to study and extend the molecular puzzle of histologically graded breast cancer, we have in this pilot project searched for additional protein biomarkers in a new space of the proteome. To this end, we have for the first time performed protein expression profiling of breast cancer tumor tissue, using recombinant antibody microarrays, targeting mainly immunoregulatory proteins. Thus, we have explored the immune system as a disease-specific sensor (clinical immunoproteomics). Uniquely, the results showed that several biologically relevant proteins reflecting histological grade could be delineated. In more detail, the tentative biomarker panels could be used to i) build a candidate model classifying grade 1 vs. grade 3 tumors, ii) demonstrate the molecular heterogeneity among grade 2 tumors, and iii) potentially re-classify several of the grade 2 tumors to more like grade 1 or grade 3 tumors. This could, in the long-term run, lead to improved prognosis, by which the patients could benefit from improved tailored care.

Protein Arrays I: Antibody Arrays

Antibody arrays represent one of the very early protein array systems where antibodies are used to capture and detect target proteins in a high-throughput platform. The development of high-quality antibodies, nanomaterial-based novel detection probes, as well as innovative imaging technologies and computational tools has tremendously improved the sensitivity, specificity, and robustness of antibody arrays during the past decade. In this protocol we will incorporate the most updated innovations and developments of antibody arrays into the step-by-step experimental procedures. This includes antibody printing, sample preparation, array detection, as well as imaging and data analysis. Antibody array could be used for cytokine profiling or mapping of phosphorylation, glycosylation, or other post-translational modifications of target proteins.

Technical Advances of the Recombinant Antibody Microarray Technology Platform for Clinical Immunoproteomics

In the quest for deciphering disease-associated biomarkers, high-performing tools for multiplexed protein expression profiling of crude clinical samples will be crucial. Affinity proteomics, mainly represented by antibody-based microarrays, have during recent years been established as a proteomic tool providing unique opportunities for parallelized protein expression profiling. But despite the progress, several main technical features and assay procedures remains to be (fully) resolved. Among these issues, the handling of protein microarray data, i.e. the biostatistics parts, is one of the key features to solve. In this study, we have therefore further optimized, validated, and standardized our in-house designed recombinant antibody microarray technology platform. To this end, we addressed the main remaining technical issues (e.g. antibody quality, array production, sample labelling, and selected assay conditions) and most importantly key biostatistics subjects (e.g. array data pre-processing and biomarker panel condensation). This represents one of the first antibody array studies in which these key biostatistics subjects have been studied in detail. Here, we thus present the next generation of the recombinant antibody microarray technology platform designed for clinical immunoproteomics.

Protein Profiling Gastric Cancer and Neighboring Control Tissues Using High-Content Antibody Microarrays

In this study, protein profiling was performed on gastric cancer tissue samples in order to identify proteins that could be utilized for an effective diagnosis of this highly heterogeneous disease and as targets for therapeutic approaches. To this end, 16 pairs of postoperative gastric adenocarcinomas and adjacent non-cancerous control tissues were analyzed on microarrays that contain 813 antibodies targeting 724 proteins. Only 17 proteins were found to be differentially regulated, with much fewer molecules than the numbers usually identified in studies comparing tumor to healthy control tissues. Insulin-like growth factor-binding protein 7 (IGFBP7), S100 calcium binding protein A9 (S100A9), interleukin-10 (IL‐10) and mucin 6 (MUC6) exhibited the most profound variations. For an evaluation of the proteins’ capacity for discriminating gastric cancer, a Receiver Operating Characteristic curve analysis was performed, yielding an accuracy (area under the curve) value of 89.2% for distinguishing tumor from non-tumorous tissue. For confirmation, immunohistological analyses were done on tissue slices prepared from another cohort of patients with gastric cancer. The utility of the 17 marker proteins, and particularly the four molecules with the highest specificity for gastric adenocarcinoma, is discussed for them to act as candidates for diagnosis, even in serum, and targets for therapeutic approaches.

Proteomic-Based Approaches for the Study of Cytokines in Lung Cancer

Proteomic techniques are currently used to understand the biology of different human diseases, including studies of the cell signaling pathways implicated in cancer progression, which is important in knowing the roles of different proteins in tumor development. Due to its poor prognosis, proteomic approaches are focused on the identification of new biomarkers for the early diagnosis, prognosis, and targeted treatment of lung cancer. Cytokines are proteins involved in inflammatory processes and have been proposed as lung cancer biomarkers and therapeutic targets because it has been reported that some cytokines play important roles in tumor development, invasion, and metastasis. In this review, we aim to summarize the different proteomic techniques used to discover new lung cancer biomarkers and therapeutic targets. Several cytokines have been identified as important players in lung cancer using these techniques. We underline the most important cytokines that are useful as biomarkers and therapeutic targets. We also summarize some of the therapeutic strategies targeted for these cytokines in lung cancer.

Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays

Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts.

Emerging proteomic technologies for elucidating context-dependent cellular signaling events: A big challenge of tiny proportions

Aberrant cell signaling events either drive or compensate for nearly all pathologies. A thorough description and quantification of maladaptive signaling flux in disease is a critical step in drug development, and complex proteomic approaches can provide valuable mechanistic insights. Traditional proteomics-based signaling analyses rely heavily on in vitro cellular monoculture. The characterization of these simplified systems generates a rich understanding of the basic components and complex interactions of many signaling networks, but they cannot capture the full complexity of the microenvironments in which pathologies are ultimately made manifest. Unfortunately, techniques that can directly interrogate signaling in situ often yield mass-limited starting materials that are incompatible with traditional proteomics workflows. This review provides an overview of established and emerging techniques that are applicable to context-dependent proteomics. Analytical approaches are illustrated through recent proteomics-based studies in which selective sample acquisition strategies preserve context-dependent information, and where the challenge of minimal starting material is met by optimized sensitivity and coverage. This review is organized into three major technological themes: (i) LC methods in line with MS; (ii) antibody-based approaches; (iii) MS imaging with a discussion of data integration and systems modeling. Finally, we conclude with future perspectives and implications of context-dependent proteomics.

Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic-based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research.