Site-Specific Stability Evaluation of Antibody-Drug Conjugate in Serum Using a Validated Liquid Chromatography-Mass Spectrometry Method.

Antibody-drug conjugate (ADC) consists of engineered antibodies and cytotoxic drugs linked via a chemical linker, and the stability of ADC plays a crucial role in ensuring its safety and efficacy. The stability of ADC is closely related to the conjugation site; however, no method has been developed to assess the stability of different conjugation sites due to the low response of conjugated peptides. In this study, an integrated strategy was developed and validated to assess the stability of different conjugation sites on ADC in serum. Initial identification of the conjugated peptides of the model drug ado-trastuzumab emtansine (T-DM1) was achieved by the proteomic method. Subsequently, a semiquantitative method for conjugated peptides was established in liquid chromatography-hybrid linear ion trap triple quadrupole mass spectrometry (LC-QTRAP-MS/MS) based on the qualitative information. The pretreatment method of the serum sample was optimized to reduce matrix interference. The method was then validated and applied to evaluate the stability of the conjugation sites on T-DM1. The results highlighted differences in stability among the different conjugation sites on T-DM1. This is the first study to assess the stability of different conjugation sites on the ADC in serum, which will be helpful for the design and screening of ADCs in the early stages of development.

Arrangement into layers and mechanobiology of multi-cell co-culture models of the uterine wall.

STUDY QUESTION: Can a co-culture of three cell types mimic the in vivo layers of the uterine wall? SUMMARY ANSWER: Three protocols tested for co-culture of endometrial epithelial cells (EEC), endometrial stromal cells (ESC), and myometrial smooth muscle cells (MSMC) led to formation of the distinct layers that are characteristic of the structure of the uterine wall in vivo. WHAT IS KNOWN ALREADY: We previously showed that a layer-by-layer co-culture of EEC and MSMC responded to peristaltic wall shear stresses (WSS) by increasing the polymerization of F-actin in both layers. Other studies showed that WSS induced significant cellular alterations in epithelial and endothelial cells. STUDY DESIGN, SIZE, DURATION: Human EEC and ESC cell lines and primary MSMC were co-cultured on a collagen-coated synthetic membrane in custom-designed wells. The co-culture model, created by seeding a mixture of all cells at once, was exposed to steady WSS of 0.5 dyne/cm2 for 10 and 30 min. PARTICIPANTS/MATERIALS, SETTING, METHODS: The co-culture of the three different cells was seeded either layer-by-layer or as a mixture of all cells at once. Validation of the models was by specific immunofluorescence staining and confocal microscopy. Alterations of the cytoskeletal F-actin in response to WSS were analyzed from the 2-dimensional confocal images through the Z-stacks following a previously published algorithm. MAIN RESULTS AND THE ROLE OF CHANCE: We generated three multi-cell in vitro models of the uterine wall with distinct layers of EEC, ESC, and MSMC that mimic the in vivo morphology. Exposure of the mixed seeding model to WSS induced increased polymerization of F-actin in all the three layers relative to the unexposed controls. Moreover, the increased polymerization of F-actin was higher (P-value < 0.05) when the length of exposure was increased from 10 to 30 min. Furthermore, the inner layers of ESC and MSMC, which are not in direct contact with the applied shearing fluid, also increased their F-actin polymerization. LARGE SCALE DATA: N/A. LIMITATIONS, RESONS FOR CAUTION: The mixed seeding co-culture model was exposed to steady WSS of one magnitude, whereas the uterus is a dynamic organ with intra-uterine peristaltic fluid motions that vary in vivo with different time-dependent magnitude. Further in vitro studies may explore the response to peristaltic WSS or other physical and/or hormonal perturbations that may mimic the spectrum of pathophysiological aspects. WIDER IMPLICATIONS OF THE FINDINGS: Numerous in vitro models were developed in order to mimic the human endometrium and endometrium-myometrium interface (EMI) region. The present co-culture models seem to be the first constructed from EEC, ESC, and MSMC on a collagen-coated synthetic membrane. These multi-cell in vitro models better represent the complex in vivo anatomy of the EMI region. The mixed seeding multi-cell in vitro model may easily be implemented in controlled studies of uterine function in reproduction and the pathogenesis of diseases. STUDY FINDING/COMPETING INTEREST(S): This study was supported in part by Tel Aviv University funds. All authors declare no conflict of interest.

A systematic review on the selection of reference genes for gene expression studies in rodents: are the classics the best choice?

Rodents are commonly used as animal models in studies investigating various experimental conditions, often requiring gene expression analysis. Quantitative real-time reverse transcription PCR (RT-qPCR) is the most widely used tool to quantify target gene expression levels under different experimental conditions in various biological samples. Relative normalization with reference genes is a crucial step in RT-qPCR to obtain reliable quantification results. In this work, the main reference genes used in gene expression studies among the three rodents commonly employed in scientific research-hamster, rat, and mouse-are analyzed and described. An individual literature search for each rodent was conducted using specific search terms in three databases: PubMed, Scopus, and Web of Science. A total of 157 articles were selected (rats = 73, mice = 79, and hamsters = 5), identifying various reference genes. The most commonly used reference genes were analyzed according to each rodent, sample type, and experimental condition evaluated, revealing a great variability in the stability of each gene across different samples and conditions. Classic genes, which are expected to be stably expressed in both samples and conditions analyzed, demonstrated greater variability, corroborating existing concerns about the use of these genes. Therefore, this review provides important insights for researchers seeking to identify suitable reference genes for their validation studies in rodents.

Monitoring the Photorhabdus spp. bacterial load in Heterorhabditis bacteriophora dauer juveniles over different storage times and temperatures: A molecular approach.

Biological control products based on the entomopathogenic nematode Heterorhabditis bacteriophora can vary in virulence (quality). The influence of their symbiotic bacteria Photorhabdus spp. inside the infective dauer juvenile (DJ) on DJ quality has not received much attention in the past. The presence of the bacteria in the DJ is crucial for its biocontrol potential. This investigation provides a method to quantify the bacterial load inside the DJ based on a qPCR technique. Information from the genome of Photorhabdus laumondii strain DE2 was used to identify single copy genes with no homology to any other bacterial accessions. One gene (hereby named CG2) was selected for primers design and for further qPCR experiments. Cross-amplification tests with P. thracensis and P. kayaii, also symbionts of H. bacteriophora, were positive, whereas no amplicons were produced for P. temperata or Xenorhabdus nematophila. We tested our qPCR system in DJ populations carrying defined proportions of bacteria-free (axenic) vs bacteria-carrying nematodes. With an increasing proportion of axenic DJ in a population, virulence declined, and the virulence was proportional to the amount of bacterial DNA detected in the population by qPCR. Along liquid storage over long time, virulence also decreased, and this factor correlated with the reduction of bacterial DNA on the respective DJ population. We observed that stored DJ kept virulent up to 90 days and thereafter the virulence as well as the amount of bacterial DNA drastically decreased. Storage temperature also influenced the bacterial survival. Inside formulated DJ, the loss of bacterial DNA on the DJ population was accelerated under storage temperatures below 7.5 °C, suggesting that reproduction of the bacterial cells takes place when growth temperature is favorable. The role of bacterial survival inside stored DJ can now be adequately addressed using this molecular quality-control technique.

qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data.

BACKGROUND: Reverse transcription quantitative real-time PCR (RT-qPCR) is a well-established method for analysing gene expression. Most RT-qPCR experiments in the field of microbiology aim for the detection of transcriptional changes by relative quantification, which means the comparison of the expression level of a specific gene between different samples by the application of a calibration condition and internal reference genes. Due to the numerous data processing procedures and factors that can influence the final result, relative expression analysis and interpretation of RT-qPCR data are still not trivial and often necessitate the use of multiple separate software packages capable of performing specific functions. RESULTS: Here we present qRAT, a stand-alone desktop application based on R that automatically processes raw output data from any qPCR machine using well-established and state-of-the-art statistical and graphical techniques. The ability of qRAT to analyse RT-qPCR data was evaluated using two example datasets generated in our laboratory. The tool successfully completed the procedure in both cases, returning the expected results. The current implementation includes functionalities for parsing, filtering, normalizing and visualisation of relative RT-qPCR data, like the determination of the relative quantity and the fold change of differentially expressed genes as well as the correction of inter-plate variation for multiple-plate experiments. CONCLUSION: qRAT provides a comprehensive, straightforward, and easy-to-use solution for the relative quantification of RT-qPCR data that requires no programming knowledge or additional software installation. All application features are available for free and without requiring a login or registration.

Immunological characterization of chitosan adjuvanted outer membrane proteins of Salmonella enterica serovar Typhi as multi-epitope typhoid vaccine candidate.

BACKGROUND: Outer membrane proteins (OMPs) of Gram-negative bacteria have been known as potential vaccine targets due to their antigenic properties and host specificity. Here, we focused on the exploration of the immunogenic potential and protective efficacy of total OMPs of Salmonella enterica serovar Typhi due to their multi epitope properties, adjuvanted with nanoporous chitosan particles (NPCPs). The study was designed to extrapolate an effective, low cost prophylactic approach for typhoid fever being getting uncontrolled in Pakistan due to emergence of extensively drug resistant (XDR) strains. METHODS & RESULTS: The OMPs of two S. Typhi variants (with and without Vi capsule) alone and with nanoporous chitosan particles as adjuvant were comparatively analyzed for immunogenic potential in mice. Adaptive immunity was evaluated by ELISA and relative quantification of cytokine gene expression (IL4, IL6, IL9, IL17, IL10, TNF, INF and PPIA as house keeping gene) using RT-qPCR. Statistical analysis was done using Welch's test. The protection was recorded by challenging the immunized mice with 50% ×LD50 of S. Typhi. The Vi + ve-OMPs of S. Typhi showed the most promising results by ELISA and significantly high expression of IL-6, IL-10 and IL-17 and 92.5% protective efficacy with no detectable side effects. CONCLUSION: We can conclude that the OMPs of Vi + ve S. Typhi are the most promising candidates for future typhoid vaccines because of cost effective preparation without expensive purification steps and multi-epitope properties. Chitosan adjuvant may have applications for oral protein based vaccines but found less effective in injectable preparations.

Digital PCR (dPCR) and qPCR mediated determination of transgene copy number in the forage legume white clover (Trifolium repens).

Obtaining data on transgene copy number is an integral step in the generation of transgenic plants. Techniques such as Southern blot, segregation analysis, and quantitative PCR (qPCR) have routinely been used for this task, in a range of species. More recently, use of Digital PCR (dPCR) has become prevalent, with a measurement accuracy higher than qPCR reported. Here, the relative merits of qPCR and dPCR for transgene copy number estimation in white clover were investigated. Furthermore, given that single copy reference genes are desirable for estimating gene copy number by relative quantification, and that no single-copy genes have been reported in this species, a search and evaluation of suitable reference genes in white clover was undertaken. Results demonstrated a higher accuracy of dPCR relative to qPCR for copy number estimation in white clover. Two genes, Pyruvate dehydrogenase (PDH), and an ATP-dependent protease, identified as single-copy genes, were used as references for copy number estimation by relative quantification. Identification of single-copy genes in white clover will enable the application of relative quantification for copy number estimation of other genes or transgenes in the species. The results generated here validate the use of dPCR as a reliable strategy for transgene copy number estimation in white clover, and provide resources for future copy number studies in this species.

Relative qPCR to quantify colonization of plant roots by arbuscular mycorrhizal fungi.

Arbuscular mycorrhiza fungi (AMF) are beneficial soil fungi that can promote the growth of their host plants. Accurate quantification of AMF in plant roots is important because the level of colonization is often indicative of the activity of these fungi. Root colonization is traditionally measured with microscopy methods which visualize fungal structures inside roots. Microscopy methods are labor-intensive, and results depend on the observer. In this study, we present a relative qPCR method to quantify AMF in which we normalized the AMF qPCR signal relative to a plant gene. First, we validated the primer pair AMG1F and AM1 in silico, and we show that these primers cover most AMF species present in plant roots without amplifying host DNA. Next, we compared the relative qPCR method with traditional microscopy based on a greenhouse experiment with Petunia plants that ranged from very high to very low levels of AMF root colonization. Finally, by sequencing the qPCR amplicons with MiSeq, we experimentally confirmed that the primer pair excludes plant DNA while amplifying mostly AMF. Most importantly, our relative qPCR approach was capable of discriminating quantitative differences in AMF root colonization and it strongly correlated (Spearman Rho = 0.875) with quantifications by traditional microscopy. Finally, we provide a balanced discussion about the strengths and weaknesses of microscopy and qPCR methods. In conclusion, the tested approach of relative qPCR presents a reliable alternative method to quantify AMF root colonization that is less operator-dependent than traditional microscopy and offers scalability to high-throughput analyses.

[Attempt to Calculate the Efficiency of Methylation Using 1H-NMR for Analyzing Brominated Vegetable Oil].

We studied the efficiency of methylation for analyzing brominated vegetable oil (BVO). In this report, we investigated whether 1H-NMR is an applicable method for assessing the efficiency of methylation to analyze BVO. 1H-NMR sufficiently calculated the efficiency of methylation using each integral and the numbers of protons derived from the methyl group, which is characteristic in products, and the methine group, which is characteristic in unreacted substances. Additionally, the efficiency of methylation calculated via 1H-NMR was in good agreement with changes in the peak area of BVO fatty acid methyl esters (BVOFAMEs) after various heating times obtained from GC-FID analysis. Therefore, 1H-NMR is applicable for calculating the efficiency of methylation to analyze BVO.

iTRAQ-Based Proteomics Reveals that the Tomato ms1035 Gene Causes Male Sterility through Compromising Fat Acid Metabolism.

So far, over 50 spontaneous male sterile mutants of tomato have been described and most of them are categorized as genetic male sterility. To date, the mechanism of tomato genetic male sterility remained unclear. In this study, differential proteomic analysis is performed between genetic male sterile line (2-517), which carries the male sterility (ms1035 ) gene, and its wild-type (VF-11) using isobaric tags for relative and absolute quantification-based strategy. A total of 8272 proteins are quantified in the 2-517 and VF-11 lines at the floral bud and florescence stages. These proteins are involved in different cellular and metabolic processes, which express obvious functional tendencies toward the hydroxylation of the ω-carbon in fatty acids, the tricarboxylic acid cycle, the glycolytic, and pentose phosphate pathways. Based on the results, a protein network explaining the mechanisms of tomato genetic male sterility is proposed, finding the compromising fat acid metabolism may cause the male sterility. These results are confirmed by parallel reaction monitoring, quantitative Real-time PCR (qRT-PCR), and physiological assays. Taken together, these results provide new insights into the metabolic pathway of anther abortion induced by ms1035 and offer useful clues to identify the crucial proteins involved in genetic male sterility in tomato.

Software tool for internal standard based normalization of lipids, and effect of data-processing strategies on resulting values.

BACKGROUND: Lipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and disease. While lipids diverse biological roles contribute to their clinical utility, the diversity of lipid structure and concentrations prove to make lipidomics analytically challenging. Without internal standards to match each lipid species, researchers often apply individual internal standards to a broad range of related lipids. To aid in standardizing and automating this relative quantitation process, we developed LipidMatch Normalizer (LMN) http://secim.ufl.edu/secim-tools/ which can be used in most open source lipidomics workflows. RESULTS: LMN uses a ranking system (1-3) to assign lipid standards to target analytes. A ranking of 1 signifies that both the lipid class and adduct of the internal standard and target analyte match, while a ranking of 3 signifies that neither the adduct or class match. If multiple internal standards are provided for a lipid class, standards with the closest retention time to the target analyte will be chosen. The user can also signify which lipid classes an internal standard represents, for example indicating that ether-linked phosphatidylcholine can be semi-quantified using phosphatidylcholine. LMN is designed to work with any lipid identification software and feature finding software, and in this study is used to quantify lipids in NIST SRM 1950 human plasma annotated using LipidMatch and MZmine. CONCLUSIONS: LMN can be integrated into an open source workflow which completes all data processing steps including feature finding, annotation, and quantification for LC-MS/MS studies. Using LMN we determined that in certain cases the use of peak height versus peak area, certain adducts, and negative versus positive polarity data can have major effects on the final concentration obtained.

High-sensitivity quantification of glycosphingolipid glycans by ESI-MS utilizing ozonolysis-based release and isotopic Girard's reagent labeling.

Quantitative analysis of glycosphingolipids (GSLs) has been hindered by the lack of chromogenic groups for spectral detection or active functional groups for specific derivatization. In this study, a highly sensitive method based on ozonolysis-induced release and isotopic Girard's reagent P labeling of GSL glycans coupled with mass spectrometric detection for the quantification of animal tissue GSLs is developed. First, different approaches for the release of glycans from GSLs were compared with each other and the ozonolysis-based method was found to have the highest glycan yield under relative mild reaction conditions. Then a relative quantification method of ozonolysis-released GSL glycans based on stable isotope labeling using nondeuterated (d0-) and 2,3,4,5,6-pentadeuterated (d5-) Girard's reagent P (GP) was established, and its good linearity, accuracy and reproducibility were statistically verified. Finally, the new method was successfully applied to revealing the difference between porcine brain and liver as well as between the brain of normal and aging rats in GSL glycome by online hydrophilic interaction liquid chromatography coupling with ultraviolet detection and tandem mass spectrometry (HILIC-UV-MS/MS). This novel method is versatile and sensitive, enabling accurate quantitative analysis of tissue GSLs and showing great significance for glycomic studies.

Neuropeptidomics: Comparison of parallel reaction monitoring and data-independent acquisition for the analysis of neuropeptides using high-resolution mass spectrometry.

Targeted peptide quantitation by mass spectrometry is a rapidly emerging field. Traditionally it relied on the development and validation of multiple reaction monitoring assays that could comply with a high level of sensitivity, specificity, accuracy and reproducibility in complex biological samples. However, with the introduction of high-resolution mass spectrometers, other acquisition modes could provide more comprehensive datasets for identification and quantification but also for in-depth data mining. The objective of this study was to evaluate two analytical approaches, parallel-reaction monitoring (PRM) and data-independent analysis (DIA) using a hybrid Quadrupole-Orbitrap mass spectrometer for the quantification of neuropeptides in animal spinal cord tissues. Mouse spinal cord tissues were harvested, homogenized and neuropeptides extracted using a C18 solid-phase extraction protocol. Chromatography was achieved using a Thermo Biobasic C8 100 × 1 mm (5 µm) column. The initial mobile phase conditions consisted of acetonitrile and water (both containing 0.1% of formic acid) at a ratio of 5:95. An 11 min linear gradient was applied up to a ratio of 50:50 and maintained for 3 min. The flow rate was fixed at 75 µL/min and 2 µL of sample was injected. Mass spectrometry analyses were performed using a Thermo Q Exactive Plus MS using PRM and DIA approaches. Quantitative data using an isotopic dilution and a label-free strategy were obtained for both methods and statistically compared. Using both approaches, we were able to clearly detect endogenous neuropeptides. However, with DIA, mass spectra alone could not distinguish Leu-Enk and Met-Enk. We used a Bland-Altman plot (Difference plot) to analyze the agreement between both approaches and no systematic bias was observed. Further statistical analyses, including variance analysis, showed more variability in DIA compared with PRM mode. Further analyses were performed using a label-free approach and confirmed an increase of the variance using a DIA approach.

Process Proteomics of Beer Reveals a Dynamic Proteome with Extensive Modifications.

Modern beer production is a complex industrial process. However, some of its biochemical details remain unclear. Using mass spectrometry proteomics, we have performed a global untargeted analysis of the proteins present across time during nanoscale beer production. Samples included sweet wort produced by a high temperature infusion mash, hopped wort, and bright beer. This analysis identified over 200 unique proteins from barley and yeast, emphasizing the complexity of the process and product. We then used data independent SWATH-MS to quantitatively compare the relative abundance of these proteins throughout the process. This identified large and significant changes in the proteome at each process step. These changes described enrichment of proteins by their biophysical properties, and identified the appearance of dominant yeast proteins during fermentation. Altered levels of malt modification also quantitatively changed the proteomes throughout the process. Detailed inspection of the proteomic data revealed that many proteins were modified by protease digestion, glycation, or oxidation during the processing steps. This work demonstrates the opportunities offered by modern mass spectrometry proteomics in understanding the ancient process of beer production.

Partially 13C-labeled mouse tissue as reference for LC-MS based untargeted metabolomics.

The inclusion of stable isotope-labeled reference standards in the sample is an established method for the detection and relative quantification of metabolic features in untargeted metabolomics. In order to quantify as many metabolites as possible, the reference should ideally include the same metabolites in their stable isotope-labeled form as the sample under investigation. We present here an attempt to use partially 13C-labeled mouse material as internal standard for relative metabolite quantification of mouse and human samples in untargeted metabolomics. We fed mice for 14 days with a13C-labeled Ralstonia eutropha based diet. Tissue and blood amino acids from these mice showed 13C enrichment levels that ranged from 6% to 75%. We used MetExtract II software to automatically detect native and labeled peak pairs in an untargeted manner. In a dilution series and with the implementation of a correction factor, partially 13C-labeled mouse plasma resulted in accurate relative quantification of human plasma amino acids using liquid chromatography coupled to mass spectrometry, The coefficient of variation for the relative quantification is reduced from 27% without internal standard to 10% with inclusion of partially 13C-labeled internal standard. We anticipate the method to be of general use for the relative metabolite quantification of human specimens.

Expression of endogenous proteins in maize hybrids in a multi-location field trial in India.

Genetically modified (GM) crops undergo large scale multi-location field trials to characterize agronomics, composition, and the concentration of newly expressed protein(s) [herein referred to as transgenic protein(s)]. The concentration of transgenic proteins in different plant tissues and across the developmental stages of the plant is considered in the safety assessment of GM crops. Reference or housekeeping proteins are expected to maintain a relatively stable expression pattern in healthy plants given their role in cellular functions. Understanding the effects of genotype, growth stage and location on the concentration of endogenous housekeeping proteins may provide insight into the contribution these factors could have on transgenic protein concentrations in GM crops. The concentrations of three endogenous proteins (actin, elongation factor 1-alpha, and glyceraldehyde 3-phosphate dehydrogenase) were measured in several different maize hybrids grown across multiple field locations over 2 years. Leaf samples were collected from healthy plants at three developmental stages across the growing seasons, and protein concentrations were quantified by indirect enzyme-linked immunosorbent assay (ELISA) for each protein. In general, the concentrations of these three endogenous proteins were relatively consistent across hybrid backgrounds, when compared within one growth stage and location (2-26%CV), whereas the concentrations of proteins in the same hybrid and growth stage across different locations were more variable (12-64%CV). In general, the protein concentrations in 2013 and 2014 show similar trends in variability. Some degree of variability in protein concentrations should be expected for both transgenic and endogenous plant-expressed proteins. In the case of GM crops, the potential variation in protein concentrations due to location effects is captured in the current model of multi-location field testing.

Calibration plot for proteomics: A graphical tool to visually check the assumptions underlying FDR control in quantitative experiments.

In MS-based quantitative proteomics, the FDR control (i.e. the limitation of the number of proteins that are wrongly claimed as differentially abundant between several conditions) is a major postanalysis step. It is classically achieved thanks to a specific statistical procedure that computes the adjusted p-values of the putative differentially abundant proteins. Unfortunately, such adjustment is conservative only if the p-values are well-calibrated; the false discovery control being spuriously underestimated otherwise. However, well-calibration is a property that can be violated in some practical cases. To overcome this limitation, we propose a graphical method to straightforwardly and visually assess the p-value well-calibration, as well as the R codes to embed it in any pipeline. All MS data have been deposited in the ProteomeXchange with identifier PXD002370 (http://proteomecentral.proteomexchange.org/dataset/PXD002370).

Comparing the Diagnostic Classification Accuracy of iTRAQ, Peak-Area, Spectral-Counting, and emPAI Methods for Relative Quantification in Expression Proteomics.

Diagnostic classification accuracy is critical in expression proteomics to ensure that as many true differences as possible are identified with acceptable false-positive rates. We present a comparison of the diagnostic accuracy of iTRAQ with three label-free methods, peak area, spectral counting, and emPAI, for relative quantification using a spiked proteome standard. We provide the first validation of emPAI for intersample relative quantification and find clear differences among the four quantification approaches that could be considered when designing an experiment. Spectral counting was observed to perform surprisingly well in all regards. Peak area performed best for smaller fold differences and was shown to be capable of discerning a 1.1-fold difference with acceptable specificity and sensitivity. The performance of iTRAQ was dramatically worse than the label-free methods with low abundance proteins. Using the iTRAQ data set for validation, we also demonstrate a novel iTRAQ analysis regime that avoids the use of ratios in significance testing and outperforms a common commercial alternative.

Relative Quantification and Higher-Order Modeling of the Plasma Glycan Cancer Burden Ratio in Ovarian Cancer Case-Control Samples.

An early-stage, population-wide biomarker for ovarian cancer (OVC) is essential to reverse its high mortality rate. Aberrant glycosylation by OVC has been reported, but studies have yet to identify an N-glycan with sufficiently high specificity. We curated a human biorepository of 82 case-control plasma samples, with 27%, 12%, 46%, and 15% falling across stages I-IV, respectively. For relative quantitation, glycans were analyzed by the individuality normalization when labeling with glycan hydrazide tags (INLIGHT) strategy for enhanced electrospray ionization, MS/MS analysis. Sixty-three glycan cancer burden ratios (GBRs), defined as the log10 ratio of the case-control extracted ion chromatogram abundances, were calculated above the limit of detection. The final GBR models, built using stepwise forward regression, included three significant terms: OVC stage, normalized mean GBR, and tag chemical purity; glycan class, fucosylation, or sialylation were not significant variables. After Bonferroni correction, seven N-glycans were identified as significant (p < 0.05), and after false discovery rate correction, an additional four glycans were determined to be significant (p < 0.05), with one borderline (p = 0.05). For all N-glycans, the vectors of the effects from stages II-IV were sequentially reversed, suggesting potential biological changes in OVC morphology or in host response.