Proteomics provides direct biological information on proteins but is still a limited platform. Bo... more Proteomics provides direct biological information on proteins but is still a limited platform. Borrowing from genomics, its cancer-specific applications can be broadly categorized as (1) pure diagnostics, (2) biomarkers, (3) identification of root causes and (4) identification of cancer-specific network rewirings. Biological networks capture complex relationships between proteins and provide an appropriate means of contextualization. While playing significantly larger roles, especially in 1 and 3, progress in proteomics-specific network-based methods is lagging as compared to genomics. Rapid hardware advances and improvements in proteomic identification and quantification have given rise to much better quality data alongside advent of new network-based analysis methods. However, a tighter integration between analytics and hardware is still essential for network analysis to play more significant roles in proteomics analysis.
Objectives Serum amyloid A1 (SAA1) is a major acute phase protein that is increasingly used as a ... more Objectives Serum amyloid A1 (SAA1) is a major acute phase protein that is increasingly used as a reliable predictor of coronary artery disease (CAD). In this study we aim to screen the SAAI promoter and exons for genetic variants and to determine their association with CAD. In addition, we also carried out functional study on a variant of p. Gly90Asp encoded by the SAA1 gene. Methods Variant screening of SAA1 was performed using high resolution melting (HRM) analysis. Genetic association of p. Gly90Asp with CAD was determined in ...
Inflammation research : official journal of the European Histamine Research Society ... [et al.], Jan 1, 2012
Objective To investigate the effect of serum amyloid A1 (SAA1) on global gene expression in macro... more Objective To investigate the effect of serum amyloid A1 (SAA1) on global gene expression in macrophages derived from THP-1 monocytes. Materials and methods Global genetic expression in THP-1-derived macrophages was determined using Illumina HT-12 microarray chips and the results were validated by real-time PCR. Cytokine levels in cellular supernatant were quantified by ELISA. Results In total, 55 genes were upregulated with fold difference greater than two when THP-1-derived macrophages were incubated with SAA1 for 8 h. SAA1 is a strong cytokine inducer with significant upregulation of chemokines CCL1, CCL3, and CCL4 and this was confirmed by both real-time PCR and ELISA quantification. SAA1 also promotes the upregulation of genes involved in phagocytosis, anti-apoptosis, and tissue remodeling. Conclusions SAA1 appears to play an important role during the immune response and in chronic inflammatory diseases through the stimulation of genes involved in cytokine production, phagocytosis, and anti-apoptosis.
Proteomics provides important information - that may not be inferable from indirect sources such ... more Proteomics provides important information - that may not be inferable from indirect sources such as RNA or DNA - on key players in biological systems or disease states. However, it suffers from coverage and consistency problems. The advent of network-based analysis methods can help in overcoming these problems but requires careful application and interpretation. This review considers briefly current trends in proteomics technologies and understanding the causes of critical issues that need to be addressed - i.e., incomplete data coverage and inter-sample inconsistency. On the coverage issue, we argue that holistic analysis based on biological networks provides a suitable background on which more robust models and interpretations can be built upon; and we introduce some recently developed approaches. On consistency, group-based approaches based on identified clusters, as well as on properly integrated pathway databases, are particularly useful. Despite that protein interactions and pathway networks are still largely incomplete, given proper quality checks, applications and reasonably sized data sets, they yield valuable insights that greatly complement data generated from quantitative proteomics.
Proteomics provides direct biological information on proteins but is still a limited platform. Bo... more Proteomics provides direct biological information on proteins but is still a limited platform. Borrowing from genomics, its cancer-specific applications can be broadly categorized as (1) pure diagnostics, (2) biomarkers, (3) identification of root causes and (4) identification of cancer-specific network rewirings. Biological networks capture complex relationships between proteins and provide an appropriate means of contextualization. While playing significantly larger roles, especially in 1 and 3, progress in proteomics-specific network-based methods is lagging as compared to genomics. Rapid hardware advances and improvements in proteomic identification and quantification have given rise to much better quality data alongside advent of new network-based analysis methods. However, a tighter integration between analytics and hardware is still essential for network analysis to play more significant roles in proteomics analysis.
Objectives Serum amyloid A1 (SAA1) is a major acute phase protein that is increasingly used as a ... more Objectives Serum amyloid A1 (SAA1) is a major acute phase protein that is increasingly used as a reliable predictor of coronary artery disease (CAD). In this study we aim to screen the SAAI promoter and exons for genetic variants and to determine their association with CAD. In addition, we also carried out functional study on a variant of p. Gly90Asp encoded by the SAA1 gene. Methods Variant screening of SAA1 was performed using high resolution melting (HRM) analysis. Genetic association of p. Gly90Asp with CAD was determined in ...
Inflammation research : official journal of the European Histamine Research Society ... [et al.], Jan 1, 2012
Objective To investigate the effect of serum amyloid A1 (SAA1) on global gene expression in macro... more Objective To investigate the effect of serum amyloid A1 (SAA1) on global gene expression in macrophages derived from THP-1 monocytes. Materials and methods Global genetic expression in THP-1-derived macrophages was determined using Illumina HT-12 microarray chips and the results were validated by real-time PCR. Cytokine levels in cellular supernatant were quantified by ELISA. Results In total, 55 genes were upregulated with fold difference greater than two when THP-1-derived macrophages were incubated with SAA1 for 8 h. SAA1 is a strong cytokine inducer with significant upregulation of chemokines CCL1, CCL3, and CCL4 and this was confirmed by both real-time PCR and ELISA quantification. SAA1 also promotes the upregulation of genes involved in phagocytosis, anti-apoptosis, and tissue remodeling. Conclusions SAA1 appears to play an important role during the immune response and in chronic inflammatory diseases through the stimulation of genes involved in cytokine production, phagocytosis, and anti-apoptosis.
Proteomics provides important information - that may not be inferable from indirect sources such ... more Proteomics provides important information - that may not be inferable from indirect sources such as RNA or DNA - on key players in biological systems or disease states. However, it suffers from coverage and consistency problems. The advent of network-based analysis methods can help in overcoming these problems but requires careful application and interpretation. This review considers briefly current trends in proteomics technologies and understanding the causes of critical issues that need to be addressed - i.e., incomplete data coverage and inter-sample inconsistency. On the coverage issue, we argue that holistic analysis based on biological networks provides a suitable background on which more robust models and interpretations can be built upon; and we introduce some recently developed approaches. On consistency, group-based approaches based on identified clusters, as well as on properly integrated pathway databases, are particularly useful. Despite that protein interactions and pathway networks are still largely incomplete, given proper quality checks, applications and reasonably sized data sets, they yield valuable insights that greatly complement data generated from quantitative proteomics.
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