Connectome-Based Neurosurgery in Primary Intra-Axial Neoplasms: Beyond the Traditional Modular Conception of Brain Architecture for the Preservation of Major Neurological Domains and Higher-Order Cognitive Functions

Despite the therapeutical advancements in the surgical treatment of primary intra-axial neoplasms, which determined both a significative improvement in OS and QoL and a reduction in the incidence of surgery-induced major neurological deficits, nowadays patients continue to manifest subtle post-operative neurocognitive impairments, preventing them from a full reintegration back into social life and into the workforce. The birth of connectomics paved the way for a profound reappraisal of the traditional conception of brain architecture, in favour of a model based on large-scale structural and functional interactions of a complex mosaic of cortical areas organized in a fluid network interconnected by subcortical bundles. Thanks to these advancements, neurosurgery is facing a new era of connectome-based resections, in which the core principle is still represented by the achievement of an ideal onco-functional balance, but with a closer eye on whole-brain circuitry, which constitutes the foundations of both major neurological functions, to be intended as motricity; language and visuospatial function; and higher-order cognitive functions such as cognition, conation, emotion and adaptive behaviour. Indeed, the achievement of an ideal balance between the radicality of tumoral resection and the preservation, as far as possible, of the integrity of local and global brain networks stands as a mandatory goal to be fulfilled to allow patients to resume their previous life and to make neurosurgery tailored and gentler to their individual needs.

A Radiomic-Based Machine Learning Model Predicts Endometrial Cancer Recurrence Using Preoperative CT Radiomic Features: A Pilot Study

BACKGROUND

Current prognostic models lack the use of pre-operative CT images to predict recurrence in endometrial cancer (EC) patients. Our study aimed to investigate the potential of radiomic features extracted from pre-surgical CT scans to accurately predict disease-free survival (DFS) among EC patients.

METHODS

Contrast-Enhanced CT (CE-CT) scans from 81 EC cases were used to extract the radiomic features from semi-automatically contoured volumes of interest. We employed a 10-fold cross-validation approach with a 6:4 training to test set and utilized data augmentation and balancing techniques. Univariate analysis was applied for feature reduction leading to the development of three distinct machine learning (ML) models for the prediction of DFS: LASSO-Cox, CoxBoost and Random Forest (RFsrc).

RESULTS

In the training set, the ML models demonstrated AUCs ranging from 0.92 to 0.93, sensitivities from 0.96 to 1.00 and specificities from 0.77 to 0.89. In the test set, AUCs ranged from 0.86 to 0.90, sensitivities from 0.89 to 1.00 and specificities from 0.73 to 0.90. Patients classified as having a high recurrence risk prediction by ML models exhibited significantly worse DSF (p-value < 0.001) across all models.

CONCLUSIONS

Our findings demonstrate the potential of radiomics in predicting EC recurrence. While further validation studies are needed, our results underscore the promising role of radiomics in forecasting EC outcomes.

Emerging Roles of Phospholipase C Beta Isozymes as Potential Biomarkers in Cardiac Disorders

Phospholipase C (PLC) enzymes represent crucial participants in the plasma membrane of mammalian cells, including the cardiac sarcolemmal (SL) membrane of cardiomyocytes. They are responsible for the hydrolysis of phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2) into 1,2-diacylglycerol (DAG) and inositol (1,4,5) trisphosphate (Ins(1,4,5)P3), both essential lipid mediators. These second messengers regulate the intracellular calcium (Ca2+) concentration, which activates signal transduction cascades involved in the regulation of cardiomyocyte activity. Of note, emerging evidence suggests that changes in cardiomyocytes' phospholipid profiles are associated with an increased occurrence of cardiovascular diseases, but the underlying mechanisms are still poorly understood. This review aims to provide a comprehensive overview of the significant impact of PLC on the cardiovascular system, encompassing both physiological and pathological conditions. Specifically, it focuses on the relevance of PLCβ isoforms as potential cardiac biomarkers, due to their implications for pathological disorders, such as cardiac hypertrophy, diabetic cardiomyopathy, and myocardial ischemia/reperfusion injury. Gaining a deeper understanding of the mechanisms underlying PLCβ activation and regulation is crucial for unraveling the complex signaling networks involved in healthy and diseased myocardium. Ultimately, this knowledge holds significant promise for advancing the development of potential therapeutic strategies that can effectively target and address cardiac disorders by focusing on the PLCβ subfamily.

Design, Pharmacological Characterization, and Molecular Docking of Minimalist Peptidomimetic Antagonists of α4β1 Integrin

Integrin receptors mediate cell-cell interactions via the recognition of cell-adhesion glycoproteins, as well as via the interactions of cells with proteins of the extracellular matrix, and upon activation they transduce signals bi-directionally across the cell membrane. In the case of injury, infection, or inflammation, integrins of β₂ and α₄ families participate in the recruitment of leukocytes, a multi-step process initiated by the capturing of rolling leukocytes and terminated by their extravasation. In particular, α₄β₁ integrin is deeply involved in leukocyte firm adhesion preceding extravasation. Besides its well-known role in inflammatory diseases, α₄β₁ integrin is also involved in cancer, being expressed in various tumors and showing an important role in cancer formation and spreading. Hence, targeting this integrin represents an opportunity for the treatment of inflammatory disorders, some autoimmune diseases, and cancer. In this context, taking inspiration from the recognition motives of α₄β₁ integrin with its natural ligands FN and VCAM-1, we designed minimalist α/β hybrid peptide ligands, with our approach being associated with a retro strategy. These modifications are expected to improve the compounds' stability and bioavailability. As it turned out, some of the ligands were found to be antagonists, being able to inhibit the adhesion of integrin-expressing cells to plates coated with the natural ligands without inducing any conformational switch and any activation of intracellular signaling pathways. An original model structure of the receptor was generated using protein-protein docking to evaluate the bioactive conformations of the antagonists via molecular docking. Since the experimental structure of α₄β₁ integrin is still unknown, the simulations might also shed light on the interactions between the receptor and its native protein ligands.

The Evaluation of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 Phenoconversion in Post-Mortem Casework: The Challenge of Forensic Toxicogenetics

In toxicogenetics, an integrative approach including the prediction of phenotype based on post-mortem genotyping of drug-metabolising enzymes might help explain the cause of death (CoD) and manner of death (MoD). The use of concomitant drugs, however, might lead to phenoconversion, a mismatch between the phenotype based on the genotype and the metabolic profile actually observed after phenoconversion. The aim of our study was to evaluate the phenoconversion of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 drug-metabolising enzymes in a series of autopsy cases tested positive for drugs that are substrates, inducers, or inhibitors of these enzymes. Our results showed a high rate of phenoconversion for all enzymes and a statistically significant higher frequency of poor and intermediate metabolisers for CYP2D6, CYP2C9, and CYP2C19 after phenoconversion. No association was found between phenotypes and CoD or MoD, suggesting that, although phenoconversion might be useful for a forensic toxicogenetics approach, more research is needed to overcome the challenges arising from the post-mortem setting.

Prognostic Impact of Pathologic Features in Molecular Subgroups of Endometrial Carcinoma

The molecular characterization of endometrial carcinoma (EC) has recently been included in the ESGO/ESTRO/ESP guidelines. The study aims to evaluate the impact of integrated molecular and pathologic risk stratification in the clinical practice and the relevance of pathologic parameters in predicting prognosis in each EC molecular subgroup. ECs were classified using immunohistochemistry and next-generation sequencing into the four molecular classes: POLE mutant (POLE), mismatch repair deficient (MMRd), p53 mutant (p53abn), and no specific molecular profile (NSMP). According to the WHO algorithm, 219 ECs were subdivided into the following molecular subgroups: 7.8% POLE, 31% MMRd, 21% p53abn, 40.2% NSMP. Molecular classes as well as ESGO/ESTRO/ESP 2020 risk groups were statistically correlated with disease-free survival. Considering the impact of histopathologic features in each molecular class, stage was found to be the strongest prognostic factor in MMRd ECs, whereas in the p53abn subgroup, only lymph node status was associated with recurrent disease. Interestingly, in the NSMP tumor, several histopathologic features were correlated with recurrence: histotype, grade, stage, tumor necrosis, and substantial lymphovascular space invasion. Considering early-stage NSMP ECs, substantial lymphovascular space invasion was the only independent prognostic factor. Our study supports the prognostic importance of EC molecular classification and demonstrated the essential role of histopathologic assessment in patients' management.

Relevance of ARID1A Mutations in Endometrial Carcinomas

Since the Cancer Genome Atlas (TCGA) project identified four distinct groups based on molecular alterations, mutation analyses have been integrated into the characterization of endometrial carcinomas (ECs). ARID1A seems to be the subunit more involved in the loss of function of the SWI/SNF complex in ECs. The aim of this study is to define the relevance of ARID1A alterations in a cohort of EC, studying the possible associations between DNA mutation (genomic level), RNA expression (transcriptomic level), and protein expression (proteomic level). A total of 50 endometrial carcinomas were characterized for ARID1A mutations (using targeted DNA next-generation sequencing-NGS), ARID1A gene expression (using RNAseq and qRT-PCR), and ARID1A protein expression (using immunohistochemistry-IHC). Moreover, we have investigated if ARID1A mutations may alter the protein structure, using the Protein Data Bank sequence. We found a good correlation between ARID1A mutations and protein immunostaining, even if we did not find statistically significant differences in the ARID1A expression levels. In conclusion, our data demonstrated that the molecular characterization of ARID1A should be associated with IHC analysis, mainly in those cases harboring "novel" ARID1A mutations or in those alterations with "uncertain" pathogenic significance.