Detlev Suckau

Correct primary structure assessment and extensive glyco-profiling of cetuximab by a combination of intact, middle-up, middle-down and bottom-up ESI and MALDI mass spectrometry techniques

The European Medicines Agency received recently the first marketing authorization application for a biosimilar monoclonal antibody (mAb) and adopted the final guidelines on biosimilar mAbs and Fc-fusion proteins. The agency requires high similarity between biosimilar and reference products for approval. Specifically, the amino acid sequences must be identical. The glycosylation pattern of the antibody is also often considered to be a very important quality attribute due to its strong effect on quality, safety, immunogenicity, pharmacokinetics and potency. Here, we describe a case study of cetuximab, which has been marketed since 2004. Biosimilar versions of the product are now in the pipelines of numerous therapeutic antibody biosimilar developers. We applied a combination of intact, middle-down, middle-up and bottom-up electrospray ionization and matrix assisted laser desorption ionization mass spectrometry techniques to characterize the amino acid sequence and major post-translational modifications of the marketed cetuximab product, with special emphasis on glycosylation. Our results revealed a sequence error in the reported sequence of the light chain in databases and in publications, thus highlighting the potency of mass spectrometry to establish correct antibody sequences. We were also able to achieve a comprehensive identification of cetuximab’s glycoforms and glycosylation profile assessment on both Fab and Fc domains. Taken together, the reported approaches and data form a solid framework for the comparability of antibodies and their biosimilar candidates that could be further applied to routine structural assessments of these and other antibody-based products.

Interlaboratory Study on Differential Analysis of Protein Glycosylation by Mass Spectrometry: the ABRF Glycoprotein Research Multi-Institutional Study 2012

One of the principal goals of glycoprotein research is to correlate glycan structure and function. Such correlation is necessary in order for one to understand the mechanisms whereby glycoprotein structure elaborates the functions of myriad proteins. The accurate comparison of glycoforms and quantification of glycosites are essential steps in this direction. Mass spectrometry has emerged as a powerful analytical technique in the field of glycoprotein characterization. Its sensitivity, high dynamic range, and mass accuracy provide both quantitative and sequence/structural information. As part of the 2012 ABRF Glycoprotein Research Group study, we explored the use of mass spectrometry and ancillary methodologies to characterize the glycoforms of two sources of human prostate specific antigen (PSA). PSA is used as a tumor marker for prostate cancer, with increasing blood levels used to distinguish between normal and cancer states. The glycans on PSA are believed to be biantennary N-linked, and it has been observed that prostate cancer tissues and cell lines contain more antennae than their benign counterparts. Thus, the ability to quantify differences in glycosylation associated with cancer has the potential to positively impact the use of PSA as a biomarker. We studied standard peptide-based proteomics/glycomics methodologies, including LC-MS/MS for peptide/glycopeptide sequencing and label-free approaches for differential quantification. We performed an interlaboratory study to determine the ability of different laboratories to correctly characterize the differences between glycoforms from two different sources using mass spectrometry methods. We used clustering analysis and ancillary statistical data treatment on the data sets submitted by participating laboratories to obtain a consensus of the glycoforms and abundances. The results demonstrate the relative strengths and weaknesses of top-down glycoproteomics, bottom-up glycoproteomics, and glycomics methods.

Revisiting Rat Spermatogenesis with MALDI Imaging at 20-μm Resolution

Matrix-assisted laser desorption/ionization (MALDI) molecular imaging technology attracts increasing attention in the field of biomarker discovery. The unambiguous correlation between histopathology and MALDI images is a key feature for success. MALDI imaging mass spectrometry (MS) at high definition thus calls for technological developments that were established by a number of small steps. These included tissue and matrix preparation steps, dedicated lasers for MALDI imaging, an increase of the robustness against cell debris and matrix sublimation, software for precision matching of molecular and microscopic images, and the analysis of MALDI imaging data using multivariate statistical methods. The goal of these developments is to approach single cell resolution with imaging MS. Currently, a performance level of 20-μm image resolution was achieved with an unmodified and commercially available instrument for proteins detected in the 2–16-kDa range. The rat testis was used as a relevant model for validating and optimizing our technological developments. Indeed, testicular anatomy is among the most complex found in mammalian bodies. In the present study, we were able to visualize, at 20-μm image resolution level, different stages of germ cell development in testicular seminiferous tubules; to provide a molecular correlate for its well established stage-specific classification; and to identify proteins of interest using a top-down approach and superimpose molecular and immunohistochemistry images.

Phosphatidylcholines and -ethanolamines can be easily mistaken in phospholipid mixtures: a negative ion MALDI-TOF MS study with 9-aminoacridine as matrix and egg yolk as selected example

AbstractPhospholipids (PL) are increasingly analyzed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). As in the case of polar molecules, however, the careful selection of the matrix is crucial for optimum results. 9-Aminoacridine (9-AA) was recently suggested as the matrix of choice to analyze PL mixtures because of (a) the improved sensitivity and (b) the reduction of suppression effects compared to other matrices. However, the distinction of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) in the negative ion mode is obscured as PC is also detectable as –CH3+ ion if 9-AA is used as matrix. This may result in the erroneous assignment of PC as a PE species. Using an organic extract from hen egg yolk as example it will be shown that the contribution of PC must be taken into consideration if the negative ion mass spectra are used to evaluate the fatty acyl compositions of PE mixtures. 9-AA can as well be used in hyphenated thin-layer chromatography (TLC)-MALDI-TOF MS where PC and PE are chromatographically well separated for unequivocal assignments. FigureComparison of negative ion MALDI-TOF mass spectra of isolated 1-palmitoyl-2-oleoyl-sn-phosphatidylcholine (POPC) and 1-palmitoyl-2-oleoyl-sn-phosphatidylethanolamine (POPE) using either DHB (blue) or 9-AA (red) as matrix. The spectra differ significantly as a function of the matrix used. In case of 9-AA, POPC is detectable as negative ion subsequent to the loss of a -CH3 group, which complicates peak assignments when complex mixtures are analyzed

Approaching MALDI molecular imaging for clinical proteomic research: current state and fields of application

MALDI imaging mass spectrometry (‘MALDI imaging’) is an increasingly recognized technique for biomarker research. After years of method development in the scientific community, the technique is now increasingly applied in clinical research. In this article, we discuss the use of MALDI imaging in clinical proteomics and put it in context with classical proteomics techniques. We also highlight a number of upcoming challenges for personalized medicine, development of targeted therapies and diagnostic molecular pathology where MALDI imaging could help.

Top-down de Novo protein sequencing of a 13.6 kDa camelid single heavy chain antibody by matrix-assisted laser desorption ionization-time-of-flight/time-of-flight mass spectrometry.

The primary structure of a 13.6 kDa single heavy chain camelid antibody (V(H)H) was determined by matrix-assisted laser desorption ionization-time-of-flight/time-of-flight (MALDI-TOF/TOF) top-down sequence analysis. The majority of the sequence was obtained by mass spectrometric de novo sequencing, with the N-terminal 14 amino acid residues being determined using T(3)-sequencing and database interrogation. The determined sequence was confirmed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of a tryptic digest, which also provided high-energy collisionally induced dissociation (CID) data permitting the clear assignment of 3 of the 14 isobaric Leu/Ile residues. Five of the 11 Leu/Ile ambiguities could be resolved by homology comparisons with known V(H)H sequences. The monoisotopic molecular weight of the V(H)H was determined by ultrahigh-resolution orthogonal electrospray (ESI)-TOF analysis and found to be 13 610.6066 Da, in excellent agreement with the established sequence. To our knowledge, this is the first time that the entire primary structure of a protein with a molecular weight >13 kDa has been established by mass spectrometric top-down sequencing.

Imaging mass spectrometry to discriminate breast from pancreatic cancer metastasis in formalin-fixed paraffin-embedded tissues.

Diagnosis of the origin of metastasis is mandatory for adequate therapy. In the past, classification of tumors was based on histology (morphological expression of a complex protein pattern), while supportive immunohistochemical investigation relied only on few “tumor specific” proteins. At present, histopathological diagnosis is based on clinical information, morphology, immunohistochemistry, and may include molecular methods. This process is complex, expensive, requires an experienced pathologist and may be time consuming. Currently, proteomic methods have been introduced in various clinical disciplines. MALDI imaging MS combines detection of numerous proteins with morphological features, and seems to be the ideal tool for objective and fast histopathological tumor classification. To study a special tumor type and to identify predictive patterns that could discriminate metastatic breast from pancreatic carcinoma MALDI imaging MS was applied to multitissue paraffin blocks. A statistical classification model was created using a training set of primary carcinoma biopsies. This model was validated on two testing sets of different breast and pancreatic carcinoma specimens. We could discern breast from pancreatic primary tumors with an overall accuracy of 83.38%, a sensitivity of 85.95% and a specificity of 76.96%. Furthermore, breast and pancreatic liver metastases were tested and classified correctly.

Capabilities and disadvantages of combined matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and high-performance thin-layer chromatography (HPTLC): Analysis of egg yolk lipids

Lipids are important natural products and essential in nutrition, cosmetic formulations, pharmaceuticals, etc. Lipids and, particularly, phospholipids are of substantial medical interest (some are molecules with messenger function) and of diagnostic potential (for instance, the lipoproteins in human blood). Among the different soft-ionization mass spectrometric methods that enable detection of the intact lipid molecules, matrix-assisted laser-desorption/ioniza-tion time-of-flight mass spectrometry (MALDI-TOF MS) has several advantages, for instance, simple performance, high sensitivity, and robustness against contaminants. Additionally, MALDI-TOF MS analyzes a solid sample. This enables (in contrast with isotropic solutions) acquisition of spatially-resolved mass spectra (‘mass spec-trometric imaging’). However, separation of complex mixtures into the individual lipid classes is normally required to enable detection of all the components. It will be shown with the example of a lipid extract from hens’ egg yolk that MALDI-TOF MS can be easily combined with TLC, enabling detection of as little as picomole amounts of lipids directly on the HPTLC plate. This results in sensitivities higher than those from established staining procedures. Additionally, because of the substantial spatial resolution, lipids separated by normal-phase TLC may not only be differentiated according to differences of their headgroups but also according to differences of their fatty acyl composition. Finally, MS-MS experiments, providing further insights into the structures of the relevant lipids, can be also performed directly on the HPTLC plate. Although the HPTLC-MALDI coupling can be easily established, there are different points to which special attention should be paid. Aspects of matrix application, data acquisition (including the stability of lipids and reproducibility), and data evaluation will be emphasized in this paper.

Tutorial: Multivariate Statistical Treatment of Imaging Data for Clinical Biomarker Discovery

Cancer research is one of the most promising application areas for the new technology of MALDI tissue imaging. Cancerous tissue can easily be distinguished from healthy tissue by dramatically changed metabolism, growth, and apoptotic processes. Of even higher interest is the fact that MALDI imaging allows to unveil molecular differentiation undetectable by classical histological techniques. Thus, MALDI imaging has tremendous potential as a tool to characterize the therapeutic susceptibility of tumors in biopsies as well as to predict tumor progression in endpoint studies. However, some aspects are important to consider for a successful MALDI imaging-based cancer research. Cancer sections are usually very heterogeneous - different biochemical pathways can be active in individual tumor clones, at different development stages or in various tumor microenvironments. Understanding tissue at this level is only possible for experienced histopathologists working on high-resolution optical images. Therefore, the largest benefit from the use of MALDI imaging results in histopathology will arise if molecular images are related to classical high-resolution histological images in a simple way without the need to interpret mass spectra directly. Each MALDI imaging data set effectively provides information on hundreds of molecules and permits the generation of molecular images displaying the relative abundance of these molecules across the tissue. The interpretation of these in the histological context is a major challenge in terms of expert analysis time. This is true especially for clinical work with hundreds of tissue specimens to be analyzed by MALDI, interpreted, and compared. Therefore, a MALDI imaging workflow is described here that enables fast and unambiguous interpretation of the MALDI imaging data in the histological context. Preprocessing of the image data using statistical tools allows efficient and straightforward interpretation by the histopathologist. In this chapter, we explain the use of principal component analysis (PCA) and hierarchical clustering (HC) for the efficient interpretation of MALDI imaging data. We also outline how these methods can be used to compare specific disease states between patients in the search for biomarkers.

Quantification of serum apolipoproteins A-I and B-100 in clinical samples using an automated SISCAPA-MALDI-TOF-MS workflow.

A fully automated workflow was developed and validated for simultaneous quantification of the cardiovascular disease risk markers apolipoproteins A-I (apoA-I) and B-100 (apoB-100) in clinical sera. By coupling of stable-isotope standards and capture by anti-peptide antibodies (SISCAPA) for enrichment of proteotypic peptides from serum digests to matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS detection, the standardized platform enabled rapid, liquid chromatography-free quantification at a relatively high throughput of 96 samples in 12h. The average imprecision in normo- and triglyceridemic serum pools was 3.8% for apoA-I and 4.2% for apoB-100 (4 replicates over 5 days). If stored properly, the MALDI target containing enriched apoA-1 and apoB-100 peptides could be re-analyzed without any effect on bias or imprecision for at least 7 days after initial analysis. Validation of the workflow revealed excellent linearity for daily calibration with external, serum-based calibrators (R(2) of 0.984 for apoA-I and 0.976 for apoB-100 as average over five days), and absence of matrix effects or interference from triglycerides, protein content, hemolysates, or bilirubins. Quantification of apoA-I in 93 normo- and hypertriglyceridemic clinical sera showed good agreement with immunoturbidimetric analysis (slope = 1.01, R(2) = 0.95, mean bias = 4.0%). Measurement of apoB-100 in the same clinical sera using both methods, however, revealed several outliers in SISCAPA-MALDI-TOF-MS measurements, possibly as a result of the lower MALDI-TOF-MS signal intensity (slope = 1.09, R(2) = 0.91, mean bias = 2.0%). The combination of analytical performance, rapid cycle time and automation potential validate the SISCAPA-MALDI-TOF-MS platform as a valuable approach for standardized and high-throughput quantification of apoA-I and apoB-100 in large sample cohorts.