An automated workflow based on data independent acquisition for practical and high-throughput personalized assay development and minimal residual disease monitoring in multiple myeloma patients.

OBJECTIVES: Minimal residual disease (MRD) status in multiple myeloma (MM) is an important prognostic biomarker. Personalized blood-based targeted mass spectrometry detecting M-proteins (MS-MRD) was shown to provide a sensitive and minimally invasive alternative to MRD-assessment in bone marrow. However, MS-MRD still comprises of manual steps that hamper upscaling of MS-MRD testing. Here, we introduce a proof-of-concept for a novel workflow using data independent acquisition-parallel accumulation and serial fragmentation (dia-PASEF) and automated data processing. METHODS: Using automated data processing of dia-PASEF measurements, we developed a workflow that identified unique targets from MM patient sera and personalized protein sequence databases. We generated patient-specific libraries linked to dia-PASEF methods and subsequently quantitated and reported M-protein concentrations in MM patient follow-up samples. Assay performance of parallel reaction monitoring (prm)-PASEF and dia-PASEF workflows were compared and we tested mixing patient intake sera for multiplexed target selection. RESULTS: No significant differences were observed in lowest detectable concentration, linearity, and slope coefficient when comparing prm-PASEF and dia-PASEF measurements of serial dilutions of patient sera. To improve assay development times, we tested multiplexing patient intake sera for target selection which resulted in the selection of identical clonotypic peptides for both simplex and multiplex dia-PASEF. Furthermore, assay development times improved up to 25× when measuring multiplexed samples for peptide selection compared to simplex. CONCLUSIONS: Dia-PASEF technology combined with automated data processing and multiplexed target selection facilitated the development of a faster MS-MRD workflow which benefits upscaling and is an important step towards the clinical implementation of MS-MRD.

The advantage of laser-capture microdissection over whole tissue analysis in proteomic profiling studies.

Laser-capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated. In order to address this, we compared previously obtained high resolution MS data from a cohort of 38 breast cancer tissues, of which both LCM enriched tumor epithelial cells and WTL samples were analyzed. Label-free quantification (LFQ) analysis through MaxQuant software showed a significantly higher number of identified and quantified proteins in LCM enriched samples (3404) compared to WTLs (2837). Furthermore, WTL samples displayed a higher amount of missing data compared to LCM both at peptide and protein levels (p-value < 0.001). 2D analysis on co-expressed proteins revealed discrepant expression of immune system and lipid metabolisms related proteins between LCM and WTL samples. We hereby show that LCM better dissected the biology of breast tumor epithelial cells, possibly due to lower interference from surrounding tissues and highly abundant proteins. All data have been deposited in the ProteomeXchange with the dataset identifier PXD002381 (http://proteomecentral.proteomexchange.org/dataset/PXD002381).

Use of universal stable isotope labeling by amino acids in cell culture (SILAC)-based selected reaction monitoring (SRM) approach for verification of breast cancer-related protein markers.

Mass spectrometry-based proteomics facilitates high-throughput discovery of protein markers for diagnosis and treatment of breast cancer patients. Hundreds of putative prognostic and predictive markers are being identified every year, but only a very small proportion of them can be validated as clinically relevant markers. A quantitative and cost-efficient verification method is highly desirable to pick up real "nuggets" from the "sand." To fulfill these criteria, we previously introduced a stable isotope labeling by amino acids in cell culture (SILAC)-based selected reaction monitoring (SRM) approach for studying breast cancer-related protein markers. Here we describe a hands-on protocol of using this SILAC-SRM method for verification of breast cancer-related markers, which can also be used for verification of protein markers in other types of solid tumor tissues.

Cerebrospinal-fluid-derived immunoglobulin G of different multiple sclerosis patients shares mutated sequences in complementarity determining regions.

B lymphocytes play a pivotal role in multiple sclerosis pathology, possibly via both antibody-dependent and -independent pathways. Intrathecal immunoglobulin G in multiple sclerosis is produced by clonally expanded B-cell populations. Recent studies indicate that the complementarity determining regions of immunoglobulins specific for certain antigens are frequently shared between different individuals. In this study, our main objective was to identify specific proteomic profiles of mutated complementarity determining regions of immunoglobulin G present in multiple sclerosis patients but absent in healthy controls. To achieve this objective, we purified immunoglobulin G from the cerebrospinal fluid of 29 multiple sclerosis patients and 30 healthy controls and separated the corresponding heavy and light chains via SDS-PAGE. Subsequently, bands were excised, trypsinized, and measured with high-resolution mass spectrometry. We sequenced 841 heavy and 771 light chain variable region peptides. We observed 24 heavy and 26 light chain complementarity determining regions that were solely present in a number of multiple sclerosis patients. Using stringent criteria for the identification of common peptides, we found five complementarity determining regions shared in three or more patients and not in controls. Interestingly, one complementarity determining region with a single mutation was found in six patients. Additionally, one other patient carrying a similar complementarity determining region with another mutation was observed. In addition, we found a skew in the κ-to-λ ratio and in the usage of certain variable heavy regions that was previously observed at the transcriptome level. At the protein level, cerebrospinal fluid immunoglobulin G shares common characteristics in the antigen binding region among different multiple sclerosis patients. The indication of a shared fingerprint may indicate common antigens for B-cell activation.

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.