Biology subjects

Campo, E.

Publications and source records attributed to Campo, E..

11 recordsLinked to original sources

bioRxiv2025

A transcriptional map of human tonsil architecture:beyond the sum of (single cell) parts

The tonsil is a highly compartmentalized organ in which different microanatomical structures orchestrate designated (immune) functions. We use this already well-studied tissue to survey spatial molecular imaging data (CosMx SMI) for studying immune responses in native tissue context; and, to demonstrate the advantages of SMI for faithfully recapitulating cellular composition in direct comparison with single-cell RNA sequencing. While SMI data still poses many analytical challenges and lacks standardization, we established a versatile analysis pipeline focused on the profitable particularities of these data: considering organization (microenvironment), interactions (signaling), and function (higher-order structures) across scales. Specifically, we resolve ~ 2M cells into 52 subpopulations across immune and, in particular, structural compartments. Various spatial niches partition tonsillar tissue into architecturally and functionally distinct regions, which we characterize through cell-cell colocalization and communication analyses, while performing various non-standard analyses at the level of spatial features. These topological readouts may help elucidate where certain immunological processes occur (e.g., class switch recombination); and, where signaling pathways are active (e.g., TNF and galectin, which have been implicated in diverse lymphomas). In all, we provide an analytical framework for Spatial Immunology, and showcase alternative views that such techniques and concomitant computational approaches can bring on tissue composition and architecture.

immunology↗

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↗

bioRxiv2022

T cell landscape definition by multi-omics identifies Galectin-9 as novel immunotherapy target in chronic lymphocytic leukemia

Failure of cancer immunotherapy is linked to T cell exhaustion. To decipher the underlying mechanisms, we explored the T cell landscape in blood, bone marrow and lymph node samples of patients with chronic lymphocytic leukemia (CLL), and spleen samples of a CLL mouse model. By single-cell RNA-sequencing, mass cytometry (CyTOF), and multiplex image analysis of tissue microarrays, we identified a disease-specific accumulation of distinct regulatory T cell subsets and T cell exhaustion stages and their trajectories in CLL lymph nodes. Integration of T cell receptor sequencing data revealed a clonal expansion of CD8+ precursor exhausted T cells (TPEX), suggesting their CLL reactivity. Interactome analyses identified the TIM3 ligand Galectin-9 as a novel immunoregulatory molecule in CLL. Blocking of Galectin-9 in CLL-bearing mice slowed down disease development and reduced the number of TIM3-expressing T cells. Galectin-9 expression correlated with shorter survival of patients with CLL, renal cell carcinoma or glioma. Statement of significanceOur findings for the first time define the T cell landscape in CLL lymph nodes and reshape the current understanding of T cell exhaustion in this malignancy. They further introduce Galectin-9 as novel immune checkpoint with a high potential to overcome resistance to PD1 targeting drugs in CLL and beyond.

cancer biology↗

bioRxiv2022

An Atlas of Cells in the Human Tonsil

Palatine tonsils are secondary lymphoid organs representing the first line of immunological defense against inhaled or ingested pathogens. Here, we present a comprehensive census of cell types forming the human tonsil by applying single-cell transcriptome, epigenome, proteome and adaptive immune repertoire sequencing as well as spatial transcriptomics, resulting in an atlas of >357,000 cells. We provide a glossary of 121 annotated cell types and states, and disentangle gene regulatory mechanisms that drive cells through specialized lineage trajectories. Exemplarily, we stratify multiple tonsil-resident myeloid slancyte subtypes, establish a distant BCL6 superenhancer as locally active in both follicle-associated T and B cells, and describe SIX5 as a potentially novel transcriptional regulator of plasma cell maturation. Further, our atlas is a reference map to understand alterations observed in disease. Here, we discover immune-phenotype plasticity in tumoral cells and microenvironment shifts of mantle cell lymphomas (MCL). To facilitate such reference-based analysis, we develop HCATonsilData and SLOcatoR, a computational framework that provides programmatic and modular access to our dataset; and allows the straightforward annotation of future single-cell profiles from secondary lymphoid organs.

immunology↗

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↗

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↗

bioRxiv2020

Sampling artifacts in single-cell genomics cohort studies

Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention.

genomics↗

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↗

bioRxiv2019

Chromatin activation as a unifying principle underlying pathogenic mechanisms in multiple myeloma

Multiple myeloma (MM) is a plasma cell neoplasm associated with a broad variety of genetic lesions. In spite of this genetic heterogeneity, MMs share a characteristic malignant phenotype whose underlying molecular basis remains poorly characterized. In the present study, we examined plasma cells from MM using a multi-epigenomics approach and demonstrated that when compared to normal B cells, malignant plasma cells showed an extensive activation of regulatory elements, in part affecting co-regulated adjacent genes. Among target genes upregulated by this process, we found members of the NOTCH, NFkB, mTOR1 signaling and p53 signaling pathways. Other activated genes included sets involved in osteoblast differentiation and response to oxidative stress, all of which have been shown to be associated with the MM phenotype and clinical behavior. We functionally characterized MM specific active distant enhancers controlling the expression of thioredoxin (TXN), a major regulator of cellular redox status, and in addition identified PRDM5 as a novel essential gene for MM. Collectively our data indicates that aberrant chromatin activation is a unifying feature underlying the malignant plasma cell phenotype.

cancer biology↗

bioRxiv2019

Differential genomic and transcriptomic events associated with high-grade transformation of Chronic Lymphocytic Leukemia

The transformation of chronic lymphocytic leukemia (CLL) to high-grade diffuse large B-cell lymphoma (DLBCL), also called Richters Syndrome (RS), is a rare cancer with dismal prognosis. Drug discovery for RS is hampered by the lack of suitable experimental models, and effective therapies remain elusive rendering RS an area of high unmet clinical need. We performed whole genome sequencing (WGS) to interrogate paired CLL and RS samples from 17 patients enrolled in a prospective multicenter Phase 2 clinical trial (CHOP-OR) and we found that subclones affected by mutations in MAPK and PI3K pathways show a high expansion probability during transformation. We also demonstrate for the first time that non-coding mutation clusters in a PAX5 enhancer, situated 330kb upstream from the transcription initiation site, correlate with transformation. Finally, we confirm our findings by employing targeted DNA sequencing (TGS) and RNA expression profiling on an extended cohort of 38 patients.\n\nStatement of significanceThrough integrated analysis of WGS, TGS and RNA expression data, we identified drivers of transformation not previously implicated in RS, which can be targeted therapeutically and tested in the clinic. Our results have informed the design of a new clinical platform study, which is now open to recruitment in the UK.

genomics↗