Publications by authors named "Laura Zaragoza-Infante"

Subset #201 is a clinically indolent subgroup of patients with chronic lymphocytic leukemia defined by the expression of stereotyped, mutated IGHV4-34/IGLV1-44 BCR Ig. Subset #201 is characterized by recurrent somatic hypermutations (SHMs) that frequently lead to the creation and/or disruption of N-glycosylation sites within the Ig H and L chain variable domains. To understand the relevance of this observation, using next-generation sequencing, we studied how SHM shapes the subclonal architecture of the BCR Ig repertoire in subset #201, particularly focusing on changes in N-glycosylation sites.

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Classification of patients with chronic lymphocytic leukemia (CLL) based on the somatic hypermutation (SHM) status of the clonotypic immunoglobulin heavy variable (IGHV) gene has established predictive and prognostic relevance. The SHM status is assessed based on the number of mutations within the IG heavy variable domain sequence, albeit only over the rearranged IGHV gene excluding the variable heavy complementarity determining region 3 (VH CDR3). This may lead to an underestimation of the actual impact of SHM, in fact overlooking the most critical region for antigen-antibody interactions, i.

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Intraclonal diversification (ID) within the immunoglobulin (IG) genes expressed by B cell clones arises due to ongoing somatic hypermutation (SHM) in a context of continuous interactions with antigen(s). Defining the nature and order of appearance of SHMs in the IG genes can assist in improved understanding of the ID process, shedding light into the ontogeny and evolution of B cell clones in health and disease. Such endeavor is empowered thanks to the introduction of high-throughput sequencing in the study of IG gene repertoires.

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The study of antigen receptor gene repertoires using next-generation sequencing (NGS) technologies has disclosed an unprecedented depth of complexity, requiring novel computational and analytical solutions. Several bioinformatics workflows have been developed to this end, including the T-cell receptor/immunoglobulin profiler (TRIP), a web application implemented in R shiny, specifically designed for the purposes of comprehensive repertoire analysis, which is the focus of this chapter. TRIP has the potential to perform robust immunoprofiling analysis through the extraction and processing of the IMGT/HighV-Quest output, via a series of functions, ensuring the analysis of high-quality, biologically relevant data through a multilevel process of data filtering.

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A rapid and accurate diagnostic assay represents an important means to detect , identify drug-resistant strains and ensure treatment success. Currently employed techniques to diagnose drug-resistant tuberculosis include slow phenotypic tests or more rapid molecular assays that evaluate a limited range of drugs. Whole-genome-sequencing-based approaches can detect known drug-resistance-conferring mutations and novel variations; however, the dependence on growing samples in culture, and the associated delays in achieving results, represents a significant limitation.

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The term monoclonal B-cell lymphocytosis (MBL) describes the presence of a clonal B cell population with a count of less than 5 × 10/L and no symptoms or signs of disease. Based on the B cell count, MBL is further classified into 2 distinct subtypes: 'low-count' and 'high-count' MBL. High-count MBL shares a series of biological and clinical features with chronic lymphocytic leukemia (CLL), at least of the indolent type, and evolves to CLL requiring treatment at a rate of 1-2% per year, whereas 'low-count' MBL seems to be distinct, likely representing an immunological rather than a pre-malignant condition.

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The clonotypic B cell receptor immunoglobulin (BcR IG) plays a seminal role in B cell lymphoma development and evolution. From a clinical perspective, this view is supported by the remarkable therapeutic efficacy of BcR signaling inhibitors, even among heavily pre-treated, relapsed/refractory patients. This clinical development complements immunogenetic evidence for antigen drive in the natural history of these tumors.

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Cells respond to external stimuli with transient gene expression changes in order to adapt to environmental alterations. However, the dose response profile of gene induction upon a given stress depends on many intrinsic and extrinsic factors. Here we show that the accurate quantification of dose dependent gene expression by live cell luciferase reporters reveals fundamental insights into stress signaling.

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