A Cohort Study of CNS Tumors in Multiple Endocrine Neoplasia Type 1.

PURPOSE: Multiple endocrine neoplasia type 1 (MEN1) is thought to increase the risk of meningioma and ependymoma. Thus, we aimed to describe the frequency, incidence, and specific clinical and histological features of central nervous system (CNS) tumors in the MEN1 population (except pituitary tumors). EXPERIMENTAL DESIGN: The study population included patients harboring CNS tumors diagnosed with MEN1 syndrome after 1990 and followed up in the French MEN1 national cohort. The standardized incidence ratio (SIR) was calculated based on the French Gironde CNS Tumor Registry. Genomic analyses were performed on somatic DNA from seven CNS tumors, including meningiomas and ependymomas from patients with MEN1, and then on 50 sporadic meningiomas and ependymomas. RESULTS: A total of 29 CNS tumors were found among the 1,498 symptomatic patients (2%; incidence = 47.4/100,000 person-years; SIR = 4.5), including 12 meningiomas (0.8%; incidence = 16.2/100,000; SIR = 2.5), 8 ependymomas (0.5%; incidence = 10.8/100,000; SIR = 17.6), 5 astrocytomas (0.3%; incidence = 6.7/100,000; SIR = 5.8), and 4 schwannomas (0.3%; incidence = 5.4/100,000; SIR = 12.7). Meningiomas in patients with MEN1 were benign, mostly meningothelial, with 11 years earlier onset compared with the sporadic population and an F/M ratio of 1/1. Spinal and cranial ependymomas were mostly classified as World Health Organization grade 2. A biallelic MEN1 inactivation was observed in 4/5 ependymomas and 1/2 meningiomas from patients with MEN1, whereas MEN1 deletion in one allele was present in 3/41 and 0/9 sporadic meningiomas and ependymomas, respectively. CONCLUSIONS: The incidence of each CNS tumor was higher in the MEN1 population than in the French general population. Meningiomas and ependymomas should be considered part of the MEN1 syndrome, but somatic molecular data are missing to conclude for astrocytomas and schwannomas.

Extreme Gradient Boosting Tuned with Metaheuristic Algorithms for Predicting Myeloid NGS Onco-Somatic Variant Pathogenicity.

The advent of next-generation sequencing (NGS) technologies has revolutionized the field of bioinformatics and genomics, particularly in the area of onco-somatic genetics. NGS has provided a wealth of information about the genetic changes that underlie cancer and has considerably improved our ability to diagnose and treat cancer. However, the large amount of data generated by NGS makes it difficult to interpret the variants. To address this, machine learning algorithms such as Extreme Gradient Boosting (XGBoost) have become increasingly important tools in the analysis of NGS data. In this paper, we present a machine learning tool that uses XGBoost to predict the pathogenicity of a mutation in the myeloid panel. We optimized the performance of XGBoost using metaheuristic algorithms and compared our predictions with the decisions of biologists and other prediction tools. The myeloid panel is a critical component in the diagnosis and treatment of myeloid neoplasms, and the sequencing of this panel allows for the identification of specific genetic mutations, enabling more accurate diagnoses and tailored treatment plans. We used datasets collected from our myeloid panel NGS analysis to train the XGBoost algorithm. It represents a data collection of 15,977 mutations variants composed of a collection of 13,221 Single Nucleotide Variants (SNVs), 73 Multiple Nucleoid Variants (MNVs), and 2683 insertion deletions (INDELs). The optimal XGBoost hyperparameters were found with Differential Evolution (DE), with an accuracy of 99.35%, precision of 98.70%, specificity of 98.71%, and sensitivity of 1.

Comparison between Immunocytochemistry, FISH and NGS for ALK and ROS1 Rearrangement Detection in Cytological Samples.

The detection of ROS1 and ALK rearrangements is performed for advanced-stage non-small cell lung cancer. Several techniques can be used on cytological samples, such as immunocytochemistry (ICC), fluorescence in situ hybridization (FISH) and, more recently, next-generation sequencing (NGS), which is gradually becoming the gold standard. We performed a retrospective study to compare ALK and ROS1 rearrangement results from immunocytochemistry, FISH and NGS methods from 131 cytological samples. Compared to NGS, the sensitivity and specificity of ICC were 0.79 and 0.91, respectively, for ALK, and 1 and 0.87 for ROS1. Regarding FISH, the sensitivity and specificity were both at 1 for ALK and ROS1 probes. False-positive cases obtained by ICC were systematically corrected by FISH. When using ICC and FISH techniques, results are very close to NGS. The false-positive cases obtained by ICC are corrected by FISH, and the true-positive cases are confirmed. NGS has the potential to improve the detection of ALK and ROS1 rearrangements in cytological samples; however, the cost of this technique is still much higher than the sequential use of ICC and FISH.