Independent validation of candidate breast cancer serum biomarkers identified by mass spectrometry

‘Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics’

In recent times, enormous progress has been made in improving the diagnosis and therapeutic strategies for breast carcinoma, yet it remains the most prevalent cancer and second highest contributor to cancer-related deaths in women. Breast cancer (BC) affects one in eight females globally. In 2018 alone, 1.4 million cases were identified worldwide in postmenopausal women and 645,000 cases in premenopausal females, and this burden is constantly increasing. This shows that still a lot of efforts are required to discover therapeutic remedies for this disease. One of the major clinical complications associated with the treatment of breast carcinoma is the development of therapeutic resistance. Multidrug resistance (MDR) and consequent relapse on therapy are prevalent issues related to breast carcinoma; it is due to our incomplete understanding of the molecular mechanisms of breast carcinoma disease. Therefore, elucidating the molecular mechanisms involved in drug resistance is critical. For management of breast carcinoma, the treatment decision not only depends on the assessment of prognosis factors but also on the evaluation of pathological and clinical factors. Integrated data assessments of these multiple factors of breast carcinoma through multiomics can provide significant insight and hope for making therapeutic decisions. This omics approach is particularly helpful since it identifies the biomarkers of disease progression and treatment progress by collective characterization and quantification of pools of biological molecules within and among the cancerous cells. The scrupulous understanding of cancer and its treatment at the molecular level led to the concept of a personalized approach, which is one of the most significant advancements in modern oncology. Likewise, there are certain genetic and non-genetic tests available for BC which can help in personalized therapy. Genetically inherited risks can be screened for personal predisposition to BC, and genetic changes or variations (mutations) can also be identified to decide on the best treatment. Ultimately, further understanding of BC at the molecular level (multiomics) will define more precise choices in personalized medicine. In this review, we have summarized therapeutic resistance associated with BC and the techniques used for its management.

Platelet Factor 4 as a Novel Exosome Marker in MALDI-MS Analysis of Exosomes from Human Serum

Exosomes are nanosized vesicles commonly found in biological fluids as a result of a secretion process involving endosomes and multivesicular bodies. The isolation and analysis of exosomes can be useful for noninvasive clinical diagnosis of a variety of human diseases. We investigated the utility of analyzing exosomal proteins, using matrix-assisted laser desorption/ionization combined with Fourier-transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS), as a means of determining the presence of exosomes. MALDI-FTICR-MS analyses of exosomes enriched from human serum via centrifugation in a mass range of m/z 1000-20 000 yielded a distinctive protein around m/z 7766. The high mass accuracy and resolution of MALDI-FTICR-MS allowed for reliable comparisons against a protein database, through which the protein was identified as platelet factor 4 (PLF4), whose singly charged protein peak has an elemental composition of C₃₄₁H₅₇₇N₉₆O₁₀₁S₄⁺, with a theoretical most abundant isotopic peak at m/z 7765.194 and a theoretical average peak at m/z 7766. The MALDI-TOF MS analysis of exosomes from the serum of 27 patients with different states of liver diseases provided the most abundant PLF4 peak for each mass spectrum, along with several additional minor peaks. In conclusion, MALDI-MS is suitable as an alternative exosome detection method, serving as a valuable confirmation tool, greatly decreasing the time and workload associated with exosome identification.

Postoperative recurrence of epithelial ovarian cancer patients and chemoresistance related protein analyses

OBJECTIVE

To identify the plasma protein biomarkers related to the chemoresistance of postoperative recurrence of epithelial ovarian cancers.

METHODS

Forty plasma samples from patients in chemotherapy-sensitive and chemotherapy-resistant groups (20 for each group) were collected at Gynecology Department in the Fourth Hospital of Hebei Medical University from September 2013 to September 2014. The differentially expressed proteins between two groups were screened with two-dimensional gel electrophoresis (2-DE) and further analyzed by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS).

RESULTS

Thirty-four differentially expressed spots were identified between the two groups. Compared with the chemo-sensitive group, 21 protein spots were up-regulated and 13 were down-regulated in the chemoresistant group, in which 14 differentially expressed proteins were identified by the Mass spectrometry and Mascot search. Among the 14 proteins, complement C4-A, IgJ chain, clusterin, α-1-antitrypsin and carbonic anhydrase 1 were up-regulated, and transthyretin, haptoglobin, β-2-glycoprotein, Ig γ-2 chain C region, Ig γ-1 chain C region, complement factor I light chain, Igκ chain C region, complement C3 and apolipoprotein E were down-regulated in the chemoresistant group when compared with the chemosensitive group.

CONCLUSION

The up-regulated proteins including transthyretin, apolipoprotein E and haptoglobin proteins and the down-regulated proteins such as clusterin, carbonic anhydrase 1, alpha-1-antitrypsin were differentially expressed in the plasma between the chemo-sensitive group and the chemoresistant group, which may be potential biomarkers for predicting the chemotresistance of epithelial ovarian cancer patients.

Early non-invasive detection of breast cancer using exhaled breath and urine analysis

The main focus of this pilot study is to develop a statistical approach that is suitable to model data obtained by different detection methods. The methods used in this study examine the possibility to detect early breast cancer (BC) by exhaled breath and urine samples analysis. Exhaled breath samples were collected from 48 breast cancer patients and 45 healthy women that served as a control group. Urine samples were collected from 37 patients who were diagnosed with breast cancer based on physical or mammography tests prior to any surgery, and from 36 healthy women. Two commercial electronic noses (ENs) were used for the exhaled breath analysis. Urine samples were analyzed using Gas-Chromatography Mass-Spectrometry (GC-MS). Statistical analysis of results is based on an artificial neural network (ANN) obtained following feature extraction and feature selection processes. The model obtained allows classification of breast cancer patients with an accuracy of 95.2% ± 7.7% using data of one EN, and an accuracy of 85% for the other EN and for urine samples. The developed statistical analysis method enables accurate classification of patients as healthy or with BC based on simple non-invasive exhaled breath and a urine sample analysis. This study demonstrates that available commercial ENs can be used, provided that the data analysis is carried out using an appropriate scheme.

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.

An efficient biomarker panel for diagnosis of breast cancer using surface-enhanced laser desorption ionization time-of-flight mass spectrometry

Breast cancer (BC) is the most frequently diagnosed cancer that affects women worldwide. Early detection of BC is important to improve survival rates and decrease mortality. The aim of the present study was to investigate serum biomarkers using surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to distinguish patients with BC from the healthy population and patients with benign breast diseases (BBDs). A total of 62 patients with invasive ductal carcinoma, as confirmed by histopathology, and 47 non-cancerous individuals (NCIs) [16 healthy controls (HCs) and 31 patients with BBD] were enrolled in the present study. Serum protein profiles were determined by SELDI-TOF-MS using an immobilized metal affinity capture array. Serum from patients with BC were compared with that from the HC group using univariate and multivariate statistical analyses. A total of 118 clusters were generated from the individual serum. Univariate analysis revealed that 5 peaks were significantly downregulated (m/z 1,452, 2,670, 3,972, 5,354 and 5,523; P<0.001) and 4 were upregulated (m/z 6,850, 7,926, 8,115 and 8,143; P<0.001) in patients with BC compared with the HC group. A comparison of patients with BC and patients with BBD revealed an additional 9 protein peaks. Among these, 3 peaks (m/z 3,972, 5,336 and 11,185) were significantly downregulated and 6 peaks (m/z 4,062, 4,071, 4,609, 6,850, 8,115 and 8,133) were significantly upregulated. A total of 3 peaks [mass-to-change ratio (m/z) 3,972, 6,850 and 8,115 (BC2)] were common in both sets. The results of the present study suggest that a 4 protein peak set [m/z 3,972, 6,850 and 8,115 (BC2) and 8,949 (BC3)] could be used to distinguish patients with BC from NCI.

Random and independent sampling of endogenous tryptic peptides from normal human EDTA plasma by liquid chromatography micro electrospray ionization and tandem mass spectrometry

Background

Normal human EDTA plasma samples were collected on ice, processed ice cold, and stored in a freezer at – 80 °C prior to experiments. Plasma test samples from the – 80 °C freezer were thawed on ice or intentionally warmed to room temperature.

Methods

Protein content was measured by CBBR binding and the release of alcohol soluble amines by the Cd ninhydrin assay. Plasma peptides released over time were collected over C18 for random and independent sampling by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) and correlated with X!TANDEM.

Results

Fully tryptic peptides by X!TANDEM returned a similar set of proteins, but was more computationally efficient, than “no enzyme” correlations. Plasma samples maintained on ice, or ice with a cocktail of protease inhibitors, showed lower background amounts of plasma peptides compared to samples incubated at room temperature. Regression analysis indicated that warming plasma to room temperature, versus ice cold, resulted in a ~ twofold increase in the frequency of peptide identification over hours–days of incubation at room temperature. The type I error rate of the protein identification from the X!TANDEM algorithm combined was estimated to be low compared to a null model of computer generated random MS/MS spectra.

Conclusion

The peptides of human plasma were identified and quantified with low error rates by random and independent sampling that revealed 1000s of peptides from hundreds of human plasma proteins from endogenous tryptic peptides.

Electronic supplementary material

The online version of this article (10.1186/s12014-017-9176-7) contains supplementary material, which is available to authorized users.

The proteins cleaved by endogenous tryptic proteases in normal EDTA plasma by C18 collection of peptides for liquid chromatography micro electrospray ionization and tandem mass spectrometry

The tryptic peptides from ice cold versus room temperature plasma were identified by C18 liquid chromatography and micro electrospray ionization tandem mass spectrometry (LC–ESI–MS/MS). Samples collected on ice showed low levels of endogenous tryptic peptides compared to the same samples incubated at room temperature. Plasma on ice contained peptides from albumin, complement, and apolipoproteins and others that were observed by the X!TANDEM and SEQUEST algorithms. In contrast to ice cold samples, after incubation at room temperature, greater numbers of tryptic peptides from well characterized plasma proteins, and from cellular proteins were observed. A total of 583,927 precursor ions and MS/MS spectra were correlated to 94,669 best fit peptides that reduced to 22,287 correlations to the best accession within a gene symbol and to 7174 correlations to at least 510 gene symbols with ≥ 5 independent MS/MS correlations (peptide counts) that showed FDR q-values ranging from E−9 (i.e. FDR = 0.000000001) to E−227. A set of 528 gene symbols identified by X!TANDEM and SEQUEST including C4B showed ≥ fivefold variation between ice cold versus room temperature incubation. STRING analysis of the protein gene symbols observed from endogenous peptides in normal plasma revealed an extensive protein-interaction network of cellular factors associated with cell signalling and regulation, the formation of membrane bound organelles, cellular exosomes and exocytosis network proteins. Taken together the results indicated that a pool of cellular proteins, or protein complexes, in plasma are apparently not stable and degrade soon after incubation at room temperature.

Complement anaphylatoxins C3a and C5a: Emerging roles in cancer progression and treatment

Recent insights into the role of complement anaphylatoxins C3a and C5a in cancer provide new opportunities for the development of innovative biomarkers and therapeutic strategies. These two complement activation products can maintain chronic inflammation, promote an immunosuppressive microenvironment, induce angiogenesis, and increase the motility and metastatic potential of cancer cells. Still, the diverse heterogeneity of responses mediated by these peptides poses a challenge both to our understanding of the role played by these molecules in cancer progression and to the development of effective treatments. This review attempts to summarize the evidence surrounding the involvement of anaphylatoxins in the biological contexts associated with tumor progression. We also describe the recent developments that support the inhibition of anaphylatoxins, or their cognate receptors C3aR and C5aR1, as a treatment option for maximizing the clinical efficacy of current immunotherapies that target the PD-1/PD-L1 immune checkpoint.

Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.

Freeze-dried plasma proteins are stable at room temperature for at least 1 year

Thirty human EDTA plasma samples from male and female subjects ranging in age from 24 to 74 years were collected on ice, processed ice cold and stored frozen at -80 °C, in liquid nitrogen (LN2), or freeze dried and stored at room temperature in a desiccator (FDRT) or freeze dried and stored at -20 °C for 1 year (FD-20). In a separate experiment, EDTA plasma samples were collected onto ice, processed ice cold and maintained on ice ± protease inhibitors versus incubated at room temperature for up to 96 h. Random and independent sampling by liquid chromatography and tandem mass spectrometry (LC-ESI-MS/MS), as correlated by the MASCOT, OMSSA, X!TANDEM and SEQUEST algorithms, showed that tryptic peptides from complement component 4B (C4B) were rapidly released in plasma at room temperature. Random sampling by LC-ESI-MS/MS showed that peptides from C4B were undetectable on ice, but peptides were cleaved from the mature C4B protein including NGFKSHALQLNNR within as little as 1 h at room temperature. The frequency and intensity of precursors within ± 3 m/z of the C4B peptide NGFKSHALQLNNR was confirmed by automated targeted analysis where the precursors from MS/MS spectra that correlated to the target sequence were analyzed in SQL/R. The C4B preproprotein was processed at the N terminus to release the mature chain that was cleaved on the carboxyl side of the isoprene C2 domain within a polar C terminal sequence of the mature C4B protein, to reveal the thioester reaction site, consistent with LC-ESI-MS/MS and Western blot. Random sampling showed that proteolytic peptides from complement component C4B were rarely observed with long term storage at - 80 °C in a freezer or in liquid nitrogen (LN2), freeze drying with storage at - 20 °C (FD-20 °C) or freeze drying and storage at room temperature (FDRT). Plasma samples maintained at room temperature (RT) showed at least 10-fold to 100-fold greater frequency of peptide correlation to C4B and measured peptide intensity compared to samples on ice for up to 72 h or stored at - 80 °C, LN2, FDRT or FD-20 °C for up to a year.

Challenges in the Analysis of Mass-Throughput Data: A Technical Commentary from the Statistical Machine Learning Perspective

Sound data analysis is critical to the success of modern molecular medicine research that involves collection and interpretation of mass-throughput data. The novel nature and high-dimensionality in such datasets pose a series of non-trivial data analysis problems. This technical commentary discusses the problems of over-fitting, error estimation, curse of dimensionality, causal versus predictive modeling, integration of heterogeneous types of data, and lack of standard protocols for data analysis. We attempt to shed light on the nature and causes of these problems and to outline viable methodological approaches to overcome them.

Biomarkers of inflammation and innate immunity in atrophic nonunion fracture

BACKGROUND

Nonunion is a failure of healing following a bone fracture. Its physiopathology remains partially unclear and the discovery of new mediators could promote the understanding of bone healing.

METHODS

Thirty-three atrophic nonunion (NU) patients that failed to demonstrate any radiographic improvement for 6 consecutive months were recruited for providing serum samples. Thirty-five healthy volunteers (HV) served as the control group. Proteomics studies were performed using SELDI-TOF-MS and 2D-DIGE approaches, associated or not with Proteominer® preprocessing, to highlight biomarkers specific to atrophic nonunion pathology. Peak intensities were analyzed by two statistical approaches, a nonparametric Mann-Whitney U tests (univariate approach) and a machine-learning algorithm called extra-trees (multivariate approach). Validation of highlighted biomarkers was performed by alternative approaches such as microfluidic LC-MS/MS, nephelometry, western blotting or ELISA assays.

RESULTS

From the 35 HV and 33 NU crude serum samples and Proteominer® eluates, 136 spectra were collected by SELDI-TOF-MS using CM10 and IMAC-Cu(2+) ProteinChip arrays, and 665 peaks were integrated for extra-trees multivariate analysis. Accordingly, seven biomarkers and several variants were identified as potential NU biomarkers. Their levels of expression were found to be down- or up-regulated in serum of HV vs NU. These biomarkers are inter-α-trypsin inhibitor H4, hepcidin, S100A8, S100A9, glycated hemoglobin β subunit, PACAP related peptide, complement C3 α-chain. 2D-DIGE experiment allowed to detect 14 biomarkers as being down- or up-regulated in serum of HV vs NU including a cleaved fragment of apolipoprotein A-IV, apolipoprotein E, complement C3 and C6. Several biomarkers such as hepcidin, complement C6, S100A9, apolipoprotein E, complement C3 and C4 were confirmed by an alternative approach as being up-regulated in serum of NU patients compared to HV controls.

CONCLUSION

Two proteomics approaches were used to identify new biomarkers up- or down-regulated in the nonunion pathology, which are involved in bone turn-over, inflammation, innate immunity, glycation and lipid metabolisms. High expression of hepcidin or S100A8/S100A9 by myeloid cells and the presence of advanced glycation end products and complement factors could be the result of a longstanding inflammatory process. Blocking macrophage activation and/or TLR4 receptor could accelerate healing of fractured bone in at-risk patients.

Identification of novel serum peptide biomarkers for high-altitude adaptation: a comparative approach

We aimed to identify serum biomarkers for screening individuals who could adapt to high-altitude hypoxia at sea level. HHA (high-altitude hypoxia acclimated; n = 48) and HHI (high-altitude hypoxia illness; n = 48) groups were distinguished at high altitude, routine blood tests were performed for both groups at high altitude and at sea level. Serum biomarkers were identified by comparing serum peptidome profiling between HHI and HHA groups collected at sea level. Routine blood tests revealed the concentration of hemoglobin and red blood cells were significantly higher in HHI than in HHA at high altitude. Serum peptidome profiling showed that ten significantly differentially expressed peaks between HHA and HHI at sea level. Three potential serum peptide peaks (m/z values: 1061.91, 1088.33, 4057.63) were further sequence identified as regions of the inter-α trypsin inhibitor heavy chain H4 fragment (ITIH4 347–356), regions of the inter-α trypsin inhibitor heavy chain H1 fragment (ITIH1 205–214), and isoform 1 of fibrinogen α chain precursor (FGA 588–624). Expression of their full proteins was also tested by ELISA in HHA and HHI samples collected at sea level. Our study provided a novel approach for identifying potential biomarkers for screening people at sea level who can adapt to high altitudes.

Identification of novel serum peptides biomarkers for female breast cancer patients in Western China

This study aimed to identify novel serum peptides biomarkers for female breast cancer (BC) patients. We analyzed the serum proteomic profiling of 247 serum samples from 96 BC patients, 48 additional paired pre- and postoperative BC patients, 39 fibroadenoma patients as benign disease controls, and 64 healthy controls, using magnetic-bead-based separation followed by MALDI-TOF MS. ClinProTools software identified 78 m/z peaks that differed among all analyzed groups, ten peaks were significantly different (P < 0.0001), with Peaks 1-6 upregulated and Peaks 7-10 downregulated in BC. Moreover, three peaks of ten (Peak 1, m/z: 2660.11; Peak 2, m/z: 1061.09; Peak 10, m/z: 1041.25) showed a tendency to return to healthy control values after surgery. And these three peptide biomarkers were identified as FGA605-629, ITIH4 347-356, and APOA2 43-52. Methods used in this study could generate serum peptidome profiles of BC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.

Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach

INTRODUCTION

Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression.

METHOD

We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20).

RESULTS

Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively.

CONCLUSIONS

Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study.

Matrix-assisted laser desorption/ionisation (MALDI) TOF analysis identifies serum angiotensin II concentrations as a strong predictor of all-cause and breast cancer (BCa)-specific mortality following breast surgery

MALDI-TOF MS was used to recognise serum peptidome profiles predictive of mortality in women affected by early BCa. Mortality was analysed based on signal profiling, and appropriate statistics were used. The results indicate that four signals were increased in deceased patients compared with living patients. Three of the four signals were individually associated with all-cause mortality, but only one having mass/charge ratio (m/z) 1,046.49 was associated with BCa-specific mortality and was the only peak to maintain an independent prognostic role after multivariate analysis. Two groups exhibiting different mortality probabilities were identified after clustering patients based on the expression of the four peptides, but m/z 1,046.49 was exclusively expressed in the cluster exhibiting the worst mortality outcome, thus confirming the crucial value of this peptide. The specific role of this peak was confirmed by competing risk analysis. MS findings were validated by ELISA analysis after demonstrating that m/z 1,046.49 structurally corresponded to Angiotensin II (ATII). In fact, mortality results obtained after arbitrarily dividing patients according to an ATII serum value of 255 pg/ml (which corresponds to the 66(th) percentile value) were approximately comparable to those previously demonstrated when the same patients were analysed according to the expression of signal m/z 1,046.49. Similarly, ATII levels were specifically correlated with BCa-related deaths after competing risk analysis. In conclusion, ATII levels were increased in women who exhibited worse mortality outcomes, reinforcing the evidence that this peptide potentially significantly affects the natural history of early BCa. Our findings also confirm that MALDI-TOF MS is an efficient screening tool to identify novel tumour markers and that MS findings can be rapidly validated through less complex techniques, such as ELISA.

Clinical proteomics and breast cancer

BACKGROUND

Breast cancer is a heterogeneous disease. Yet, many molecular players and mechanisms behind the complexity of its clinical behaviour remain unknown, and advances in biomedical research are expected to unravel novel molecular discoveries in breast and other cancers. Clinical proteomics is currently experiencing rapid advances in technology that promise new means to improve breast cancer early diagnosis, stratification, and treatment response.

METHODS

We reviewed recent literature adopting clinical proteomics in breast cancer research.

FINDINGS

This review highlights the principles, advantages, limitations, discoveries and future prospects of recent clinical proteomics discovery efforts in breast cancer research.

CONCLUSION

Numerous proteomic studies of breast cancer have been accomplished aiming to aid the development of personalised therapies, increase understanding of post treatment relapse, and help improve prediction of patient prognosis. This has led to the possible identification of profiles refining breast cancer subtypes and the discovery of novel biomarkers pointing towards diagnostic and prognostic potential.

Search for breast cancer biomarkers in fractionated serum samples by protein profiling with SELDI-TOF MS

BACKGROUND

Many high-abundant acute phase reactants have been previously detected as potential breast cancer biomar-kers. However, they are unlikely to be specific for breast cancer. Cancer-specific biomarkers are thought to be among the lower abundant proteins.

METHODS

We aimed to detect lower abundant discriminating proteins by performing serum fractionation by strong anion exchange chromatography preceding protein profiling with SELDI-TOF MS. In a pilot study, we tested the different fractions resulting from fractionation, on several array types. Fraction 3 on IMAC30 and Fraction 6 on Q10 yielded the most discriminative proteins and were used for serum protein profiling of 73 incident breast cancer cases and 73 matched controls.

RESULTS

Eight peaks showed statistically significantly different intensities between cases and controls (P⧁0.05), and had less than 10% chance to be a false-positive finding. Seven of these were tentatively identified as apolipoprotein C-II (m/z 8,909), oxidized apolipoprotein C-II (m/z 8,925), apolipoprotein C-III (m/z 8,746), fragment of coagulation factor XIIIa (m/z 3,959), heterodimer of apolipoprotein A-I and apolipoprotein A-II (m/z 45,435), hemoglobin B-chain (m/z 15,915), and post-translational modified hemoglobin (m/z 15,346).

CONCLUSION

By extensive serum fractionation, we detected many more proteins than in previous studies without fractionation. However, discriminating proteins were still high abundant. Results indicate that either lower abundant proteins are less distinctive, or more rigorous fractionation and selective protein depletion, or a more sensitive assay, are needed to detect lower abundant discriminative proteins.

Proteomic Profiling of Invasive Ductal Carcinoma (IDC) using Magnetic Beads-based Serum Fractionation and MALDI-TOF MS

AIM

To reveal the serum proteomic profiling of intraductal carcinoma (IDC) patients in China, establish a serum proteome fractionation technique for choosing magnetic beads for proteomic analysis in breast cancer research; and identify differentially expressed peptides (m/z; P < 0.0001) as potential biomarkers of early IDCs.

METHODS

We used two different kinds of magnetic beads (magnetic bead-based weak cation exchange chromatography (MB-WCX) and immobilized metal ion affinity chromatography (MB-IMAC-Cu)) to analyze 32 patients with early stage (stages I-II) IDC and 32 healthy control serum samples for proteomic profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The mass spectra, analyzed using ClinProTools software, distinguished between IDC patients and healthy individuals based on k-nearest neighbor genetic algorithm.

RESULTS

The serum samples purified in the MB-WCX group provided better proteomic patterns than the MB-IMAC-Cu group. The samples purified by MB-WCX had better average peak numbers, higher peak intensities, and better capturing ability of low abundance proteins or peptides in serum samples. In addition, the MB-WCX and MB-IMAC-Cu purification methods, followed MALDI-TOF MS identification and use of ClinProTools software accurately distinguished patients with early stage IDC from healthy individuals.

CONCLUSION

Serum proteomic profiling by MALDI-TOF MS is a novel potential tool for the clinical diagnosis of patients with IDC in China.

Dermcidin expression is associated with disease progression and survival among breast cancer patients

Improved diagnostic screening has led to earlier detection of many tumors, but screening may still miss many aggressive tumor types. Proteomic and genomic profiling studies of breast cancer samples have identified tumor markers that may help improve screening for more aggressive, rapidly growing breast cancers. To identify potential blood-based biomarkers for the early detection of breast cancer, we assayed serum samples via matrix-assisted laser desorption ionization-time of flight mass spectrometry from a rat model of mammary carcinogenesis. We found elevated levels of a fragment of the protein dermcidin (DCD) to be associated with early progression of N-methylnitrosourea-induced breast cancer, demonstrating significance at weeks 4 (p = 0.045) and 5 (p = 0.004), a time period during which mammary pathologies rapidly progress from ductal hyperplasia to adenocarcinoma. The highest serum concentrations were observed in rats bearing palpable mammary carcinomas. Increased DCD was also detected with immunoblotting methods in 102 serum samples taken from women just prior to breast cancer diagnosis. To validate these findings in a larger population, we applied a 32-gene in vitro DCD response signature to a dataset of 295 breast tumors and assessed correlation with intrinsic breast cancer subtypes and overall survival. The DCD-derived gene signature was significantly associated with subtype (p < 0.001) and poorer overall survival [HR (95 % CI) = 1.60 (1.01-2.51), p = 0.044]. In conclusion, these results present novel evidence that DCD levels may increase in early carcinogenesis, particularly among more aggressive forms of breast cancer.

Modern approach of breast cancer diagnostics

In the review have been classified literature data concerning modern instrumental, microscopic and molecular (metabolomics, proteomics, genetics and epigenetics) approaches for early breast cancer diagnostics. The analytical performance and perspectives of their application in clinical practice also have been evaluated.

Advances in MALDI mass spectrometry in clinical diagnostic applications

The concept of matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) was first reported in 1985. Since then, MALDI MS technologies have been evolving, and successfully used in genome, proteome, metabolome, and clinical diagnostic research. These technologies are high-throughput and sensitive. Emerging evidence has shown that they are not only useful in qualitative and quantitative analyses of proteins, but also of other types of biomolecules, such as DNA, glycans, and metabolites. Recently, parallel fragmentation monitoring (PFM), which is a method comparable to selected reaction monitoring, has been reported. This highlights the potentials of MALDI-TOF/TOF tandem MS in quantification of metabolites. Here we critically review the applications of the major MALDI MS technologies, including MALDI-TOF MS, MALDI-TOF/TOF MS, SALDI-TOF MS, MALDI-QqQ MS, and SELDI-TOF MS, to the discovery and quantification of disease biomarkers in biological specimens, especially those in plasma/serum specimens. Using SELDI-TOF MS as an example, the presence of systemic bias in biomarker discovery studies employing MALDI-TOF MS and its possible solutions are also discussed in this chapter. The concepts of MALDI, SALDI, SELDI, and PFM are complementary to each other. Theoretically, all these technologies can be combined, leading to the next generation of the MALDI MS technologies. Real applications of MALDI MS technologies in clinical diagnostics should be forthcoming.

Isothermal vitrification methodology development for non-cryogenic storage of archival human sera

Biorepositories worldwide collect human serum samples and store them for future research. Currently, hundreds of biorepositories across the world store human serum samples in refrigerators, freezers, or liquid nitrogen without following any specific cryopreservation protocol. This method of storage is both expensive and potentially detrimental to the biospecimens. To decrease both cost of storage and the freeze/thaw stresses, we explored the feasibility of storing archival human serum samples at non-cryogenic temperatures using isothermal vitrification. When biospecimens are vitrified, biochemical reactions can be stopped, the specimen ceases to degrade, and macromolecules can be stabilized without requiring cryogenic storage. In this study, 0.2, 0.4, or 0.8M trehalose; 0, 0.005 or 0.01M dextran; and 0 or 10% (v/v) glycerol was added to human serum samples. The samples were either dried diffusively as sessile droplets or desiccated under vacuum after they are adsorbed onto glass microfiber filters. The glass transition temperatures (Tg) of the desiccated samples were measured by temperature-ramp Fourier Transform Infrared (FTIR) spectroscopy. Sera samples vitrified at 4±2°C when 0.8M trehalose and 0.01M dextran were added and the samples were vacuum dried for two hours. Western immunoblotting showed that vitrified serum proteins were minimally degraded when stored for up to one month at 4°C. About 80% of all proteins were recovered after storage at 4°C on glass microfiber filters, and recovery did not decrease with storage time. These results demonstrated the feasibility of long-term storage of vitrified serum at hypothermic (and non-cryogenic) temperatures.

Proteomic profile in familial breast cancer patients

OBJECTIVES

Breast cancer is the most common form of cancer affecting women, and the strongest risk factor remains family history. Although screening in asymptomatic women seems able to reduce breast-cancer related mortality, it is of limited usefulness in young women and patients with familial breast cancer syndrome. New diagnostic tools useful for breast cancer management are urgently needed. The aim of the present paper is to look for new candidate tumor markers useful for diagnosis in these patients.

DESIGN AND METHODS

In this prospective study 292 serum samples (100 from healthy people, 100 from sporadic breast cancer patients and 92 from familial breast cancer patients) were analyzed by SELDI-TOF-MS. All samples both from cancer patients and healthy subjects were run in duplicate and randomly spotted on CM10 and IMAC30 protein chip array. Data were analyzed using the expression differential mapping (EDM) tool, decisional tree and multivariate analysis. A further in silico investigation was performed in order to hypothesize the identity of evidenced peptides.

RESULTS

EDM highlighted thirteen and sixteen significant differentially expressed peaks by CM10 and IMAC30 protein chip respectively. Subsequent analysis showed that two peaks at m/z 11730 and 5066 were differentially expressed in sporadic and familial breast cancer patients respectively, while a peak at m/z 8127 was overexpressed only in familial breast cancer patients. The diagnostic power of protein peaks was tested by decisional tree; sensitivity and specificity ranged from 17% to 91.67%.

CONCLUSIONS

We show that the serum profile of familial breast cancer patients was different when compared with that of sporadic breast cancer patients. We hypothesized the identity of the most significant peaks, and further studies are now planned in order to definitively establish the identity.

Sensitive and specific peak detection for SELDI-TOF mass spectrometry using a wavelet/neural-network based approach

SELDI-TOF mass spectrometer's compact size and automated, high throughput design have been attractive to clinical researchers, and the platform has seen steady-use in biomarker studies. Despite new algorithms and preprocessing pipelines that have been developed to address reproducibility issues, visual inspection of the results of SELDI spectra preprocessing by the best algorithms still shows miscalled peaks and systematic sources of error. This suggests that there continues to be problems with SELDI preprocessing. In this work, we study the preprocessing of SELDI in detail and introduce improvements. While many algorithms, including the vendor supplied software, can identify peak clusters of specific mass (or m/z) in groups of spectra with high specificity and low false discover rate (FDR), the algorithms tend to underperform estimating the exact prevalence and intensity of peaks in those clusters. Thus group differences that at first appear very strong are shown, after careful and laborious hand inspection of the spectra, to be less than significant. Here we introduce a wavelet/neural network based algorithm which mimics what a team of expert, human users would call for peaks in each of several hundred spectra in a typical SELDI clinical study. The wavelet denoising part of the algorithm optimally smoothes the signal in each spectrum according to an improved suite of signal processing algorithms previously reported (the LibSELDI toolbox under development). The neural network part of the algorithm combines those results with the raw signal and a training dataset of expertly called peaks, to call peaks in a test set of spectra with approximately 95% accuracy. The new method was applied to data collected from a study of cervical mucus for the early detection of cervical cancer in HPV infected women. The method shows promise in addressing the ongoing SELDI reproducibility issues.

Candidate biomarker verification: Critical examination of a serum protein pattern for human colorectal cancer

PURPOSE

We critically examine a candidate serum protein pattern for human colorectal cancer (CRC) with respect to reproducibility, sample handling, and disease specificity.

EXPERIMENTAL DESIGN

Serum samples from CRC patients, patients with benign colon tumors and healthy individuals, were obtained at two collection sites and analyzed by SELDI-TOF MS on 8 days, over a period of 5 weeks. The spectra were subjected to multivariate analysis. Tissues from normal colon and CRC were analyzed by SELDI-TOF MS. Selected mass peaks were identified.

RESULTS

Using an elaborate experimental design we developed a multivariate classifier that correctly classified CRC and control serum measured on an independent day. The classifier did not discriminate between samples from CRC patients and patients with benign colon tumors, and, secondly, did not correctly classify serum from an independent collection site. All discriminatory mass peaks were identified as high abundant plasma proteins. Tissue profiling provided support of increased proteolytic activity in CRC tissue.

CONCLUSION AND CLINICAL RELEVANCE

Critical verification did not justify advancing the identified CRC serum protein pattern into clinical validation without improvement. We believe that proteomics biomarker research could benefit if the presented, or a similar, verification scheme was more commonly employed in explorative biomarker studies.

Proteomic studies in breast cancer (Review)

Breast cancer is one of the most common types of invasive cancer in females worldwide. Despite major advances in early cancer detection and emerging therapeutic strategies, further improvement has to be achieved for precise diagnosis to reduce the chance of metastasis and relapses. Recent proteomic technologies have offered a promising opportunity for the identification of new breast cancer biomarkers. Matrix-assisted laser desorption/ionization, time-of-flight mass spectrometry (MALDI-TOF MS) and the derived surface-enhanced laser desorption/ionization mass spectrometry (SELDI-TOF MS) enable the development of high-throughput proteome analysis based on comprehensive reliable biomarkers. In this review, we examined proteomic technologies and their applications, and provided focus on the proteomics-based profiling analyses of tumor tissues/cells in order to identify and confirm novel biomarkers of breast cancer.

Changes in the expression of plasma proteins associated with thrombosis in BRCA1 mutation carriers

PURPOSE

Although BRCA1 gene mutations have been associated with breast cancer, BRCA1 mutations have been also involved in other functions. Thrombosis and coagulation are novel mechanisms recently associated with cancer. The aims of the present study were (a) to evaluate, using proteomics, if BRCA1 mutation carriers have a different plasma proteins expression related to thrombosis and coagulation profile than non-mutant BRCA1 women and (b) to analyze if the expression of these proteins may be different among BRCA1 mutation carriers with and without breast cancer.

METHODS

Proteomic study was based on 2-dimensional electrophoresis and mass spectrometry. The study was performed in 10 BRCA1 non-mutant controls and 21 women with BRCA1 mutations (with breast cancer (n = 8) and breast cancer-free (n = 13)), all of them free of family history or diagnosis of ovarian cancer.

RESULTS

Proteomic study showed that fibrinogen gamma chain isotypes 2 and 3, serotransferrin isotype 4, and convertase C3/C5 isotypes 1-5 were significantly increased in plasma from BRCA1 mutation carriers with respect to BRCA1 non-mutant controls. Plasma levels of alpha-1 antitrypsin isotypes 2-5, apolipoprotein A-IV, and vitamin D-binding protein isotypes 1 and 2 were significantly reduced in BRCA1 mutation carriers with respect to non-mutant controls. Only apolipoprotein A-IV plasma levels were significantly higher in cancer-free BRCA1 mutations carriers compared with BRCA1 mutations carriers who developed breast cancer.

CONCLUSION

It is suggested that independently of breast cancer generation, BRCA1-encoded gene alterations are associated with changes in the expression of circulating proteins associated with thrombosis and coagulation.

Functional protease profiling for diagnosis of malignant disease

Clinical proteomic profiling by mass spectrometry (MS) aims at uncovering specific alterations within mass profiles of clinical specimens that are of diagnostic value for the detection and classification of various diseases including cancer. However, despite substantial progress in the field, the clinical proteomic profiling approaches have not matured into routine diagnostic applications so far. Their limitations are mainly related to high-abundance proteins and their complex processing by a multitude of endogenous proteases thus making rigorous standardization difficult. MS is biased towards the detection of low-molecular-weight peptides. Specifically, in serum specimens, the particular fragments of proteolytically degraded proteins are amenable to MS analysis. Proteases are known to be involved in tumour progression and tumour-specific proteases are released into the blood stream presumably as a result of invasive progression and metastasis. Thus, the determination of protease activity in clinical specimens from patients with malignant disease can offer diagnostic and also therapeutic options. The identification of specific substrates for tumour proteases in complex biological samples is challenging, but proteomic screens for proteases/substrate interactions are currently experiencing impressive progress. Such proteomic screens include peptide-based libraries, differential isotope labelling in combination with MS, quantitative degradomic analysis of proteolytically generated neo-N-termini, monitoring the degradation of exogenous reporter peptides with MS, and activity-based protein profiling. In the present article, we summarize and discuss the current status of proteomic techniques to identify tumour-specific protease-substrate interactions for functional protease profiling. Thereby, we focus on the potential diagnostic use of the respective approaches.

Early diagnostic protein biomarkers for breast cancer: how far have we come?

Many studies have used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to search for blood-based proteins that are related to the presence of breast cancer. We review the biomarkers discovered or targeted measured by these methods and discuss the strengths and weaknesses of these studies. We highlight two proteins that were most often related to breast cancer: C3a des-arginine anaphylatoxin (C3adesArg) (molecular weight: 8,938 Da) and fragments of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4). In addition, we elaborate on three important methodological aspects related to these studies: protein identification, specificity of the markers, and disease heterogeneity. Finally, we propose some points to be addressed in future studies. These include the use of other analytical measurement techniques, need of protein identification, the importance of identical sample handling protocols for cases and controls, and the stratification of the results according to molecular subtypes and stages of breast cancer. Ultimately this may lead to the discovery of new and valid breast cancer specific biomarkers.

PEAK DETECTION IN MASS SPECTROMETRY BY GABOR FILTERS AND ENVELOPE ANALYSIS

Mass Spectrometry (MS) is increasingly being used to discover diseases-related proteomic patterns. The peak detection step is one of the most important steps in the typical analysis of MS data. Recently, many new algorithms have been proposed to increase true position rate with low false discovery rate in peak detection. Most of them follow two approaches: one is the denoising approach and the other is the decomposing approach. In the previous studies, the decomposition of MS data method shows more potential than the first one. In this paper, we propose two novel methods, named GaborLocal and GaborEnvelop, both of which can detect more true peaks with a lower false discovery rate than previous methods. We employ the method of Gaussian local maxima to detect peaks, because it is robust to noise in signals. A new approach, peak rank, is defined for the first time to identify peaks instead of using the signal-to-noise ratio. Meanwhile, the Gabor filter is used to amplify important information and compress noise in the raw MS signal. Moreover, we also propose the envelope analysis to improve the quantification of peaks and remove more false peaks. The proposed methods have been performed on the real SELDI-TOF spectrum with known polypeptide positions. The experimental results demonstrate that our methods outperform other commonly used methods in the Receiver Operating Characteristic (ROC) curve.

Serum proteomic profiling reveals potential biomarkers for cutaneous malignant melanoma

Cutaneous malignant melanoma (CMM) is the most serious type of skin cancer because of its tendency to metastasize. The prognosis and therapeutic management of patients are primarily based on clinical criteria (number of cancerous lymph nodes and/or the presence of distant metastases) and histopathological criteria (tumor depth, presence of ulceration and mitotic index). Although these factors are informative in advanced stages of the disease, they are less important in the early stages. In recent years, a number of attempts have been made to identify new serological prognostic biomarkers, especially for early forms of CMM. The recent development of proteomic techniques may offer new perspectives in this field. This article details the considerations of each of the proteomic techniques used today and describes the results of the most recent clinical studies conducted to identify new potential prognostic serum biomarkers for CMM. However, independent and large validation studies are needed before such markers can be used in everyday clinical practice.

A serum protein profile predictive of the resistance to neoadjuvant chemotherapy in advanced breast cancers

Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Searching for early breast cancer biomarkers by serum protein profiling of pre-diagnostic serum; a nested case-control study

Background

Serum protein profiles have been investigated frequently to discover early biomarkers for breast cancer. So far, these studies used biological samples collected at or after diagnosis. This may limit these studies' value in the search for cancer biomarkers because of the often advanced tumor stage, and consequently risk of reverse causality. We present for the first time pre-diagnostic serum protein profiles in relation to breast cancer, using the Prospect-EPIC (European Prospective Investigation into Cancer and nutrition) cohort.

Methods

In a nested case-control design we compared 68 women diagnosed with breast cancer within three years after enrollment, with 68 matched controls for differences in serum protein profiles. All samples were analyzed with SELDI-TOF MS (surface enhanced laser desorption/ionization time-of-flight mass spectrometry). In a subset of 20 case-control pairs, the serum proteome was identified and relatively quantified using isobaric Tags for Relative and Absolute Quantification (iTRAQ) and online two-dimensional nano-liquid chromatography coupled with tandem MS (2D-nanoLC-MS/MS).

Results

Two SELDI-TOF MS peaks with m/z 3323 and 8939, which probably represent doubly charged apolipoprotein C-I and C3a des-arginine anaphylatoxin (C3a_desArg), were higher in pre-diagnostic breast cancer serum (p = 0.02 and p = 0.06, respectively). With 2D-nanoLC-MS/MS, afamin, apolipoprotein E and isoform 1 of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4) were found to be higher in pre-diagnostic breast cancer (p < 0.05), while alpha-2-macroglobulin and ceruloplasmin were lower (p < 0.05). C3a_desArg and ITIH4 have previously been related to the presence of symptomatic and/or mammographically detectable breast cancer.

Conclusions

We show that serum protein profiles are already altered up to three years before breast cancer detection.

Identification of β2-microglobulin as a urinary biomarker for chronic allograft nephropathy using proteomic methods

PURPOSE

Chronic allograft nephropathy (CAN) remains the leading cause of renal graft loss after the first year following renal transplantation. This study aimed to identify novel urinary proteomic profiles, which could distinguish and predict CAN in susceptible individuals.

EXPERIMENTAL DESIGN

The study included 34 renal transplant patients with histologically proven CAN and 36 patients with normal renal transplant function. High-throughput proteomic profiles were generated from urine samples with three different ProteinChip arrays by surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Following SELDI, a biomarker pattern software analysis was performed which led to the identification of a novel biomarker pattern that could distinguish patients with CAN from those with normal renal function.

RESULTS

An 11.7 kDa protein identified as β2 microglobulin was the primary protein of this biomarker pattern, distinguishing CAN from control patients (receiver operator characteristic [ROC]=0.996). SELDI-TOF-MS comparison of purified β2 microglobulin protein and CAN urine demonstrated identical 11.7 kDa protein peaks. Significantly, higher concentrations of 2 microglobulin were found in the urine of patients with CAN compared with the urine of normal renal function transplant recipients (p<0.001).

CONCLUSIONS AND CLINICAL RELEVANCE

Although further validation in a larger more diverse patient population is required to determine if this β2 microglobulin protein biomarker will provide a potential means of diagnosing CAN by noninvasive methods in a clinical setting, this study clearly shows a capability to stratify control and disease patients.

Genome-based and transcriptome-based molecular classification of breast cancer

PURPOSE OF REVIEW

The highly heterogeneous clinical, histological, biological and genetic nature of breast malignancies is due in part to their extreme molecular complexity.

RECENT FINDINGS

Many genetic and epigenetic alterations have been described, affecting a relatively small number of signaling pathways (PI3K, NK-κB, FGF, etc.) and thus several molecular subtypes of breast cancer have been identified.

SUMMARY

The next decade will see even more prolific developments, notably with the advent of next-generation sequencing (NGS) technologies capable of providing individual patients' constitutional and somatic genome sequences both rapidly and cheaply. Knowledge of the full catalogue of somatic genetic alterations will pave the way for fully individualized management of breast cancer patients.

The value of serum biomarkers (Bc1, Bc2, Bc3) in the diagnosis of early breast cancer

BACKGROUND

Surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF) is an approach to biomarker discovery that combines chromatography and mass spectrometry. We aimed to consider the efficacy of Bc1, Bc2, and Bc3 serum biomarkers on early detection of breast cancer (BC) in this study.

STUDY DESIGN

In this prospective study, 91 patients who were admitted to our hospital between January 2007 and July 2008 were included. Serum samples from 91 women were stored at -80 °C until use. The cancer group included 27 cases of BC. The benign breast disease group included 24 women with benign breast diseases and control group 37 age-matched apparently healthy women. The data obtained for these three groups of patients was worked out for each serum biomarker (Bc1, Bc2, and Bc3) by using SELDI-TOF individually and compared with each other separately and evaluated statistically.

RESULTS

Bc2 possesses the highest individual diagnostic power. Bc2 was statistically significant in comparison between the malignant disease group, control group and benign disease group. Bc1 was statistically significant in the malignant disease group compared to control group as well as in the benign disease group compared to control group. Thus Bc1, rather than showing malignant progression, it shows tumoral progression or inflammatory process. Bc3 was found upregulated in all malignant cases; however, it was not statistically significant compared to the benign disease group or the control group.

CONCLUSIONS

It has been shown that Bc2 profiles might be useful in clinical practice to improve BC diagnosis. However none of the proteomics reach reasonable AUC values for the discrimination of the BC. Additional confirmation in larger and similarly-designed prospective studies is needed to consider of the efficacy of Bc1 and Bc2 in early diagnosis of the BC.

Is SELDI-TOF a valid tool for diagnostic biomarkers?

The genome revolution is providing fresh insights into host and parasite genomes, and new tools are becoming available for examining host-parasite interactions at the proteome level. Technologies such as surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) can be applied to discover biomarkers (alterations in both host and parasite proteomes) associated with parasitic diseases. Such biomarkers can represent host proteins, fragments of host proteins or parasite proteins that appear in body fluids or tissues following infection. Individual biomarkers or biomarker patterns not only have diagnostic utility (e.g. in active disease, prognosis, tests of cure) but can also provide unique insights into the mechanisms underlying host responses and pathogenesis.