Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field

Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field.</p

Context-dependent T-cell Receptor Gene Repertoire Profiles in Proliferations of T Large Granular Lymphocytes

T cell large granular lymphocyte (T-LGL) lymphoproliferations constitute a disease spectrum ranging from poly/oligo to monoclonal. Boundaries within this spectrum of proliferations are not well established. T-LGL lymphoproliferations co-occur with a wide variety of other diseases ranging from autoimmune disorders, solid tumors, hematological malignancies, post solid organ, and hematopoietic stem cell transplantation, and can therefore arise as a consequence of a wide variety of antigenic triggers. Persistence of a dominant malignant T-LGL clone is established through continuous STAT3 activation. Using next-generation sequencing, we profiled a cohort of 27 well-established patients with T-LGL lymphoproliferations, aiming to identify the subclonal architecture of the T-cell receptor beta (TRB) chain gene repertoire. Moreover, we searched for associations between TRB gene repertoire patterns and clinical manifestations, with the ultimate objective of discriminating between T-LGL lymphoproliferations developing in different clinical contexts and/or displaying distinct clinical presentation. Altogether, our data demonstrates that the TRB gene repertoire of patients with T-LGL lymphoproliferations is context-dependent, displaying distinct clonal architectures in different settings. Our results also highlight that there are monoclonal T-LGL cells with or without STAT3 mutations that cause symptoms such as neutropenia on one end of a spectrum and reactive oligoclonal T-LGL lymphoproliferations on the other. Longitudinal analysis revealed temporal clonal dynamics and showed that T-LGL cells might arise as an epiphenomenon when co-occurring with other malignancies, possibly reactive toward tumor antigens.</p

IgIDivA : immunoglobulin intraclonal diversification analysis

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. However, few existing tools allow the identification, quantification and characterization of SHMs related to ID, all of which have limitations in their analysis, highlighting the need for developing a purpose-built tool for the comprehensive analysis of the ID process. In this work, we present the immunoglobulin intraclonal diversification analysis (IgIDivA) tool, a novel methodology for the in-depth qualitative and quantitative analysis of the ID process from high-throughput sequencing data. IgIDivA identifies and characterizes SHMs that occur within the variable domain of the rearranged IG genes and studies in detail the connections between identified SHMs, establishing mutational pathways. Moreover, it combines established and new graph-based metrics for the objective determination of ID level, combined with statistical analysis for the comparison of ID level features for different groups of samples. Of importance, IgIDivA also provides detailed visualizations of ID through the generation of purpose-built graph networks. Beyond the method design, IgIDivA has been also implemented as an R Shiny web application. IgIDivA is freely available at https://bio.tools/igidiv

Evidence of somatic hypermutation in the antigen binding sites of patients with CLL harboring IGHV genes with 100% germline identity

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.e. the VH CDR3. Here we investigated whether SHM may be present within the VH CDR3 of cases bearing ‘truly unmutated’ IGHV genes (i.e. 100% germline identity across VH FR1-VH FR3) employing Next Generation Sequencing. We studied 16 patients bearing a ‘truly unmutated’ CLL clone assigned to stereotyped subsets #1 (n=12) and #6 (n=4). We report the existence of SHM within the germline-encoded 3’IGHV, IGHD, 5’IGHJ regions of the VH CDR3 in both the main IGHV-IGHD-IGHJ gene clonotype and its variants. Recurrent somatic mutations were identified between different patients of the same subset, supporting the notion that they represent true mutational events rather than technical artefacts; moreover, they were located adjacent to/within AID hotspots, pointing to SHM as the underlying mechanism. In conclusion, we provide immunogenetic evidence for intra-VH CDR3 variations, attributed to SHM, in CLL patients carrying ‘truly unmutated’ IGHV genes. Although the clinical implications of this observation remain to be defined, our findings offer a new perspective into the immunobiology of CLL, alluding to the operation of VH CDR3-restricted SHM in U-CLL

Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks

There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype.- Pfizer Pharmaceuticals(undefined