ViCloD, an interactive web tool for visualizing B cell repertoires and analyzing intraclonal diversities: application to human B-cell tumors.

High throughput sequencing of adaptive immune receptor repertoire (AIRR-seq) has provided numerous human immunoglobulin (IG) sequences allowing specific B cell receptor (BCR) studies such as the antigen-driven evolution of antibodies (soluble forms of the membrane-bound IG part of the BCR). AIRR-seq data allows researchers to examine intraclonal differences caused primarily by somatic hypermutations in IG genes and affinity maturation. Exploring this essential adaptive immunity process could help elucidate the generation of antibodies with high affinity or broadly neutralizing activities. Retracing their evolutionary history could also clarify how vaccines or pathogen exposition drive the humoral immune response, and unravel the clonal architecture of B cell tumors. Computational methods are necessary for large-scale analysis of AIRR-seq properties. However, there is no efficient and interactive tool for analyzing intraclonal diversity, permitting users to explore adaptive immune receptor repertoires in biological and clinical applications. Here we present ViCloD, a web server for large-scale visual analysis of repertoire clonality and intraclonal diversity. ViCloD uses preprocessed data in the format defined by the Adaptive Immune Receptor Repertoire (AIRR) Community. Then, it performs clonal grouping and evolutionary analyses, producing a collection of useful plots for clonal lineage inspection. The web server presents diverse functionalities, including repertoire navigation, clonal abundance analysis, and intraclonal evolutionary tree reconstruction. Users can download the analyzed data in different table formats and save the generated plots as images. ViCloD is a simple, versatile, and user-friendly tool that can help researchers and clinicians to analyze B cell intraclonal diversity. Moreover, its pipeline is optimized to process hundreds of thousands of sequences within a few minutes, allowing an efficient investigation of large and complex repertoires.

Reconstructing B cell lineage trees with minimum spanning tree and genotype abundances.

B cell receptor (BCR) genes exposed to an antigen undergo somatic hypermutations and Darwinian antigen selection, generating a large BCR-antibody diversity. This process, known as B cell affinity maturation, increases antibody affinity, forming a specific B cell lineage that includes the unmutated ancestor and mutated variants. In a B cell lineage, cells with a higher antigen affinity will undergo clonal expansion, while those with a lower affinity will not proliferate and probably be eliminated. Therefore, cellular (genotype) abundance provides a valuable perspective on the ongoing evolutionary process. Phylogenetic tree inference is often used to reconstruct B cell lineage trees and represents the evolutionary dynamic of BCR affinity maturation. However, such methods should process B-cell population data derived from experimental sampling that might contain different cellular abundances. There are a few phylogenetic methods for tracing the evolutionary events occurring in B cell lineages; best-performing solutions are time-demanding and restricted to analysing a reduced number of sequences, while time-efficient methods do not consider cellular abundances. We propose ClonalTree, a low-complexity and accurate approach to construct B-cell lineage trees that incorporates genotype abundances into minimum spanning tree (MST) algorithms. Using both simulated and experimental data, we demonstrate that ClonalTree outperforms MST-based algorithms and achieves a comparable performance to a method that explores tree-generating space exhaustively. Furthermore, ClonalTree has a lower running time, being more convenient for building B-cell lineage trees from high-throughput BCR sequencing data, mainly in biomedical applications, where a lower computational time is appreciable. It is hundreds to thousands of times faster than exhaustive approaches, enabling the analysis of a large set of sequences within minutes or seconds and without loss of accuracy. The source code is freely available at github.com/julibinho/ClonalTree.

A multi-objective based clustering for inferring BCR clonal lineages from high-throughput B cell repertoire data.

The adaptive B cell response is driven by the expansion, somatic hypermutation, and selection of B cell clonal lineages. A high number of clonal lineages in a B cell population indicates a highly diverse repertoire, while clonal size distribution and sequence diversity reflect antigen selective pressure. Identifying clonal lineages is fundamental to many repertoire studies, including repertoire comparisons, clonal tracking, and statistical analysis. Several methods have been developed to group sequences from high-throughput B cell repertoire data. Current methods use clustering algorithms to group clonally-related sequences based on their similarities or distances. Such approaches create groups by optimizing a single objective that typically minimizes intra-clonal distances. However, optimizing several objective functions can be advantageous and boost the algorithm convergence rate. Here we propose MobiLLe, a new method based on multi-objective clustering. Our approach requires V(D)J annotations to obtain the initial groups and iteratively applies two objective functions that optimize cohesion and separation within clonal lineages simultaneously. We show that our method greatly improves clonal lineage grouping on simulated benchmarks with varied mutation rates compared to other tools. When applied to experimental repertoires generated from high-throughput sequencing, its clustering results are comparable to the most performing tools and can reproduce the results of previous publications. The method based on multi-objective clustering can accurately identify clonally-related antibody sequences and presents the lowest running time among state-of-art tools. All these features constitute an attractive option for repertoire analysis, particularly in the clinical context. MobiLLe can potentially help unravel the mechanisms involved in developing and evolving B cell malignancies.

Characterizing and exploiting the many roles of aberrant H2B monoubiquitination in cancer pathogenesis.

Monoubiquitination of histone H2B on lysine 120 (H2Bub1) is implicated in the control of multiple essential processes, including transcription, DNA damage repair and mitotic chromosome segregation. Accordingly, aberrant regulation of H2Bub1 can induce transcriptional reprogramming and genome instability that may promote oncogenesis. Remarkably, alterations of the ubiquitin ligases and deubiquitinating enzymes regulating H2Bub1 are emerging as ubiquitous features in cancer, further supporting the possibility that the misregulation of H2Bub1 is an underlying mechanism contributing to cancer pathogenesis. To date, aberrant H2Bub1 dynamics have been reported in multiple cancer types and are associated with transcriptional changes that promote oncogenesis in a cancer type-specific manner. Owing to the multi-functional nature of H2Bub1, misregulation of its writers and erasers may drive disease initiation and progression through additional synergistic processes. Accordingly, understanding the molecular determinants and pathogenic impacts associated with aberrant H2Bub1 regulation may reveal novel drug targets and therapeutic vulnerabilities that can be exploited to develop innovative precision medicine strategies that better combat cancer. In this review, we present the normal functions of H2Bub1 in the control of DNA-associated processes and describe the pathogenic implications associated with its misregulation in cancer. We further discuss the challenges coupled with the development of therapeutic strategies targeting H2Bub1 misregulation and expose the potential benefits of designing treatments that synergistically exploit the multiple functionalities of H2Bub1 to improve treatment selectivity and efficacy.

Employing Cross-Species Approaches to Construct Humanized Genetic Interaction Networks.

Characterizing genetic interactions in humans, including synthetic lethal interactions, can provide fundamental insight into protein functions and pathway interactions. However, it can also assist in the development of innovative therapeutic strategies by uncovering novel drug targets used to combat diseases like cancer. To expedite the discovery of novel synthetic lethal interactions in humans, cross-species candidate gene approaches rely on the evolutionary conservation of genetic interactions between organisms. Here, we provide a guide that couples bioinformatic approaches and publicly available datasets from model organisms with cross-species approaches to expedite the identification of candidate synthetic lethal interactions to test in humans. First, we detail a method to identify relevant genetic interactions in budding yeast and subsequently provide a prioritization scheme to identify the most promising yeast interactions to pursue. Finally, we provide details on the tools and approaches used to identify the corresponding human orthologs to ultimately generate a testable network of candidate human synthetic lethal interactions. In summary, this approach leverages publicly available resources and datasets to expedite the identification of conserved synthetic lethal interactions in humans.

Exploring Candidate Human Synthetic Lethal Interactions Through siRNA and Quantitative Imaging-Based Approaches.

Synthetic lethal interactions can assist in characterizing protein functions and cellular processes, but they can also be used to identify novel drug targets for the development of innovative cancer therapeutic strategies. Despite recent technological advancements including CRISPR/Cas9 approaches, the systematic assessment of all pairwise gene interactions in humans (~ 200 million pairs) remains an unmet goal. Thus, hypothesis-driven approaches, which prioritize subsets of promising candidate SL interactions for experimental assessment, are critical to expedite the identification of novel SL interactions. Here, we provide a guide to screen and validate focused libraries of promising candidate SL interactions, typically consisting of 50-500 targets. First, we describe two siRNA and image-based screening protocols to rapidly assess candidate SL interactions. Subsequently, we provide methods to validate a subset of the most promising interactions uncovered in the screens. These approaches employ commercially available reagents and standard laboratory equipment to facilitate and expedite the identification of bona fide human SL interactions.

Reduced USP22 Expression Impairs Mitotic Removal of H2B Monoubiquitination, Alters Chromatin Compaction and Induces Chromosome Instability That May Promote Oncogenesis.

Chromosome instability (CIN) is an enabling feature of oncogenesis associated with poor patient outcomes, whose genetic determinants remain largely unknown. As mitotic chromatin compaction defects can compromise the accuracy of chromosome segregation into daughter cells and drive CIN, characterizing the molecular mechanisms ensuring accurate chromatin compaction may identify novel CIN genes. In vitro, histone H2B monoubiquitination at lysine 120 (H2Bub1) impairs chromatin compaction, while in vivo H2Bub1 is rapidly depleted from chromatin upon entry into mitosis, suggesting that H2Bub1 removal may be a pre-requisite for mitotic fidelity. The deubiquitinating enzyme USP22 catalyzes H2Bub1 removal in interphase and may also be required for H2Bub1 removal in early mitosis to maintain chromosome stability. In this study, we demonstrate that siRNA-mediated USP22 depletion increases H2Bub1 levels in early mitosis and induces CIN phenotypes associated with mitotic chromatin compaction defects revealed by super-resolution microscopy. Moreover, USP22-knockout models exhibit continuously changing chromosome complements over time. These data identify mitotic removal of H2Bub1 as a critical determinant of chromatin compaction and faithful chromosome segregation. We further demonstrate that USP22 is a CIN gene, indicating that USP22 deletions, which are frequent in many tumor types, may drive genetic heterogeneity and contribute to cancer pathogenesis.

Reduced RBX1 expression induces chromosome instability and promotes cellular transformation in high-grade serous ovarian cancer precursor cells.

Despite high-grade serous ovarian cancer (HGSOC) being the most common and lethal gynecological cancer in women, the early etiological events driving disease development remain largely unknown. Emerging evidence now suggests that chromosome instability (CIN; ongoing changes in chromosome numbers) may play a central role in the development and progression of HGSOC. Importantly, genomic amplification of the Cyclin E1 gene (CCNE1) contributes to HGSOC pathogenesis in ~20% of patients, while Cyclin E1 overexpression induces CIN in model systems. Cyclin E1 levels are normally regulated by the SCF (SKP1-CUL1-FBOX) complex, an E3 ubiquitin ligase that includes RBX1 as a core component. Interestingly, RBX1 is heterozygously lost in ~80% of HGSOC cases and reduced expression corresponds with worse outcomes, suggesting it may be a pathogenic event. Using both short (siRNA) and long (CRISPR/Cas9) term approaches, we show that reduced RBX1 expression corresponds with significant increases in CIN phenotypes in fallopian tube secretory epithelial cells, a cellular precursor of HGSOC. Moreover, reduced RBX1 expression corresponds with increased Cyclin E1 levels and anchorage-independent growth. Collectively, these data identify RBX1 as a novel CIN gene with pathogenic implications for HGSOC.

Reduced Expression of Genes Regulating Cohesion Induces Chromosome Instability that May Promote Cancer and Impact Patient Outcomes.

Chromosome instability (CIN), or continual changes in chromosome complements, is an enabling feature of cancer; however, the molecular determinants of CIN remain largely unknown. Emerging data now suggest that aberrant sister chromatid cohesion may induce CIN and contribute to cancer. To explore this possibility, we employed clinical and fundamental approaches to systematically assess the impact reduced cohesion gene expression has on CIN and cancer. Ten genes encoding critical functions in cohesion were evaluated and remarkably, each exhibits copy number losses in 12 common cancer types, and reduced expression is associated with worse patient survival. To gain mechanistic insight, we combined siRNA-based silencing with single cell quantitative imaging microscopy to comprehensively assess the impact reduced expression has on CIN in two karyotypically stable cell lines. We show that reduced expression induces CIN phenotypes, namely increases in micronucleus formation and nuclear areas. Subsequent direct tests involving a subset of prioritized genes also revealed significant changes in chromosome numbers with corresponding increases in moderate and severe cohesion defects within mitotic chromosome spreads. Collectively, our clinical and fundamental findings implicate reduced sister chromatid cohesion, resulting from gene copy number losses, as a key pathogenic event in the development and progression of many cancer types.

Diminished Condensin Gene Expression Drives Chromosome Instability That May Contribute to Colorectal Cancer Pathogenesis.

Chromosome instability (CIN), or constantly evolving chromosome complements, is a form of genome instability implicated in the development and progression of many cancer types, however, the molecular determinants of CIN remain poorly understood. Condensin is a protein complex involved in chromosome compaction, and recent studies in model organisms show that aberrant compaction adversely impacts mitotic fidelity. To systematically assess the clinical and fundamental impacts that reduced condensin gene expression have in cancer, we first assessed gene copy number alterations of all eight condensin genes. Using patient derived datasets, we show that shallow/deep deletions occur frequently in 12 common cancer types. Furthermore, we show that reduced expression of each gene is associated with worse overall survival in colorectal cancer patients. To determine the overall impact that reduced condensin gene expression has on CIN, a comprehensive siRNA-based screen was performed in two karyotypically stable cell lines. Following gene silencing, quantitative imaging microscopy identified increases in CIN-associated phenotypes, including changes in nuclear areas, micronucleus formation, and chromosome numbers. Although silencing corresponded with increases in CIN phenotypes, the most pronounced phenotypes were observed following SMC2 and SMC4 silencing. Collectively, our clinical and fundamental findings suggest reduced condensin expression and function may be a significant, yet, underappreciated driver of colorectal cancer.

Developing Targeted Therapies That Exploit Aberrant Histone Ubiquitination in Cancer.

Histone ubiquitination is a critical epigenetic mechanism regulating DNA-driven processes such as gene transcription and DNA damage repair. Importantly, the cellular machinery regulating histone ubiquitination is frequently altered in cancers. Moreover, aberrant histone ubiquitination can drive oncogenesis by altering the expression of tumor suppressors and oncogenes, misregulating cellular differentiation and promoting cancer cell proliferation. Thus, targeting aberrant histone ubiquitination may be a viable strategy to reprogram transcription in cancer cells, in order to halt cellular proliferation and induce cell death, which is the basis for the ongoing development of therapies targeting histone ubiquitination. In this review, we present the normal functions of histone H2A and H2B ubiquitination and describe the role aberrant histone ubiquitination has in oncogenesis. We also describe the key benefits and challenges associated with current histone ubiquitination targeting strategies. As these strategies are predicted to have off-target effects, we discuss additional efforts aimed at developing synthetic lethal strategies and epigenome editing tools, which may prove pivotal in achieving effective and selective therapies targeting histone ubiquitination, and ultimately improving the lives and outcomes of those living with cancer.

Ubiquitin Specific Peptidase 22 Regulates Histone H2B Mono-Ubiquitination and Exhibits Both Oncogenic and Tumor Suppressor Roles in Cancer.

Ubiquitin-Specific Peptidase 22 (USP22) is a ubiquitin hydrolase, notably catalyzing the removal of the mono-ubiquitin moiety from histone H2B (H2Bub1). Frequent overexpression of USP22 has been observed in various cancer types and is associated with poor patient prognosis. Multiple mechanisms have been identified to explain how USP22 overexpression contributes to cancer progression, and thus, USP22 has been proposed as a novel drug target in cancer. However, gene re-sequencing data from numerous cancer types show that USP22 expression is frequently diminished, suggesting it may also harbor tumor suppressor-like properties. This review will examine the current state of knowledge on USP22 expression in cancers, describe its impact on H2Bub1 abundance and present the mechanisms through which altered USP22 expression may contribute to oncogenesis, including an emerging role for USP22 in the maintenance of genome stability in cancer. Clarifying the impact aberrant USP22 expression and abnormal H2Bub1 levels have in oncogenesis is critical before precision medicine therapies can be developed that either directly target USP22 overexpression or exploit the loss of USP22 expression in cancer cells.

Evolving Therapeutic Strategies to Exploit Chromosome Instability in Cancer.

Cancer is a devastating disease that claims over 8 million lives each year. Understanding the molecular etiology of the disease is critical to identify and develop new therapeutic strategies and targets. Chromosome instability (CIN) is an abnormal phenotype, characterized by progressive numerical and/or structural chromosomal changes, which is observed in virtually all cancer types. CIN generates intratumoral heterogeneity, drives cancer development, and promotes metastatic progression, and thus, it is associated with highly aggressive, drug-resistant tumors and poor patient prognosis. As CIN is observed in both primary and metastatic lesions, innovative strategies that exploit CIN may offer therapeutic benefits and better outcomes for cancer patients. Unfortunately, exploiting CIN remains a significant challenge, as the aberrant mechanisms driving CIN and their causative roles in cancer have yet to be fully elucidated. The development and utilization of CIN-exploiting therapies is further complicated by the associated risks for off-target effects and secondary cancers. Accordingly, this review will assess the strengths and limitations of current CIN-exploiting therapies, and discuss emerging strategies designed to overcome these challenges to improve outcomes and survival for patients diagnosed with cancer.