Biology subjects

Bea, S.

Publications and source records attributed to Bea, S..

7 recordsLinked to original sources

bioRxiv2025

Establishment and Characterization of a CCND1-Rearranged Non-Mantle Cell Lymphoma Cell Line and Patient-Derived Xenograft Model

The pathobiology of aggressive B-cell lymphomas with CCND1 rearrangements, distinct from Mantle Cell Lymphoma (MCL), presents a significant clinical challenge. These lymphomas are often difficult to diagnose and demonstrate resistance to standard immunochemotherapy, underscoring the urgent need for a deeper understanding of their underlying biology to develop more effective treatments. A major impediment to progress has been the lack of robust preclinical models that accurately reflect the complex genomics and clinical behavior of this disease. Here we directly address this critical gap by reporting the establishment and in-depth characterization of the first patient-derived cell line and a corresponding systemic patient-derived xenograft (PDX) model of a CCND1-rearranged, non-MCL lymphoma with a rapidly fatal clinical course. Through a comprehensive multi-omics approach, we demonstrate that these novel in vitro and in vivo models faithfully recapitulate the primary tumors unique immunophenotype, its intricate genetic and transcriptional landscape, and its intrinsic resistance to conventional therapeutic agents.

cancer biology↗

bioRxiv2024

Translocations can drive expression changes of multiple genes in regulons covering entire chromosome arms

Translocations have largely been implicated in tumor development. However, beyond the consequences of aberrant gene expression near the breakpoint, their effects remain unexplored. In this work, we characterize the interplay between translocations, chromatin organization and gene expression using mantle cell lymphoma (MCL) as a model. We show that in vitro induced MCL-associated translocations can drive transcriptional changes at entire chromosome arms affecting multiple genes in a regulon-like fashion. Additionally, overexpressed genes in MCL patients are enriched in the exact same genomic regions, further underlining its potential relevance for lymphomagenesis. Moreover, we demonstrate a clear link between the translocation-induced transcriptional alterations and genome organization, with genes most susceptible to change expression residing in pre-existing long-range interacting loops spanning 50 megabases. The translocation places the strong immunoglobulin enhancer into this loop, allowing the spread of its regulatory potential over the entire affected chromosome arm. Finally, we show that translocation-induced effects mainly represent expression enhancement of genes already active prior to translocation formation, highlighting the importance of the epigenetic state of the cell in which this initial hit occurs. In summary, we show that translocations can induce ample, simultaneous gene expression changes affecting entire chromosome arms, representing an important new mechanism for tumorigenesis.

cancer biology↗

bioRxiv2022

RFcaller: a machine learning approach combined with read-level features to detect somatic mutations

MotivationThe cost reduction in sequencing and the extensive genomic characterization of a wide variety of cancers is expanding the use of tumor sequencing approaches to a wide number of research groups and to the clinical practice. Although specific pipelines have been generated for the identification of somatic mutations, their results usually differ considerably, and a common approach in many projects is to use several callers to achieve a more reliable set of mutations. This procedure is computationally very expensive and time-consuming, and it suffers from the same limitations in sensitivity and specificity as other approaches. Expert revision of mutant calls is therefore required to verify calls that might be used for clinical diagnosis. Machine learning techniques provide a useful approach to incorporate expert-reviewed information for the identification of somatic mutations. ResultsWe have developed RFcaller, a pipeline based on machine learning algorithms, for the detection of somatic mutations in tumor-normal paired samples. RFcaller shows high accuracy for the detection of substitutions and indels from whole genome or exome data. It allows the detection of mutations in driver genes missed by other approaches, and has been validated by comparison to deep sequencing and Sanger sequencing. The pipeline is able to analyze a whole genome in a small period of time, and with a small computational footprint. Availability and implementationRFcaller is available at GitHub repository (https://github.com/xa-lab/RFcaller) and DockerHub (https://hub.docker.com/repository/docker/labxa/rfcaller). Contactxspuente@uniovi.es Supplementary informationSupplementary data is available online.

cancer biology↗

bioRxiv2021

Targeted Reactivation of X-linked Endogenous FOXP3 Gene from X-chromosome Inactivation in Human Female Breast Cancer Cells

Unlike autosomal tumor suppressors, which must be inactivated by a two-hit Knudson mechanism, X-linked tumor suppressors can be inactivated by a single hit due to X-chromosome inactivation (XCI). Here, we argue that targeted reactivation of the non-mutated allele from XCI offers a potential therapy for female breast cancers. Towards this goal, we developed a dual CRISPR interference and activation (CRISPRi/a) approach for simultaneously silencing and reactivating multiple X-linked genes using two orthogonal, nuclease-deficient CRISPR/Cas9 (dCas9) proteins. We verified the efficacy for use of Streptococcus pyogenes (Sp) dCas9-KRAB for silencing XIST and Staphylococcus aureus (Sa) dCas9-VPR for activating FOXP3 in various cell lines of human female breast cancers. We confirmed CRISPR reactivation of the non-mutated copy of FOXP3 from XCI in human breast cancer CRL2316 cells, which express a synonymous heterozygous mutation (p.L266L; c.798G>C) in the coding region of FOXP3. Further, simultaneous silencing of XIST from XCI led to enhanced and prolonged FOXP3 reactivation. We optimized CRISPRa by fusing SadCas9 to the demethylase TET1 and observed enhanced FOXP3 activation. Analysis of the conserved CpG-rich region of FOXP3 intron 1 confirmed that CRISPRi/a-mediated simultaneous FOXP3 activation and XIST silencing were accompanied by elevated H4 acetylation, including H4K5ac, H4K8ac, and H4K16ac, and H3K4me3 and lower DNA methylation. This indicates that CRISPRi/a targeting to XIST and FOXP3 loci alters their transcription and their nearby epigenetic modifications. The simultaneous activation and repression of the X-linked, endogenous FOXP3 and XIST from XCI offers a useful research tool and a potential therapeutic for female breast cancers. This approach also provides new routes of targeted therapy for other X-chromosome-linked genetic disorders.

cancer biology↗

bioRxiv2020

SAMHD1 mutations in mantle cell lymphoma: identification as disease driver conferring in vitro resistance to nucleoside analogues

The genomic landscape of mantle cell lymphoma (MCL) includes frequent alterations of TP53, ATM, CCND1 and KMT2D. Thus far, the mutational landscape provides little information for treatment stratification. We characterized a cohort of MCL by targeted next generation sequencing and discovered SAMHD1 as a novel recurrently mutated gene (8.5% of investigated cases, 4/47 samples). Furthermore, we provide evidence of in vitro resistance of SAMHD1 mutated patient-derived MCL cells to cytarabine and fludarabine.

cancer biology↗

bioRxiv2020

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome

We report a systematic analysis of the biological and clinical implications of DNA methylation variability in five categories of B-cell tumors derived from B cells spanning the entire maturation spectrum. We used 2056 primary samples including training and validation series and show that 88% of the human DNA methylome is dynamically modulated under normal and neoplastic conditions. B-cell tumors display both epigenetic imprints of their cellular origin and de novo, disease-specific epigenetic alterations that in part are related to differential transcription factor binding. These differential methylation patterns were used by a machine-learning approach to create a diagnostic algorithm that accurately classifies 14 B-cell tumor entities and subtypes with different clinical management. Beyond this, we identified extensive patient-specific epigenetic variability targeting constitutively silenced chromatin regions, a phenomenon we could relate to the proliferative history of normal and neoplastic B cells. We observed that, depending on the maturation stage of the tumor cell of origin, mitotic activity leaves different imprints into the DNA methylome. Subsequently, we constructed a novel DNA methylation-based mitotic clock called epiCMIT (epigenetically-determined Cumulative MIToses), whose lapse magnitude represents a strong independent prognostic variable within specific B-cell tumor subtypes and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracker of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of the outcome of the patients.

cancer biology↗

bioRxiv2019

Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation

Despite recent advances, the dynamics of genome architecture and chromatin function during human cell differentiation and its potential reorganization upon neoplastic transformation remains poorly characterized. Here, we integrate in situ Hi-C and nine additional omic layers to define and biologically characterize the dynamic changes in three-dimensional (3D) genome architecture across normal B cell differentiation and in neoplastic cells from different subtypes of chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL) patients. Beyond conventional active (A) and inactive (B) compartments, an integrative analysis of Hi-C data reveals the presence of a highly-dynamic intermediate compartment enriched in poised and polycomb-repressed chromatin. During B cell development, we detect that 28% of the compartments change at defined maturation stages and mostly involve the intermediate compartment. The transition from naive to germinal center B cells is associated with widespread chromatin activation, which mostly reverts into the naive state upon further maturation of germinal center cells into memory B cells. The analysis of CLL and MCL neoplastic cells points both to entity and subtype-specific alterations in chromosome organization. Remarkably, we observe that large chromatin blocks containing key disease-specific genes alter their 3D genome organization. These include the inactivation of a 2Mb region containing the EBF1 gene in CLL and the activation of a 6.1Mb region containing the SOX11 gene in clinically aggressive MCL. This study indicates that 3D genome interactions are extensively modulated during normal B cell differentiation and that the genome of B cell neoplasias acquires a tumor-specific 3D genome architecture.

genomics↗