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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

ABSTRACT: Minimal residual disease (MRD) status in multiple myeloma (MM) is an important prognostic biomarker. Personalized blood-based targeted mass spectrometry (MS-MRD) detecting M-proteins was shown to provide a sensitive and minimally invasive alternative to MRD assessment in bone marrow. However, MS-MRD still comprises manual steps that hamper upscaling of sample size. Here, we introduce a proof-of-concept for a novel workflow using dia-PASEF technology and automated data processing.Using automated data processing of PASEF DDA and 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 follow-up samples from MM patients. Assay performance of prm-PASEF and dia-PASEF workflows were compared and we tested mixing patient intake sera for multiplexed target identification and selection.

INSTRUMENT(S): timsTOF Pro 2

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

DISEASE(S): Multiple Myeloma

SUBMITTER: Hans Wessels

LAB HEAD: Hans Wessels

PROVIDER: PXD050329 | Pride | 2025-06-10

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	20240203_FilesForRepository.xlsx	Xlsx
	PASER_MSMRD_Manuscript_Data.zip	Other
	PaSER_DIA-NN_and_Skyline_PRM_results.zip	Other

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Project description:Epitope mapping studies aim to identify the binding sites of antibody-antigen interactions to enhance the development of vaccines, diagnostics and immunotherapeutic compounds. However, mapping is a laborious process employing time- and resource-consuming M-bM-^@M-^Xwet benchM-bM-^@M-^Y techniques or epitope prediction software that are still in their infancy. For polymorphic antigens, another challenge is characterizing cross-reactivity between epitopes, teasing out distinctions between broadly cross-reactive responses, limited cross-reactions among variants and the truly type-specific responses. A refined understanding of cross-reactive antibody binding could guide the selection of the most informative subsets of variants for diagnostics and multivalent subunit vaccines. We explored the antibody binding reactivity of sera from human patients and Peromyscus leucopus rodents infected with Borrelia burgdorferi to the polymorphic outer surface protein C (OspC), an attractive candidate antigen for vaccine and improved diagnostics for Lyme disease. We constructed a protein microarray displaying 23 natural variants of OspC and quantified the degree of cross-reactive antibody binding between all pairs of variants, using Pearson correlation calculated on the reactivity values using three independent transforms of the raw data: (1) logarithmic, (2) rank, and (3) binary indicators. We observed that the global amino acid sequence identity between OspC pairs was a poor predictor of cross-reactive antibody binding. Then we asked if specific regions of the protein would better explain the observed cross-reactive binding and performed in silico screening of the linear sequence and 3-dimensional structure of OspC. This analysis pointed to the C-terminal helix of the structure as a major determinant of type-specific cross-reactive antibody binding. We developed bioinformatics methods to systematically analyze the relationship between local sequence/structure variation and cross-reactive antibody binding patterns among variants of a polymorphic antigen, and this method can be applied to other polymorphic antigens for which immune response data is available for multiple variants. Antibody profiling was performed on sera from Borrelia burgdorferi infected and non-infected humans and Peromyscus leucopus rodents against 23 variants of the surface protein OspC . For infected human serum samples, the OspC type of the infecting B. burgdorferi strain is unknown; for experimentally-infected P. leucopus serum samples, it is known. Of human serum samples, 55 were from infected individuals and 25 from naive controls. Of P. leucopus serum samples, 23 were from infected individuals and 7 were from naive controls.

Dataset Information

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

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