Deciphering Asthma Biomarkers with Protein Profiling Technology

Asthma is a chronic inflammatory disease of the airways, resulting in bronchial hyperresponsiveness with every allergen exposure. It is now clear that asthma is not a single disease, but rather a multifaceted syndrome that results from a variety of biologic mechanisms. Asthma is further problematic given that the disease consists of many variants, each with its own etiologic and pathophysiologic factors, including different cellular responses and inflammatory phenotypes. These facets make the rapid and accurate diagnosis (not to mention treatments) of asthma extremely difficult. Protein biomarkers can serve as powerful detection tools in both clinical and basic research applications. Recent endeavors from biomedical researchers have developed technical platforms, such as cytokine antibody arrays, that have been employed and used to further the global analysis of asthma biomarker studies. In this review, we discuss potential asthma biomarkers involved in the pathophysiologic process and eventual pathogenesis of asthma, how these biomarkers are being utilized, and how further testing methods might help improve the diagnosis and treatment strain that current asthma patients suffer

Network-driven plasma proteomics expose molecular changes in the Alzheimer’s brain

Background Biological pathways that significantly contribute to sporadic Alzheimer’s disease are largely unknown and cannot be observed directly. Cognitive symptoms appear only decades after the molecular disease onset, further complicating analyses. As a consequence, molecular research is often restricted to late-stage post-mortem studies of brain tissue. However, the disease process is expected to trigger numerous cellular signaling pathways and modulate the local and systemic environment, and resulting changes in secreted signaling molecules carry information about otherwise inaccessible pathological processes. Results To access this information we probed relative levels of close to 600 secreted signaling proteins from patients’ blood samples using antibody microarrays and mapped disease-specific molecular networks. Using these networks as seeds we then employed independent genome and transcriptome data sets to corroborate potential pathogenic pathways. Conclusions We identified Growth-Differentiation Factor (GDF) signaling as a novel Alzheimer’s disease-relevant pathway supported by in vivo and in vitro follow-up experiments, demonstrating the existence of a highly informative link between cellular pathology and changes in circulatory signaling proteins

Network-Driven Plasma Proteomics Expose Molecular Changes in the Alzheimer\u27s Brain

Background: Biological pathways that significantly contribute to sporadic Alzheimer’s disease are largely unknown and cannot be observed directly. Cognitive symptoms appear only decades after the molecular disease onset, further complicating analyses. As a consequence, molecular research is often restricted to late-stage post-mortem studies of brain tissue. However, the disease process is expected to trigger numerous cellular signaling pathways and modulate the local and systemic environment, and resulting changes in secreted signaling molecules carry information about otherwise inaccessible pathological processes. Results: To access this information we probed relative levels of close to 600 secreted signaling proteins from patients’ blood samples using antibody microarrays and mapped disease-specific molecular networks. Using these networks as seeds we then employed independent genome and transcriptome data sets to corroborate potential pathogenic pathways. Conclusions: We identified Growth-Differentiation Factor (GDF) signaling as a novel Alzheimer’s disease-relevant pathway supported by in vivo and in vitro follow-up experiments, demonstrating the existence of a highly informative link between cellular pathology and changes in circulatory signaling proteins

Genomic and oncogenic preference of HBV integration in hepatocellular carcinoma

Hepatitis B virus (HBV) can integrate into the human genome, contributing to genomic instability and hepatocarcinogenesis. Here by conducting high-throughput viral integration detection and RNA sequencing, we identify 4,225 HBV integration events in tumour and adjacent non-tumour samples from 426 patients with HCC. We show that HBV is prone to integrate into rare fragile sites and functional genomic regions including CpG islands. We observe a distinct pattern in the preferential sites of HBV integration between tumour and non-tumour tissues. HBV insertional sites are significantly enriched in the proximity of telomeres in tumours. Recurrent HBV target genes are identified with few that overlap. The overall HBV integration frequency is much higher in tumour genomes of males than in females, with a significant enrichment of integration into chromosome 17. Furthermore, a cirrhosis-dependent HBV integration pattern is observed, affecting distinct targeted genes. Our data suggest that HBV integration has a high potential to drive oncogenic transformation

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