Poster

  • P-II-0731

ProteoGenomics characterization reveals a new molecular classification of chronic lymphocytic leukemia: novel insights in personalized therapeutical response

Presented in

Infectious Biology Insights

Poster topics

Authors

Manuel Fuentes (Salamanca / ES), Pablo Juanes-Velasco (Salamanca / ES), Carlota Arias-Hidalgo (Salamanca / ES), Ana Nuno-Soriano (Salamanca / ES), Angela-Patricia Hernandez (Salamanca / ES), Almudena Navarro-Bailon (Salamanca / ES), Miguel Alcoceba (Salamanca / ES), Marcos Gonzalez (Salamanca / ES), Javier de las Rivas (Salamanca / ES)

Abstract

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics.

B-cell chronic lymphocytic leukemia (B-CLL) is a blood cancer with highly heterogeneous genomic alterations and altered signaling pathways. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as B-CLL. Here, we characterized the proteome, phosphoproteome, tumor microenviroment profiling (TME), immunocheckpoint profiling and differential serological profiles (against 121 auto-antigen & 32 microbial antigens) alongside B-CLL and monoclonal B cell lymphocytosis (MBL Hi) in a discovery cohort (n= 67). From proteome and phosphoproteome dataset, it is revealing 7 subgroups, which 5 of them are correlated with genomic and transcriptomic alterations; meanwhile 2 new groups are only detectable at proteomics level. Classified developed to identify these new groups on tis characteristic proteome in one independent cohort ( n= 197) confirm that these new groups comprised 25% of B-CLL patients. The overall survival rate is highly different in this new group and is independent of the conventional target therapeutic algorithm based on TP53 mutation and IGHV mutation status. Based on multi-omics factor analysis is established a novel molecular classification of B-CLL and proteomics is providing novel insights to improve patient stratification beyond genetic alterations and heterogeneity.

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