An antibody-based biomarker discovery method by mass spectrometry sequencing of complementarity determining regions

Autoantibodies are increasingly used as biomarkers in the detection of autoimmune disorders and cancer. Disease specific antibodies are generally detected by their binding to specific antigens. As an alternative approach, we propose to identify specific complementarity determining regions (CDR) of IgG that relate to an autoimmune disorder or cancer instead of the specific antigen(s). In this manuscript, we tested the technical feasibility to detect and identify CDRs of specific antibodies by mass spectrometry. We used a commercial pooled IgG preparation as well as purified serum IgG fractions that were spiked with different amounts of a fully human monoclonal antibody (adalimumab). These samples were enzymatically digested and analyzed by nanoLC Orbitrap mass spectrometry. In these samples, we were able to identify peptides derived from the CDRs of adalimumab. These peptides could be detected at an amount of 110 attomole, 5 orders of magnitude lower than the total IgG concentration in these samples. Using higher energy collision induced dissociation (HCD) fragmentation and subsequent de novo sequencing, we could successfully identify 50% of the detectable CDR peptides of adalimumab. In addition, we demonstrated that an affinity purification with anti-dinitrophenol (DNP) monoclonal antibody enhanced anti-DNP derived CDR detection in a serum IgG background. In conclusion, specific CDR peptides could be detected and sequenced at relatively low levels (attomole-femtomole range) which should allow the detection of clinically relevant CDR peptides in patient samples

Mass spectrometry analyses of ? and ? fractions result in increased number of complementarity-determining region identifications

Sera from lung cancer patients contain antibodies against tumor-associated antigens. Specific amino acid sequences of the complementarity-determining regions (CDRs) in the antigen-binding fragment (Fab) of these antibodies have potential as lung cancer biomarkers. Detection and identification of CDRs by mass spectrometry can significantly be improved by reduction of the complexity of the immunoglobulin molecule. Our aim was to molecular dissect IgG into ? and ? fragments to reduce the complexity and thereby identify substantially more CDRs than by just total Fab isolation. We purified Fab, Fab-?, Fab-?, ? and ? light chains from serum from 10 stage I lung adenocarcinoma patients and 10 matched controls from the current and former smokers. After purification, the immunoglobulin fragments were enzymatically digested and measured by high-resolution mass spectrometry. Finally, we compared the number of CDRs identified in these immunoglobulin fragments with that in the Fab fragments. Twice as many CDRs were identified when Fab-?, Fab-?, ? and ? (3330) were combined than in the Fab fraction (1663) alone. The number of CDRs and ?:? ratio was statistically similar in both cases and controls. Molecular dissection of IgG identifies significantly more CDRs, which increases the likelihood of finding lung cancer-related CDR sequences

De Novo Protein Sequencing by Combining Top-Down and Bottom-Up Tandem Mass Spectra

There are two approaches for de novo protein sequencing: Edman degradation and mass spectrometry (MS). Existing MS-based methods characterize a novel protein by assembling tandem mass spectra of overlapping peptides generated from multiple proteolytic digestions of the protein. Because each tandem mass spectrum covers only a short peptide of the target protein, the key to high coverage protein sequencing is to find spectral pairs from overlapping peptides in order to assemble tandem mass spectra to long ones. However, overlapping regions of peptides may be too short to be confidently identified. High-resolution mass spectrometers have become accessible to many laboratories. These mass spectrometers are capable of analyzing molecules of large mass values, boosting the development of top-down MS. Top-down tandem mass spectra cover whole proteins. However, top-down tandem mass spectra, even combined, rarely provide full ion fragmentation coverage of a protein. We propose an algorithm, TBNovo, for de novo protein sequencing by combining top-down and bottom-up MS. In TBNovo, a top-down tandem mass spectrum is utilized as a scaffold, and bottom-up tandem mass spectra are aligned to the scaffold to increase sequence coverage. Experiments on data sets of two proteins showed that TBNovo achieved high sequence coverage and high sequence accuracy

Peptides from the variable region of specific antibodies are shared among lung cancer patients

textabstractLate diagnosis of lung cancer is still the main reason for high mortality rates in lung cancer. Lung cancer is a heterogeneous disease which induces an immune response to different tumor antigens. Several methods for searching autoantibodies have been described that are based on known purified antigen panels. The aim of our study is to find evidence that parts of the antigen-binding-domain of antibodies are shared among lung cancer patients. This was investigated by a novel approach based on sequencing antigen-binding- fragments (Fab) of immunoglobulins using proteomic techniques without the need of previously known antigen panels. From serum of 93 participants of the NELSON trial IgG was isolated and subsequently digested into Fab and Fc. Fab was purified from the digested mixture by SDS-PAGE. The Fab containing gel-bands were excised, tryptic digested and measured on a nano-LC-Orbitrap-Mass- spectrometry system. Multivariate analysis of the mass spectrometry data by linear canonical discriminant analysis combined with stepwise logistic regression resulted in a 12-antibody-peptide model which was able to distinguish lung cancer patients from controls in a high risk population with a sensitivity of 84% and specificity of 90%. With our Fab-purification combined Orbitrap-mass-spectrometry approach, we found peptides from the variable-parts of antibodies which are shared among lung cancer patients