Proteomic biomarkers predicting lymph node involvement in serum of cervical cancer patients. Limitations of SELDI-TOF MS

ABSTRACT: BACKGROUND: Lymph node status is not part of the staging system for cervical cancer, but provides important information for prognosis and treatment. We investigated whether lymph node status can be predicted with proteomic profiling. Material & methods Serum samples of 60 cervical cancer patients (FIGO I/II) were obtained before primary treatment. Samples were run through a HPLC depletion column, eliminating the 14 most abundant proteins ubiquitously present in serum. Unbound fractions were concentrated with spin filters. Fractions were spotted onto CM10 and IMAC30 surfaces and analyzed with surface-enhanced laser desorption time of flight (SELDI-TOF) mass spectrometry (MS). Unsupervised peak detection and peak clustering was performed using MASDA software. Leave-one-out (LOO) validation for weighted Least Squares Support Vector Machines (LSSVM) was used for prediction of lymph node involvement. Other outcomes were histological type, lymphvascular space involvement (LVSI) and recurrent disease. RESULTS: LSSVM models were able to determine LN status with a LOO area under the receiver operating characteristics curve (AUC) of 0.95, based on peaks with m/z values 2,698.9, 3,953.2, and 15,254.8. Furthermore, we were able to predict LVSI (AUC 0.81), to predict recurrence (AUC 0.92), and to differentiate between squamous carcinomas and adenocarcinomas (AUC 0.88), between squamous and adenosquamous carcinomas (AUC 0.85), and between adenocarcinomas and adenosquamous carcinomas (AUC 0.94). CONCLUSIONS: Potential markers related with lymph node involvement were detected, and protein/peptide profiling support differentiation between various subtypes of cervical cancer. However, identification of the potential biomarkers was hampered by the technical limitations of SELDI-TOF MS.     

Proteomic serum biomarkers for neuromuscular diseases

Introduction: The clinical evaluation of neuromuscular symptoms often includes the assessment of altered blood proteins or changed enzyme activities. However, the blood concentration of many muscle-derived serum markers is not specific for different neuromuscular disorders and also shows alterations in the course of these diseases. Thus, the establishment of more reliable biomarker signatures for improved muscle diagnostics is required.

Areas covered: To address the lack of muscle disease-specific marker molecules, mass spectrometry-based proteomics was applied to the systematic identification and biochemical characterization of new serum biomarker candidates. This article outlines serum proteomics in relation to neuromuscular disorders and reviews the bioanalytical results from recent proteomic profiling studies of representative neuromuscular disorders, including motor neuron disease, muscular dystrophies and sarcopenia of old age. Pathophysiological changes in the skeletal muscle proteome are reflected by serum alterations in a variety of sarcomeric proteins, metabolic enzymes and signaling proteins.

Expert commentary: Based on the proteomic identification of actively secreted or passively released skeletal muscle proteins following pathophysiological insults, new biomarker candidates can now be used to develop liquid biopsy procedures for superior diagnostic approaches, design novel prognostic tools and establish more reliable methods for the systematic evaluation of experimental therapies to treat neuromuscular disease.     

Proteomic tracking of serum protein isoforms as screening biomarkers of ovarian cancer

Epithelial ovarian cancer is the fourth leading cause of cancer death among women. Due to the asymptomatic nature and poor survival characteristic of the disease, screening for specific biomarkers for ovarian cancer is a major health priority. Differentially expressed proteins in the serum of ovarian cancer patients have the potential to be used as cancer-specific biomarkers. In this study, proteomic methods were used to screen 24 serum samples from women with high-grade ovarian cancer and compared to a control group of 11 healthy women. Affigel-Blue treated serum samples were processed either by linear (pH 4-7) or narrow range (pH 5.5-6.7) IEF strips for the first dimension. Proteins separated in first dimension were resolved by 8-16% gradient SDS-PAGE. Protein spots were visualized by SYPRO Ruby staining, imaged by FX-imager and compared and analyzed by PDQuest software. Twenty-two protein spots were consistently differentially expressed between normal and ovarian cancer patients by resolving proteins in a linear pH strip of 4-7 for the first dimension. Six of the protein spots, significantly up-regulated in grade 3 ovarian cancer patients (p < 0.05), were identified by MALDI-TOF MS and Western blotting as the isoforms of haptoglobin precursor. When serum proteins were resolved on narrow pH range strips (5.5-6.7), 23 spots were consistently differentially expressed between normal and grade 3 ovarian cancer patients. Of these, 4 protein spots significantly down regulated in grade 3 ovarian cancer patients (p < 0.05) were identified by MALDI-TOF MS and Western blotting, as isoforms of transferrin precursor. Increased expression of serum haptoglobin and transferrin was also identified in peritoneal tumor fluid obtained from women diagnosed with grade 2/3 ovarian cancer (n = 7). Changes in the expression of haptoglobin and transferrin in the serum of women with different pathological grades of ovarian cancer was examined by one-dimensional Western blotting method. Serum samples collected from women suffering from benign, borderline, grade 1, grade 2 and grade 3 cancer (n = 4 for haptoglobin and n = 5 for transferrin in each group) were analyzed and compared to the serum of normal healthy women. The mean serum haptoglobin expression in grade 3 ovarian cancer patients was fourfold higher than in the control subjects (p < 0.05). On the other hand, transferrin expression in grade 3 ovarian cancer patients was decreased by twofold than in normal healthy women (p < 0.05). Haptoglobin expression in the serum of cancer patients (n = 7) decreased following chemotherapy (six cycles of taxol/carboplatin). Concomitant with the decrease of haptoglobin, transferrin expression remained constant in four patients, but increased in three out of seven patients included in the study. Changes in serum expression of haptoglobin correlated with the change of CA 125 levels before and after chemotherapy. In conclusion, proteomic profiling of differentially expressed proteins in the sera of normal women compared to women with ovarian cancer can greatly facilitate the discovery of a panel of biomarkers that may aid in the detection of ovarian cancer with greater specificity.     

Proteomic detection of prostate-specific antigen using a serum fractionation procedure: potential implication for new low-abundance cancer biomarkers detection

One of the major obstacles in proteomic analysis of biological fluids is the presence of highly abundant proteins such as albumin and immunoglobulins, which can interfere with the resolution and sensitivity of the proteome profiling techniques used. In this paper, we describe an anion exchange fractionation procedure for serum using denaturating conditions allowing protein-protein interaction disruption before analysis by surface-enhanced laser desorption/ionization and by two-dimensional electrophoresis. This method simplifies the serum proteome into subproteomes and markedly increases resolution and sensitivity without any loss of minor proteins. To confirm the applicability of this method, fractionated serum of a patient with prostate cancer was analyzed for the presence of the prostate-specific antigen (PSA) which is a low-abundance tumor marker protein. The results demonstrate that PSA can be detected by two-dimensional electrophoresis only in serum following fractionation. Hence, this procedure may facilitate the identification of other, so far unknown, tumor markers in patient sera.     

A new insight on serum microRNA expression as novel biomarkers in breast cancer patients

Breast cancer (BC) is one of the widespread lethal diseases affecting a large number of women worldwide. As such, employing and identifying significant markers for detecting BC in different stages can assist in better diagnosis and management of the disease. Several diverse markers have been introduced for diagnosis, but their limitations, including low specificity and sensitivity, reduce their application. microRNAs (miRNAs), as short noncoding RNAs, have been shown to significantly influence gene expression in different disease pathologies, especially BC. Clearly, among different samples used for detecting miRNA expressions, circulating miRNAs present as promising and useful biomarkers. Among different body fluid samples, serum serves as one of the most reliable samples, thanks to its high stability under various severe conditions and some unique features. Extensive research has suggested that BC-related miRNAs can remain stable in the serum. The objective of this review is to describe different samples used for detecting miRNAs in BC subjects with emphasis on serum miRNAs. So, this study highlights serum miRNAs with the potential of acting as biomarkers for different stages of BC. We reviewed the possible correlation between potential miRNAs and the risk of early breast cancer, metastatic breast cancer, response to chemotherapy, and relapse.     

Proteomic analysis of maternal serum in down syndrome: identification of novel protein biomarkers

Down syndrome (DS) is the most prevalent chromosomal disorder, accounting for significant morbidity and mortality. Definitive diagnosis requires invasive amniocentesis, and current maternal serum-based testing requires a false-positive rate of about 5% to detect 85% of affected pregnancies. We have performed a comprehensive proteomic analysis to identify potential serum biomarkers to detect DS. First- and second-trimester maternal serum samples of DS and gestational age-matched controls were analyzed using multiple, complementary proteomic approaches, including fluorescence 2-dimensional gel electrophoresis (2D-DIGE), 2-dimensional liquid chromatography-chromatofocusing (2D-CF), multidimensional protein identification technology (MudPIT; LC/LC-MS/MS), and MALDI-TOF-MS peptide profiling. In total, 28 and 26 proteins were differentially present in first- and second-trimester samples, respectively. Of these, 19 were specific for the first trimester and 16 for the second trimester, and 10 were differentially present in both trimesters. Analysis of MALDI-TOF-MS peptide profiles with pattern-recognition software also discriminated between DS and controls in both trimesters, with an average recognition capability approaching 96%. A majority of the biomarkers identified are serum glycoproteins that may play a role in cellular differentiation and growth of fetus. Further characterization and quantification of these markers in a larger cohort of subjects may provide the basis for new tests for improved DS screening.     

Serum-based protein biomarkers for detection of lung cancer

Lung cancer is one of the most common cancers in terms of both incidence and mortality.The major reasons for the increasing number of deaths from lung cancer are late detection and lack of effective therapies. To improve our understanding of lung cancer biology, there is urgent need for blood-based, non-invasive molecular tests to assist in its detection in a cost-effective manner at an early stage when curative interventions are still possible. Recent advances in proteomic technology have provided extensive, high throughput analytical tools for identification, characterization and functional studies of proteomes. Changes in protein expression patterns in response to stimuli can serve as indicators or biomarkers of biological and pathological processes as well as physiological and pharmacological responses to drug treatment, thus aiding in early diagnosis and prognosis of disease. However, only a few biomarkers have been approved by the FDA to date for screening and diagnostic purposes. This review provides a brief overview of currently available proteomic techniques, their applications and limitations and the current state of knowledge about important serum biomarkers in lung cancer and their potential value as prognostic and diagnostic tools.     

MicroRNA expression profile in serum reveals novel diagnostic biomarkers for endometrial cancer

Purpose: Circulating microRNAs (miRNAs) prove to be promising diagnostic biomarkers for various cancers, including endometrial cancer (EC). The present study aims to identify serum microRNAs that can serve as potential biomarkers for EC diagnosis.Patients and methods: A total of 92 EC and 102 normal control (NC) serum samples were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) in this four-phase experiment. The logistic regression method was used to construct a diagnostic model based on the differentially expressed miRNAs in serum. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value. To further validate the diagnostic capacity of the identified signature, the 6-miRNA marker was compared with previously reported biomarkers and verified in three public datasets. In addition, the expression characteristics of the identified miRNAs were further explored in tissue and serum exosomes samples.Results: Six miRNAs (miR-143-3p, miR-195-5p, miR-20b-5p, miR-204-5p, miR-423-3p, and miR-484) were significantly overexpressed in the serum of EC compared with NCs. Areas under the ROC of the 6-miRNA signatures were 0.748, 0.833, and 0.967 for the training, testing, and the external validation phases, respectively. The identified signature has a very stable diagnostic performance in the large cohorts of three public datasets. Compared with previously identified miRNA biomarkers, the 6-miRNA signature in the present study has superior performance in diagnosing EC. Moreover, the expression of miR-143-3p and miR-195-5p in tissues and the expression of miR-20b-5p in serum exosomes were consistent with those in serum.Conclusions: We established a 6-miRNA signature in serum and they could function as potential non-invasive biomarker for EC diagnosis.     

Nano-bio-chips for high performance multiplexed protein detection: Determinations of cancer biomarkers in serum and saliva using quantum dot bioconjugate labels

The integration of semiconductor nanoparticle quantum dots (QDs) into a modular, microfluidic biosensor for the multiplexed quantitation of three important cancer markers, carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), and Her-2/Neu (C-erbB-2) was achieved. The functionality of the integrated sample processing, analyte capture and detection modalities was demonstrated using both serum and whole saliva specimens. Here, nano-bio-chips that employed a fluorescence transduction signal with QD-labeled detecting antibody were used in combination with antigen capture by a microporous agarose bead array supported within a microfluidics ensemble so as to complete the sandwich-type immunoassay. The utilization of QD probes in this miniaturized biosensor format resulted in signal amplification 30 times relative to that of standard molecular fluorophores as well as affording a reduction in observed limits of detection by nearly 2 orders of magnitude (0.02 ng/mL CEA; 0.11 pM CEA) relative to enzyme-linked immunosorbent assay (ELISA). Assay validation studies indicate that measurements by the nano-bio-chip system correlate to standard methods at R² = 0.94 and R² = 0.95 for saliva and serum, respectively. This integrated nano-bio-chip assay system, in tandem with next-generation fluorophores, promises to be a sensitive, multiplexed tool for important diagnostic and prognostic applications.     

Determination of iron in blood serum using flow injection with luminol chemiluminescence detection.

A simple and rapid fl ow injection method is reported for the determination of iron in blood serum after acid digestion with HNO3 and HClO4, based on luminol CL detection in the absence of added oxidant. The detection limit (3 s) was 1.0 nmol/L with a sample throughput of 120/h. The calibration graph was linear over the range 0.001-1.0 micromol/L (r2 = 0.9974), with relative standard deviations (RSD) (n = 4) in the range 3.2-5%. The effect of interfering cations (Ca(II), Mg(II), Cu(II), Cd(II), Pb(II), Mn(II), Zn(II), Ni(II), Co(II) and Fe(III)) and anions (Cl-, SO4(2-), HCO3-, NO3-, NO2-) were studied using a luminol CL system for Fe(II) determination. The method was applied to normal blood serum and the results (1.32 +/- 0.08-1.74 +/- 0.05 mg/L) were compared with those from a spectrophotometric reference method (1.34 +/- 0.06-1.80 +/- 0.10 mg/L), which agree fairly well with the overall reference range in blood.     

Serological protein profiling of neuroblastoma by ProteinChip SELDI-TOF technology

Serological proteins of neuroblastoma were profiled and analyzed by ProteinChip-SELDI-TOF MS technology with five types of protein chips. By comparing with normal control, a number of protein or polypeptide signals were found significantly and consistently different in their intensities (expression levels) in tumor sera. Interestingly, nine polypeptide peaks in these proteomic features can be simultaneously detected with consistent variations by more than one type of protein chips. None of the expression differences of these nine polypeptides was found in similar comparisons between healthy controls and hepatomas. Preliminary protein identification showed hints for that some of these proteomic alterations may be closely related to the tumorigenesis of neuroblastoma. These results demonstrated the potential of serological biomarker identification for neuroblastoma by ProteinChip-SELDI technology.     

Proteomic biomarkers for acute interstitial lung disease in gefitinib-treated Japanese lung cancer patients

Interstitial lung disease (ILD) events have been reported in Japanese non-small-cell lung cancer (NSCLC) patients receiving EGFR tyrosine kinase inhibitors. We investigated proteomic biomarkers for mechanistic insights and improved prediction of ILD. Blood plasma was collected from 43 gefitinib-treated NSCLC patients developing acute ILD (confirmed by blinded diagnostic review) and 123 randomly selected controls in a nested case-control study within a pharmacoepidemiological cohort study in Japan. We generated ∼7 million tandem mass spectrometry (MS/MS) measurements with extensive quality control and validation, producing one of the largest proteomic lung cancer datasets to date, incorporating rigorous study design, phenotype definition, and evaluation of sample processing. After alignment, scaling, and measurement batch adjustment, we identified 41 peptide peaks representing 29 proteins best predicting ILD. Multivariate peptide, protein, and pathway modeling achieved ILD prediction comparable to previously identified clinical variables; combining the two provided some improvement. The acute phase response pathway was strongly represented (17 of 29 proteins, p = 1.0×10⁻²⁵), suggesting a key role with potential utility as a marker for increased risk of acute ILD events. Validation by Western blotting showed correlation for identified proteins, confirming that robust results can be generated from an MS/MS platform implementing strict quality control.     

DNA methylation-based biomarkers in serum of patients with breast cancer

Alterations of genetic and epigenetic features can provide important insights into the natural history of breast cancer. Although DNA methylation analysis is a rapidly developing field, a reproducible epigenetic blood-based assay for diagnosis and follow-up of breast cancer has yet to be successfully developed into a routine clinical test. The aim of this study was to review multiple serum DNA methylation assays and to highlight the value of those novel biomarkers in diagnosis, prognosis and prediction of therapeutic outcome. Serum is readily accessible for molecular diagnosis in all individuals from a peripheral blood sample. The list of hypermethylated genes in breast cancer is heterogeneous and no single gene is methylated in all breast cancer types. There is increasing evidence that a panel of epigenetic markers is essential to achieve a higher sensitivity and specificity in breast cancer detection. However, the reported percentages of methylation are highly variable, which can be partly explained by the different sensitivities and the different intra-/inter-assay coefficients of variability of the analysis methods. Moreover, there is a striking lack of receiver operating characteristic (ROC) curves of the proposed biomarkers. Another point of criticism is the fact that 'normal' patterns of DNA methylation of some tumor suppressor and other cancer-related genes are influenced by several factors and are often poorly characterized. A relatively frequent methylation of those genes has been observed in high-risk asymptomatic women. Finally, there is a call for larger prospective cohort studies to determine methylation patterns during treatment and follow-up. Identification of patterns specific for a differential response to therapeutic interventions should be useful. Only in this way, it will be possible to evaluate the predictive and prognostic characteristics of those novel promising biomarkers.     

Characterization of serum biomarkers for detection of early stage ovarian cancer

We have previously reported the identification of three ovarian cancer biomarker panels comprised of SELDI-TOF-MS peaks representing 14 differentially expressed serum proteins for the diagnosis of ovarian cancer. Using micro-LC-MS/MS, we identified five m/z peaks as transthyretin (TTR 13.9 kDa, TTR fragment 12.9 kDa), beta-hemoglobin (Hb, 15.9 kDa), apolipoprotein AI (ApoAI, 28 kDa) and transferrin (TF, 79 kDa). Western and/or ELISA methods confirmed the differential expression of TTR, Hb, and TF, and multivariate analyses resulted in improving the detection of early stage ovarian tumors (low malignant potential and malignant; receiver operating characteristic, ROC 0.933) as compared to cancer antigen CA125 alone (ROC 0.833). Interestingly, when CA125 was included with our markers in the multivariate analysis, the ROC increased to 0.959. Furthermore, multivariate analysis with only the mucinous subtype of early stage ovarian tumors, showed our markers to greatly improve the detection of disease (ROC 0.959) as compared to CA125 alone (ROC 0.613). Interestingly, the combination of CA125 with our markers did not seem to further improve the detection of mucinous tumors (ROC 0.955). We conclude that TTR, Hb, ApoAI and TF, when combined with CA125 should significantly improve the detection of early stage ovarian cancer.