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Purpose Currently, the standard screening tool for breast cancer is screening mammography. There have been many efforts to develop a blood-based diagnostic assay for breast cancer diagnosis; however, none have been approved for clinical use at this time. The purpose of this study was to determine the accuracy of a novel blood-based proteomic test for aiding breast cancer diagnosis in a relatively large cohort of cancer patients. Methods A blood-based test using multiple reaction monitoring (MRM) measured by mass spectrometry to quantify 3 peptides (apolipoprotein C-1, carbonic anhydrase 1, and neural cell adhesion molecule L1-like protein) present in human plasma was investigated. A total of 1,129 blood samples from 575 breast cancer patients, 454 healthy controls, and 100 patients with other malignancies were used to verify and optimize the assay. Results The diagnostic sensitivity, specificity, and accuracy of the MRM-based proteomic assay were 71.6%, 85.3%, and 77%, respectively; the area under the receiver operating characteristic curve was 0.8323. The proteomic assay did not demonstrate diagnostic accuracy in patients with other types of malignancies including thyroid, pancreatic, lung, and colon cancers. The diagnostic performance of the proteomic assay was not associated with the timing of blood sampling before or after anesthesia. Conclusion The data demonstrated that an MRM-based proteomic assay that measures plasma levels of three specific peptides can be a useful tool for breast cancer screening and its accuracy is cancer-type specific.

We propose to use cRFP (common Repository of FBS Proteins) in the MS (mass spectrometry) raw data search of cell secretomes. cRFP is a small supplementary sequence list of highly abundant fetal bovine serum proteins added to the reference database in use. The aim behind using cRFP is to prevent the contaminant FBS proteins from being misidentified as other proteins in the reference database, just as we would use cRAP (common Repository of Adventitious Proteins) to prevent contaminant proteins present either by accident or through unavoidable contacts from being misidentified as other proteins. We expect it to be widely used in experiments where the proteins are obtained from serum-free media after thorough washing of the cells, or from a complex media such as SILAC, or from extracellular vesicles directly.

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

High-grade serous ovarian carcinoma (HGSOC) and basal-like breast cancer (BLBC) share many features including TP53 mutations, genomic instability and poor prognosis. We recently reported that Elafin is overexpressed by HGSOC and is associated with poor overall survival. Here, we confirm that Elafin overexpression is associated with shorter survival in 1000 HGSOC patients. Elafin confers a proliferative advantage to tumor cells through the activation of the MAP kinase pathway. This mitogenic effect can be neutralized by RNA interference, specific antibodies and a MEK inhibitor. Elafin expression in patient-derived samples was also associated with chemoresistance and strongly correlates with bcl-xL expression. We extended these findings into the examination of 1100 primary breast tumors and six breast cancer cell lines. We observed that Elafin is overexpressed and secreted specifically by BLBC tumors and cell lines, leading to a similar mitogenic effect through activation of the MAP kinase pathway. Here too, Elafin overexpression is associated with poor overall survival, suggesting that it may serve as a biomarker and therapeutic target in this setting.

Leucine-rich repeat kinase 2 (LRRK2) is a large multidomain protein that is expressed in many tissues and participates in numerous biological pathways. Mutations in LRRK2 are recognized as genetic risk factors for familial Parkinson's disease (PD) and may also represent causal factors in the more common sporadic form of PD. The structure of LRRK2 comprises a combination of GTPase, kinase, and scaffolding domains. This functional diversity, combined with a potentially central role in genetic and idiopathic PD motivates significant effort to further credential LRRK2 as a therapeutic target. Here, we review the current understanding for LRRK2 function in normal physiology and PD, with emphasis on insight gained from proteomic approaches.

Screening patients at high risk of recurrence of cancer would allow for more accurate and personalized treatment. In this study, we tried to identify the prognosis-related protein profile by applying two different quantitative proteomic techniques, difference in-gel electrophoresis and cleavable isotope-coded affinity tag method. Six tumor tissues were obtained from stage IV colorectal cancer (CRC) patients, of which three have survived more than five years (good prognostic group, GPG) and the other three died within 25 months (poor prognostic group, PPG) after palliative surgery and subsequent chemotherapy treatment. From the two independent quantitative analyses, we identified 175 proteins with abundance ratios greater than 2-fold. Gene ontology analysis revealed that proteins related to cellular assembly/organization and movement were generally increased in the PPG. Twenty-two proteins, including caveolin-1, were chosen for confirmatory studies by Western blot and immunohistochemistry. The Western blot data for each individual protein were analyzed with Mann–Whitney tests, and a multi-marker panel was generated by logistic regression analysis. Five proteins, fatty acid binding protein 1, intelectin 1, transitional endoplasmic reticulum ATPase, transgelin and tropomyosin 2, were significantly different between the two prognostic groups within 95% confidence. No single protein could completely distinguish the two groups from each other. However, a combination of the five proteins effectively distinguished PPG from GPG patients (AUC = 1). Our study suggests a multi-marker panel composed of proteome signatures that provide accurate predictive information and potentially assist personalized therapy. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Proteomic techniques are mostly used these days to identify proteins in a biological sample. Quantification of the differences between two or more physiological conditions, such as disease or no disease, has become an increasingly challenging task in proteomics. Mass tags introducing stable isotopes into peptides or proteins provide means for quantification in mass spectrometry. The mass tags are recognized by mass spectrometry and at the same time provide quantitative information. In the current study, we introduce mTRAQ for the purpose of quantification by full MS scans. Although mTRAQ reagent was initially designed for multiple reaction monitoring, we verified the utility of mTRAQ for MS1-based relative quantification using standard protein mixtures and blood plasma samples. mTRAQ-labeled peptides showed better quality MS2 spectra with increased XCorr values in a SEQUEST search output than corresponding unlabeled peptides. The improved spectral quality was due mostly to the enhanced matching of b-type ions. By combining mTRAQ with ICAT and applying them to colon cancer tissues, we identified and quantified a total of 3,320 proteins. mTRAQ covered a wider range of the proteome than did ICAT, and only 1053 proteins were shared by the two independent methods. Our results suggest the usefulness of mTRAQ, alone or in combination with ICAT, as a comparative profiling method in quantitative proteomics.

Protein quantification is one of the principal computational problems in mass spectrometry (MS) based proteomics. For robust and trustworthy protein quantification, accurate peptide quantification must be preceded. In recent years, stable isotope labeling has become the most popular method for relative quantification of peptides. However, some stable isotope labeling methods may carry a critical problem, which is an overlap of isotopic clusters. If the mass difference between the light- and heavy-labeled peptides is very small, the overlap of their isotopic clusters becomes larger as the mass of original peptide increases. Here we propose a new algorithm for peptide quantification that separates overlapping isotopic clusters using quadratic equations. It can be easily applied in Trans-Proteomic Pipeline (TPP) instead of XPRESS. For the mTRAQ-labeled peptides obtained by an Orbitrap mass spectrometer, it showed more accurate ratios and better standard deviations than XPRESS. Especially, for the peptides that do not contain lysine, the ratio difference between XPRESS and our algorithm became larger as the peptide masses increased. We expect that this algorithm can also be applied to other labeling methods such as (18)O labeling and acrylamide labeling.

Absence seizure has been of interest because the symptom is related to sensory processing. However, the mechanism that causes the disease is not understood yet. To better understand the molecular mechanism related to the disease progress at protein level, we performed proteomic studies using the thalamus of mice for which absence seizure was induced by gamma-butyrolactone (GBL). Differential proteome expression between GBL-treated mice and control mice was examined by fluorescence 2D difference gel electrophoresis (DIGE) at three different time points (5, 10, and 30 min) after GBL-administration. We identified 16 proteins differentially expressed by >1.4-fold at any of the three time points. All proteins besides the serine protease inhibitor EIA were down-regulated in absence seizure-induced mice. The down-regulated proteins can be classified into five groups by their biological functions: cytoskeleton rearrangement, neuroprotection, neurotransmitter secretion, calcium binding, and metabolism. The maximum level of change was reached by 10 min after GBL-treatment, with the expression level returning back to the original at 30 min when mice were awakened from absence seizure thereby demonstrating the proteomic response is reversible. Our results suggest that absence seizures are associated with restricted functional sets of proteins, whose down-regulation may interfere with general function of neuronal cells.

We aimed to develop a plasma protein signature for breast cancer diagnosis by using multiple reaction monitoring (MRM)-based mass spectrometry.Based on our previous studies, we selected 124 proteins for MRM. Plasma samples from 80 patients with breast cancer and 80 healthy women were used to develop a plasma proteomic signature by an MRM approach. The proteomic signature was then validated in plasma samples from 100 patients with breast cancer and 100 healthy women.A total of 56 proteins were optimized for MRM. In the verification cohort, 11 proteins exhibited significantly differential expression in plasma from patients with breast cancer. Three proteins (neural cell adhesion molecule L1-like protein, apolipoprotein C-1 and carbonic anhydrase-1) with highest statistical significance which gave consistent results for patients of stage I and II breast cancer were selected and a 3-protein signature was developed using binary logistic regression analysis [area under the curve (AUC)=0.851, sensitivity=80.6%]. The 3-protein signature showed similar performance in an independent validation cohort with an AUC of 0.797 and sensitivity of 77.2% for detection of stage I and II breast cancer.We developed a distinct plasma protein signature for breast cancer diagnosis based on an MRM-based approach, and the clinical value of the 3-protein signature was validated in an independent cohort.

Post-genomic studies continue to highlight the potential clinical importance of protein phosphorylation signaling pathways in drug discovery. Unfortunately the dynamic range and variable stoichiometry of protein phosphorylation continues to stymie efforts to achieve comprehensive characterization of the human phosphoproteome. In this study, we develop a complementary, two-stage method for enrichment of cysteine-containing phosphopeptides combined with TMT multiplex labeling for relative quantification. Use of this approach with multi-dimension fractionation in mammalian cells yielded more than 7,000 unique cys-phosphopeptide sequences, comprising 15%–20% novel phosphorylation sites. Use of our approach in combination with pharmacologic inhibitors of the mammalian target of rapamycin complex 1 and 2 (mTORC1/2) identified several putatively novel protein substrates for the mechanistic target of rapamycin (mTOR) kinase.

Breast cancer is the most common cancer in women worldwide. It is necessary to identify biomarkers for early detection, to make accurate prognoses, and to monitor for any recurrence of the cancer. In order to identify potential breast cancer biomarkers, we analyzed the plasma samples of women diagnosed with breast cancer and age-matched normal healthy women by mTRAQ-based stable isotope-labeling mass spectrometry. We identified and quantified 204 proteins including thrombospondin-1 (THBS1) and bromodomain and WD repeat-containing protein 3 (BRWD3) which were increased by more than 5-fold in breast cancer plasma. The plasma levels of the two proteins were evaluated by Western blot assay to confirm for their diagnostic value as serum markers. A 1.8-fold increase in BRWD3 was observed while comparing the plasma levels of breast cancer patients (n = 54) with age-matched normal healthy controls (n = 30), and the area under the receiver operating characteristic curve (AUC) was 0.917. THBS1 was detected in pooled breast cancer plasma at the ratio similar to mTRAQ ratio (> 5-fold). The AUC value for THBS1 was 0.875. The increase of THBS1 was more prominent in estrogen receptor negative and progesterone receptor negative patients than receptor-positive patients. Our results are evidence of the diagnostic value of THBS1 in detecting breast cancer. Based on our findings, we suggest a proteomic method for protein identification and quantification lead to effective biomarker discovery.

An efficient means of identifying protein biomarkers is essential to proper cancer management. A well-characterized proteome resource holds special promise for the discovery of novel biomarkers. However, quantification of the differences between physiological conditions together with deep down profiling has become increasingly challenging in proteomics. Here, we perform expression profiling of the colorectal cancer (CRC) proteome by stable isotope labeling and mass spectrometry. Quantitative analysis included performing mTRAQ and cICAT labeling in a pooled sample of three microsatellite stable (MSS) type CRC tissues and a pooled sample of their matched normal tissues. We identified and quantified a total of 3688 proteins. Among them, 1487 proteins were expressed differentially between normal and cancer tissues by higher than 2-fold; 1009 proteins showed increased expression in cancer tissue, whereas 478 proteins showed decreased expression. Bioinformatic analysis revealed that our data were largely consistent with known CRC relevant signaling pathways, such as the Wnt/β-catenin, caveolar-mediated endocytosis, and RAN signaling pathways. Mitochondrial dysfunction, known as the Waburg hypothesis, was also confirmed. Therefore, our data showing alterations in the proteomic profile of CRC constitutes a useful resource that may provide insights into tumor progression with later goal of identifying biologically and clinically relevant marker proteins. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Glycosylation is the most important and abundant post-translational modification in serum proteome. Several specific types of glycan epitopes have been shown to be associated with various types of disease. Direct analysis of serum glycoproteins is challenging due to its wide dynamic range. Alternatively, glycoproteins can be discovered in the secretome of model cell lines and then confirmed in blood. However, there has been little experi-mental evidence showing cell line secretome as a tractable target for the study of serum glycoproteins. We used a hydrazine-based glycocapture method to selectively enrich glycoproteins from the secretome of the breast cancer cell line Hs578T. A total of 132 glycoproteins were identified by nanoLC-MS/MS analysis. Among the identified proteins, we selected 13 proteins that had one or more N-glycosylation motifs in the matched peptides, which were included in the Secreted Protein Database but not yet in the Plasma Proteome Database (PPD), and whose antibodies were commercially available. Nine out of the 13 selected proteins were detected from human blood plasma by western analysis. Furthermore, eight proteins were also detected from the plasma by targeted LC-MS/MS, which had never been previously identified by data-dependent LC-MS/MS. Our results provide novel proteins that should be enrolled in PPD and suggest that analysis of cell line secretome with subfractionation is an efficient strategy for discovering disease-relevant serum proteins.

Diabetes can lead to serious microvascular complications like proliferative diabetic retinopathy (PDR), which is the leading cause of blindness in adults. The proteomic changes that occur during PDR cannot be measured in the human retina for ethical reasons, but could be reflected by proteomic changes in vitreous humor. Thus, we considered that comparisons between the proteome profiles of the vitreous humors of PDR and nondiabetic controls could lead to the discovery of novel pathogenic proteins and clinical biomarkers. In this study, the authors used several proteomic methods to comprehensively examine vitreous humor proteomes of PDR patients and nondiabetic controls. These methods included immunoaffinity subtraction (IS)/2-DE/MALDI-MS, nano-LC-MALDI-MS/MS, and nano-LC-ESI-MS/MS. The identified proteins were subjected to the Trans-Proteomic Pipeline validation process. Resultantly, 531 proteins were identified, i.e., 415 and 346 proteins were identified in PDR and nondiabetic control vitreous humor samples, respectively, and of these 531 proteins, 240 were identified for the first time in this study. The PDR vitreous proteome was also found to contain many proteins possibly involved in the pathogenesis of PDR. The proteins described provide the most comprehensive proteome listing in the vitreous humor samples of PDR and nondiabetic control patients.

Absence seizure has been of interest because the symptom is related to sensory processing. However, the mechanism that causes the disease is not understood yet. To better understand the molecular mechanism related to the disease progress at protein level, we performed proteomic studies using the thalamus of mice for which absence seizure was induced by gamma-butyrolactone (GBL). Differential proteome expression between GBL-treated mice and control mice was examined by fluorescence 2D difference gel electrophoresis (DIGE) at three different time points (5, 10, and 30 min) after GBL-administration. We identified 16 proteins differentially expressed by1.4-fold at any of the three time points. All proteins besides the serine protease inhibitor EIA were down-regulated in absence seizure-induced mice. The down-regulated proteins can be classified into five groups by their biological functions: cytoskeleton rearrangement, neuroprotection, neurotransmitter secretion, calcium binding, and metabolism. The maximum level of change was reached by 10 min after GBL-treatment, with the expression level returning back to the original at 30 min when mice were awakened from absence seizure thereby demonstrating the proteomic response is reversible. Our results suggest that absence seizures are associated with restricted functional sets of proteins, whose down-regulation may interfere with general function of neuronal cells.

Comparative proteome analysis was performed on the cultured media of human nontumor and malignant breast cell lines, Hs578Bst and Hs578T, respectively, in search of a serological biomarker(s) for breast cancer. Proteins in the conditioned media were separated by 2-D PAGE and then visualized by silver-staining. Eight proteins changed differentially by more than two-fold were identified by MALDI-TOF/TOF MS. Among the proteins identified, the terminal laminin-like globular (LG3) domain of endorepellin, which was recently reported as an antiangiogenesis factor, was decreased in the cancer cell line. We confirmed the bone morphogenic protein-1 (BMP-1) mediated cleavage site on the N-terminus of endorepellin LG3 fragment. This finding suggests that the LG3 fragment is specifically released by a BMP-1 driven limited proteolytic process. The protein was also detected in plasma by Western blot analysis and selected reaction monitoring (SRM). The plasma level of the endorepellin LG3 fragment was significantly lower in breast cancer patients compared to healthy donors (p = 0.017; n = 12). The LG3 protein concentration in the control plasma was measured at approximately 3.7 pmol/mL compared to 1.8 pmol/mL in plasma from the cancer patients. We suggest that these results support the potential use of the endorepellin LG3 fragment as a new serological biomarker for breast cancer.