Background: One of the hallmarks of cancer is the disruption of gene expression patterns. Many molecular lesions contribute to this phenotype, and the importance of aberrant DNA methylation profiles ...is increasingly recognized. Much of the research effort in this area has examined proximal promoter regions and epigenetic alterations at other loci are not well characterized. Results: Using whole genome bisulfite sequencing to examine uncharted regions of the epigenome, we identify a type of far-reaching DNA methylation alteration in cancer cells of the distal regulatory sequences described as super-enhancers. Human tumors undergo a shift in super-enhancer DNA methylation profiles that is associated with the transcriptional silencing or the overactivation of the corresponding target genes. Intriguingly, we observe locally active fractions of super-enhancers detectable through hypomethylated regions that suggest spatial variability within the large enhancer clusters. Functionally, the DNA methylomes obtained suggest that transcription factors contribute to this local activity of super-enhancers and that trans-acting factors modulate DNA methylation profiles with impact on transforming processes during carcinogenesis. Conclusions: We develop an extensive catalogue of human DNA methylomes at base resolution to better understand the regulatory functions of DNA methylation beyond those of proximal promoter gene regions. CpG methylation status in normal cells points to locally active regulatory sites at super-enhancers, which are targeted by specific aberrant DNA methylation events in cancer, with putative effects on the expression of downstream genes.
Background: One of the hallmarks of cancer is the disruption of gene expression patterns. Many molecular lesions contribute to this phenotype, and the importance of aberrant DNA methylation profiles ...is increasingly recognized. Much of the research effort in this area has examined proximal promoter regions and epigenetic alterations at other loci are not well characterized. Results: Using whole genome bisulfite sequencing to examine uncharted regions of the epigenome, we identify a type of far-reaching DNA methylation alteration in cancer cells of the distal regulatory sequences described as super-enhancers. Human tumors undergo a shift in super-enhancer DNA methylation profiles that is associated with the transcriptional silencing or the overactivation of the corresponding target genes. Intriguingly, we observe locally active fractions of super-enhancers detectable through hypomethylated regions that suggest spatial variability within the large enhancer clusters. Functionally, the DNA methylomes obtained suggest that transcription factors contribute to this local activity of super-enhancers and that trans-acting factors modulate DNA methylation profiles with impact on transforming processes during carcinogenesis. Conclusions: We develop an extensive catalogue of human DNA methylomes at base resolution to better understand the regulatory functions of DNA methylation beyond those of proximal promoter gene regions. CpG methylation status in normal cells points to locally active regulatory sites at super-enhancers, which are targeted by specific aberrant DNA methylation events in cancer, with putative effects on the expression of downstream genes.
Abstract
Introduction: Clonal evolution drives cancer development due to the emergence and/or selection of proliferatively advantageous subclones. Its understanding may facilitate the design of ...anticipation-based management strategies. Richter transformation (RT) is a paradigmatic tumor evolution in which chronic lymphocytic leukemia (CLL), an indolent neoplasia of mature B-cells, transforms into a high-grade lymphoma, usually diffuse large B-cell lymphoma (DLBCL), conferring a dismal prognosis. The evolutionary trajectories of RT and its driving (epi)genomic mechanisms remain largely unknown.
Aims: To reconstruct the evolutionary history of RT and to reveal the molecular processes underlying this transformation.
Methods: We characterized the whole genome (WGS), epigenome (DNA methylation, H3K27ac, ATAC-seq), and transcriptome (RNA-seq), combined with single-cell DNA and RNA sequencing analyses, of 19 CLL patients developing RT before (n=3) or after treatment with chemoimmunotherapy (n=6) and targeted therapies (BCR or BCL2 inhibitors, n=10). We analyzed 54 longitudinal samples covering up to 19 years of disease course.
Results: Our WGS analyses uncovered that RT is characterized by a remarkable structural complexity. We also identified a novel treatment-independent RT-specific mutational process, which we named SBS-RT. The genetic driver landscape of RT is a compendium of alterations in genes involved in cell cycle, MYC, and NF-κB pathways, frequently targeted in single catastrophic events including chromothripsis and chromoplexy. The WGS-based phylogenic reconstruction and single-cell DNA/RNA-seq analyses identified a very early diversification of CLL leading to emergence of RT-cells carrying specific genetic drivers and transcriptomic profiles of RT already at CLL diagnosis. These small subclones were dormant for 6-19 years until rapid expansion associated with the clinical transformation. While the DNA methylome kept track of the cell of origin and proliferative history of RT cells, their chromatin configuration and transcriptional program converged into the overexpression of cell cycle regulators, Toll-like receptors, MYC, MTORC1, and OXPHOS related transcripts, as well as downregulation of BCR pathway. This phenotypic shift was related to de novo activation of key transcription factors. In vitro experiments confirmed that RT cells have a 4-fold higher oxygen consumption at routine respiration and electron transfer system capacity compared to CLL. The resistance of RT to BCR inhibition is consistent with its high OXPHOS and low BCR signaling, which mimics de novo DLBCL-OXPHOS insensitive to BCR inhibition. This OXPHOShigh-BCRlow transcriptional axis of RT can be exploited therapeutically.
Conclusions: These findings demonstrate the early seeding of subclones driving advanced stages of cancer evolution and uncover therapeutic targets for the, once expanded, lethal Richter transformation.
Citation Format: Ferran Nadeu, Romina Royo, Ramon Massoni-Badosa, Beatriz Garcia-Torre, Martí Duran-Ferrer, Kevin J. Dawson, Marta Kulis, Ander Diaz-Navarro, Neus Villamor, Juan L. Melero, Vicente Chapaprieta, Ana Dueso-Barroso, Julio Delgado, Riccardo Moia, Sara Ruiz-Gil, Domenica Marchese, Núria Verdaguer-Dot, Mónica Romo, Maria Rozman, Gerard Frigola, Alfredo Rivas-Delgado, Tycho Baumann, Miguel Alcoceba, Marcos González, Fina Climent, Pau Abrisqueta, Josep Castellví, Francesc Bosch, Marta Aymerich, Anna Enjuanes, Sílvia Ruiz-Gaspà, Armando López-Guillermo, Pedro Jares, Sílvia Beà, Dolors Colomer, Núria López-Bigas, Josep LlGelpí, David Torrents, Peter J. Campbell, Ivo Gut, Pablo M. Garcia-Roves, Davide Rossi, Gianluca Gaidano, Xose S. Puente, Holger Heyn, Francesco Maura, José I. Martín-Subero, Elías Campo. Early seeding of Richter transformation in chronic lymphocytic leukemia abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3795.
The continuously increasing size of biological sequence databases has motivated the development of analysis suites that, by means of parallelization, are capable of performing faster searches on such ...databases. However, many of these tools are not suitable for execution on mid-to-large scale parallel infrastructures such as computational Grids.
This paper shows how COMP Superscalar can be used to effectively parallelize on the Grid a sequence analysis program. In particular, we present a sequential version of the HMMER hmmpfam tool that, when run with COMP Superscalar, is decomposed into tasks and run on a set of distributed resources, not burdening the programmer with parallelization efforts.
Although performance is not a main objective of this work, we also present some test results where COMP Superscalar, using a new pre-scheduling technique, clearly outperforms a well-known parallelization of the hmmpfam algorithm.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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