Effectiveness of Radiomic ZOT Features in the Automated Discrimination of Oncocytoma from Clear Cell Renal Cancer

Background: Benign renal tumors, such as renal oncocytoma (RO), can be erroneously diagnosed as malignant renal cell carcinomas (RCC), because of their similar imaging features. Computer-aided systems leveraging radiomic features can be used to better discriminate benign renal tumors from the malignant ones. The purpose of this work was to build a machine learning model to distinguish RO from clear cell RCC (ccRCC). Method: We collected CT images of 77 patients, with 30 cases of RO (39%) and 47 cases of ccRCC (61%). Radiomic features were extracted both from the tumor volumes identified by the clinicians and from the tumor’s zone of transition (ZOT). We used a genetic algorithm to perform feature selection, identifying the most descriptive set of features for the tumor classification. We built a decision tree classifier to distinguish between ROs and ccRCCs. We proposed two versions of the pipeline: in the first one, the feature selection was performed before the splitting of the data, while in the second one, the feature selection was performed after, i.e., on the training data only. We evaluated the efficiency of the two pipelines in cancer classification. Results: The ZOT features were found to be the most predictive by the genetic algorithm. The pipeline with the feature selection performed on the whole dataset obtained an average ROC AUC score of 0.87 ± 0.09. The second pipeline, in which the feature selection was performed on the training data only, obtained an average ROC AUC score of 0.62 ± 0.17. Conclusions: The obtained results confirm the efficiency of ZOT radiomic features in capturing the renal tumor characteristics. We showed that there is a significant difference in the performances of the two proposed pipelines, highlighting how some already published radiomic analyses could be too optimistic about the real generalization capabilities of the models

Whole exome sequencing highlights rare variants in CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1 as associated with FSHD

Introduction: Despite the progress made in the study of Facioscapulohumeral Dystrophy (FSHD), the wide heterogeneity of disease complicates its diagnosis and the genotype-phenotype correlation among patients and within families. In this context, the present work employed Whole Exome Sequencing (WES) to investigate known and unknown genetic contributors that may be involved in FSHD and may represent potential disease modifiers, even in presence of a D4Z4 Reduced Allele (DRA).Methods: A cohort of 126 patients with clinical signs of FSHD were included in the study, which were characterized by D4Z4 sizing, methylation analysis and WES. Specific protocols were employed for D4Z4 sizing and methylation analysis, whereas the Illumina® Next-Seq 550 system was utilized for WES. The study included both patients with a DRA compatible with FSHD diagnosis and patients with longer D4Z4 alleles. In case of patients harboring relevant variants from WES, the molecular analysis was extended to the family members.Results: The WES data analysis highlighted 20 relevant variants, among which 14 were located in known genetic modifiers (SMCHD1, DNMT3B and LRIF1) and 6 in candidate genes (CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1). Most of them were found together with a permissive short (4–7 RU) or borderline/long DRA (8–20 RU), supporting the possibility that different genes can contribute to disease heterogeneity in presence of a FSHD permissive background. The segregation and methylation analysis among family members, together with clinical findings, provided a more comprehensive picture of patients.Discussion: Our results support FSHD pathomechanism being complex with a multigenic contribution by several known (SMCHD1, DNMT3B, LRIF1) and possibly other candidate genes (CTCF, DNMT1, DNMT3A, EZH2, SUV39H1) to disease penetrance and expressivity. Our results further emphasize the importance of extending the analysis of molecular findings within the proband’s family, with the purpose of providing a broader framework for understanding single cases and allowing finer genotype-phenotype correlations in FSHD-affected families

Buchbesprechungen

Buchbesprechunge

Nusinersen safety and effects on motor function in adult spinal muscular atrophy type 2 and 3

Objective: To retrospectively investigate safety and efficacy of nusinersen in a large cohort of adult Italian patients with spinal muscular atrophy (SMA). Methods: Inclusion criteria were: (1) clinical and molecular diagnosis of SMA2 or SMA3; (2) nusinersen treatment started in adult age (>18 years); (3) clinical data available at least at baseline (T0-beginning of treatment) and 6 months (T6). Results: We included 116 patients (13 SMA2 and 103 SMA3) with median age at first administration of 34 years (range 18-72). The Hammersmith Functional Rating Scale Expanded (HFMSE) in patients with SMA3 increased significantly from baseline to T6 (median change +1 point, p<0.0001), T10 (+2, p<0.0001) and T14 (+3, p<0.0001). HFMSE changes were independently significant in SMA3 sitter and walker subgroups. The Revised Upper Limb Module (RULM) in SMA3 significantly improved between T0 and T14 (median +0.5, p=0.012), with most of the benefit observed in sitters (+2, p=0.018). Conversely, patients with SMA2 had no significant changes of median HFMSE and RULM between T0 and the following time points, although a trend for improvement of RULM was observed in those with some residual baseline function. The rate of patients showing clinically meaningful improvements (as defined during clinical trials) increased from 53% to 69% from T6 to T14. Conclusions: Our data provide further evidence of nusinersen safety and efficacy in adult SMA2 and SMA3, with the latter appearing to be cumulative over time. In patients with extremely advanced disease, effects on residual motor function are less clear

Adults with spinal muscular atrophy: a large-scale natural history study shows gender effect on disease

Natural history of spinal muscular atrophy (SMA) in adult age has not been fully elucidated yet, including factors predicting disease progression and response to treatments. Aim of this retrospective, cross-sectional study, is to investigate motor function across different ages, disease patterns and gender in adult SMA untreated patients