SOM Analysis of 873 Malignant Lymphomas
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We present a transcriptome map of mature B-cell lymphomas that was obtained by analyzing expression data of 873 biopsy specimens including diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma (BL), mixed FL/DLBCL lymphomas, primary mediastinal large B-cell lymphoma (PMBL), multiple myeloma (MM), IRF4-rearranged large cell lymphoma, MYC-negative high-grade B-cell lymphomas with Chr. 11q aberration pattern (mnBLL-11q), and Mantle cell lymphoma (MCL) to describe their molecular heterogeneity and diverse regimes of biological dysfunctions by means of a holistic view on their expression landscape. It decomposes into one dozen modules of co-expressed genes related to the genetic defects and the pathogenesis of lymphomas and it is visualized on different levels of stratification down to ‘personalized’ transcriptomic portraits of single samples. We introduced the concept of combinatorial pattern types (PATs) of activated modules to stratify the lymphomas into nine PAT-types and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma-signatures as the most relevant transcriptional dimensions. Inflammation (and stromal) signatures in combination with healthy B-cell and tonsil signatures improves survival, while inflammation in combination with the proliferative signature worsens it. A phenotypic similarity tree is presented that reveals possible progression paths of lymphomas along their transcriptional dimensions. Our holistic approach uncovered transcriptomic subtypes of mature B-cell lymphomas based on a set of gene modules with distinct functional, genotypic and clinical characteristics and with potential impact as nosology scheme for mature B-cell lymphomas including all classes studied.

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Created: 20th May 2019 at 13:10

Last updated: 20th May 2019 at 13:10

Last used: 24th Jun 2019 at 23:55

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The Leipzig Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields.

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