Dataset Information

Retrospective longitudinal monitoring of multiple myeloma patients by mass spectrometry using archived serum protein electrophoresis gels and de novo sequence analysis

ABSTRACT: M-proteins are antibody molecules produced by a clone of Multiple Myeloma cells. Thus, they are used as a disease activity marker. Traditionally, serum protein electrophoresis gels (SPEP) are used to quantify M-proteins. While effective for diagnostics, sensitivity of SPEP is limited. Here, we demonstrate that M-protein gels can be excised from SPEP gels, even when the band is undetectable by visible inspection. Clonotypic peptides are identified by de novo sequencing of mass spectrometry data, and these clonotypic peptides are then monitored in the longitudinal data covering the course of disease. Thus, it is possible to follow disease activity in a blood sample with a sensitivity that may be similar to that of minimal residual diseas platforms that rely on bone marrow biopsies.

ORGANISM(S): Homo Sapiens

SUBMITTER: Martijn van Duijn

PROVIDER: PXD034406 | panorama | Wed Aug 10 00:00:00 BST 2022

REPOSITORIES: PanoramaPublic

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Publications

Retrospective Longitudinal Monitoring of Multiple Myeloma Patients by Mass Spectrometry Using Archived Serum Protein Electrophoresis Gels and De Novo Sequence Analysis.

Noori Somayya S Zajec Marina M Russcher Henk H Tintu Andrei N AN Broijl Annemiek A Jacobs Joannes F M JFM Luider Theo M TM de Rijke Yolanda B YB vanDuijn Martijn M MM

HemaSphere 20220802 8

PMID: 35935609

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Project description:The Rationale: Molecular markers of disease activity that are predictive of forced vital capacity (FVC) progression in idiopathic pulmonary fibrosis are needed. Objectives: Develop a predictor using longitudinal within-patient gene expression differences (ΔGE) in peripheral blood mononuclear cells (PBMC) to predict of FVC progression. Methods: Patients in the training cohort (n=74) experiencing ≥10% relative reduction in FVC% of predicted over 12 months were categorized as progressors in contrast to the remaining stable patients. Baseline to 4-month within-patient ΔGE were correlated with FVC status. FVC-predictor genes were prioritized by two-group comparison with FDR<5%, logistic LASSO regression with p<0.05, and 10-Fold Cross-Validation with ≥50% support. Receiver operating characteristic with area under the curve (AUC) analyses were conducted in training subsets and independent validation cohorts from UChicago (n=27), UPMC (n=35), and Imperial (n=24) where different transcriptome assay platforms and varying transcriptome sampling times were used to derive ΔGE. Results: Intra-subject Compared to cross-sectional analysis of baseline GE, our longitudinal ΔGE variation approach demonstratedlargely reduced within-group sample variation and increased statistic power fin progressor and stable groups for prediction model development. A 25-gene FVC-predictor separated “progressors” from “stable” by Principal Component Analysis in the training and subsets of the training cohort. The resulting FVC-predictor consistently demonstrated high discriminatory performance independent of transcriptome assay platforms and varying sampling times in validation cohorts (AUC= 0.77-0.80). TGF beta was the highest-ranking canonical pathway by Gene Set Enrichment Analysis. Conclusions: Our novel short-term longitudinal within-patient ΔGE approach identified a FVC-predictor which may reflect disease activity and prove to be a reliable biomarker predictive of future FVC decline.

Dataset Information

Retrospective longitudinal monitoring of multiple myeloma patients by mass spectrometry using archived serum protein electrophoresis gels and de novo sequence analysis

Publications

Retrospective Longitudinal Monitoring of Multiple Myeloma Patients by Mass Spectrometry Using Archived Serum Protein Electrophoresis Gels and De Novo Sequence Analysis.

Similar Datasets

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