Quantitative proteome analysis of breast cancer cell lines using 18O-labeling and an accurate mass and time tag strategy

Proteome comparison of cell lines derived from cancer and normal breast epithelium provide opportunities to identify differentially expressed proteins and pathways associated with specific phenotypes. We employed 16O/18O peptide labeling, FT-ICR MS, and an accurate mass and time (AMT) tag strategy to simultaneously compare the relative abundance of hundreds of proteins in non-cancer and cancer cell lines derived from breast tissue. A cell line reference panel allowed relative protein abundance comparisons among multiple cell lines and across multiple experiments. A peptide database generated from multidimensional LC separations and MS/MS analysis was used for subsequent AMT tag-based peptide identifications. This peptide database represented a total of 2299 proteins, including 514 that were quantified in five cell lines using the AMT tag and 16O/18O strategies. Eighty-six proteins showed at least a threefold protein abundance change between cancer and non-cancer cell lines. Hierarchical clustering of protein abundance ratios revealed that several groups of proteins were differentially expressed between the cancer cell lines.     

Proteomic analysis in human breast cancer: identification of a characteristic protein expression profile of malignant breast epithelium

Gene expression analysis has become a promising tool in predicting the clinical course of malignant disease and the response to antineoplastic therapy. Surprisingly, only little is known about the protein expression pattern of human tumors. Recent advances in proteomic analysis allow proteins of interest to be identified by their expression and/or modification pattern in 2-DE rather than using the traditional approach of translating gene expression data. To identify a proteomic pattern that is characteristic for malignant breast epithelium, we performed differential 2-DE analysis in sets of microdissected malignant breast epithelia and corresponding adjacent normal breast epithelia from five patients with invasive breast carcinoma. Thirty-two protein spots were found to be selectively regulated in malignant epithelium, and were subjected to MALDI-TOF and/or immunoblotting for protein identification. Thirteen of the identified proteins had previously not been associated with breast cancer. The validity of these findings was confirmed by literature review and immunohistochemistry for identified proteins in an independent cohort of 50 breast cancer specimens. We here describe, for the first time, a proteomic analysis of matched normal and malignant epithelia from invasive breast carcinomas. This strategy leads to a better understanding of oncogenesis at an operational level and helps to characterize the malignant phenotype of individual tumors, and thereby to identify novel targets for antineoplastic therapy.     

Personalized liposome–protein corona in the blood of breast,gastric and pancreatic cancer patients

When nanoparticles (NPs) are dispersed in a biofluid, they are covered by a protein corona the composition of which strongly depends on the protein source. Recent studies demonstrated that the type of disease has a crucial role in the protein composition of the NP corona with relevant implications on personalized medicine. Proteomic variations frequently occur in cancer with the consequence that the bio-identity of NPs in the blood of cancer patients may differ from that acquired after administration to healthy volunteers. In this study we investigated the correlation between alterations of plasma proteins in breast, gastric and pancreatic cancer and the biological identity of clinically approved AmBisome-like liposomes as determined by a combination of dynamic light scattering, zeta potential analysis, one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) and semi-quantitative densitometry. While size of liposome–protein complexes was not significantly different between cancer groups, the hard corona from pancreatic cancer patients was significantly less negatively charged. Of note, the hard corona from pancreatic cancer patients was more enriched than those of other cancer types this enrichment being most likely due to IgA and IgG with possible correlations with the autoantibodies productions in cancer. Given the strict relationship between tumor antigen-specific autoantibodies and early cancer detection, our results could be the basis for the development of novel nanoparticle-corona-based screening tests of cancer.     

Probing conformational changes of proteins by quantitative second-derivative infrared spectroscopy

Probing protein conformational changes plays a crucial role in protein structure and function studies. However, the lack of efficient biophysical techniques makes it difficult to obtain the distinct behaviors of different secondary structure elements in a protein upon perturbation. This paper presents a discussion of the two major problems, the effect of sidelobes and different half-width at half-height (HWHH) values, encountered in quantitative second-derivative infrared (QSD-IR) spectroscopy and introduces the development of two criteria for checking the validity of the results obtained using the QSD-IR method. It was found that neither the sidelobes nor the HWHH significantly affected the quantitative result of protein conformational changes by using poly-l-lysine and hemoglobin as model proteins. A case study of bovine serum albumin (BSA) thermal aggregation suggested that the thermal transition of BSA was a process involving sequential events, and the two helical components were found to have a distinct response to heat perturbation. These results were confirmed by two-dimensional infrared correlation spectroscopy and by results in literature, suggesting that the QSD-IR method might be a potentially powerful tool to probe the distinct response of different secondary structures to perturbation.     

The diagnostic value of combined detection of genetic markers and serum protein markers on breast cancer

Objective: The research is to explore the diagnostic value of several detection methods including separated and combined detection of the related genes and related proteins of breast cancer and combined detection of all genetic markers and serum protein markers on breast cancer. Method: The mRNA level expression of the related genes of breast cancer was detected by FQ-PCR technique and the ratio of BRCA-1, Myc, C-erbB2 and β2 micro-globulin was used to express levels of BRCA-1, Myc and C-erbB2; the related proteins of breast cancer were detected through ELISA. Then the research data was analyzed by SPSS19.0 software with t-test as comparison method, and ROC curve was used to calculate the sensitivity, specificity and accuracy of the diagnostic models. Result: No difference can be found among the six indexes in the control group and benign breast tumor group while compared with the benign breast tumor group and the control group, the breast cancer group was significantly different from them; combined detection of genes and that of proteins were both superior to their separated detection; all-marker combined detection was superior to separated detection, which is consistent with combined detection of genes and proteins. Conclusion: More detection indexes will not necessarily outcome better detection effect. Hence, appropriate detection indexes and number are needed to achieve better diagnosis effect. In order to conduct more specific method, more test samples are needed for further researches.     

ER/PR阳性和阴性乳腺癌的定量蛋白质组学和生物信息学比较研究

目的:建立雌/孕激素受体(ER/PR)阴性和阳性乳腺癌的蛋白质表达谱,寻找ER/PR阴性和阳性乳腺癌中差异表达蛋白,为乳腺癌患者提供新的预后预测指标和治疗新靶点。方法:应用蛋白质组学i TRAQ技术建立ER/PR阳性和阴性乳腺癌的蛋白质差异表达谱,鉴定两组乳腺癌的差异表达蛋白,对部分差异表达蛋白进行生物信息学分析,包括蛋白功能注释和分类GO分析和KEGG通路分析。结果:应用i TRAQ蛋白质组学技术对乳腺癌组织进行了蛋白组学分析,鉴定出ER/PR阳性和阴性组间有差异表达的蛋白4999种,以ER/PR阳性:ER/PR阴性≥3为上调标准,确定ER/PR阳性组上调蛋白101种。以ER/PR阳性:ER/PR阴性≤0.5为下调标准,ER/PR阳性组下调蛋白122种。GO分析结果显示ER/PR受体阴性和阳性乳腺癌的差异表达蛋白的分子功能、生物过程、细胞定位较为复杂,并且在上调蛋白和下调蛋白上存在分布差异。KEGG通路分析发现部分差异表达蛋白涉及201条信号通路。结论:ER/PR阳性和阴性乳腺癌间存在差异表达蛋白,这些蛋白涉及复杂的分子功能、生物过程和信号通路。     

Microarray-based kinetic colorimetric detection for quantitative multiplex protein phosphorylation analysis

Commonly used colorimetric detection applied to protein microarrays with enzymatic signal amplification leads to non‐linear signal production upon increase in analyte concentration, thereby considerably limiting the range and accuracy of quantitative readout interpretation. To extend the detection range, we developed a kinetic colorimetric detection protocol for the analysis of ELISA microarrays designed to measure multiple phosphorylated proteins using the platforms ArrayTube? and ArrayStrip?. With our novel quantification approach, microarrays were calibrated over a broad concentration range spanning four orders of magnitude of analyte concentration with picomolar threshold. We used this design for the simultaneous quantitative measurement of 15 phosphorylated proteins on a single chip.