Home Research Multi-factorial diseases B. Kahn-Perlès

Brigitte Kahn-Perlès

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Research interests

My current research focuses on the characterization of major transcriptional deregulations occurring in haematological malignancies, with a particular emphasis on the expression of genes coding for cell cycle and cell death regulators.

 

Projects

  •  The Sézary project


Investigators: Rabie Chelbi, Régis Costello, Brigitte Kahn-Perlès
Internal collaborators: Ramy Ragheb, Pascal Rihet, Béatrice Loriod
External collaborators: Thérèse la Treut, Pascale Poullin (APHM)
Funding: this project was supported by the ANR-08-SYS-003 CALAMAR

Sézary syndrome is a rare cancer which belongs to the heterogeneous group of cutaneous lymphomas and corresponds to the leukemic phase of mycosis fungoides. The prognosis for Sézary patients is poor (less than 30 % survival after 5 years of evolution). The histone deacetylase inhibitor (HDACi) suberoylanilide hydroxamic acid (SAHA) has been approved by the FDA for the treatment of refractory Sézary. This drug has a global response rate of 30 % urging for its use in combined treatment. Since Sp1 family factors are key mediators of the action of HDACi, we thought of testing the combination of SAHA and Mithramycin A, a competitive inhibitor of Sp factors binding to DNA. We have conducted an analysis of the transcriptome and the miRNome of primary patient cells and Sézary cell lines co-treated in vitro in order to get clues on the mechanisms of synergy exerted by the two drugs. This should allow to better fine tune our innovative therapeutic strategy.

 

  • The PTCL transcriptional meta-analysis project


Investigators: Luca Grieco, Denis Thieffry, Brigitte Kahn-Perlès
Internal collaborators: Régis Costello
External collaborators: Laurence Calzone, U900 INSERM, Institut Curie, Claudine Chaouiya-Chantegrel, IGH, Lisbonne

The aim of this project is to identify novel robust gene signatures enabling to better distinguish and characterize the most common peripheral T cell lymphoma (PTCL) subtypes, e.g. ALCL-ALK+ and ALCL ALK-, PTCL-NOS, AILT and ATLL. Such signatures should hopefully improve the diagnosis, prognosis and therapeutic strategies. Our approach is based on the analysis of public transcriptional datasets retrieved from the GEO database and produced using the same Affimetrix human genome platform. Lists of significantly differentially expressed genes are cross-checked with biological processes from the GO database and pathways from the KEGG database. They are also cross-checked with different generic cancer-relevant reaction maps that were built by some of us, as the RB/E2F¤ and the MAPK maps. Our most significant conclusions will be experimentally validated.