Decellularized homograft for aortic valve replacement two years after lung transplantation

Cardiac valvular surgery in patients after lung transplantation is a challenging procedure, reports are scarce. We report a 29-year-old patient who underwent concomitant mitral valve reconstruction and implantation of a decellularized aortic homograft two years after bilateral lung transplantation.Cardiac valvular surgery in patients after lung transplantation is a challenging procedure, reports are scarce. We report a 29-year-old patient who underwent concomitant mitral valve reconstruction and implantation of a decellularized aortic homograft two years after bilateral lung transplantation

Glioma Associated Stem Cells (GASCs) Isolation and Culture.

Glioma Associated Stem Cells (GASCs) represent a population of nontumorigenic multipotent stem cells hosted in the microenvironment of human gliomas. In vitro, these cells are able, through the release of exosomes, to increase the biological aggressiveness of glioma-initiating cells. The clinical importance of this finding is supported by the strong prognostic value associated with the GASCs surface immunophenotype thus suggesting that this patient-based approach can provide a groundbreaking method to predict prognosis and to exploit novel strategies that target the tumor strom

Exploring Deep Cervical Compartments in Head and Neck Surgical Oncology through Augmented Reality Vision: A Proof of Concept

Background: Virtual surgical planning allows surgeons to meticulously define surgical procedures by creating a digital replica of patients’ anatomy. This enables precise preoperative assessment, facilitating the selection of optimal surgical approaches and the customization of treatment plans. In neck surgery, virtual planning has been significantly underreported compared to craniofacial surgery, due to a multitude of factors, including the predominance of soft tissues, the unavailability of intraoperative navigation and the complexity of segmenting such areas. Augmented reality represents the most innovative approach to translate virtual planning for real patients, as it merges the digital world with the surgical field in real time. Surgeons can access patient-specific data directly within their field of view, through dedicated visors. In head and neck surgical oncology, augmented reality systems overlay critical anatomical information onto the surgeon’s visual field. This aids in locating and preserving vital structures, such as nerves and blood vessels, during complex procedures. In this paper, the authors examine a series of patients undergoing complex neck surgical oncology procedures with prior virtual surgical planning analysis. For each patient, the surgical plan was imported in Hololens headset to allow for intraoperative augmented reality visualization. The authors discuss the results of this preliminary investigation, tracing the conceptual framework for an increasing AR implementation in complex head and neck surgical oncology procedures

Role of Microenvironment in Glioma Invasion. What We Learned from In Vitro Models

The invasion properties of glioblastoma hamper a radical surgery and are responsible for its recurrence. Understanding the invasion mechanisms is thus critical to devise new therapeutic strategies. Therefore, the creation of in vitro models that enable these mechanisms to be studied represents a crucial step. Since in vitro models represent an over-simplification of the in vivo system, in these years it has been attempted to increase the level of complexity of in vitro assays to create models that could better mimic the behaviour of the cells in vivo. These levels of complexity involved: 1. The dimension of the system, moving from two-dimensional to three-dimensional models; 2. The use of microfluidic systems; 3. The use of mixed cultures of tumour cells and cells of the tumour micro-environment in order to mimic the complex cross-talk between tumour cells and their micro-environment; 4. And the source of cells used in an attempt to move from commercial lines to patient-based models. In this review, we will summarize the evidence obtained exploring these different levels of complexity and highlighting advantages and limitations of each system used

Risk Assessment by Pre-surgical Tractography in Left Hemisphere Low-Grade Gliomas

Background: Tracking the white matter principal tracts is routinely typically included during the pre-surgery planning examinations and has revealed to limit functional resection of low-grade gliomas (LGGs) in eloquent areas. Objective: We examined the integrity of the Superior Longitudinal Fasciculus (SLF) and Inferior Fronto-Occipital Fasciculus (IFOF), both known to be part of the language-related network in patients with LGGs involving the temporo-insular cortex. In a comparative approach, we contrasted the main quantitative fiber tracking values in the tumoral (T) and healthy (H) hemispheres to test whether or not this ratio could discriminate amongst patients with different post-operative outcomes. Methods: Twenty-six patients with LGGs were included. We obtained quantitative fiber tracking values in the tumoral and healthy hemispheres and calculated the ratio (HIFOF\u2013TIFOF)/HIFOF and the ratio (HSLF\u2013TSLF)/HSLF on the number of streamlines. We analyzed how these values varied between patients with and without post-operative neurological outcomes and between patients with different post-operative Engel classes. Results: The ratio for both IFOF and SLF significantly differed between patient with and without post-operative neurological language deficits. No associations were found between white matter structural changes and post-operative seizure outcomes. Conclusions: Calculating the ratio on the number of streamlines and fractional anisotropy between the tumoral and the healthy hemispheres resulted to be a useful approach, which can prove to be useful during the pre-operative planning examination, as it gives a glimpse on the potential clinical outcomes in patients with LGGs involving the left temporo-insular cortex

Systemic T Cells Immunosuppression of Glioma Stem Cell-Derived Exosomes Is Mediated by Monocytic Myeloid-Derived Suppressor Cells

A major contributing factor to glioma development and progression is its ability to evade the immune system. Nano-meter sized vesicles, exosomes, secreted by glioma-stem cells (GSC) can act as mediators of intercellular communication to promote tumor immune escape. Here, we investigated the immunomodulatory properties of GCS-derived exosomes on different peripheral immune cell populations. Healthy donor peripheral blood mononuclear cells (PBMCs) stimulated with anti-CD3, anti-CD28 and IL-2, were treated with GSC-derived exosomes. Phenotypic characterization, cell proliferation, Th1/Th2 cytokine secretion and intracellular cytokine production were analysed by distinguishing among effector T cells, regulatory T cells and monocytes. In unfractionated PBMCs, GSC-derived exosomes inhibited T cell activation (CD25 and CD69 expression), proliferation and Th1 cytokine production, and did not affect cell viability or regulatory T-cell suppression ability. Furthermore, exosomes were able to enhance proliferation of purified CD4+ T cells. In PBMCs culture, glioma-derived exosomes directly promoted IL-10 and arginase-1 production and downregulation of HLA-DR by unstimulated CD14+ monocytic cells, that displayed an immunophenotype resembling that of monocytic myeloid-derived suppressor cells (Mo-MDSCs). Importantly, the removal of CD14+ monocytic cell fraction from PBMCs restored T-cell proliferation. The same results were observed with exosomes purified from plasma of glioblastoma patients. Our results indicate that glioma-derived exosomes suppress T-cell immune response by acting on monocyte maturation rather than on direct interaction with T cells. Selective targeting of Mo-MDSC to treat glioma should be considered with regard to how immune cells allow the acquirement of effector functions and therefore counteracting tumor progression

The mirna content of exosomes released from the glioma microenvironment can affect malignant progression

Low-grade gliomas (LGG) are infiltrative primary brain tumors that in 70% of the cases undergo anaplastic transformation, deeply affecting prognosis. However, the timing of progression is heterogeneous. Recently, the tumor microenvironment (TME) has gained much attention either as prognostic factor or therapeutic target. Through the release of extracellular vesicles, the TME contributes to tumor progression by transferring bioactive molecules such as microRNA. The aim of the study was to take advantage of glioma-associated stem cells (GASC), an in vitro model of the glioma microenvironment endowed with a prognostic significance, and their released exosomes, to investigate the possible role of exosome miRNAs in favoring the anaplastic transformation of LGG. Therefore, by deep sequencing, we analyzed and compared the miRNA profile of GASC and exosomes obtained from LGG patients characterized by different prognosis. Results showed that exosomes presented a different signature, when compared to their cellular counterpart and that, although sharing several miRNAs, exosomes of patients with a bad prognosis, selectively expressed some miRNAs possibly responsible for the more aggressive phenotype. These findings get insights into the value of TME and exosomes as potential biomarkers for precision medicine approaches aimed at improving LGG prognostic stratification and therapeutic strategies

Glioblastoma cusa fluid protein profiling: A comparative investigation of the core and peripheral tumor zones

The present investigation aimed to characterize the protein profile of cavitating ultrasound aspirator fluid of newly diagnosed and recurrent glioblastoma comparing diverse zones of collection, i.e., tumor core and tumor periphery, with the aid of 5\u2010aminolevulinic acid fluorescence. The samples were pooled and analyzed in triplicate by LC\u2010MS following the shotgun proteomic approach. The identified proteins were then grouped to disclose elements exclusive and common to the tumor state or tumor zones and submitted to gene ontology classification and pathway overrepresentation analysis. The proteins common to the distinct zones were further investigated by relative quantitation, following a label free approach, to disclose possible differences of expression. Nine proteins, i.e., tubulin 2B chain, CD59, far upstream element\u2010binding, CD44, histone H1.4, caldesmon, osteopontin, tropomyosin chain and metallothionein\u20102, marked the core of newly diagnosed glioblastoma with respect to tumor periphery. Considering the tumor zone, including the core and the fluorescence positive periphery, the serine glycine biosynthesis, pentose phosphate, 5\u2010 hydroxytryptamine degredation, de novo purine biosynthesis and huntington disease pathways resulted statistically significantly overrepresented with respect to the human genome of reference. The fluorescence negative zone shared several protein elements with the tumor zone, possibly indicating the presence of pathological aspects of glioblastoma rather than of normal brain parenchyma. On the other hand, its exclusive protein elements were considered to represent the healthy zone and, accordingly, exhibiting no pathways overrepresentation. On the contrary to newly diagnosed glioblastoma, pathway overrepresentation was recognized only in the healthy zone of recurrent glioblastoma. The TGF\u3b2 signaling pathway, exclusively classified in the fluorescence negative periphery in newly diagnosed glioblastoma, was instead the exclusive pathway classified in the tumor core of recurrent glioblastoma. These results, preliminary obtained on sample pools, demonstrated the potential of cavitron ultrasonic sur gical aspirate fluid for proteomic profiling of glioblastoma able to distinguish molecular features specific of the diverse tumor zones and tumor states, possibly contributing to the understanding of the highly infiltrative capability and recurrent rate of this aggressive brain tumor and opening to potential clinical applications to be further investigated

Machine learning to improve interpretability of clinical, radiological and panel-based genomic data of glioma grade 4 patients undergoing surgical resection

Background: Glioma grade 4 (GG4) tumors, including astrocytoma IDH-mutant grade 4 and the astrocytoma IDH wt are the most common and aggressive primary tumors of the central nervous system. Surgery followed by Stupp protocol still remains the first-line treatment in GG4 tumors. Although Stupp combination can prolong survival, prognosis of treated adult patients with GG4 still remains unfavorable. The introduction of innovative multi-parametric prognostic models may allow refinement of prognosis of these patients. Here, Machine Learning (ML) was applied to investigate the contribution in predicting overall survival (OS) of different available data (e.g. clinical data, radiological data, or panel-based sequencing data such as presence of somatic mutations and amplification) in a mono-institutional GG4 cohort. Methods: By next-generation sequencing, using a panel of 523 genes, we performed analysis of copy number variations and of types and distribution of nonsynonymous mutations in 102 cases including 39 carmustine wafer (CW) treated cases. We also calculated tumor mutational burden (TMB). ML was applied using eXtreme Gradient Boosting for survival (XGBoost-Surv) to integrate clinical and radiological information with genomic data. Results: By ML modeling (concordance (c)- index = 0.682 for the best model), the role of predicting OS of radiological parameters including extent of resection, preoperative volume and residual volume was confirmed. An association between CW application and longer OS was also showed. Regarding gene mutations, a role in predicting OS was defined for mutations of BRAF and of other genes involved in the PI3K-AKT-mTOR signaling pathway. Moreover, an association between high TMB and shorter OS was suggested. Consistently, when a cutoff of 1.7 mutations/megabase was applied, cases with higher TMB showed significantly shorter OS than cases with lower TMB. Conclusions: The contribution of tumor volumetric data, somatic gene mutations and TBM in predicting OS of GG4 patients was defined by ML modeling

Article a new epigenetic model to stratify glioma patients according to their immunosuppressive state

Gliomas are the most common primary neoplasm of the central nervous system. A promising frontier in the definition of glioma prognosis and treatment is represented by epigenetics. Further-more, in this study, we developed a machine learning classification model based on epigenetic data (CpG probes) to separate patients according to their state of immunosuppression. We considered 573 cases of low-grade glioma (LGG) and glioblastoma (GBM) from The Cancer Genome Atlas (TCGA). First, from gene expression data, we derived a novel binary indicator to flag patients with a favorable immune state. Then, based on previous studies, we selected the genes related to the immune state of tumor microenvironment. After, we improved the selection with a data-driven procedure, based on Boruta. Finally, we tuned, trained, and evaluated both random forest and neural network classifiers on the resulting dataset. We found that a multi-layer perceptron network fed by the 338 probes selected by applying both expert choice and Boruta results in the best performance, achieving an out-of-sample accuracy of 82.8%, a Matthews correlation coefficient of 0.657, and an area under the ROC curve of 0.9. Based on the proposed model, we provided a method to stratify glioma patients according to their epigenomic state