Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models

The emergence and development of cancer is a consequence of the accumulation over time of genomic mutations involving a specific set of genes, which provides the cancer clones with a functional selective advantage. In this work, we model the order of accumulation of such mutations during the progression, which eventually leads to the disease, by means of probabilistic graphic models, i.e., Bayesian Networks (BNs). We investigate how to perform the task of learning the structure of such BNs, according to experimental evidence, adopting a global optimization meta-heuristics. In particular, in this work we rely on Genetic Algorithms, and to strongly reduce the execution time of the inference -- which can also involve multiple repetitions to collect statistically significant assessments of the data -- we distribute the calculations using both multi-threading and a multi-node architecture. The results show that our approach is characterized by good accuracy and specificity; we also demonstrate its feasibility, thanks to a 84x reduction of the overall execution time with respect to a traditional sequential implementation

Multi-objective optimization to explicitly account for model complexity when learning Bayesian Networks

Bayesian Networks have been widely used in the last decades in many fields, to describe statistical dependencies among random variables. In general, learning the structure of such models is a problem with considerable theoretical interest that still poses many challenges. On the one hand, this is a well-known NP-complete problem, which is practically hardened by the huge search space of possible solutions. On the other hand, the phenomenon of I-equivalence, i.e., different graphical structures underpinning the same set of statistical dependencies, may lead to multimodal fitness landscapes further hindering maximum likelihood approaches to solve the task. Despite all these difficulties, greedy search methods based on a likelihood score coupled with a regularization term to account for model complexity, have been shown to be surprisingly effective in practice. In this paper, we consider the formulation of the task of learning the structure of Bayesian Networks as an optimization problem based on a likelihood score. Nevertheless, our approach do not adjust this score by means of any of the complexity terms proposed in the literature; instead, it accounts directly for the complexity of the discovered solutions by exploiting a multi-objective optimization procedure. To this extent, we adopt NSGA-II and define the first objective function to be the likelihood of a solution and the second to be the number of selected arcs. We thoroughly analyze the behavior of our method on a wide set of simulated data, and we discuss the performance considering the goodness of the inferred solutions both in terms of their objective functions and with respect to the retrieved structure. Our results show that NSGA-II can converge to solutions characterized by better likelihood and less arcs than classic approaches, although paradoxically frequently characterized by a lower similarity to the target network

Sankey diagrams of woody biomass flows in the EU-28

Sankey diagrams of woody biomass flows in the European Union as a whole are now available for the years 2009 to 2015 on the European Commission’s Knowledge Centre for Bioeconomy web portal at: https://ec.europa.eu/knowledge4policy/publication/forestry-sankey. This technical brief provides definitions, data sources and methods applied to derive the estimates.JRC.D.1-Bio-econom

Task-oriented exercises improve disability of working patients with surgically-treated proximal humeral fractures. A randomized controlled trial with one-year follow-up

Background: General physiotherapy is a common means of rehabilitation after surgery for proximal humeral fracture (PHF). Better-targeted exercises seem worthy of investigation and the aim of this study was to assess the efficacy of a rehabilitation program including task-oriented exercises in improving disability, pain, and quality of life in patients after a PHF. Methods: By means of a randomized controlled trial with one-year follow-up, 70 working patients (mean age of 49 ± 11 years; 41 females), who were selected for open reduction and internal fixation with plates caused by PHF, were randomized to be included in an experimental (n = 35) or control group (n = 35). There was a permuted-block randomization plan, and a list of program codes was previously created; subsequently, an automatic assignment system was used to conceal the allocation. The first group underwent a supervised rehabilitation program of task-oriented exercises based on patients’ specific job activities, and occupational therapy. The second group underwent general physiotherapy, including supervised mobility, strengthening and stretching exercises. Both groups individually followed programs of 60-min session three times per week for 12 weeks in the outpatient setting. The Disability Arm Shoulder Hand questionnaire (DASH; scores range from 0 to 100; primary outcome), a Pain intensity Numerical Rating Scale (scores range 0 to 10; secondary outcomes), and the Short-Form Health Survey (scores range from 0 to 100; secondary outcomes) assessed the interventions. Participants were evaluated before surgery, before and after rehabilitation (primary endpoint), and at the one-year follow-up (secondary endpoint). A linear mixed model analysis for repeated measures was carried out for each outcome measure (p < 0.05). Results: Time, group and time by group showed significant effects for all outcome measures in favour of the experimental group. The DASH and the DASH work achieved clinically important between-group differences of 16.0 points (95% confidence interval [C.I.] 7.3 to 24.7) and 19.7 (95% C.I. 9.0 to 30.5) at follow-up, respectively. The NRS achieved a between-group difference of 2.9 (95% C.I. 1.0 to 3.9) at follow-up. As for SF-36, there were between-group differences ranging from 17.9 to 37.0 at follow-up. Conclusions: A rehabilitation program based on task-oriented exercises was useful in improving disability, pain, and quality of life in working patients after PHFs. Improvements lasted for at least 12 months. Trial registration: On 16/12/2019, the trial was retrospectively registered in the ISRCTN registry with the ID number 17996552

Aromatase inhibitors: the journey from the state of the art to clinical open questions

Breast cancer is a major cause of death among females. Great advances have been made in treating this disease, and aromatase inhibitors (AIs) have been recognized as the cornerstone. They are characterized by high efficacy and low toxicity. The authors reviewed the available literature and defined state-of-the-art AI management. This study was designed to assist clinicians in addressing the need to equally weigh patients’ needs and disease control rates in their everyday clinical practice. Today, AIs play a central role in the treatment of hormone receptor-positive breast cancer. In this study, an expert panel reviewed the literature on the use of AIs, discussing the evolution of their use in various aspects of breast cancer, from pre- and postmenopausal early breast cancer to metastatic breast cancer, along with their management regarding efficacy and toxicity. Given the brilliant results that have been achieved in improving survival in everyday clinical practice, clinicians need to address their concerns about therapy duration and the adverse effects they exert on bone health, the cardiovascular system, and metabolism. Currently, in addition to cancer treatment, patient engagement is crucial for improving adherence to therapy and supporting patients’ quality of life, especially in a selected subset of patients, such as those receiving an extended adjuvant or combination with targeted therapies. A description of modern technologies that contribute to this important goal is provided

gene expression profiling in breast cancer a clinical perspective

Gene expression profiling tests are used in an attempt to determine the right treatment for the right person with early-stage breast cancer that may have spread to nearby lymph nodes but not to distant parts of the body. These new diagnostic approaches are designed to spare people who do not need additional treatment (adjuvant therapy) the side effects of unnecessary treatment, and allow people who may benefit from adjuvant therapy to receive it. In the present review we discuss in detail the major diagnostic tests available such as MammaPrint dx, Oncotype dx, PAM50, Mammostrat, IHC4, MapQuant DX, Theros-Breast Cancer Gene Expression Ratio Assay, and their potential clinical applications

Abnormal B-Cell Maturation and Increased Transitional B Cells in CBL Syndrome

CBL syndrome is a Noonan-like RASopathy with heterogeneous clinical phenotype and predisposition to juvenile myelomonocytic leukemia (JMML). Here we describe two patients with identical germline CBL mutation and clinical and immune-hematological overlapping features with autoimmune lymphoproliferative syndrome (ALPS) and B-cell expansion with NF-κB and T-cell anergy (BENTA) syndrome. Increased immature/transitional B cells can be depicted in CBL syndrome, ALPS, and BENTA. Nonetheless, our patients here described showed peculiar B-cell phenotype due to increased immature/transitional CD34+ B cells. This feature differentiates CBL syndrome from BENTA, pointing toward an abnormal proliferation of B-cell early precursors

Absent B Cells, agammaglobulinemia, and Hypertrophic Cardiomyopathy in Folliculin-interacting Protein 1 Deficiency

Agammaglobulinemia is the most profound primary antibody deficiency that can occur due to an early termination of B-cell development. We here investigated 3 novel patients, including the first known adult, from unrelated families with agammaglobulinemia, recurrent infections, and hypertrophic cardiomyopathy (HCM). Two of them also presented with intermittent or severe chronic neutropenia. We identified homozygous or compound-heterozygous variants in the gene for folliculin interacting protein 1 (FNIP1), leading to loss of the FNIP1 protein. B-cell metabolism, including mitochondrial numbers and activity and phosphatidylinositol 3-kinase/AKT pathway, was impaired. These defects recapitulated the Fnip1-/- animal model. Moreover, we identified either uniparental disomy or copy-number variants (CNVs) in 2 patients, expanding the variant spectrum of this novel inborn error of immunity. The results indicate that FNIP1 deficiency can be caused by complex genetic mechanisms and support the clinical utility of exome sequencing and CNV analysis in patients with broad phenotypes, including agammaglobulinemia and HCM. FNIP1 deficiency is a novel inborn error of immunity characterized by early and severe B-cell development defect, agammaglobulinemia, variable neutropenia, and HCM. Our findings elucidate a functional and relevant role of FNIP1 in B-cell development and metabolism and potentially neutrophil activity

AKR1C enzymes sustain therapy resistance in paediatric T-ALL

BACKGROUND: Despite chemotherapy intensification, a subgroup of high-risk paediatric T-cell acute lymphoblastic leukemia (TALL) patients still experience treatment failure. In this context, we hypothesised that therapy resistance in T-ALL might involve aldo-keto reductase 1C (AKR1C) enzymes as previously reported for solid tumors.METHODS: Expression of NRF2-AKR1C signaling components has been analysed in paediatric T-ALL samples endowed with different treatment outcomes as well as in patient-derived xenografts of T-ALL. The effects of AKR1C enzyme modulation has been investigated in T-ALL cell lines and primary cultures by combining AKR1C inhibition, overexpression, and gene silencing approaches.RESULTS: We show that T-ALL cells overexpress AKR1C1-3 enzymes in therapy-resistant patients. We report that AKR1C1-3 enzymes play a role in the response to vincristine (VCR) treatment, also ex vivo in patient-derived xenografts. Moreover, we demonstrate that the modulation of AKR1C1-3 levels is sufficient to sensitise T-ALL cells to VCR. Finally, we show that T-ALL chemotherapeutics induce overactivation of AKR1C enzymes independent of therapy resistance, thus establishing a potential resistance loop during T-ALL combination treatment.CONCLUSIONS: Here, we demonstrate that expression and activity of AKR1C enzymes correlate with response to chemotherapeutics in T-ALL, posing AKR1C1-3 as potential targets for combination treatments during T-ALL therapy