Proteomics

Dataset Information

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Single-cell-type Spatial Proteomics Unveils Precision Medicine Insights in Composite Small Lymphocytic and Classical Hodgkin Lymphoma


ABSTRACT: Deep Visual Proteomics (DVP) is an innovative technique that enables spatially resolved sing-cell-type proteome analysis. The coexistence of classical Hodgkin lymphoma (cHL) and small lymphocytic lymphoma (SLL) in a single patient presents a challenging scenario for clinical decision-making. In this study, we investigate the potential of DVP to provide insights into precision medicine strategies. We use DVP to comprehensively profile the proteomic landscapes and signaling pathways within cHL and SLL compartments in a 71-year-old woman with composite lymphoma. Our analysis reveals distinct proteome profiles in cHL and SLL populations, highlighting their clonal unrelatedness. Beyond ABVD chemotherapy, we identify subtype-specific therapeutic targets: Minichromosome Maintenance protein inhibitors and proteasome inhibitors for cHL, and H3K27 methylation inhibitors and receptor tyrosine kinase inhibitors for SLL. Additionally, we explore interleukin-4 inhibition as a potential strategy to manage chemo-resistance. DVP provides insights into spatial single-cell proteomics, guiding personalized treatments for composite lymphoma patients.

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): B Cell, Lymph Node

DISEASE(S): Lymphoma

SUBMITTER: Mario Oroshi  

LAB HEAD: Matthias Mann

PROVIDER: PXD051795 | Pride | 2024-10-29

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
LibrarySearch.pg_matrix.tsv Tabular
Library_ddaPASEF.zip Other
Lymphoma_diaPASEF.zip Other
Metadata.xlsx Xlsx
library.tsv Tabular
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