Advances in mass spectrometry-based technologies to direct personalized medicine in ovarian cancer

Particle packed mixed-mode chromatographic stationary phase for the separation of peptide in liquid chromatography

A particle-based stationary phase has been prepared for the separation of five synthetic peptides and a mixture containing tryptic digest of cytochrome C in liquid chromatography. Particles originating from silica monolith were differentially sedimented to obtain 1-2 μm particles. A stationary phase was achieved by the coating of poly(styrene-methacrylic acid-N-phenylacrylamide) copolymer onto the particles via reversible addition-fragmentation chain transfer polymerization reaction. Stainless steel column (30 cm long and 1 mm internal diameter) was packed with stationary phase. Very high separation efficiency (ca. 351 000 plates/m) was achieved for five commercial peptides with a percent relative standard deviation of less than 1%. Protocol for the synthesis and modification of silica monolith particles has been well optimized with a good reproducibility both in particle and pore size. The column resolved about 21 peptide components from a mixture containing tryptic digest of cytochrome C, under the elution conditions of acetonitrile/15 mM ammonium format (65/35 v/v%) with a flow rate of 28 μL/min.

Salivary Protein Panel to Diagnose Systolic Heart Failure

Screening for systolic heart failure (SHF) has been problematic. Heart failure management guidelines suggest screening for structural heart disease and SHF prevention strategies should be a top priority. We developed a multi-protein biomarker panel using saliva as a diagnostic medium to discriminate SHF patients and healthy controls. We collected saliva samples from healthy controls (n = 88) and from SHF patients (n = 100). We developed enzyme linked immunosorbent assays to quantify three specific proteins/peptide (Kallikrein-1, Protein S100-A7, and Cathelicidin antimicrobial peptide) in saliva samples. The analytical and clinical performances and predictive value of the proteins were evaluated. The analytical performances of the immunoassays were all within acceptable analytical ranges. The multi-protein panel was able to significantly (p < 0.001) discriminate saliva samples collected from patients with SHF from controls. The multi-protein panel demonstrated good performance with an overall diagnostic accuracy of 81.6% (sensitivity of 79.2% and specificity of 85.7%) when distinguishing SHF patients from healthy individuals. In conclusion, we have developed immunoassays to measure the salivary concentrations of three proteins combined as a panel to accurately distinguish SHF patients from healthy controls. While this requires confirmation in larger cohorts, our findings suggest that this three-protein panel has the potential to be used as a biomarker for early detection of SHF.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2013-2014

This review is the eighth update of the original article published in 1999 on the application of Matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2014. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly- saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. © 2018 Wiley Periodicals, Inc. Mass Spec Rev 37:353-491, 2018.

Epithelial ovarian carcinoma diagnosis by desorption electrospray ionization mass spectrometry imaging

Ovarian cancer is highly prevalent among European women, and is the leading cause of gynaecological cancer death. Current histopathological diagnoses of tumour severity are based on interpretation of, for example, immunohistochemical staining. Desorption electrospray mass spectrometry imaging (DESI-MSI) generates spatially resolved metabolic profiles of tissues and supports an objective investigation of tumour biology. In this study, various ovarian tissue types were analysed by DESI-MSI and co-registered with their corresponding haematoxylin and eosin (H&E) stained images. The mass spectral data reveal tissue type-dependent lipid profiles which are consistent across the n = 110 samples (n = 107 patients) used in this study. Multivariate statistical methods were used to classify samples and identify molecular features discriminating between tissue types. Three main groups of samples (epithelial ovarian carcinoma, borderline ovarian tumours, normal ovarian stroma) were compared as were the carcinoma histotypes (serous, endometrioid, clear cell). Classification rates >84% were achieved for all analyses, and variables differing statistically between groups were determined and putatively identified. The changes noted in various lipid types help to provide a context in terms of tumour biochemistry. The classification of unseen samples demonstrates the capability of DESI-MSI to characterise ovarian samples and to overcome existing limitations in classical histopathology.

Proteomics in cancer research: Are we ready for clinical practice?

Although genomics has delivered major advances in cancer prognostics, treatment and diagnostics, it still only provides a static image of the situation. To study more dynamic molecular entities, proteomics has been introduced into the cancer research field more than a decade ago. Currently, however, the impact of clinical proteomics on patient management and clinical decision-making is low and the implementations of scientific results in the clinic appear to be scarce. The search for cancer-related biomarkers with proteomics however, has major potential to improve risk assessment, early detection, diagnosis, prognosis, treatment selection and monitoring. In this review, we provide an overview of the transition of oncoproteomics towards translational oncology. We describe which lessons are learned from currently approved protein biomarkers and previous proteomic studies, what the pitfalls and challenges are in clinical proteomics applications, and how proteomic research can be successfully translated into medical practice.

Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery

Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics.

Open tubular lab-on-column/mass spectrometry for targeted proteomics of nanogram sample amounts

A novel open tubular nanoproteomic platform featuring accelerated on-line protein digestion and high-resolution nano liquid chromatography mass spectrometry (LC-MS) has been developed. The platform features very narrow open tubular columns, and is hence particularly suited for limited sample amounts. For enzymatic digestion of proteins, samples are passed through a 20 µm inner diameter (ID) trypsin + endoproteinase Lys-C immobilized open tubular enzyme reactor (OTER). Resulting peptides are subsequently trapped on a monolithic pre-column and transferred on-line to a 10 µm ID porous layer open tubular (PLOT) liquid chromatography LC separation column. Wnt/ß-catenein signaling pathway (Wnt-pathway) proteins of potentially diagnostic value were digested+detected in targeted-MS/MS mode in small cell samples and tumor tissues within 120 minutes. For example, a potential biomarker Axin1 was identifiable in just 10 ng of sample (protein extract of ∼1,000 HCT15 colon cancer cells). In comprehensive mode, the current OTER-PLOT set-up could be used to identify approximately 1500 proteins in HCT15 cells using a relatively short digestion+detection cycle (240 minutes), outperforming previously reported on-line digestion/separation systems. The platform is fully automated utilizing common commercial instrumentation and parts, while the reactor and columns are simple to produce and have low carry-over. These initial results point to automated solutions for fast and very sensitive MS based proteomics, especially for samples of limited size.

In 2014, can we do better than CA125 in the early detection of ovarian cancer?

Ovarian cancer is a lethal gynecologic malignancy with greater than 70% of women presenting with advanced stage disease. Despite new treatments, long term outcomes have not significantly changed in the past 30 years with the five-year overall survival remaining between 20% and 40% for stage III and IV disease. In contrast patients with stage I disease have a greater than 90% five-year overall survival. Detection of ovarian cancer at an early stage would likely have significant impact on mortality rate. Screening biomarkers discovered at the bench have not translated to success in clinical trials. Existing screening modalities have not demonstrated survival benefit in completed prospective trials. Advances in high throughput screening are making it possible to evaluate the development of ovarian cancer in ways never before imagined. Data in the form of human “-omes” including the proteome, genome, metabolome, and transcriptome are now available in various packaged forms. With the correct pooling of resources including prospective collection of patient specimens, integration of high throughput screening, and use of molecular heterogeneity in biomarker discovery, we are poised to make progress in ovarian cancer screening. This review will summarize current biomarkers, imaging, and multimodality screening strategies in the context of emerging technologies.