In vitro hBM-MSCs characterization and differentiation on the scaffold for bone regenerative medicine

New methods have been developed to achieve tissue regeneration of complex bone defects and restore the healing process, which is impaired by several factors; in this contest bone tissue engineering (BTE) is an alternative to autologous gold-standard treatment. BTE combines biocompatible scaffolds with morphogenic signals and stem cells, to create a biomimetic microenvironment that provides mechanical and chemical cues. In this project, we studied all key elements of BTE and evaluated Mesenchymal stem cells (MSC) with xenograft-derived bone scaffold (SmartBone® SBN) and rhBMP-2 as growth factor. MSCs are an attractive source of stem cells because of their ability to undergo self-renewal, multi-lineage differentiation (including into osteoblast lineage) and paracrine actions. Here, we reported our experience in MSCs expansion protocols and proposed human Platelet-Rich Plasma (PRP) as a substitute for Fetal Bovine Serum (FBS) in media supplementation. After MSCs isolation from patients bone marrow, we expanded the cells in media supplemented with FBS or PRP, obtained from a venous blood sample of the same patients. Our final outcome indicated that PRP is a good cell culture supplement, since it did not impact MSCs marker expression and differentiation potential. In the second part of the project, we seeded hBM-MSC on xenograft-derived bone scaffold and cultured them in osteogenic and MSC expansion media to investigate the effects of the composition of support on cell metabolic activity and osteogenic differentiation. The scaffold retains biological properties and resembles the human bone structure. We demonstrated its biocompatibility supporting both BM-MSCs proliferation and differentiation. Moreover, new collagen deposition was revealed in both analyzed conditions, suggesting a good osteoconductivity of the scaffold. Finally, we aimed to modify the scaffold by the addition of rhBMP-2 to improve its osteogenic abilities and enhance new bone formation. Future experiments will assess the impact of BMP2 modification on cellular differentiation

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways.publishedVersio

AIRO Breast Cancer Group Best Clinical Practice 2022 Update

Introduction: Breast cancer is the most common tumor in women and represents the leading cause of cancer death. Radiation therapy plays a key-role in the treatment of all breast cancer stages. Therefore, the adoption of evidence-based treatments is warranted, to ensure equity of access and standardization of care in clinical practice.Method: This national document on the highest evidence-based available data was developed and endorsed by the Italian Association of Radiation and Clinical Oncology (AIRO) Breast Cancer Group.We analyzed literature data regarding breast radiation therapy, using the SIGN (Scottish Intercollegiate Guidelines Network) methodology (www.sign.ac.uk). Updated findings from the literature were examined, including the highest levels of evidence (meta-analyses, randomized trials, and international guidelines) with a significant impact on clinical practice. The document deals with the role of radiation therapy in the treatment of primary breast cancer, local relapse, and metastatic disease, with focus on diagnosis, staging, local and systemic therapies, and follow up. Information is given on indications, techniques, total doses, and fractionations.Results: An extensive literature review from 2013 to 2021 was performed. The work was organized according to a general index of different topics and most chapters included individual questions and, when possible, synoptic and summary tables. Indications for radiation therapy in breast cancer were examined and integrated with other oncological treatments. A total of 50 questions were analyzed and answered.Four large areas of interest were investigated: (1) general strategy (multidisciplinary approach, contraindications, preliminary assessments, staging and management of patients with electronic devices); (2) systemic therapy (primary, adjuvant, in metastatic setting); (3) clinical aspects (invasive, non-invasive and micro-invasive carcinoma; particular situations such as young and elderly patients, breast cancer in males and cancer during pregnancy; follow up with possible acute and late toxicities; loco-regional relapse and metastatic disease); (4) technical aspects (radiation after conservative surgery or mastectomy, indications for boost, lymph node radiotherapy and partial breast irradiation).Appendixes about tumor bed boost and breast and lymph nodes contouring were implemented, including a dedicated web application. The scientific work was reviewed and validated by an expert group of breast cancer key-opinion leaders.Conclusions: Optimal breast cancer management requires a multidisciplinary approach sharing therapeutic strategies with the other involved specialists and the patient, within a coordinated and dedicated clinical path. In recent years, the high-level quality radiation therapy has shown a significant impact on local control and survival of breast cancer patients. Therefore, it is necessary to offer and guarantee accurate treatments according to the best standards of evidence-based medicine

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

Role of prenatal magnetic resonance imaging in fetuses with isolated mild or moderate ventriculomegaly in the era of neurosonography: international multicenter study

Objectives To assess the role of fetal magnetic resonance imaging (MRI) in detecting associated anomalies in fetuses presenting with mild or moderate isolated ventriculomegaly (VM) undergoing multiplanar ultrasound evaluation of the fetal brain. Methods This was a multicenter, retrospective, cohort study involving 15 referral fetal medicine centers in Italy, the UK and Spain. Inclusion criteria were fetuses affected by isolated mild (ventricular atrial diameter, 10.0–11.9 mm) or moderate (ventricular atrial diameter, 12.0–14.9 mm) VM on ultrasound, defined as VM with normal karyotype and no other additional central nervous system (CNS) or extra‐CNS anomalies on ultrasound, undergoing detailed assessment of the fetal brain using a multiplanar approach as suggested by the International Society of Ultrasound in Obstetrics and Gynecology guidelines for the fetal neurosonogram, followed by fetal MRI. The primary outcome of the study was to report the incidence of additional CNS anomalies detected exclusively on prenatal MRI and missed on ultrasound, while the secondary aim was to estimate the incidence of additional anomalies detected exclusively after birth and missed on prenatal imaging (ultrasound and MRI). Subgroup analysis according to gestational age at MRI (< 24 vs ≥ 24 weeks), laterality of VM (unilateral vs bilateral) and severity of dilatation (mild vs moderate VM) were also performed. Results Five hundred and fifty‐six fetuses with a prenatal diagnosis of isolated mild or moderate VM on ultrasound were included in the analysis. Additional structural anomalies were detected on prenatal MRI and missed on ultrasound in 5.4% (95% CI, 3.8–7.6%) of cases. When considering the type of anomaly, supratentorial intracranial hemorrhage was detected on MRI in 26.7% of fetuses, while polymicrogyria and lissencephaly were detected in 20.0% and 13.3% of cases, respectively. Hypoplasia of the corpus callosum was detected on MRI in 6.7% of cases, while dysgenesis was detected in 3.3%. Fetuses with an associated anomaly detected only on MRI were more likely to have moderate than mild VM (60.0% vs 17.7%; P < 0.001), while there was no significant difference in the proportion of cases with bilateral VM between the two groups (P = 0.2). Logistic regression analysis showed that lower maternal body mass index (adjusted odds ratio (aOR), 0.85 (95% CI, 0.7–0.99); P = 0.030), the presence of moderate VM (aOR, 5.8 (95% CI, 2.6–13.4); P < 0.001) and gestational age at MRI ≥ 24 weeks (aOR, 4.1 (95% CI, 1.1–15.3); P = 0.038) were associated independently with the probability of detecting an associated anomaly on MRI. Associated anomalies were detected exclusively at birth and missed on prenatal imaging in 3.8% of cases. Conclusions The incidence of an associated fetal anomaly missed on ultrasound and detected only on fetal MRI in fetuses with isolated mild or moderate VM undergoing neurosonography is lower than that reported previously. The large majority of these anomalies are difficult to detect on ultrasound. The findings from this study support the practice of MRI assessment in every fetus with a prenatal diagnosis of VM, although parents can be reassured of the low risk of an associated anomaly when VM is isolated on neurosonography

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

A first update on mapping the human genetic architecture of COVID-19

peer reviewe