Serum peptidome patterns that distinguish metastatic thyroid carcinoma from cancer-free controls are unbiased by gender and age

Computational peptide discovery with a genetic programming approach

The development of peptides for therapeutic targets or biomarkers for disease diagnosis is a challenging task in protein engineering. Current approaches are tedious, often time-consuming and require complex laboratory data due to the vast search spaces that need to be considered. In silico methods can accelerate research and substantially reduce costs. Evolutionary algorithms are a promising approach for exploring large search spaces and can facilitate the discovery of new peptides. This study presents the development and use of a new variant of the genetic-programming-based POET algorithm, called POETRegex , where individuals are represented by a list of regular expressions. This algorithm was trained on a small curated dataset and employed to generate new peptides improving the sensitivity of peptides in magnetic resonance imaging with chemical exchange saturation transfer (CEST). The resulting model achieves a performance gain of 20% over the initial POET models and is able to predict a candidate peptide with a 58% performance increase compared to the gold-standard peptide. By combining the power of genetic programming with the flexibility of regular expressions, new peptide targets were identified that improve the sensitivity of detection by CEST. This approach provides a promising research direction for the efficient identification of peptides with therapeutic or diagnostic potential.

MALDI-TOF MS Analysis of Serum Peptidome Patterns in Cervical Cancer

BACKGROUND

Cervical cancer is the fourth most common cancer among females worldwide. Identifying peptide patterns discriminating healthy individuals from those with diseases has gained interest in the early detection of cancers. Our study aimed to determine signature peptide patterns for cervical cancer screening.

METHODS

Our study focused on the serum peptidome analysis of 83 healthy women and 139 patients with cervical cancer. All spectra derived from matrix-assisted laser desorption/ionization time-of-flight mass spectrometry were analyzed using FlexAnalysis 3.0 and ClinProTools 2.2 software.

RESULTS

In the mass range of 1000-10,000 Da, the total average spectra were represented as the signature pattern. Principal component analysis showed that all the groups were separately distributed. Furthermore, the peaks at m/z 1466.91, 1898.01, 3159.09, and 4299.40 significantly differed among the investigated groups (Wilcoxon/Kruskal-Wallis test and ANOVA, p < 0.001).

CONCLUSIONS

Laboratory-based rapid mass spectrometry showed that serum peptidome patterns could serve as diagnostic tools for diagnosing cervical cancer; however, verification through larger cohorts and association with clinical data are required, and the use of externally validated samples, such as patients with other types of cancers, should be investigated to validate the specific peptide patterns.

Nanopore Discrimination of Coagulation Biomarker Derivatives and Characterization of a Post-Translational Modification

One of the most important health challenges is the early and ongoing detection of disease for prevention, as well as personalized treatment management. Development of new sensitive analytical point-of-care tests are, therefore, necessary for direct biomarker detection from biofluids as critical tools to address the healthcare needs of an aging global population. Coagulation disorders associated with stroke, heart attack, or cancer are defined by an increased level of the fibrinopeptide A (FPA) biomarker, among others. This biomarker exists in more than one form: it can be post-translationally modified with a phosphate and also cleaved to form shorter peptides. Current assays are long and have difficulties in discriminating between these derivatives; hence, this is an underutilized biomarker for routine clinical practice. We use nanopore sensing to identify FPA, the phosphorylated FPA, and two derivatives. Each of these peptides is characterized by unique electrical signals for both dwell time and blockade level. We also show that the phosphorylated form of FPA can adopt two different conformations, each of which have different values for each electrical parameter. We were able to use these parameters to discriminate these peptides from a mix, thereby opening the way for the potential development of new point-of-care tests.

A Circulating Risk Score, Based on Combined Expression of Exo-miR-130a-3p and Fibrinopeptide A, as Predictive Biomarker of Relapse in Resectable Non-Small Cell Lung Cancer Patients

Simple Summary

To date, the five-year survival rate of early stages of non-small cell lung cancer (NSCLC) is still disappointing and reliable prognostic factors are mandatory. Here, we performed in-depth high-throughput analyses of plasma circulating markers, including exosomal microRNAs and peptidome to identify a prognostic score. The miRnome profile selected the Exo-miR-130a-3p as the most overexpressed in relapsed patients. Peptidome analysis identified four progressively more degraded forms of fibrinopeptide A (FpA), which were depleted in relapse patients. Notably, a stepwise algorithm selected Exo-miR-130a-3p and the greatest FpA (2–16) to build a prognostic score, where high-risk patients had 18 months of median disease-free survival. Overexpression of miR-130a-3p cells led to a deregulation of pathways such as angiogenesis as well as the coagulation and metalloprotease, which might be linked to FpA reduction. The risk score integrating circulating markers may help clinicians predict early-stage NSCLC patients who are more likely to relapse after surgery.

Abstract

To date, the 5-year overall survival rate of 60% for early-stage non-small cell lung cancer (NSCLC) is still unsatisfactory. Therefore, reliable prognostic factors are needed. Growing evidence shows that cancer progression may depend on an interconnection between cancer cells and the surrounding tumor microenvironment; hence, circulating molecules may represent promising markers of cancer recurrence. In order to identify a prognostic score, we performed in-depth high-throughput analyses of plasma circulating markers, including exosomal microRNAs (Exo-miR) and peptides, in 67 radically resected NSCLCs. The miRnome profile selected the Exo-miR-130a-3p as the most overexpressed in relapsed patients. Peptidome analysis identified four progressively more degraded forms of fibrinopeptide A (FpA), which were depleted in progressing patients. Notably, stepwise Cox regression analysis selected Exo-miR-130a-3p and the greatest FpA (2-16) to build a score predictive of recurrence, where high-risk patients had 18 months of median disease-free survival. Moreover, in vitro transfections showed that higher levels of miR-130a-3p lead to a deregulation of pathways involved in metastasis and angiogenesis, including the coagulation process and metalloprotease increase which might be linked to FpA reduction. In conclusion, by integrating circulating markers, the identified risk score may help clinicians predict early-stage NSCLC patients who are more likely to relapse after primary surgery.

Cardio- and reno-protective effects of dipeptidyl peptidase III in diabetic mice

Diabetes mellitus (DM) causes injury to tissues and organs, including to the heart and kidney, resulting in increased morbidity and mortality. Thus, novel potential therapeutics are continuously required to minimize DM-related organ damage. We have previously shown that dipeptidyl peptidase III (DPPIII) has beneficial roles in a hypertensive mouse model, but it is unknown whether DPPIII has any effects on DM. In this study, we found that intravenous administration of recombinant DPPIII in diabetic db/db mice for 8 weeks suppressed the DM-induced cardiac diastolic dysfunctions and renal injury without alteration of the blood glucose level. This treatment inhibited inflammatory cell infiltration and fibrosis in the heart and blocked the increase in albuminuria by attenuating the disruption of the glomerular microvasculature and inhibiting the effacement of podocyte foot processes in the kidney. The beneficial role of DPPIII was, at least in part, mediated by the cleavage of a cytotoxic peptide, named Peptide 2, which was increased in db/db mice compared with normal mice. This peptide consisted of nine amino acids, was a digested fragment of complement component 3 (C3), and had an anaphylatoxin-like effect determined by the Miles assay and chemoattractant analysis. The effect was dependent on its interaction with the C3a receptor and protein kinase C-mediated RhoA activation downstream of the receptor in endothelial cells. In conclusion, DPPIII plays a protective role in the heart and kidney in a DM animal model through cleavage of a peptide that is a part of C3.

The plasma peptides of sepsis

Background

A practical strategy to discover sepsis specific proteins may be to compare the plasma peptides and proteins from patients in the intensive care unit with and without sepsis. The aim was to discover proteins and/or peptides that show greater observation frequency and/or precursor intensity in sepsis. The endogenous tryptic peptides of ICU-Sepsis were compared to ICU Control, ovarian cancer, breast cancer, female normal, sepsis, heart attack, Alzheimer’s and multiple sclerosis along with their institution-matched controls, female normals and normal samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from individual sepsis and control EDTA plasma samples in a step gradient of acetonitrile for random and independent sampling by LC–ESI–MS/MS with a set of robust and sensitive linear quadrupole ion traps. The MS/MS spectra were fit to fully tryptic peptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The protein observation frequency of ICU-sepsis versus ICU Control was subsequently tested by Chi square analysis. The average protein or peptide log₁₀ precursor intensity was compared across disease and control treatments by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as ITIH3, SAA2, SAA1, and FN1 showed increased observation frequency by Chi square (χ² > 9, p < 0.003) and/or precursor intensity in sepsis. Cellular gene symbols with large Chi square values from tryptic peptides included POTEB, CTNNA1, U2SURP, KIF24, NLGN2, KSR1, GTF2H1, KIT, RPS6KL1, VAV2, HSPA7, SMC2, TCEB3B, ZNF300, SUPV3L1, ADAMTS20, LAMB4, MCCC1, SUPT6H, SCN9A, SBNO1, EPHA1, ABLIM2, cB5E3.2, EPHA10, GRIN2B, HIVEP2, CCL16, TKT, LRP2 and TMF1 amongst others showed increased observation frequency. Similarly, increased frequency of tryptic phosphopeptides were observed from POM121C, SCN8A, TMED8, NSUN7, SLX4, MADD, DNLZ, PDE3B, UTY, DEPDC7, MTX1, MYO1E, RXRB, SYDE1, FN1, PUS7L, FYCO1, USP26, ACAP2, AHI1, KSR2, LMAN1, ZNF280D and SLC8A2 amongst others. Increases in mean precursor intensity in peptides from common plasma proteins such as ITIH3, SAA2, SAA1, and FN1 as well as cellular proteins such as COL24A1, POTEB, KANK1, SDCBP2, DNAH11, ADAMTS7, MLLT1, TTC21A, TSHR, SLX4, MTCH1, and PUS7L among others were associated with sepsis. The processing of SAA1 included the cleavage of the terminal peptide D/PNHFRPAGLPEKY from the most hydrophilic point of SAA1 on the COOH side of the cystatin C binding that was most apparent in ICU-Sepsis patients compared to all other diseases and controls. Additional cleavage of SAA1 on the NH2 terminus side of the cystatin binding site were observed in ICU-Sepsis. Thus there was disease associated variation in the processing of SAA1 in ICU-Sepsis versus ICU controls or other diseases and controls.

Conclusion

Specific proteins and peptides that vary between diseases might be discovered by the random and independent sampling of multiple disease and control plasma from different hospital and clinics by LC–ESI–MS/MS for storage in a relational SQL Server database and analysis with the R statistical system that will be a powerful tool for clinical research. The processing of SAA1 may play an unappreciated role in the inflammatory response to Sepsis.

The plasma peptides of breast versus ovarian cancer

Background

There is a need to demonstrate a proof of principle that proteomics has the capacity to analyze plasma from breast cancer versus other diseases and controls in a multisite clinical trial design. The peptides or proteins that show a high observation frequency, and/or precursor intensity, specific to breast cancer plasma might be discovered by comparison to other diseases and matched controls. The endogenous tryptic peptides of breast cancer plasma were compared to ovarian cancer, female normal, sepsis, heart attack, Alzheimer's and multiple sclerosis along with the institution-matched normal and control samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from individual breast cancer and control EDTA plasma samples in a step gradient of acetonitrile, and collected over preparative C18 for LC-ESI-MS/MS with a set of LTQ XL linear quadrupole ion traps working together in parallel to randomly and independently sample clinical populations. The MS/MS spectra were fit to fully tryptic peptides or phosphopeptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The observation frequency was subsequently tested by Chi Square analysis. The log₁₀ precursor intensity was compared by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as APOE, C4A, C4B, C3, APOA1, APOC2, APOC4, ITIH3 and ITIH4 showed increased observation frequency and/or precursor intensity in breast cancer. Many cellular proteins also showed large changes in frequency by Chi Square (χ² > 100, p < 0.0001) in the breast cancer samples such as CPEB1, LTBP4, HIF-1A, IGHE, RAB44, NEFM, C19orf82, SLC35B1, 1D12A, C8orf34, HIF1A, OCLN, EYA1, HLA-DRB1, LARS, PTPDC1, WWC1, ZNF562, PTMA, MGAT1, NDUFA1, NOGOC, OR1E1, OR1E2, CFI, HSA12, GCSH, ELTD1, TBX15, NR2C2, FLJ00045, PDLIM1, GALNT9, ASH2L, PPFIBP1, LRRC4B, SLCO3A1, BHMT2, CS, FAM188B2, LGALS7, SAT2, SFRS8, SLC22A12, WNT9B, SLC2A4, ZNF101, WT1, CCDC47, ERLIN1, SPFH1, EID2, THOC1, DDX47, MREG, PTPRE, EMILIN1, DKFZp779G1236 and MAP3K8 among others. The protein gene symbols with large Chi Square values were significantly enriched in proteins that showed a complex set of previously established functional and structural relationships by STRING analysis. An increase in mean precursor intensity of peptides was observed for QSER1 as well as SLC35B1, IQCJ-SCHIP1, MREG, BHMT2, LGALS7, THOC1, ANXA4, DHDDS, SAT2, PTMA and FYCO1 among others. In contrast, the QSER1 peptide QPKVKAEPPPK was apparently specific to ovarian cancer.

Conclusion

There was striking agreement between the breast cancer plasma peptides and proteins discovered by LC-ESI-MS/MS with previous biomarkers from tumors, cells lines or body fluids by genetic or biochemical methods. The results indicate that variation in plasma peptides from breast cancer versus ovarian cancer may be directly discovered by LC-ESI-MS/MS that will be a powerful tool for clinical research. It may be possible to use a battery of sensitive and robust linear quadrupole ion traps for random and independent sampling of plasma from a multisite clinical trial.

Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome

Recent advances in high-throughput molecular and multi-omics technologies have improved our understanding of the molecular changes associated with thyroid cancer initiation and progression. The translation into clinical use based on molecular profiling of thyroid tumors has allowed a significant improvement in patient risk stratification and in the identification of targeted therapies, and thereby better personalized disease management and outcome. This review compiles the following: (1) the major molecular alterations of the genome, epigenome, transcriptome, proteome, and metabolome found in all subtypes of thyroid cancer, thus demonstrating the complexity of these tumors and (2) the great translational potential of multi-omics studies to improve patient outcome.

Comparative analysis of the serum proteome profiles of thyroid cancer: An initial focus on the lipid profile

The serum lipid profile and clinical outcomes of cancer patients are commonly correlated in a wide range of carcinomas. However, few studies have investigated the serum lipid profile of patients with thyroid cancer (TC). The present study therefore aimed to analyze the lipid profiles of patients with TC. The serum proteomes of 31 participants with stage I-IV TC were screened using Orbitrap Q Exactive Plus. Analytical data collected between November 1, 2013 and November 11, 2018 from the laboratory information system included the total cholesterol (CHO), triglyceride (TG), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), lipoprotein (a) and apolipoprotein B (ApoB) levels that were used to validate the screening results. A total of 3875 outpatients were enrolled in this study. A number of 17 differentially expressed proteins were identified. An Ingenuity pathway analysis identified activation of the liver X receptor/retinoid X receptor (LXR/RXR) activation, which is a crucial pathway involved in lipid metabolism. The results demonstrated that the total CHO levels were significantly different between patients with TC and control groups, both in men and women. In women, the levels of TG, HDL-C, Apo A1 and LDL-C/HDL-C were significantly different between patients with TC and control groups (all P<0.05). Higher concentrations of TG and LDL-C/HDL-C were observed in the cancer group compared with the control group. However, lower levels of Apo A1 and HDL-C were observed in women from the cancer group compared with the control group. The results from the present study revealed the presence of a disordered lipid profile in patients with TC. The molecular mechanism underlying the association between lipid metabolism and cancer requires further investigation and may be used to develop novel diagnostic biomarkers and therapeutic targets in human cancers.

Peptidome analysis reveals the involvement of endogenous peptides in mouse pancreatic dysfunction with aging

Type 2 diabetes (T2D) is a glucose regulation disorder that has significantly enhanced mortality and the global disease burden. The prevalence of T2D has increased worldwide and is higher in the elderly. The function of pancreatic islets decreases with age, which is one important reason for the occurrence of diabetes in the elderly. Recently, peptidome analysis has attracted attention. However, the role of age-related peptides in pancreatic dysfunction has not been investigated extensively. Here, we conducted a comparison of endogenous peptides between pancreas from adult and aging mice by liquid chromatography tandem mass spectrometry (LC-MS/MS). A total of 2,089 peptides originating from 1,280 protein precursors were identified, of which 232 were upregulated and 183 were downregulated in the aging mice (fold change ≥ 2 and p < 0.05), suggesting that the expression of pancreatic peptides in mice varied with age. The molecular weight of most peptides was <3.0 kDa, and the isoelectric point distribution had a bimodal characteristic. Further analysis of cleavage site patterns indicated that proteases cleaved pancreatic proteins according to their rules. Moreover, Gene Ontology and pathway analyses showed that the differentially expressed peptides potentially had specific effects on pancreatic dysfunction. Some differential peptides were located within the domains of precursor proteins that were closely associated with the development of diabetes. We believe that our research may advance the current understanding of pancreas-derived peptides and that certain peptides may be involved in the etiology of diabetes.

Selected reaction monitoring for colorectal cancer diagnosis using a set of five serum peptides identified by BLOTCHIP®-MS analysis

BACKGROUND

Colorectal cancer (CRC) is one of the most predominant types of cancer, and it is the fourth most common cause of cancer-related death and it is important to diagnose CRC in early stage to decrease the mortality by CRC. In our previous study, we identified a combination of five peptides as a biomarker candidate to diagnose CRC by BLOTCHIP^®-MS analysis using a set of healthy control subjects and CRC patients (stage II-IV). The aim of the present study was to validate the serum biomarker peptides reported in our previous study using a second cohort and to establish their potential usefulness in CRC diagnosis.

METHODS

A total of 56 patients with CRC (n = 14 each of stages I-IV), 60 healthy controls, and 60 patients with colonic adenoma were included in this study. The five peptides were extracted and analyzed by selected reaction monitoring using ProtoKey^® Colorectal Cancer Risk Test Kit (Protosera, Inc., Amagasaki, Japan).

RESULTS

The results clearly showed that the four CRC groups, stages I-IV, could be sufficiently discriminated from the control group and colonic polyp group. This five-peptide set could identify CRC at each stage compared to the control population in this validation cohort, including those with early-stage disease. The AUC values for each stage of CRC compared to the control population were 0.779, 0.946, 0.852, and 0.973 for stages I, II, III, and IV, respectively.

CONCLUSIONS

In this case-control validation study, we confirmed high diagnostic performance for CRC using five peptides that were identified in our previous study as serum biomarker candidates for the detection of CRC.

Contribution of the plasma and lymph Degradome and Peptidome to the MHC Ligandome

Every biological fluid, blood, interstitial fluid and lymph, urine, saliva, lacrimal fluid, nipple aspirate, and spinal fluid, contains a peptidome-degradome derived from the cellular secretome along with byproducts of the metabolic/catabolic activities of each parenchymal organ. Clement et al. (J Proteomics 78:172-187, 2013), Clement et al. (J Biol Chem 291:5576-5595, 2016), Clement et al. (PLoS One 5:e9863, 2010), Clement et al. (Trends Immunol 32:6-11, 2011), Clement et al. (Front Immunol 4:424, 2013), Geho et al. (Curr Opin Chem Biol 10, 50-55, 2006), Interewicz et al. (Lymphology 37:65‑72, 2004), Leak et al. (Proteomics 4:753‑765, 2004), Popova et al. (PLoS One 9:e110873, 2014), Zhou et al. (Electrophoresis 25:1289‑1298, 2004), D'Alessandro et al. (Shock 42:509‑517, 2014), Dzieciatkowska et al. (Shock 42:485‑498, 2014), Dzieciatkowska et al. (Shock 35:331‑338, 2011), Jordan et al. (J Surg Res 143:130‑135, 2007), Peltz et al. (Surgery 146:347‑357, 2009), Zurawel et al. (Clin Proteomics 8:1, 2011), Ling et al. (Clin Proteomics 6:175‑193, 2010), Sturm et al. (Nat Commun 4:1616, 2013). Over the last decade, qualitative and quantitative analysis of the biological fluids peptidome and degradome have provided a dynamic measurement of tissue homeostasis as well as the tissue response to pathological damage. Proteomic profiling has mapped several of the proteases and resulting degradation by-products derived from cell cycle progression, organ/tissue remodeling and cellular growth, physiological apoptosis, hemostasis, and angiogenesis. Currently, a growing interest lies in the degradome observed during pathological conditions such as cancer, autoimmune diseases, and immune responses to pathogens as a way to exploit biological fluids as liquid biopsies for biomarker discovery Dzieciatkowska et al. (Shock 42:485-498, 2014), Dzieciatkowska et al. (Shock 35:331-338, 2011), Ling et al. (Clin Proteomics 6:175-193, 2010), Ugalde et al. (Methods Mol Biol 622:3-29, 2010), Quesada et al. (Nucleic Acids Res 37:D239‑243, 2009), Cal et al. (Front Biosci 12, 4661-4669, 2007), Shen et al. (PLoS One 5:e13133, 2010a), Antwi et al. (Mol Immunol 46:2931-2937, 2009a), Antwi et al. (J Proteome Res 8:4722‑4731, 2009b), Bedin et al. (J Cell Physiol 231, 915‑925, 2016), Bery et al. (Clin Proteomics 11:13, 2014), Bhalla et al. (Sci Rep 7:1511, 2017), Fan et al. (Diagn Pathol 7:45, 2012a), Fang et al. (Shock 34:291‑298, 2010), Fiedler et al. (Clin Cancer Res 15:3812‑3819, 2009), Fredolini et al. (AAPS J 12:504‑518, 2010), Greening et al. (Enzymes 42:27‑64, 2017), He et al. (PLoS One 8:e63724, 2013), Huang et al. (Int J Gynecol Cancer 28:355‑362, 2018), Hashiguchi et al. (Med Hypotheses 73:760‑763, 2009), Liotta and Petricoin (J Clin Invest 116:26‑30, 2006), Petricoin et al. (Nat Rev Cancer 6:961‑967, 2006), Shen et al. (J Proteome Res 9:2339‑2346, 2010a), Shen et al. (J Proteome Res 5:3154‑3160, 2006), Smith (Clin Proteomics 11:23, 2014), Wang et al. (Oncotarget 8:59376‑59386, 2017), Yang et al. (Clin Exp Med 12:79‑87, 2012a), Yang et al. (J Clin Lab Anal 26:148‑154, 2012b), Yang et al. (Anat Rec (Hoboken) 293:2027‑2033, 2010), Zapico-Muniz et al. (Pancreas 39:1293‑1298, 2010), Villanueva et al. (Mol Cell Proteomics 5:1840‑1852, 2006), Robbins et al. (J Clin Oncol 23:4835‑4837, 2005), Klupczynska et al. (Int J Mol Sci 17:410, 2016). In this review, we focus on the current knowledge of the degradome/peptidome observed in two main biological fluids (plasma and lymph) during physiological and pathological conditions and its importance for immune surveillance.

A novel approach for characterizing variations in serum peptides in rheumatic heart disease

Background & objectives:

Acute rheumatic fever and rheumatic heart disease (RHD) are important public health problems in developing countries. In this study, peptidomic analyses on RHD patients and healthy individuals were performed to characterize variations in serum peptide levels using label-free quantitation approaches.

Methods:

Blood samples were obtained from 160 healthy controls and 160 RHD patients. Of the 448 identified peptides, 272 were analyzed by two label-free mass spectrometry methods, the spectral count and spectral index.

Results:

There were 38 proteins and 95 peptides with significant (adjusted P<0.001) differences in the abundance of peptides between healthy controls and RHD patients, including multiple peptides derived from histone H2B, villin-like protein, complement C4-B and motile sperm domain containing protein-2. The levels of 10 peptides were upregulated, and 85 peptides were downregulated in patients compared to controls. In addition, in patients, the levels of four proteins were upregulated and 34 were downregulated compared to controls.

Interpretation & conclusions:

This study shows that detection of significant changes in serum peptides reflects the difference between RHD patients and healthy controls. This label-free method may be helpful for clinicians to treat RHD patients during the perioperative period.

Detection of Breast Cancer by Surface-enhanced Laser Desorption/Ionization Time-of-flight Mass Spectrometry Tissue and Serum Protein Profiling

Aim

Novel diagnostic breast cancer markers have been extensively searched for in the proteome, using, among others, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Thus far, the majority of SELDI-TOF MS studies have investigated samples originating from biorepositories, which hampers biomarker discovery as they likely suffer from variable adherence to collection protocols.

Material and methods

We investigated breast cancer (n=75) and control (n=26) serum and tissue samples, collected prospectively by rigorous adherence to a strictly defined protocol. Sera were collected preoperatively and postoperatively, and serum and tissue samples were analyzed by SELDI-TOF MS using the IMAC30 Ni and Q10 pH 8 array.

Results

Three serum peaks were significantly associated with breast cancer, while in tissue, 27 discriminative peaks were detected. Several peak clusters gradually increased or decreased in intensity from healthy to benign to cancer, or with increasing cancer stage. The constructed classification trees had a tenfold cross-validated performance of 67% to 87%. Two tissue peaks were identified as N-terminal albumin fragments. These are likely to have been generated by (breast) cancer-specific proteolytic activity in the tumor microenvironment.

Conclusions

These albumin fragments can potentially provide insights into the pathophysiological mechanisms associated with, or underlying, breast cancer, and aid in improving breast cancer diagnosis.

Complement in cancer: untangling an intricate relationship

In tumour immunology, complement has traditionally been considered as an adjunctive component that enhances the cytolytic effects of antibody-based immunotherapies, such as rituximab. Remarkably, research in the past decade has uncovered novel molecular mechanisms linking imbalanced complement activation in the tumour microenvironment with inflammation and suppression of antitumour immune responses. These findings have prompted new interest in manipulating the complement system for cancer therapy. This Review summarizes our current understanding of complement-mediated effector functions in the tumour microenvironment, focusing on how complement activation can act as a negative or positive regulator of tumorigenesis. It also offers insight into clinical aspects, including the feasibility of using complement biomarkers for cancer diagnosis and the use of complement inhibitors during cancer treatment.

Identification of ᴅ-amino acid-containing peptides in human serum

Biologically uncommon d-aspartate (d-Asp) residues have been shown to accumulate in proteins associated with age-related human disorders, such as cataract and Alzheimer disease. Such d-Asp-containing proteins are unlikely to be broken down completely because metabolic enzymes recognize only proteins or peptides composed exclusively of l-amino acids. Therefore, undigested d-Asp-containing peptides may exist in blood and, if detectable, may be a useful biomarker for associated diseases. In this study, we investigated d-amino acid-containing peptides in adult human serum by a qualitative d-amino acid analysis based on a diastereomer method and LC-MS/MS method. As a result, two d-Asp-containing peptides were detected in serum, both derived from the fibrinogen β-chain, a glycoprotein that helps in the formation of blood clots. One of the peptides was fibrinopeptide B, which prevents fibrinogen from forming polymers of fibrin, and the other was same peptide with C-terminal Arginine missing. To our knowledge, this is the first report of the presence of d-amino acid-containing peptides in serum and the approach described will provide a new direction on the serum proteome and fragmentome.

Metabolomic Profiling of Serum Retinol in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study

The role of retinol in the prevention of multifactorial chronic diseases remains uncertain, and there is sparse evidence regarding biological actions and pathways implicated in its effects on various outcomes. The aim is to investigate whether serum retinol in an un-supplemented state is associated with low molecular weight circulating metabolites. We performed a metabolomic analysis of 1,282 male smoker participants based on pre-supplementation fasting serum in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. We examined the association between 947 metabolites measured by ultra-high performance LC-MS/GC-MS and retinol concentration (from HPLC) using linear regression that estimated the difference in metabolite concentrations per unit difference in retinol concentration as standardized β-coefficients and standard errors (SE). We identified 63 metabolites associated with serum retinol below the Bonferroni-corrected P-value (p < 5.3 × 10^–5). The strongest signals were for N-acetyltryptophan (β = 0.27; SE = 0.032; p = 9.8 × 10⁻¹⁷), myo-inositol (β = 0.23; SE = 0.032; p = 9.8 × 10⁻¹³), and 1-palmitoylglycerophosphoethanolamine (β = 0.22; SE = 0.032; p = 3.2 × 10⁻¹²). Several chemical class pathways were strongly associated with retinol, including amino acids (p = 1.6 × 10⁻¹⁰), lipids (p = 3.3 × 10^–7), and cofactor/vitamin metabolites (3.3 × 10⁻⁷). The strongest sub-pathway association was for inositol metabolism (p = 2.0 × 10^–14). Serum retinol concentration is associated with circulating metabolites in various metabolic pathways, particularly lipids, amino acids, and cofactors/vitamins. These interrelationships may have relevance to the biological actions of retinol, including its role in carcinogenesis.

Evaluation of serum phosphopeptides as potential biomarkers of gastric cancer

A serum phosphopeptide (DpSGEGDFLAEGGGVR) was demonstrated to be a potential biomarker for gastric cancer diagnosis, particularly for early stage cases.

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

Identification of Serum Peptidome Signatures of Non-Small Cell Lung Cancer

Due to high mortality rates of lung cancer, there is a need for identification of new, clinically useful markers, which improve detection of this tumor in early stage of disease. In the current study, serum peptide profiling was evaluated as a diagnostic tool for non-small cell lung cancer patients. The combination of the ZipTip technology with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for the analysis of peptide pattern of cancer patients (n = 153) and control subjects (n = 63) was presented for the first time. Based on the observed significant differences between cancer patients and control subjects, the classification model was created, which allowed for accurate group discrimination. The model turned out to be robust enough to discriminate a new validation set of samples with satisfactory sensitivity and specificity. Two peptides from the diagnostic pattern for non-small cell lung cancer (NSCLC) were identified as fragments of C3 and fibrinogen α chain. Since ELISA test did not confirm significant differences in the expression of complement component C3, further study will involve a quantitative approach to prove clinical utility of the other proteins from the proposed multi-peptide cancer signature.

Proteomic study of benign and malignant pleural effusion

BACKGROUND

Lung adenocarcinoma can easily cause malignant pleural effusion which was difficult to discriminate from benign pleural effusion. Now there was no biomarker with high sensitivity and specificity for the malignant pleural effusion.

PURPOSE

This study used proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model.

METHODS

We chose the weak cationic-exchanger magnetic bead (WCX-MB) to purify peptides in the pleural effusion, used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to obtain peptide expression profiles from the benign and malignant pleural effusion samples, established and validated the diagnostic model through a genetic algorithm (GA) and finally identified the most promising protein biomarker.

RESULTS

A GA diagnostic model was established with spectra of 3930.9 and 2942.8 m/z in the training set including 25 malignant pleural effusion and 26 benign pleural effusion samples, yielding both 100 % sensitivity and 100 % specificity. The accuracy of diagnostic prediction was validated in the independent testing set with 58 malignant pleural effusion and 34 benign pleural effusion samples. Blind evaluation was as follows: the sensitivity was 89.6 %, specificity 88.2 %, PPV 92.8 %, NPV 83.3 % and accuracy 89.1 % in the independent testing set. The most promising peptide biomarker was identified successfully: Isoform 1 of caspase recruitment domain-containing protein 9 (CARD9), with 3930.9 m/z, was decreased in the malignant pleural effusion.

CONCLUSIONS

This model is suitable to discriminate benign and malignant pleural effusion and CARD9 can be used as a new peptide biomarker.

Discovery of Candidate Biomarkers

Properly performed, biomarker discovery can lead to effective candidates that can ultimately serve as predictors of disease, medical condition, define therapeutic parameters, and many other applications in medicine. Preferably, biomarkers comprise a panel of indicators, e.g. proteins and/or peptides that can be predictive or diagnostic of the medical condition of interest. Emphasis here is placed on "panel," as single candidates are rarely sufficient to provide the necessary sensitivity and specificity. To develop an effective panel that survives the development process described in Chap. 19 , proper experimental design and attention to important statistical parameters are critical to ensure success. Errors in discovery can lead to an inefficient use of expensive resources, as these may not be uncovered until the latter stages in biomarker development. Hence, accuracy, precision, and an estimate of the power of the proposed analyses are critical in the discovery of the panel of candidate biomarkers by proteomic methods, as is the selection of statistical approaches to refine and appropriately reduce the dataset for subsequent confirmatory assays.

Fibrinogen-derived fibrinostatin inhibits tumor growth through anti-angiogenesis

Angiogenesis is a prerequisite of tumor growth and metastasis and, thus, anti‐angiogenesis treatment has become an important part of cancer therapy. A 15‐amino acid peptide of the fibrinogen α chain, fibrinostatin, was previously found in serum samples of gastric cancer patients. Herein we demonstrated that fibrinostatin has anti‐angiogenesis activity in several angiogenesis models and it reduces tumor growth in mouse xenografts and allografts. Increased tumor necrosis and reduced microvessel density in tumors were observed in mouse xenograft models. Fibrinostatin inhibited proliferation and induced apoptosis in HUVEC, but not in cancer cells. In addition, fibrinostatin specifically entered HUVEC. Fibrinostatin also prevented migration, adhesion and tubule formation of HUVEC in vitro. A single‐dose acute toxicity testing and a repeated‐dose chronic toxicity study in the mouse, rat and monkey indicated that fibrinostatin had a wide margin of safety. Taken together, fibrinostatin shows promise as a potential anti‐angiogenesis therapeutic agent.

Alterations of the Plasma Peptidome Profiling in Colorectal Cancer Progression

Early detection of colorectal cancer (CRC) remains a challenge. It has been highlighted that the pathological alterations within an organ and tissues might be reflected in serum or plasma proteomic/peptidic patterns. The aim of the study was to follow the changes in the plasma peptides associated to colorectal cancer progression by mass spectrometry. This study included 27 adenoma, 67 CRC (n = 33 I-II stage and n = 34 III-IV stage), 23 liver metastasis from CRC patients and 34 subjects disease-free as controls. For plasma peptides analysis, samples purification was performed on the Nanoporous Silica Chips technology followed by matrix-assisted laser desorption/ionisation-time of flight analysis. Since the high complexity of the obtained dataset, multivariate statistical analysis, and discriminant pattern recognition were performed for study groups classification. Forty-four of 88 ionic species were successfully identified as fragments of peptides and proteins physiologically circulating in the blood and belonging to immune and coagulation systems and inflammatory mediators. Many peptides clustered into sets of overlapping sequences with ladder-like truncation clearly associated to proteolytic processes of both endo- and exoproteases activity. Comparing to controls, a different median ion intensity of the group-type fragments distribution was observed. Moreover, the degradation pattern obtained by proteolytic cleavage was different into study groups. This pattern was specific and characteristic of each group: controls, colon tumour disease (including adenoma and CRC), and liver metastasis, revealing a role as biomarker in early diagnosis and prognosis. Our findings highlighted peculiar changes in protease activity characteristic of CRC progression from pre-cancer lesion to metastatic disease. J. Cell. Physiol. 231: 915-925, 2016. © 2015 Wiley Periodicals, Inc.

Proteomic proof that a probiotic elevates glutathione level in human serum

Lactobacillus fermentum ME-3 (LfME-3) has been proven to synthesize and secrete glutathione. A regular use of the foods fermented by it has shown a favourable influence on human lipid profiles and several antioxidant parameters. We administered the LfME-3-fermented kefir for 14 days to 43 human subjects and evaluated their serum with MALDI-TOF mass spectrometer at the beginning and end of the test period. We found an increase of the peak at m/z 308 (corresponding to glutathione) and a new peak at m/z 1467.

Deconvolution analysis for classifying gastric adenocarcinoma patients based on differential scanning calorimetry serum thermograms

Recently, differential scanning calorimetry (DSC) has been acknowledged as a novel tool for diagnosing and monitoring several diseases. This highly sensitive technique has been traditionally used to study thermally induced protein folding/unfolding transitions. In previous research papers, DSC profiles from blood samples of patients were analyzed and they exhibited marked differences in the thermal denaturation profile. Thus, we investigated the use of this novel technology in blood serum samples from 25 healthy subjects and 30 patients with gastric adenocarcinoma (GAC) at different stages of tumor development with a new multiparametric approach. The analysis of the calorimetric profiles of blood serum from GAC patients allowed us to discriminate three stages of cancer development (I to III) from those of healthy individuals. After a multiparametric analysis, a classification of blood serum DSC parameters from patients with GAC is proposed. Certain parameters exhibited significant differences (P < 0.05) and allowed the discrimination of healthy subjects/patients from patients at different tumor stages. The results of this work validate DSC as a novel technique for GAC patient classification and staging, and offer new graphical tools and value ranges for the acquired parameters in order to discriminate healthy from diseased subjects with increased disease burden.

Proteomic study of pilocytic astrocytoma pediatric brain tumor intracystic fluid

Liquid chromatography in coupling with high-resolution ESI-LTQ-Orbitrap mass spectrometry was applied for a proteomic study of pediatric pilocytic astrocytoma brain tumor intracystic fluid by an integrated top-down/bottom-up platform. Both of the proteomic strategies resulted complementary and support each other in contributing to a wide characterization of the protein and peptide content of the tumor fluid. Top-down approach allowed to identify several proteins and peptides involved in different biological activities together with the characterization of interesting proteoforms such as fibrinopeptide A and its truncated form, fibrinopeptide B, complement C3f fragments, β-thymosin peptides, ubiquitin, several apolipoproteins belonging to A and C families, apolipoprotein J and D, and cystatin C. Of particular interest resulted the identification of a N-terminal truncated cystatin C proteoform, likely involved in immune response mechanism modulations and the identification of oxidized and glycosylated apolipoproteins including disulfide bridge dimeric forms. The bottom-up approach confirmed some of the experimental data findings together with adding the characterization of high-molecular-mass proteins in the samples. These data could contribute to elucidate the molecular mechanisms involved in onset and progression of the disease and cyst development.

[Search for potential gastric cancer biomarkers using low molecular weight blood plasma proteome profiling by mass spectrometry]

Gastric cancer, one of the most widespread malignant tumors, still lacks reliable serum/plasma biomarkers of its early detection. In this study we have developed, unified, and tested a new methodology for search of gastric cancer biomarkers based on profiling of low molecular weight proteome (LMWP) (1-17 kDa). This approach included three main components: sample pre-fractionation, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), data analysis by a bioinformatics software package. Applicability and perspectives of the developed approach for detection of potential gastric cancer markers during LMWP analysis have been demonstrated using 69 plasma samples from patients with gastric cancer (stages I-IV) and 238 control samples. The study revealed peptides/polypeptides, which may be potentially used for detection of this pathology.

Mechanistic peptidomics: factors that dictate specificity in the formation of endogenous peptides in human milk

An extensive mass spectrometry analysis of the human milk peptidome has revealed almost 700 endogenous peptides from 30 different proteins. Two in-house computational tools were created and used to visualize and interpret the data through both alignment of the peptide quasi-molecular ion intensities and estimation of the differential enzyme participation. These results reveal that the endogenous proteolytic activity in the mammary gland is remarkably specific and well conserved. Certain proteins-not necessarily the most abundant ones-are digested by the proteases present in milk, yielding endogenous peptides from selected regions. Our results strongly suggest that factors such as the presence of specific proteases, the position and concentration of cleavage sites, and, more important, the intrinsic disorder of segments of the protein drive this proteolytic specificity in the mammary gland. As a consequence of this selective hydrolysis, proteins that typically need to be cleaved at specific positions in order to exert their activity are properly digested, and bioactive peptides encoded in certain protein sequences are released. Proteins that must remain intact in order to maintain their activity in the mammary gland or in the neonatal gastrointestinal tract are unaffected by the hydrolytic environment present in milk. These results provide insight into the intrinsic structural mechanisms that facilitate the selectivity of the endogenous milk protease activity and might be useful to those studying the peptidomes of other biofluids.

Liquid chromatography-mass spectrometry based serum peptidomic approach for renal clear cell carcinoma diagnosis

Serum peptidomic approach was applied to investigate the peptidomic signature and discover the clinical biomarkers and biomarker patterns for RCC patients. The holistic orthogonal partial least-squares-discriminant analysis (OPLS-DA) based on qualified profile data successfully classified RCC patients from healthy controls, showing 100% sensitivity and specificity. Following critical criteria, several peptides presenting significant differences in serum level were picked out. The unsupervised hierarchical cluster analysis on those peptides was performed, showing 100% sensitivity and 93.3% specificity for RCC diagnosis regarding the present samples. Besides, receiver-operating characteristic (ROC) analysis was applied on single peptide biomarkers, with four peptides showing excellent predictive power. Among them, IYQLNSKLV and AGISMRSGDSPQD are reported for the first time for cancer detection.

Peptidomics of Urine and Other Biofluids for Cancer Diagnostics

BACKGROUND

Cancer is a leading cause of death worldwide. The low diagnostic sensitivity and specificity of most current cancer biomarkers make early cancer diagnosis a challenging task. The comprehensive study of peptides and small proteins in a living system, known as “peptidomics,” represents an alternative technological approach to the discovery of potential biomarkers for the assessment of a wide variety of pathologies. This review examines the current status of peptidomics for several body fluids, with a focus on urine, for cancer diagnostics applications.

CONTENT

Several studies have used high-throughput technologies to characterize the peptide content of different body fluids. Because of its noninvasive collection and high stability, urine is a valuable source of candidate cancer biomarkers. A wide variety of preanalytical issues concerning patient selection and sample handling need to be considered, because not doing so can affect the quality of the results by introducing bias and artifacts. Optimization of both the analytical strategies and the processing of bioinformatics data is also essential to minimize the false-discovery rate.

SUMMARY

Peptidomics-based studies of urine and other body fluids have yielded a number of biomolecules and peptide panels with potential for diagnosing different types of cancer, especially of the ovary, prostate, and bladder. Large-scale studies are needed to validate these molecules as cancer biomarkers.

Aminopeptidase activities as prospective urinary biomarkers for bladder cancer

PURPOSE

Proteases have been implicated in cancer progression and invasiveness. We have investigated the activities, as opposed to simple protein levels, of selected aminopeptidases in urine specimens to serve as potential novel biomarkers for urothelial cancer.

EXPERIMENTAL DESIGN

The unique urinary proteomes of males and females were profiled to establish the presence of a gender-independent set of aminopeptidases. Samples were also collected from patients with urothelial cancer and matched controls. A SOP for urine processing was developed taking into account hydration variation. Five specific aminopeptidase activity assays, using fluorophoric substrates, were optimized for evaluation of marker potential.

RESULTS

Nineteen exopeptidases and 21 other proteases were identified in urine and the top-five most abundant aminopeptidases, identical in both genders, selected for functional studies. Depending on the enzyme, activities were consistently lower (p ≤ 0.05), higher or unchanged in the cancer samples as compared to controls. Two selected aminopeptidase activities used as a binary classifier resulted in a ROC curve with an AUC = 0.898.

CONCLUSION AND CLINICAL RELEVANCE

We have developed functional assays that characterize aminopeptidase activities in urine specimens with adequate technical and intraindividual reproducibility. With further testing, it could yield a reliable biomarker test for bladder cancer detection or prognostication.

Identification of potential serum peptide biomarkers of biliary tract cancer using MALDI MS profiling

BACKGROUND

The aim of this discovery study was the identification of peptide serum biomarkers for detecting biliary tract cancer (BTC) using samples from healthy volunteers and benign cases of biliary disease as control groups. This work was based on the hypothesis that cancer-specific exopeptidases exist and that their activities in serum can generate cancer-predictive peptide fragments from circulating proteins during coagulation.

METHODS

This case control study used a semi-automated platform incorporating polypeptide extraction linked to matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to profile 92 patient serum samples. Predictive models were generated to test a validation serum set from BTC cases and healthy volunteers.

RESULTS

Several peptide peaks were found that could significantly differentiate BTC patients from healthy controls and benign biliary disease. A predictive model resulted in a sensitivity of 100% and a specificity of 93.8% in detecting BTC in the validation set, whilst another model gave a sensitivity of 79.5% and a specificity of 83.9% in discriminating BTC from benign biliary disease samples in the training set. Discriminatory peaks were identified by tandem MS as fragments of abundant clotting proteins.

CONCLUSIONS

Serum MALDI MS peptide signatures can accurately discriminate patients with BTC from healthy volunteers.

Peptidomics analysis of human blood specimens for biomarker discovery

This review addresses the concepts, limitations and perspectives for the application of peptidomics science and technologies to discover putative biomarkers in blood specimens. Peptidomics can be defined as the comprehensive multiplex analysis of endogenous peptides contained within a biological sample under defined conditions to describe the multitude of native peptides in a biological compartment. In addition to the discovery of disease associated biomarkers, an emerging field in peptidomics is the analysis of peptides to describe in vivo effects of protease inhibitors. The development and application of peptidomics technologies represent an arena of biomarker research that has the potential for adding significant clinical value.

Detection of cervical cancer biomarker patterns in blood plasma and urine by differential scanning calorimetry and mass spectrometry

Improved methods for the accurate identification of both the presence and severity of cervical intraepithelial neoplasia (CIN) and extent of spread of invasive carcinomas of the cervix (IC) are needed. Differential scanning calorimetry (DSC) has recently been shown to detect specific changes in the thermal behavior of blood plasma proteins in several diseases. This methodology is being explored to provide a complementary approach for screening of cervical disease. The present study evaluated the utility of DSC in differentiating between healthy controls, increasing severity of CIN and early and advanced IC. Significant discrimination was apparent relative to the extent of disease with no clear effect of demographic factors such as age, ethnicity, smoking status and parity. Of most clinical relevance, there was strong differentiation of CIN from healthy controls and IC, and amongst patients with IC between FIGO Stage I and advanced cancer. The observed disease-specific changes in DSC profiles (thermograms) were hypothesized to reflect differential expression of disease biomarkers that subsequently bound to and affected the thermal behavior of the most abundant plasma proteins. The effect of interacting biomarkers can be inferred from the modulation of thermograms but cannot be directly identified by DSC. To investigate the nature of the proposed interactions, mass spectrometry (MS) analyses were employed. Quantitative assessment of the low molecular weight protein fragments of plasma and urine samples revealed a small list of peptides whose abundance was correlated with the extent of cervical disease, with the most striking plasma peptidome data supporting the interactome theory of peptide portioning to abundant plasma proteins. The combined DSC and MS approach in this study was successful in identifying unique biomarker signatures for cervical cancer and demonstrated the utility of DSC plasma profiles as a complementary diagnostic tool to evaluate cervical cancer health.

Circulating proteolytic products of carboxypeptidase N for early detection of breast cancer

BACKGROUND

Carboxypeptidase N (CPN) is important in regulating vasoactive peptide hormones, growth factors, and cytokines by specifically cleaving their C-terminal basic residues. We investigated whether circulating peptides specifically cleaved by CPN in the tumor microenvironment can be stage-specific indicators of breast cancer.

METHODS

CPN activity was measured using an ex vivo peptide cleavage assay by incubating synthesized C3f peptide (His6-C3f_S1304-R1320-His6) in interstitial fluids of breast tumors and adjacent normal breast tissues in mice with orthotopic implantation of the human cell line MDA-MB-231. The nature and extent of peptide cleavage by CPN was investigated by fragment profiling using nanopore fractionation and mass spectrometry. The fragment profiles in interstitial fluid correlated with concentrations of CPN-catalyzed peptides in blood samples taken from the tumor-bearing mice, healthy women, and breast cancer patients. CPN expression in the same set of samples was further examined by immunohistochemistry and immunoblotting.

RESULTS

We showed that generation of C3f_R1310-L1319 specifically correlated with the CPN expression level. In both the mouse and clinical patient samples, CPN was clearly increased in tumor tissues compared with normal breast tissue, whereas corresponding CPN abundance in blood remained constant. Concentrations of 6 CPN-catalyzed peptides predominantly increased in sera taken from the mice (n = 8) at 2 weeks after orthotopic implantation. Six homologous peptides displayed significantly higher expression in the patients' plasma as early as the first pathologic stage of breast cancer.

CONCLUSIONS

Circulating CPN-catalyzed peptide concentrations reflect the CPN activity in tumors. These biomarkers show strong potential for the noninvasive and early diagnosis of breast cancer.

Preparation of titanium-grafted magnetic mesoporous silica for the enrichment of endogenous serum phosphopeptides

As one of the most important post-translational modifications, reversible phosphorylation of protein plays crucial roles in a large number of biological processes. Moreover, endogenous phosphopeptides are also associated with certain human diseases. An efficient enrichment and separation method is the premise for successful identification and quantification of phosphopeptides. In this work, titanium grafted magnetic mesoporous silica (Fe3O4@Ti-mSiO2) was developed and applied for the enrichment of endogenous phosphopeptides. Fe3O4@Ti-mSiO2 particles were prepared by grafting titanocene dichloride on the inner walls of magnetic mesoporous silica and then being calcined to remove cyclopentadienyl ligand. The physicochemical properties of the prepared materials were characterized by energy dispersive X-ray spectroscopy (EDX), nitrogen adsorption-desorption analysis, X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM). For selective enrichment of phosphopeptides, the prepared Fe3O4@Ti-mSiO2 particles were applied for tryptic digests of β-casein, mixtures of β-casein and bovine serum albumin (BSA), and low-fat milk. Finally, Fe3O4@Ti-mSiO2 was successfully applied for the enrichment of endogenous phosphopeptides from human serum.

Peptidome analysis of human skim milk in term and preterm milk

The abundant proteins in human milk have been well characterized and are known to provide nutritional, protective, and developmental advantages to both term and preterm infants. Due to the difficulties associated with detection technology of the peptides, the expression of the peptides present in human milk is not known widely. In recent years, peptidome analysis has received increasing attention. In this report, the analysis of endogenous peptides in human milk was done by mass spectrometry. A method was also developed by our researchers, which can be used in the extraction of peptide from human milk. Analysis of the extracts by LC-MS/MS resulted in the detection of 1000-3000Da peptide-like features. Out of these, 419 peptides were identified by MS/MS. The identified peptides were found to originate from 34 proteins, of which several have been reported. Analysis of the peptides' cleavage sites showed that the peptides are cleaved with regulations. This may reflect the protease activity and distribution in human body, and also represent the biological state of the tissue and provide a fresh source for biomarker discovery. Isotope dimethyl labeling analysis was also used to test the effects of premature delivery on milk protein composition in this study. Differences in peptides expression between breast milk in term milk (38-41weeks gestation) and preterm milk (28-32weeks gestation) were investigated in this study. 41 Peptides in these two groups were found expressed differently. 23 Peptides were present at higher levels in preterm milk, and 18 were present at higher levels in term milk.