Comparative proteomic analysis for the insoluble fractions of colorectal cancer patients

We used label-free quantitative proteomics with the insoluble fractions from colorectal cancer (CRC) patients to gain further insight into the utility of profiling altered protein expression as a potential biomarker for cancer. The insoluble fractions were prepared from paired tumor/normal biopsies from 13 patients diagnosed with CRC (stages I to IV). Fifty-six proteins identified in data pooled from the 13 cases were differentially expressed between the tumor and adjacent normal tissue. The connections between these proteins are involved in reciprocal networks related to tumorigenesis, cancer incidence based on genetic disorder, and skeletal and muscular disorders. To assess their potential utility as biomarkers, the relative expression levels of the proteins were validated using personal proteomics and a heat map to compare five individual CRC samples with five normal tissue samples. Further validation of a panel of proteins (KRT5, JUP, TUBB, and COL6A1) using western blotting confirmed the differential expression. These proteins gave specific network information for CRC, and yielded a panel of novel markers and potential targets for treatment. It is anticipated that the experimental approach described here will increase our understanding of the membrane environment in CRC, which may provide direction for making diagnoses and prognoses through molecular biomarker targeting.     

Quantitative analysis of caveolin-rich lipid raft proteins from primary and metastatic colorectal cancer clones

Caveolin-rich lipid rafts (CLRs) are thickened sections of the cell membrane that are composed of the integral membrane proteins caveolins together with saturated long chain fatty acids, cholesterol and lipids. Membrane proteins - lipid raft proteins in particular - may play important roles in cell signaling and cell-cell interaction. Due to their unique structure, CLRs seem to be the preferred docking site for specific proteins involved in focal adhesion and cancer metastasis. Our objective was thus to identify and quantify CLR proteins from primary and metastatic colorectal cancer (CRC) clones. We found differential expression of nine CLR proteins from primary and metastatic CRC clones. Among the identified proteins, an immune system inhibiting protein was significantly overexpressed in the metastatic clone, while cell adhesion and transport molecules were among the overexpressed proteins in the primary clone. All the identified CRL proteins are involved in tumorigenesis, specifically metastasis, and may thus serve as therapeutic targets. A novel concept for identification and quantification of CLR proteins with label-free mass spectrometry method was specifically examined in this study. Validation of the method against immunoblotting and FACS analysis indicates that it can be applied for the identification of novel biomarkers for cancer and metastasis.     

N-glycoproteome Analysis of the Secretome of Human Metastatic Hepatocellular Carcinoma Cell Lines Combining Hydrazide Chemistry,HILIC Enrichment and Mass Spectrometry

Cancer cell metastasis is a major cause of cancer death. Unfortunately, the underlying molecular mechanisms remain unknown, which results in the lack of efficient diagnosis, therapy and prevention approaches. Nevertheless, the dysregulation of the cancer cell secretome is known to play key roles in tumor transformation and progression. The majority of proteins in the secretome are secretory proteins and membrane-released proteins, and, mostly, the glycosylated proteins. Until recently, few studies have explored protein N-glycosylation changes in the secretome, although protein glycosylation has received increasing attention in the study of tumor development processes. Here, the N-glycoproteins in the secretome of two human hepatocellular carcinoma (HCC) cell lines with low (MHCC97L) or high (HCCLM3) metastatic potential were investigated with a in-depth characterization of the N-glycosites by combining two general glycopeptide enrichment approaches, hydrazide chemistry and zwitterionic hydrophilic interaction chromatography (zic-HILIC), with mass spectrometry analysis. A total of 1,213 unique N-glycosites from 611 N-glycoproteins were confidently identified. These N-glycoproteins were primarily localized to the extracellular space and plasma membrane, supporting the important role of N-glycosylation in the secretory pathway. Coupling label-free quantification with a hierarchical clustering strategy, we determined the differential regulation of several N-glycoproteins that are related to metastasis, among which AFP, DKK1, FN1, CD151 and TGFβ2 were up-regulated in HCCLM3 cells. The inclusion of the well-known metastasis-related proteins AFP and DKK1 in this list provides solid supports for our study. Further western blotting experiments detecting FN1 and FAT1 confirmed our discovery. The glycoproteome strategy in this study provides an effective means to explore potential cancer biomarkers.     

Ribosomal Protein S27-Like in Colorectal Cancer: A Candidate for Predicting Prognoses

Background

The development and progression of colorectal cancer (CRC) involve a complex process of multiple genetic changes. Tumor suppressor p53 is capable of determining the fate of CRC cells. However, the role of a p53-inducible modulator, ribosomal protein S27-like (RPS27L), in CRC is unknown.

Methods

Here, the differential expression of RPS27L was examined in the feces and colonic tissues of CRC patients, to explore its possible correlation with patient survival and to investigate the cellular mechanisms underlying their clinical outcomes. Eighty intermediate-stage CRC patients (42 at stage II and 38 at stage III) were divided into two groups according to their fecal RPS27L mRNA levels. The survival probabilities of the groups were estimated using the Kaplan–Meier method. The RPS27L protein in the colonic tissues of stage III patients with different prognoses was further examined immunohistochemically. RPS27L expression in LoVo cells was manipulated to examine the possible cellular responses in vitro.

Results

Elevated RPS27L expression, in either feces or tissues, was related to a better prognosis. In vitro, RPS27L-expressing LoVo cells ceased DNA synthesis and apoptotic activity while the expression of their DNA repair molecules was upregulated.

Conclusions

Elevated RPS27L may improve the prognoses of certain CRC patients by enhancing the DNA repair capacity of their colonic cells, and can be determined in feces. By integrating clinical, molecular, and cellular data, our study demonstrates that fecal RPS27L may be a useful index for predicting prognoses and guiding personalized therapeutic strategies, especially in patients with intermediate-stage CRC.     

A novel alignment method and multiple filters for exclusion of unqualified peptides to enhance label-free quantification using peptide intensity in LC-MS/MS

Though many software packages have been developed to perform label-free quantification of proteins in complex biological samples using peptide intensities generated by LC-MS/MS, two critical issues are generally ignored in this field: (i) peptides have multiple elution patterns across runs in an experiment, and (ii) many peptides cannot be used for protein quantification. To address these two key issues, we have developed a novel alignment method to enable accurate peptide peak retention time determination and multiple filters to eliminate unqualified peptides for protein quantification. Repeatability and linearity have been tested using six very different samples, i.e., standard peptides, kidney tissue lysates, HT29-MTX cell lysates, depleted human serum, human serum albumin-bound proteins, and standard proteins spiked in kidney tissue lysates. At least 90.8% of the proteins (up to 1,390) had CVs ≤ 30% across 10 technical replicates, and at least 93.6% (up to 2,013) had R(2) ≥ 0.9500 across 7 concentrations. Identical amounts of standard protein spiked in complex biological samples achieved a CV of 8.6% across eight injections of two groups. Further assessment was made by comparing mass spectrometric results to immunodetection, and consistent results were obtained. The new approach has novel and specific features enabling accurate label-free quantification.     

应用蛋白质组学筛选宫颈癌患者尿液中的肿瘤标志物

通过比较健康女性和宫颈癌患者的尿蛋白质组,发现并分析差异表达蛋白,从中筛选潜在的宫颈癌的标志物。研究对象由43名宫颈癌患者（CC）和47名健康女性（HW）组成。用超速离心法沉淀尿蛋白,再用一维凝胶电泳（SDS-PAGE）与液相色谱-质谱联用技术（LC-MS/MS）鉴定尿液中的蛋白质,蛋白质定量采用无标定量。比较患者尿蛋白质组、健康对照的尿蛋白质组和宫颈癌组织蛋白质组,有1910个蛋白质是患者和健康对照共有的尿蛋白,这其中有746个蛋白质也存在于宫颈癌组织蛋白质组。在这746个蛋白质中找到84个上调蛋白和82下调蛋白。通过生物信息学分析发现牛皮癣素（S100A7）和癌胚抗原相关细胞黏附分子8（CEACAM8）是宫颈癌尿液样本独有蛋白质。在验证组的70例样本中,双盲法测试S100A7、CEACAM8以及两者联合诊断宫颈癌的敏感性能达到73%、87%、93%。结果提示,宫颈癌患者的尿蛋白质组与健康女性的尿蛋白质组不同,并且S100A7和CEACAM8可以作为宫颈癌潜在的肿瘤标志物。     

Regulation of ASIC channels by a stomatin/STOML3 complex located in a mobile vesicle pool in sensory neurons

A complex of stomatin-family proteins and acid-sensing (proton-gated) ion channel (ASIC) family members participate in sensory transduction in invertebrates and vertebrates. Here, we have examined the role of the stomatin-family protein stomatin-like protein-3 (STOML3) in this process. We demonstrate that STOML3 interacts with stomatin and ASIC subunits and that this occurs in a highly mobile vesicle pool in dorsal root ganglia (DRG) neurons and Chinese hamster ovary cells. We identify a hydrophobic region in the N-terminus of STOML3 that is required for vesicular localization of STOML3 and regulates physical and functional interaction with ASICs. We further characterize STOML3-containing vesicles in DRG neurons and show that they are Rab11-positive, but not part of the early-endosomal, lysosomal or Rab14-dependent biosynthetic compartment. Moreover, uncoupling of vesicles from microtubules leads to incorporation of STOML3 into the plasma membrane and increased acid-gated currents. Thus, STOML3 defines a vesicle pool in which it associates with molecules that have critical roles in sensory transduction. We suggest that the molecular features of this vesicular pool may be characteristic of a 'transducosome' in sensory neurons.     

Comparative Analysis of Label-Free and 8-Plex iTRAQ Approach for Quantitative Tissue Proteomic Analysis

High resolution proteomics approaches have been successfully utilized for the comprehensive characterization of the cell proteome. However, in the case of quantitative proteomics an open question still remains, which quantification strategy is best suited for identification of biologically relevant changes, especially in clinical specimens. In this study, a thorough comparison of a label-free approach (intensity-based) and 8-plex iTRAQ was conducted as applied to the analysis of tumor tissue samples from non-muscle invasive and muscle-invasive bladder cancer. For the latter, two acquisition strategies were tested including analysis of unfractionated and fractioned iTRAQ-labeled peptides. To reduce variability, aliquots of the same protein extract were used as starting material, whereas to obtain representative results per method further sample processing and MS analysis were conducted according to routinely applied protocols. Considering only multiple-peptide identifications, LC-MS/MS analysis resulted in the identification of 910, 1092 and 332 proteins by label-free, fractionated and unfractionated iTRAQ, respectively. The label-free strategy provided higher protein sequence coverage compared to both iTRAQ experiments. Even though pre-fraction of the iTRAQ labeled peptides allowed for a higher number of identifications, this was not accompanied by a respective increase in the number of differentially expressed changes detected. Validity of the proteomics output related to protein identification and differential expression was determined by comparison to existing data in the field (Protein Atlas and published data on the disease). All methods predicted changes which to a large extent agreed with published data, with label-free providing a higher number of significant changes than iTRAQ. Conclusively, both label-free and iTRAQ (when combined to peptide fractionation) provide high proteome coverage and apparently valid predictions in terms of differential expression, nevertheless label-free provides higher sequence coverage and ultimately detects a higher number of differentially expressed proteins. The risk for receiving false associations still exists, particularly when analyzing highly heterogeneous biological samples, raising the need for the analysis of higher sample numbers and/or application of adjustment for multiple testing.     

A new method for quantitative analysis of cell surface glycoproteome

As the altered glycosylation expressions of cell surface proteins are associated with many diseases, glycoproteomics approach has been widely applied to characterization of surface glycosylation alteration. In general, the abundances of proteolytic glycopeptides derived from corresponding glycoproteins can be measured to determine the abundances of glycoproteins. However, this quantification strategy cannot distinguish whether the changes are results from changes of protein abundance or changes in glycosite occupancy. For the accurate and specific quantification of the cell surface glycosylation profile, we proposed a modified cell surface‐capturing strategy where the glycopeptides were submitted to LC‐MS/MS analysis directly for identification of glycoproteins and the non‐glycopeptides were isotopically labelled for quantification of glycoproteins. This strategy was applied to comparatively analyze cell surface glycoproteins of two human cell lines, i.e. Chang Liver and HepG2 cells. Totally 341 glycoproteins were identified with 82.4% specificity for cell membrane proteins and 33 glycoproteins were quantified with significant expression change between the two cell lines. The differential expressions of two selected proteins (EMMPRIN and BCAM) were validated by Western blotting. This method enables specific and accurate analysis of the cell surface glycoproteins and may have broad application in the field of biomarker and drug target discovery.     

Protein Analysis of Atrial Fibrosis via Label-Free Proteomics in Chronic Atrial Fibrillation Patients with Mitral Valve Disease

Background

Atrial fibrosis, as a hallmark of atrial structure remodeling, plays an important role in maintenance of chronic atrial fibrillation, but interrelationship of atrial fibrosis and atrial fibrillation is uncertain. Label-free proteomics can implement high throughput screening for finding and analyzing pivotal proteins related to the disease.. Therefore, we used label-free proteomics to explore and analyze differentially proteins in chronic atrial fibrillation patients with mitral valve disease.

Methods

Left and right atrial appendages obtained from patients with mitral valve disease were both in chronic atrial fibrillation (CAF, AF≥6 months, n = 6) and in sinus rhythm (SR, n = 6). One part of the sample was used for histological analysis and fibrosis quantification; other part were analyzed by label-free proteomic combining liquid chromatography with mass spectrometry (LC-MS), we utilized bioinformatics analysis to identify differential proteins.

Results

Degree of atrial fibrosis was higher in CAF patients than that of SR patients. 223 differential proteins were detected between two groups. These proteins mainly had vital functions such as cell proliferation, stress response, focal adhesion apoptosis. We evaluated that serine/threonine protein kinase N2 (PKN2), dermatopontin(DP), S100 calcium binding protein B(S100B), protein tyrosine kinase 2(PTK2) and discoidin domain receptor tyrosine kinase 2(DDR2) played important roles in fibrotic process related to atrial fibrillation.

Conclusion

The study presented differential proteins responsible for atrial fibrosis in chronic atrial fibrillation patients through label-free proteomic analysis. We assessed some vital proteins including their characters and roles. These findings may open up new realm for mechanism research of atrial fibrillation.     

GABAB receptor inhibits tumor progression and epithelial-mesenchymal transition via the regulation of Hippo/YAP1 pathway in colorectal cancer

Gamma-Aminobutyric Acid Type B Receptor (GABABR) plays essential roles in tumor progression. However, the function of GABABR in colorectal cancer (CRC) needs further clarification. As the main part of GABABR, GABABR1 expression was identified significantly lower in tumor tissues than those in non-tumor normal tissues and that CRC patients with high GABABR1 expression lived longer. Further studies indicated that knockdown of GABABR1 elevated CRC cell proliferation, migration, and invasion. Furthermore, knockdown of GABABR1 activated the expression of the epithelial-mesenchymal transition (EMT)-related proteins N-cadherin and Vimentin, whereas decrease the protein level of E-cadherin. In addition, activation of Hippo/YAP1 signaling contributes to the GABABR1 down-regulation promoted proliferation, migration, invasion and EMT in CRC cells. At last, we verified the contribution of Hippo/YAP1 signaling in the GABABR1 down-regulation impaired biological phenotype of colon cancer cells in vivo. In summary, these data indicate that GABABR1 impairs the migration and invasion of CRC cells by inhibiting EMT and the Hippo/YAP1 pathway, suggesting that GABABR1 could be a potential therapeutic target for CRC.     

Proteomics of differential extraction fractions enriched for chromatin-binding proteins from colon adenoma and carcinoma tissues

Background: Altered nuclear and genomic structure and function are hallmarks of cancer cells. Research into nuclear proteins in human tissues could uncover novel molecular processes in cancer. Here, we examine biochemical tissue fractions containing chromatin-binding (CB) proteins in the context of colorectal cancer (CRC) progression. Methods: CB protein-containing fractions were biochemically extracted from human colorectal tissues, including carcinomas with chromosomal instability (CIN), carcinomas with microsatellite instability (MIN), and adenomas. The CB proteins were subjected to label-free LC–MS/MS and the data were analyzed by bioinformatics. Results: Over 1700 proteins were identified in the CB fraction from colonic tissues, including 938 proteins associated with nuclear annotation. Of the latter, 169 proteins were differential between adenomas and carcinomas. In this adenoma-versus-carcinoma comparison, apart from specific changes in components of the splicing and protein translational machineries, we also identified significant changes in several proteins associated with chromatin-directed functions. Furthermore, several key cell cycle proteins as well as those involved in cellular stress were increased, whereas specific components of chromosome segregation and DNA recombination/repair systems were decreased. Conclusions: Our study identifies proteomic changes at the subnuclear level that are associated with CRC and may be further investigated. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Label-free relative quantification method for low-abundance glycoproteins in human serum by micrOTOF-Q

In this study, a label-free relative quantification strategy was developed for quantifying low-abundance glycoproteins in human serum. It included three steps: (1) immunodepletion of 12 high-abundance proteins, (2) enrichment of low-abundance glycoproteins by multi-lectin column, (3) relative quantification of them between different samples by micrOTOF-Q. We also evaluated the specificity and efficiency of immunodepletion, the accuracy of protein quantification and the possible influence of immunodepletion, glycoprotein enrichment, trypsin digestion and peptide ionization on quantification. In conclusion, the relative quantification method can be effectively applied to the screening of low-abundance biomarkers.     

Integrated proteomic profiling of cell line conditioned media and pancreatic juice for the identification of pancreatic cancer biomarkers

Pancreatic cancer is one of the leading causes of cancer-related deaths, for which serological biomarkers are urgently needed. Most discovery-phase studies focus on the use of one biological source for analysis. The present study details the combined mining of pancreatic cancer-related cell line conditioned media and pancreatic juice for identification of putative diagnostic leads. Using strong cation exchange chromatography, followed by LC-MS/MS on an LTQ-Orbitrap mass spectrometer, we extensively characterized the proteomes of conditioned media from six pancreatic cancer cell lines (BxPc3, MIA-PaCa2, PANC1, CAPAN1, CFPAC1, and SU.86.86), the normal human pancreatic ductal epithelial cell line HPDE, and two pools of six pancreatic juice samples from ductal adenocarcinoma patients. All samples were analyzed in triplicate. Between 1261 and 2171 proteins were identified with two or more peptides in each of the cell lines, and an average of 521 proteins were identified in the pancreatic juice pools. In total, 3479 nonredundant proteins were identified with high confidence, of which ～ 40% were extracellular or cell membrane-bound based on Genome Ontology classifications. Three strategies were employed for identification of candidate biomarkers: (1) examination of differential protein expression between the cancer and normal cell lines using label-free protein quantification, (2) integrative analysis, focusing on the overlap of proteins among the multiple biological fluids, and (3) tissue specificity analysis through mining of publically available databases. Preliminary verification of anterior gradient homolog 2, syncollin, olfactomedin-4, polymeric immunoglobulin receptor, and collagen alpha-1(VI) chain in plasma samples from pancreatic cancer patients and healthy controls using ELISA, showed a significant increase (p < 0.01) of these proteins in plasma from pancreatic cancer patients. The combination of these five proteins showed an improved area under the receiver operating characteristic curve to CA19.9 alone. Further validation of these proteins is warranted, as is the investigation of the remaining group of candidates.     

Circulating exosomal CPNE3 as a diagnostic and prognostic biomarker for colorectal cancer

Exosomal proteins are emerging as relevant diagnostic and prognostic biomarkers for cancer. This study was aimed at illustrating the clinical significance of exosomal Copine III (CPNE3) purified from the plasma of colorectal cancer (CRC) patients. The CPNE3 expression levels in CRC tissues were analyzed by real-time PCR, western blot, and immunohistochemistry. Plasma exosomes were isolated to examine the CPNE3 level using ELISA. Pearson’s correlation analysis was performed to investigate the CPNE3 levels between CRC tissues and matched plasma samples. Receiver operating characteristic curve analysis was developed to measure the diagnostic performance of exosomal CPNE3. The Kaplan–Meier method and Cox's proportional hazards model were utilized to determine statistical differences in survival times. CPNE3 showed increased expressions in the CRC tissues. A moderately significant correlation was found between CPNE3 expression in CRC tissues by immunohistochemistry and matched serum exosomal CPNE3 expression by ELISA (r = 0.645,(r = 0.645, p < 0.001). < 0.001). Exosomal CPNE3 yielded a sensitivity of 67.5% and a specificity of 84.4% in CRC at the cutoff value of 0.143 pg per 1ug1 ug exosome. Combined data from carcinoembryonic antigen and exosomal CPNE3 achieved 84.8% sensitivity and 81.2% specificity as a diagnostic tool. CRC patients with lower exosomal CPNE3 levels had substantially better disease-free survival (hazard ratio [HR], 2.9; 95% confidence interval [CI]: 1.3–6.4; p = 0.009) = 0.009) and overall survival (HR, 3.4; 95% CI: 1.2–9.9; p = 0.026) = 0.026) compared with those with higher exosomal CPNE3 levels. Exosomal CPNE3 show potential implications in CRC diagnosis and prognosis.     

Detecting differential and correlated protein expression in label-free shotgun proteomics

Recent studies have revealed a relationship between protein abundance and sampling statistics, such as sequence coverage, peptide count, and spectral count, in label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics. The use of sampling statistics offers a promising method of measuring relative protein abundance and detecting differentially expressed or coexpressed proteins. We performed a systematic analysis of various approaches to quantifying differential protein expression in eukaryotic Saccharomyces cerevisiae and prokaryotic Rhodopseudomonas palustris label-free LC-MS/MS data. First, we showed that, among three sampling statistics, the spectral count has the highest technical reproducibility, followed by the less-reproducible peptide count and relatively nonreproducible sequence coverage. Second, we used spectral count statistics to measure differential protein expression in pairwise experiments using five statistical tests: Fisher's exact test, G-test, AC test, t-test, and LPE test. Given the S. cerevisiae data set with spiked proteins as a benchmark and the false positive rate as a metric, our evaluation suggested that the Fisher's exact test, G-test, and AC test can be used when the number of replications is limited (one or two), whereas the t-test is useful with three or more replicates available. Third, we generalized the G-test to increase the sensitivity of detecting differential protein expression under multiple experimental conditions. Out of 1622 identified R. palustris proteins in the LC-MS/MS experiment, the generalized G-test detected 1119 differentially expressed proteins under six growth conditions. Finally, we studied correlated expression of these 1119 proteins by analyzing pairwise expression correlations and by delineating protein clusters according to expression patterns. Through pairwise expression correlation analysis, we demonstrated that proteins co-located in the same operon were much more strongly coexpressed than those from different operons. Combining cluster analysis with existing protein functional annotations, we identified six protein clusters with known biological significance. In summary, the proposed generalized G-test using spectral count sampling statistics is a viable methodology for robust quantification of relative protein abundance and for sensitive detection of biologically significant differential protein expression under multiple experimental conditions in label-free shotgun proteomics.     

Label-free quantification and shotgun analysis of complex proteomes by one-dimensional SDS-PAGE/NanoLC-MS: evaluation for the large scale analysis of inflammatory human endothelial cells

To perform differential studies of complex protein mixtures, strategies for reproducible and accurate quantification are needed. Here, we evaluated a quantitative proteomic workflow based on nanoLC-MS/MS analysis on an LTQ-Orbitrap-VELOS mass spectrometer and label-free quantification using the MFPaQ software. In such label-free quantitative studies, a compromise has to be found between two requirements: repeatability of sample processing and MS measurements, allowing an accurate quantification, and high proteomic coverage of the sample, allowing quantification of minor species. The latter is generally achieved through sample fractionation, which may induce experimental bias during the label-free comparison of samples processed, and analyzed independently. In this work, we wanted to evaluate the performances of MS intensity-based label-free quantification when a complex protein sample is fractionated by one-dimensional SDS-PAGE. We first tested the efficiency of the analysis without protein fractionation and could achieve quite good quantitative repeatability in single-run analysis (median coefficient of variation of 5%, 99% proteins with coefficient of variation <48%). We show that sample fractionation by one-dimensional SDS-PAGE is associated with a moderate decrease of quantitative measurement repeatability while largely improving the depth of proteomic coverage. We then applied the method for a large scale proteomic study of the human endothelial cell response to inflammatory cytokines, such as TNFα, interferon γ, and IL1β, which allowed us to finely decipher at the proteomic level the biological pathways involved in endothelial cell response to proinflammatory cytokines.