ArticleLeukemia2022
RPPA-based proteomics recognizes distinct epigenetic signatures in chronic lymphocytic leukemia with clinical consequences.
Article in Leukemia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Advances in lymphoma biomarkers research based on proteomics technology (Review).Oncology reports · 2025Review
- Proteomics for optimizing therapy in acute myeloid leukemia: venetoclax plus hypomethylating agents versus conventional chemotherapy.Leukemia · 2024Article
- Proteogenomics refines the molecular classification of chronic lymphocytic leukemia.Nature communications · 2022Article
- Proteomic profiling based classification of CLL provides prognostication for modern therapy and identifies novel therapeutic targets.Blood cancer journal · 2022Article
- Angiogenesis-related gene signatures reveal the prognosis of cervical cancer based on single cell sequencing and co-expression network analysis.Frontiers in cell and developmental biology · 2022Article
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Authors and funding
12 authors.
Funding
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Abstract
The chronic lymphocytic leukemia (CLL) armamentarium has evolved significantly, with novel therapies that inhibit Bruton Tyrosine Kinase, PI3K delta and/or the BCL2 protein improving outcomes. Still, the clinical course of CLL patients is highly variable and most previously recognized prognostic features lack the capacity to predict response to modern treatments indicating the need for new prognostic markers. In this study, we identified four epigenetically distinct proteomic signatures of a large cohort of CLL and related diseases derived samples (n = 871) using reverse phase protein array technology. These signatures are associated with clinical features including age, cytogenetic abnormalities [trisomy 12, del(13q) and del(17p)], immunoglobulin heavy-chain locus (IGHV) mutational load, ZAP-70 status, Binet and Rai staging as well as with the outcome measures of time to treatment and overall survival. Protein signature membership was identified as predictive marker for overall survival regardless of other clinical features. Among the analyzed epigenetic proteins, EZH2, HDAC6, and loss of H3K27me3 levels were the most independently associated with poor survival. These findings demonstrate that proteomic based epigenetic biomarkers can be used to better classify CLL patients and provide therapeutic guidance.
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