Molecular and clinical diversity in primary central nervous system lymphoma

authors

• Hernández-Verdin I.
• Kirasic E.
• Wienand K.
• Mokhtari K.
• Eimer S.
• Loiseau H.
• Rousseau A.
• Paillassa J.
• Ahle G.
• Lerintiu F.
• Uro-Coste E.
• Oberic L.
• Figarella-Branger D.
• Chinot O.
• Gauchotte G.
• Taillandier L.
• Marolleau J.-P.
• Polivka M.
• Adam C.
• Ursu R.
• Schmitt A.
• Barillot N.
• Nichelli L.
• Lozano-Sánchez F.
• Ibañez-Juliá M.-J.
• Peyre M.
• Mathon B.
• Abada Y.
• Charlotte F.
• Davi F.
• Stewart C.
• de Reyniès A.
• Choquet S.
• Soussain C.
• Houillier C.
• Chapuy B.
• Hoang-Xuan K.
• Alentorn A.

keywords

• PCNSL
• Microenvironment
• Multi-omics
• Tumor heterogeneity

document type

abstract

Background: Primary central nervous system lymphoma (PCNSL) is a rare and distinct entity within diffuse large B cell lymphoma presenting with variable response rates probably to underlying molecular heterogeneity. Patients and methods: To identify and characterize PCNSL heterogeneity and facilitate clinical translation, we performed a comprehensive multi-omic analysis (whole-exome sequencing, RNA-seq, methyl-seq, and clinical features) in a discovery cohort of 147 fresh-frozen immunocompetent PCNSLs and a validation cohort of formalin-fixed, paraffin-embedded (FFPE) 93 PCNSLs with RNA-seq and clinico-radiological data. Results: Consensus clustering of multi-omics data uncovered concordant classification of four robust, non-overlapping, prognostically significant clusters (CS). The CS1 and CS2 groups presented an immune-cold hypermethylated profile but distinct clinical behavior. The "immune-hot" CS4 group, enriched with mutations increasing the JAK-STAT and NF-κB activity, had the most favorable clinical outcome while the heterogeneous-immune CS3 group had the worse prognosis probably due to its association with meningeal infiltration and enriched HIST1H1E mutations. The CS1 was characterized by high Polycomb repressive complex 2 activity and CDKN2A/B loss leading to higher proliferation activity. Integrated analysis on proposed targets suggests potential use of immune checkpoint inhibitors/JAK1 inhibitors for CS4, cyclin D-Cdk4,6 plus PI3K inhibitors for CS1, lenalidomide/demethylating drugs for CS2, and EZH2 inhibitors for CS3. We developed an algorithm to identify the PCNSL subtypes using RNA-seq data from either FFPE or FF tissue. Conclusions: The integration of genome-wide data from multi-omics data revealed four molecular patterns in PCNSL with a distinctive prognostic impact that provides a basis for future clinical stratification and subtype-based targeted interventions.

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