Computational Analysis of Cytokine Release Following Bispecific T-Cell Engager Therapy: Applications of a Logic-Based Model.

Bispecific T-cell engaging therapies harness the immune system to elicit an effective anticancer response. Modulating the immune activation avoiding potential adverse effects such as cytokine release syndrome (CRS) is a critical aspect to realizing the full potential of this therapy. The use of suitable exogenous intervention strategies to mitigate the CRS risk without compromising the antitumoral capability of bispecific antibody treatment is crucial. To this end, computational approaches can be instrumental to systematically exploring the effects of combining bispecific antibodies with CRS intervention strategies. Here, we employ a logical model to describe the action of bispecific antibodies and the complex interplay of various immune system components and use it to perform simulation experiments to improve the understanding of the factors affecting CRS. We performed a sensitivity analysis to identify the comedications that could ameliorate CRS without impairing tumor clearance. Our results agree with publicly available experimental data suggesting anti-TNF and anti-IL6 as possible co-treatments. Furthermore, we suggest anti-IFNγ as a suitable candidate for clinical studies.

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms.

RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testing has provided some key insights on how RNA vaccines interact with the innate immune system, their mechanism of action appears to be fragmented amid the literature, making it difficult to formulate new hypotheses to be tested in clinical settings and ultimately improve this technology platform. Here, we propose a systems biology approach, based on the combination of literature mining and mechanistic graphical modeling, to consolidate existing knowledge around mRNA vaccines mode of action and enhance the translatability of preclinical hypotheses into clinical evidence. A Natural Language Processing (NLP) pipeline for automated knowledge extraction retrieved key biological evidences that were joined into an interactive mechanistic graphical model representing the chain of immune events induced by mRNA vaccines administration. The achieved mechanistic graphical model will help the design of future experiments, foster the generation of new hypotheses and set the basis for the development of mathematical models capable of simulating and predicting the immune response to mRNA vaccines.

A QSP model of prostate cancer immunotherapy to identify effective combination therapies.

Immunotherapy, by enhancing the endogenous anti-tumor immune responses, is showing promising results for the treatment of numerous cancers refractory to conventional therapies. However, its effectiveness for advanced castration-resistant prostate cancer remains unsatisfactory and new therapeutic strategies need to be developed. To this end, systems pharmacology modeling provides a quantitative framework to test in silico the efficacy of new treatments and combination therapies. In this paper we present a new Quantitative Systems Pharmacology (QSP) model of prostate cancer immunotherapy, calibrated using data from pre-clinical experiments in prostate cancer mouse models. We developed the model by using Ordinary Differential Equations (ODEs) describing the tumor, key components of the immune system, and seven treatments. Numerous combination therapies were evaluated considering both the degree of tumor inhibition and the predicted synergistic effects, integrated into a decision tree. Our simulations predicted cancer vaccine combined with immune checkpoint blockade as the most effective dual-drug combination immunotherapy for subjects treated with androgen-deprivation therapy that developed resistance. Overall, the model presented here serves as a computational framework to support drug development, by generating hypotheses that can be tested experimentally in pre-clinical models.

A network-based approach to identify deregulated pathways and drug effects in metabolic syndrome.

Metabolic syndrome is a pathological condition characterized by obesity, hyperglycemia, hypertension, elevated levels of triglycerides and low levels of high-density lipoprotein cholesterol that increase cardiovascular disease risk and type 2 diabetes. Although numerous predisposing genetic risk factors have been identified, the biological mechanisms underlying this complex phenotype are not fully elucidated. Here we introduce a systems biology approach based on network analysis to investigate deregulated biological processes and subsequently identify drug repurposing candidates. A proximity score describing the interaction between drugs and pathways is defined by combining topological and functional similarities. The results of this computational framework highlight a prominent role of the immune system in metabolic syndrome and suggest a potential use of the BTK inhibitor ibrutinib as a novel pharmacological treatment. An experimental validation using a high fat diet-induced obesity model in zebrafish larvae shows the effectiveness of ibrutinib in lowering the inflammatory load due to macrophage accumulation.

Small supernumerary marker chromosomes: A legacy of trisomy rescue?

We studied by a whole genomic approach and trios genotyping, 12 de novo, nonrecurrent small supernumerary marker chromosomes (sSMC), detected as mosaics during pre- or postnatal diagnosis and associated with increased maternal age. Four sSMCs contained pericentromeric portions only, whereas eight had additional non-contiguous portions of the same chromosome, assembled together in a disordered fashion by repair-based mechanisms in a chromothriptic event. Maternal hetero/isodisomy was detected with a paternal origin of the sSMC in some cases, whereas in others two maternal alleles in the sSMC region and biparental haplotypes of the homologs were detected. In other cases, the homologs were biparental while the sSMC had the same haplotype of the maternally inherited chromosome. These findings strongly suggest that most sSMCs are the result of a multiple-step mechanism, initiated by maternal meiotic nondisjunction followed by postzygotic anaphase lagging of the supernumerary chromosome and its subsequent chromothripsis.

Dynamics of genetically engineered hematopoietic stem and progenitor cells after autologous transplantation in humans.

Hematopoietic stem and progenitor cells (HSPC) are endowed with the role of generating and maintaining lifelong the extremely diverse pool of blood cells1. Clinically, transplantation of human HSPC from an allogeneic healthy donor or infusion of autologous gene-corrected HSPC can effectively replenish defective blood cell production caused by congenital or acquired disorders2-9. However, due to methodological and ethical constraints that have limited the study of human HSPC primarily to in vitro assays10 or xenotransplantation models11,12, the in vivo activity of HSPC has to date remained relatively unexplored in humans13-16. Here we report a comprehensive study of the frequencies, dynamics and output of seven HSPC subtypes in humans that was performed by tracking 148,093 individual clones in six patients treated with lentiviral gene therapy using autologous HSPC transplantation and followed for up to 5 years. We discovered that primitive multipotent progenitor and hematopoietic stem cell (HSC) populations have distinct roles during the initial reconstitution after transplant, compared with subsequent steady-state phases. Furthermore, we showed that a fraction of in vitro-activated HSC are resilient and undergo a defined delayed activation period upon transplant. Finally, our data support the concept that early lymphoid-biased progenitors might be capable of long-term survival, such that they can be maintained independently of their continuous production from HSC. Overall, this study provides comprehensive data on HSPC dynamics after autologous transplantation and gene therapy in humans.

Preclinical Efficacy and Safety Evaluation of Hematopoietic Stem Cell Gene Therapy in a Mouse Model of MNGIE.

Mitochondrial neurogastrointestinal encephalomyopathy (MNGIE) is an autosomal recessive disorder caused by thymidine phosphorylase (TP) deficiency resulting in systemic accumulation of thymidine (d-Thd) and deoxyuridine (d-Urd) and characterized by early-onset neurological and gastrointestinal symptoms. Long-term effective and safe treatment is not available. Allogeneic bone marrow transplantation may improve clinical manifestations but carries disease and transplant-related risks. In this study, lentiviral vector-based hematopoietic stem cell gene therapy (HSCGT) was performed in Tymp-/-Upp1-/- mice with the human phosphoglycerate kinase (PGK) promoter driving TYMP. Supranormal blood TP activity reduced intestinal nucleoside levels significantly at low vector copy number (median, 1.3; range, 0.2-3.6). Furthermore, we covered two major issues not addressed before. First, we demonstrate aberrant morphology of brain astrocytes in areas of spongy degeneration, which was reversed by HSCGT. Second, long-term follow-up and vector integration site analysis were performed to assess safety of the therapeutic LV vectors in depth. This report confirms and supplements previous work on the efficacy of HSCGT in reducing the toxic metabolites in Tymp-/-Upp1-/- mice, using a clinically applicable gene transfer vector and a highly efficient gene transfer method, and importantly demonstrates phenotypic correction with a favorable risk profile, warranting further development toward clinical implementation.

In Vivo Tracking of Human Hematopoiesis Reveals Patterns of Clonal Dynamics during Early and Steady-State Reconstitution Phases.

Hematopoietic stem/progenitor cells (HSPCs) are capable of supporting the lifelong production of blood cells exerting a wide spectrum of functions. Lentiviral vector HSPC gene therapy generates a human hematopoietic system stably marked at the clonal level by vector integration sites (ISs). Using IS analysis, we longitudinally tracked >89,000 clones from 15 distinct bone marrow and peripheral blood lineages purified up to 4 years after transplant in four Wiskott-Aldrich syndrome patients treated with HSPC gene therapy. We measured at the clonal level repopulating waves, populations' sizes and dynamics, activity of distinct HSPC subtypes, contribution of various progenitor classes during the early and late post-transplant phases, and hierarchical relationships among lineages. We discovered that in-vitro-manipulated HSPCs retain the ability to return to latency after transplant and can be physiologically reactivated, sustaining a stable hematopoietic output. This study constitutes in vivo comprehensive tracking in humans of hematopoietic clonal dynamics during the early and late post-transplant phases.

Current Approaches and Future Perspectives for In Vivo Clonal Tracking of Hematopoietic Cells.

Over the past years, clonal tracking has gained the center stage as a unique technology capable to unveil population dynamics and hierarchical relationships in vivo. We here highlighted the main open questions related to the in vivo clonal behavior of hematopoietic cells with a particular focus on hematopoietic stem and progenitor cells and T cells as main targets of cell- and gene-therapies. We walked through the current methods applied for tracing in vivo dynamics and functions of hematopoietic cells in animal models and we described the results of early studies conducted on humans. We specifically focused our attention on the recent use of retroviral/lentiviral vector Integration Site (IS) analyses to follow stably marked clones and their progeny in vivo. We showed how this molecular tracking method can be successfully employed in human studies to unveil the clonal behavior of hematopoietic cells, describing pioneering works conducted on samples from gene therapy treated patients. Clonal tracking through IS identification still comes with a complex wet-experimental protocol and technical/analytical constraints. In this regard, we reviewed the features of the available computational tools for the identification and quantification of ISs and we highlighted the potential future improvements of IS-based tracking, as this technology is becoming a major source of information on in vivo fate and survival of engineered cells in humans.

Pinot blanc and Pinot gris arose as independent somatic mutations of Pinot noir.

Somatic mutation is a natural mechanism which allows plant growers to develop new cultivars. As a source of variation within a uniform genetic background, it also represents an ideal tool for studying the genetic make-up of important traits and for establishing gene functions. Layer-specific molecular characterization of the Pinot family of grape cultivars was conducted to provide an evolutionary explanation for the somatic mutations that have affected the locus of berry colour. Through the study of the structural dynamics along chromosome 2, a very large deletion present in a single Pinot gris cell layer was identified and characterized. This mutation reveals that Pinot gris and Pinot blanc arose independently from the ancestral Pinot noir, suggesting a novel parallel evolutionary model. This proposed 'Pinot-model' represents a breakthrough towards the full understanding of the mechanisms behind the formation of white, grey, red, and pink grape cultivars, and eventually of their specific enological aptitude.