Secretome-based proteomics reveals sulindac-modulated proteins released from colon cancer cells

Although experiments in rodents and human population-based studies have demonstrated the efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs) such as sulindac in colorectal cancer (CRC) prevention, a detailed knowledge of the underlying mechanism of action of this drug is limited. To better understand the chemopreventitive effects of sulindac, especially early sulindac-induced apoptotic events, we used the CRC cell line LIM1215 as an experimental model, focusing on proteins secreted into the LIM1215 culture medium - i.e., the secretome. This subproteome comprises both soluble-secreted proteins and exosomes (30-100?nm diameter membrane vesicles released by several cell types). Selected secretome proteins whose expression levels were dysregulated by 1?mM sulindac treatment over 16?h were analyzed using 2-D DIGE, cytokine array, Western blotting, and MS. Overall, 150 secreted proteins were identified, many of which are implicated in molecular and cellular functions such as cell proliferation, differentiation, adhesion, invasion, angiogenesis, metastasis, and apoptosis. Our secretome-based proteomic studies have identified several secreted modulators of sulindac-induced apoptosis action (e.g., Mac-2 binding protein, Alix, 14-3-3 isoforms, profilin-1, calumenin/Cab45 precursors, and the angiogenic/tumor growth factors interleukin 8 (IL-8) and growth related oncogene (GRO-α)) that are likely to improve our understanding of the chemopreventitive action of this NSAID in CRC.     

The human synovial fluid proteome: A key factor in the pathology of joint disease

This review aims to summarise our knowledge to date on the protein complement of the synovial fluid (SF). The tissues, structure and pathophysiology of the synovial joint are briefly described. The salient features of the SF proteome, how it is composed and the influence of arthritic disease are highlighted and discussed. The concentrations of proteins that have been detected and quantified in SF are drawn together from the literature on osteoarthritis, rheumatoid arthritis and juvenile idiopathic arthritis. The measurements are plotted to give a perspective on the dynamic range of protein levels within the SF. Approaches to proteomic analysis of SF to date are discussed along with their findings. From the recent literature reviewed within, it is becoming increasingly clear that analysis of the SF proteome as a whole, could deliver the most valuable differential diagnostic fingerprints of a number of arthritic disorders. Further development of proteomic platforms could characterise prognostic profiles to improve the clinician's ability to resolve unremitting disease by existing and novel therapeutics.     

Using tissue samples for proteomic studies—Critical considerations

From my experience of 22 years working in a pathology research laboratory and overseeing dozens of collaborations with research groups from basic sciences and industry, I have the impression that researchers are rarely aware of the special issues related to acquisition and processing of frozen or formalin-fixed tissue samples for proteomic analysis. While challenges are expected for formalin-fixed tissues because of the cross-linking activities of formaldehyde, researchers believe when using frozen tissue samples they are safe and always have excellent material to analyze—but this is not always the case. It is alarming that many researchers do not question the quality of the tissue samples they are analyzing and focus only on their analytical technique. Standardization of the entire workflow from test ordering to the report of the proteomic assay, with special emphasis on the preanalytical phase, is crucial for successful integration of proteomic studies in the clinic as protein profiles may change due to sample processing before the proteomic analysis is performed. The aim of this review is to discuss the progress of proteomic studies with human tissues and to highlight the challenges that must be understood and addressed for successful translation of proteomic methods to clinical practice.     

New horizon for breast cancer biomarker discoveries: What might the liquid biopsy of nipple aspirate fluid hold?

The existence of cellular, molecular and biochemical heterogeneity of human breast cancers reveals the intricacy of biomarkers complexity, stimulating studies on new approaches (like “liquid biopsies”) for the improvements in precision medicine. Breast cancer is recognized as a leading cause of morbidity and mortality worldwide with tumors significantly diverse and containing many types of cells showing different genetic and epigenetic profiles. In this field, the technology of liquid biopsy (applied to a fluid produced by breast gland, named nipple aspirate fluids, NAF) highlights the power of combining basic and clinical research. NAF is the mirror of the entire ductal/alveolar breast tree providing almost complete proteomic profile and a valuable source for biomarker discovery, in non‐invasive manner than tissue biopsies. The liquid biopsy technology using NAF may represent the outstanding breakthrough of proteomic cancer research revealing novel diagnostic and prognostic applications. In conjunction to metabolomic and degradome profiling, the use of NAF as liquid biopsy approach will improve the detection of changes in the cellular microenvironment of the breast tumors, understanding molecular and biochemical mechanisms which drive breast tumor initiation, maintenance and progression, and finally enhancing the development of novel drug targets and new treatment strategies.     

Towards a comprehensive proteome of normal and malignant human colon tissue by 2-D-LC-ESI-MS and 2-DE proteomics and identification of S100A12 as potential cancer biomarker

The aim of this study was to characterize the proteome of normal and malignant colonic tissue. We previously studied the colon proteome using 2‐DE and MALDI‐MS and identified 734 proteins (Roeßler, M., Rollinger, W., Palme S., Hagmann, M.‐L., et al.., Clin. Cancer Res. 2005, 11, 6550–6557). Here we report the identification of additional colon proteins from the same set of tissue samples using a complementary nano‐flow 2‐D‐LC‐ESI‐MS. In total, 484 proteins were identified in colon. Of these, 252 had also been identified by the 2‐DE/MALDI‐MS approach, whereas 232 proteins were unique to the 2‐D‐LC‐ESI‐MS analysis. Comparing protein expression in neoplastic and normal colon tissue indicated elevated expression of several proteins in colorectal cancer, among them the well established tumor marker carcinoembryonic antigen, as well as calnexin, 40S ribosomal protein S15a, serpin H1, and S100A12. Overexpression of these proteins was confirmed by immunoblotting. Serum levels of S100A12 were determined by ELISA and were found to be strongly elevated in colorectal cancer patients compared to healthy individuals. We conclude, that 2‐D‐LC‐ESI‐MS is a powerful approach to identify and compare protein profiles of tissue samples, that it is complementary to 2‐DE/MALDI‐MS approaches and has the potential to identify novel biomarkers.     

Comparative proteomic analysis to discover potential therapeutic targets in human multiple myeloma

To clarify the molecular mechanisms that participate in the formation of multiple myeloma (MM) and to detect any tumor-related biomarkers, we performed proteomic analysis of cellular protein extracts from MM cells and normal plasma cells. Plasma cells from nine patients with newly diagnosed MM and nine healthy donors were purified by using anti-CD138 based immunomagnetic bead-positive selection. The protein profiles of purified MM and normal plasma cells were compared using 2-DE. We identified a total of 43 differentially expressed proteins, and confirmed with Western blotting six proteins. The altered proteins were analyzed using the software program Pathway Studio and the biological network can be accessed via (http://life-health.jnu.edu.cn/pathway/pathway.html). Further functional studies showed that annexin A1 knock down modestly induces lethality alone and potentiates the effects of dexamethasone on both dexamethasone-sensitive and dexamethasone-resistant MM cells. By correlating the proteomic data with these functional studies, the current results provide not only new insights into the pathogenesis of MM but also direct implications for the development of novel anti-MM therapeutic strategies and could lead to the discovery of potential therapeutic targets. Future molecular and functional studies would provide novel insights into the roles of these dysregulated proteins in the molecular etiology of MM.     

Construction of human monoclonal single-chain Fv antibodies against small-cell lung cancer by phage display libraries derived from cell-immunized SCID mice engrafted with human peripheral blood lymphocytes

In this study, we describe a phage display strategy to obtain human monoclonal single-chain Fv (scFv) antibodies binding target cancer cell surface proteins. By developing a cancer cell immunization protocol for SCID mice engrafted with human peripheral blood lymphocytes in combination with an antibody phage display method, we have isolated phage antibodies binding small-cell lung cancer cell line H889 by subtractive selection. One of the isolated scFv antibodies, 12EAb, recognized the E2 component of pyruvate dehydrogenase complex (PDC-E2) by immunoprecipitation according to MALDI-TOF MS analysis. Furthermore, we have confirmed the plasma membrane localization of PDC-E2 in small-cell lung cancer cells by immunocytochemistry and cell surface protein biotinylation, although PDC-E2 is usually located in the mitochondrial matrix. These results, including unique localization of identified antigens, were obtained by proteomic approaches. The present methods can be applied to generate human monoclonal scFv antibodies against tumor cells and to identify new molecular targets for immunotherapy and markers for diagnosis.     

基于BP神经网络的肿瘤特征基因选取

该文提出基于BP神经网络的灵敏度分析方法,并用于选取肿瘤特征基因。以结肠癌基因表达谱为例,首先定义基因对BP神经网络模型输出函数的灵敏度,递归去除灵敏度较低的若干基因,生成一组嵌套的候选特征基因子集。然后以支持向量机为分类器,检验候选特征基因子集对样本分类的贡献,选取错分率最低的候选特征基因子集为结肠癌特征基因子集。通过实验对比,该特征基因子集的分类结果优于文献给出的其他特征基因子集,表明了该方法的可行性和有效性。     

Proteomic approaches to the study of malignant lymphoma: Analyses on patient samples

We describe the application of proteomic techniques for protein profiling and biomarker discovery in malignant lymphoma. Hematologic malignancies are primarily characterized by their clinical, morphological, immunophenotypical, and molecular-genetic features. However, when based on these parameters, apparently identical lymphomas may show distinct clinical courses, suggesting underlying biological heterogeneity. Recent proteomic analyses have identified differences in protein expression both with regard to subclassification of the malignant lymphoma entities, as well as in correlation with clinical outcome. In this review, studies on quantification of differential protein expression in and between malignant lymphoma entities are included. Studies are included that are based on patient samples, that is, serum/plasma or cytological specimens, as well as intact tumor tissues, together with studies that focus on tumor cells alone, or in conjunction with the tumor microenvironment. For biomarker discovery in malignant lymphoma, these approaches are used to uncover the underlying biological mechanisms and identify proteins with potential diagnostic and prognostic utility, either as predictive biomarkers or as novel future treatment targets.     

Urinary proteomics in renal pathophysiology: Impact of proteinuria

Urinary differential proteomics is used to study renal pathophysiological mechanisms, find novel markers of biological processes and renal diseases, and stratify patients according to proteomic profiles. The proteomic procedure determines the pathophysiological meaning and clinical relevance of results. Urine samples for differential proteomic studies are usually normalized by protein content, regardless of its pathophysiological characteristics. In the field of nephrology, this approach translates into the comparison of a different fraction of the total daily urine output between proteinuric and nonproteinuric samples. Accordingly, alterations in the level of specific proteins found by this method reflect the relative presence of individual proteins in the urine; but they do not necessarily show alterations in their daily excretion, which is a key parameter for the understanding of the pathophysiological meaning of urinary components. For renal pathophysiology studies and clinical biomarker identification or determination, an alternative proteomic concept providing complementary information is based on sample normalization by daily urine output, which directly informs on changes in the daily excretion of individual proteins. This is clinically important because daily excretion (rather than absolute or relative concentration) is the only self-normalized way to evaluate the real meaning of urinary parameters, which is also independent of urine concentration.     

Impact of incomplete DNase I treatment on human macrophage proteome analysis

The aim of our study was to analyze the proteomic pattern of human macrophages obtained over a 4 year period from blood donors. The purpose was to simulate a long-term clinical study to assess the application of 2-D DIGE technique for differential proteomic analysis of these scarce samples. Bioinformatic analysis of 2-D DIGE gels of 19 different cultures of macrophages assessed whether they did or did not contain at least specific five spots identified by MS as being or containing bovine deoxyribonuclease I (DNase I). Bovine DNase I was used during sample treatment to remove nucleic acids from protein extracts. Macrophages were classified in two groups, which appeared to be differentiated by the completeness of DNase I treatment. Further detailed analysis revealed a different proteomic pattern of macrophage protein samples according to the completeness of this treatment. The major group of proteins affected, accounting for one third of the differentially expressed proteins, included proteins involved in cell motion and actin cytoskeleton reorganization. The use of DNase I for the removal of nucleic acids from protein samples must be avoided in proteomic studies since it can generate bias in the analysis of protein expression patterns.     

The murine plasma protein response to polymicrobial intra-abdominal sepsis

Protein biomarkers in the peripheral blood could potentially be used as early indicators of sepsis and a means to stratify patients for clinical trials. Although individual molecular markers have been proposed for sepsis, none has clinical utility. The global changes in plasma proteins over the clinical course of sepsis have not been characterized using proteomic methods. We used cecal ligation and puncture to induce polymicrobial sepsis in mice and generated plasma protein profiles using 2‐D DIGE of plasma from septic mice and surgical controls. Replicate cohorts (n = 3) of 4–7 animals each were used to identify 62 gel features that changed significantly (Student's t‐test, p<0.05). We identified a suite of plasma proteins that describe uniquely the host plasma response to polymicrobial septic insult. Principal components analysis of protein abundance showed that ～90% of the variability between samples was due to sepsis. In addition to canonical acute phase proteins, we identified proteins that are associated with metabolic changes (e.g. α‐2 HS glycoprotein and zinc α‐2 glycoprotein) consistent with the pathophysiology of sepsis. The panel of sepsis‐associated molecular markers identified herein may prove useful in the diagnosis and categorization of sepsis.     

Protein profiling of oral brush biopsies: S100A8 and S100A9 can differentiate between normal, premalignant, and tumor cells

In oral mucosa lesions it is frequently difficult to differentiate between precursor lesions and already manifest oral squamous cell carcinoma. Therefore, multiple scalpel biopsies are necessary to detect tumor cells already in early stages and to guarantee an accurate follow‐up. We analyzed oral brush biopsies (n = 49) of normal mucosa, inflammatory and hyperproliferative lesions, and oral squamous cell carcinoma with ProteinChip Arrays (SELDI) as a non‐invasive method to characterize putative tumor cells. Three proteins were found that differentiated between these three stages. These three proteins are able to distinguish between normal cells and tumor cells with a sensitivity of 100% and specificity of 91% and can distinguish inflammatory/hyperproliferative lesions from tumor cells with a sensitivity of up to 91% and specificity of up to 90%. Two of these proteins have been identified by immunodepletion as S100A8 and S100A9 and this identification was confirmed by immunocytochemistry. For the first time, brush biopsies have been successfully used for proteomic biomarker discovery. The identified protein markers are highly specific for the distinction of the three analyzed stages and therewith reflect the progression from normal to premalignant non‐dysplastic and finally to tumor tissue. This knowledge could be used as a first diagnostic step in the monitoring of mucosal lesions.     

Understanding dendritic cell biology and its role in immunological disorders through proteomic profiling

Dendritic cells (DC) have always been present on the bright spot of immune research. They have been extensively studied for the last 35 years, and much is known about their different phenotypes, stimulatory capacity, and role in the immune system. During the last 15 years, great attention has been given to studies on global gene and protein expression profiles during the differentiation and maturation processes of these cells. It is well understood that studying the proteome, together with information on the role of protein post-translational modifications (PTM), will reveal the real dynamics of a living cell. The rapid increase of proteomic studies during the last decade describing the differentiation and maturation process in DCs, as well as modifications brought by the use of different compounds that either increase or decrease their immunogenicity, reflects the importance of understanding the molecular processes behind the functional properties of these cells. In the present review, we will give an overview of proteomic studies focusing on DCs. Thereby we will concentrate on the importance of these studies in understanding DC behavior from a molecular point of view and how these findings have aided in understanding the differences in functional properties of these cells.     

Shotgun immunoproteomics to identify disease‐associated bacterial antigens: Application to human colon cancer

Circulating antibodies reflect a mirror view of invading antigens that are related to infection and cancer. This was recently exemplified by using serum antibodies to capture Streptococcus bovis antigens followed by MS to generate antigen profiles that were diagnostic for colon cancer. These bacterial antigen profiles have a high potential to aid in the immuno‐diagnosis of this disease, as the magnitude of the immune response to bacterial antigens is, in general, superior to the immune response against tumor (self) antigens. In this study, the identity of individual colon cancer‐associated streptococcal antigens was revealed by enrichment of these “diagnostic” antigens by selected patient antibodies followed by high‐accuracy nanoLC‐MS/MS peptide identification. This showed that both the histone‐like protein HlpA and the ribosomal protein Rp L7/L12 are members of the colon cancer‐associated S. bovis immunome. Both antigens also seem to belong to the group of anchorless surface proteins, like 14 additional proteins that were co‐identified in S. bovis cell wall extracts. Among these were the known streptococcal anchorless surface proteins GAPDH and Enolase. Taken together, these data show that shotgun immunoproteomics, combining immunocapture in‐line with LC MS/MS, is a convenient approach for the rapid identification of disease‐associated bacterial antigens.     

Vitreous humor in the pathologic scope: Insights from proteomic approaches

The vitreous humor (VH) is the largest component of the eye. It is a colorless, gelatinous, highly hydrated matrix that fills the posterior segment of the eye between the lens and retina in vertebrates. In VH, a diversity of proteins that can influence retinal physiology is present, including growth factors, hormones, proteins with transporter activity, and enzymes. More importantly, the protein composition of VH has been described as being altered in a number of disease states. Therefore, attempts aiming at establishing a map of VH proteins and detecting putative biomarkers for ocular illness or protein fluctuations with putative physiologic significance were conducted over the last two decades, using proteomic approaches. Proteomic strategies often involve gel-based or LC techniques as sample fractioning approaches, subsequently coupled with MS procedures. This set of studies resulted in the proteomic characterization of a range of ocular disease samples, with particular incidence on diabetic retinopathy. However, practical therapeutic applications arising from these studies are scarce at the moment. A pertinent example of therapeutic targets arising from VH proteomics has emerged concerning vasoproliferative factors present in the vitreous, which should be involved in neovascularization and subsequent fibrovascular proliferation of the retina, in ocular disease context. Therefore, this review attempts to sum up the information acquired from the proteomic approaches to ocular disease conducted in VH samples, highlighting its clinical potential for disclosing ocular disease mechanisms and engendering pharmacological therapeutic treatments.     

Proteomic approaches to the analysis of atopic dermatitis and new insights from interactomics

In this review, we summarized the recent findings regarding atopic dermatitis (AD) skin disease based on proteomic studies. AD is a chronic relapsing inflammatory skin disease typically characterized by a distribution of eczematous skin lesions with lichenification, pruritic excoriations and dry skin with wide varieties of pathophysiological aspects. We summarized the alterations of the protein expressions in the primary cultured AD cells from the patients'-biopsy samples that were mostly analyzed by 2-D PAGE and MALDI-TOF. Further, we also conducted protein-protein interaction mapping according to the obtained candidate proteins. As a result, we found that several hub proteins, i.e. heat shock 70-kDa protein 2, heat shock 70-kDa protein 9, tumor rejection antigen-1 (gp96), spermatogenesis-associated factor, protein kinase C inhibitor 1, vimentin, tenascin, semaphorin 4f (SEMA4F), complement component C1r deficiency (C1R) and apolipoprotein A (LPA), respectively, could receive important consideration in future studies. Since the mechanism of AD disease has been shown to be complex, our results may provide new clues to aid understanding of AD.     

Application of proteomic technologies to discover and identify biomarkers for periodontal diseases in gingival crevicular fluid: A review

Periodontal disease is a bacterial infection that destroys the gingiva and surrounding tissues of the oral cavity. In recent years, studies have shown a definite association between periodontal disease and other inflammatory conditions of the body. High-throughput analysis of proteins has become possible with the development of MS technology. This breakthrough in proteome technology enables comparative studies of comprehensive protein expression and identification of protein. In case of periodontal disease, proteome analysis using 2DE, as well as gel-free methods, has been reported. As a fluid lying in close proximity to periodontal tissue, the gingival crevicular fluid (GCF) is the principal target in the search for biomarkers of periodontal disease, because its protein composition may reflect the disease pathophysiology. Biochemical marker analysis of GCF is effective for objective diagnosis in the early and advanced stages of periodontal disease. Increasing numbers of recent reports have provided evidence that the proteomic approach is a promising tool for the discovery and identification of biochemical markers of periodontal disease. This search is of continuing interest in the field of experimental and clinical periodontal disease research. In this article, we summarize recent comprehensive proteomic studies aimed at discovering and identifying biomarkers of periodontal disease in GCF.     

结肠癌基因表达谱的分类检测问题研究

随着大规模基因表达谱技术的发展,基于基因表达谱的癌症诊断方法正在成为临床医学上一种快速有效的诊断方法,但是由于基因表达数据维数过高、样本量小、噪声大,使得正确提取有关癌症的特征基因成为关键。以结肠癌肿瘤的基因表达谱数据为例,提出了结合Fisher权函数、离散傅里叶变换和主成分分析的混合特征基因提取方法,以多元Logistic回归分析和贝叶斯决策作为分类器进行肿瘤分类检测。实验结果表明,该方法对于结肠癌数据集CV识别准确率高达96.80%。     

Colorectal cancer proteomics, molecular characterization and biomarker discovery

Colorectal cancer (CRC) is a widespread disease, whose major genetic changes and mutations have been well characterized in the sporadic form. Much less is known at the protein and proteome level. Still, CRC has been the subject of multiple proteomic studies due to the urgent necessity of finding clinically relevant markers and to elucidate the molecular mechanisms underlying the progression of the disease. These proteomic approaches have been limited by different technical issues, mainly related with sensitivity and reproducibility. However, recent advances in proteomic techniques and MS systems have rekindled the quest for new biomarkers in CRC and an improved molecular characterization. In this review, we will discuss the application of different proteomic approaches to the identification of differentially expressed proteins in CRC. In particular, we will make a critical assessment about the use of 2-D DIGE, MS and protein microarray technologies, in their different formats, to identify up- or downregulated proteins and/or autoantibodies profiles that could be useful for CRC characterization and diagnosis. Despite a wide list of potential biomarkers, it is clear that more scientific efforts and technical advances are still needed to cover the range of low-abundant proteins, which may play a key role in CRC diagnostics and progression.