Identification of MicroRNA Expression Profiles Related to the Aggressiveness of Salivary Gland Adenoid Cystic Carcinomas.

Adenoid cystic carcinoma (ACC) has been reported as the second most common carcinoma of the salivary glands. Few studies have associated miRNA expression with ACC aggressiveness. In this study, we evaluated the miRNA profile of formalin-fixed, paraffin-embedded (FFPE) samples of salivary gland ACC patients using the NanoString platform. We studied the miRNA expression levels associated with the solid growth pattern, the more aggressive histologic feature of ACCs, compared with the tubular and cribriform growth patterns. Moreover, the perineural invasion status, a common clinicopathological feature of the disease that is frequently associated with the clinical progression of ACC, was investigated. The miRNAs showing significant differences between the study groups were selected for target prediction and functional enrichment, which included associations with the disease according to dedicated databases. We observed decreased expression of miR-181d, miR-23b, miR-455, miR-154-5p, and miR-409 in the solid growth pattern compared with tubular and cribriform growth patterns. In contrast, miR-29c, miR-140, miR-195, miR-24, miR-143, and miR-21 were overexpressed in patients with perineural invasion. Several target genes of the miRNAs identified have been associated with molecular processes involved in cell proliferation, apoptosis, and tumor progression. Together, these findings allowed the characterization of miRNAs potentially associated with aggressiveness in salivary gland adenoid cystic carcinoma. Our results highlight important new miRNA expression profiles involved in ACC carcinogenesis that could be associated with the aggressive behavior of this tumor type.

Single nCounter assay for prediction of MYCN amplification and molecular classification of medulloblastomas: a multicentric study.

PURPOSE: Medulloblastoma is the most frequent pediatric malignant brain tumor, and is divided into four main subgroups: WNT, SHH, group 3, and group 4. MYCN amplification is an important medulloblastoma prognostic biomarker. We aimed to molecular classify and predict MYCN amplification in a single assay. METHODS: It was included 209 medulloblastomas from 205 patients (Brazil, Argentina, and Portugal), divided into training (n = 50) and validation (n = 159) sets. A nCounter assay was carried out using a custom panel for molecular classification, with additional genes, including MYCN. nSolver 4.0 software and the R environment were used for profiling and MYCN mRNA analysis. MYCN amplification by FISH was performed in 64 cases. RESULTS: The 205 medulloblastomas were classified in SHH (44.9%), WNT (15.6%), group 3 (18.1%) and group 4 (21.4%). In the training set, MYCN amplification was detected in three SHH medulloblastomas by FISH, which showed significantly higher MYCN mRNA counts than non-FISH amplified cases, and a cutoff for MYCN amplification was established ([Formula: see text] + 4σ = 11,124.3). Applying this threshold value in the validation set, we identified MYCN mRNA counts above the cutoff in three cases, which were FISH validated. CONCLUSION: We successfully stratified medulloblastoma molecular subgroups and predicted MYCN amplification using a single nCounter assay without the requirement of additional biological tissue, costs, or bench time.

Information theory approaches to improve glioma diagnostic workflows in surgical neuropathology.

AIMS: Resource-strained healthcare ecosystems often struggle with the adoption of the World Health Organization (WHO) recommendations for the classification of central nervous system (CNS) tumors. The generation of robust clinical diagnostic aids and the advancement of simple solutions to inform investment strategies in surgical neuropathology would improve patient care in these settings. METHODS: We used simple information theory calculations on a brain cancer simulation model and real-world data sets to compare contributions of clinical, histologic, immunohistochemical, and molecular information. An image noise assay was generated to compare the efficiencies of different image segmentation methods in H&E and Olig2 stained images obtained from digital slides. An auto-adjustable image analysis workflow was generated and compared with neuropathologists for p53 positivity quantification. Finally, the density of extracted features of the nuclei, p53 positivity quantification, and combined ATRX/age feature was used to generate a predictive model for 1p/19q codeletion in IDH-mutant tumors. RESULTS: Information theory calculations can be performed on open access platforms and provide significant insight into linear and nonlinear associations between diagnostic biomarkers. Age, p53, and ATRX status have significant information for the diagnosis of IDH-mutant tumors. The predictive models may facilitate the reduction of false-positive 1p/19q codeletion by fluorescence in situ hybridization (FISH) testing. CONCLUSIONS: We posit that this approach provides an improvement on the cIMPACT-NOW workflow recommendations for IDH-mutant tumors and a framework for future resource and testing allocation.

A Unique Case Report of Infant-Type Hemispheric Glioma (Gliosarcoma Subtype) with TPR-NTRK1 Fusion Treated with Larotrectinib.

Herein, we present a rare case of a nine-month-old boy diagnosed with infant-type hemispheric glioma (gliosarcoma subtype) at the left frontal lobe. Following subtotal resection, the patient started chemotherapy with the BABY POG protocol. We describe the clinical diagnosis, histological characteristics, radiological features, molecular aspects, and management of this tumor. A comprehensive molecular analysis on the tumor tissue showed a TPR-NTRK1 gene fusion. The patient was treated with a TRK inhibitor, larotrectinib, and exhibited a stable disease with residual lesion following 8 months of target therapy. The present study is the first report of an infantile gliosarcoma harboring NTRK1 rearrangement treated with larotrectinib.

Simultaneous analysis of ALK, RET, and ROS1 gene fusions by NanoString in Brazilian lung adenocarcinoma patients.

BACKGROUND: Gene fusions have been successfully employed as therapeutic targets for lung adenocarcinoma. However, tissue availability for molecular testing of multiples alterations is frequently unfeasible. We aimed to detect the presence of ALK, RET, and ROS1 rearrangements by a RNA-based single assay in Brazilian lung adenocarcinomas and to associate with clinicopathological features and genetic ancestry. METHODS: From a FFPE series of 444 molecularly characterized lung adenocarcinomas, 253 EGFR/KRAS wild-type cases were eligible for gene rearrangement analysis. Following RNA isolation, ALK, RET, and ROS1 rearrangements were simultaneously analyzed employing the ElementsXT Custom panel (NanoString Technologies). Rearrangements were further associated with clinicopathological features and genetic ancestry of the patients. RESULTS: The NanoString platform was performed in subset of 142 cases. Gene fusion results were conclusive for 94.4% (n=134) cases (failure rate =5.6%). ALK rearrangements were observed in 21 out of 134 cases, and associated with younger, never smokers, metastatic disease, and metastases in the central nervous system. RET and ROS1 fusions were detected in two and one out of 134 cases, respectively. Genetic ancestry was not associated with gene fusions. Overall, considering all cases for which a molecular analysis was conclusive (EGFR/KRAS/ALK/RET/ROS1), ALK fusions frequency was observed in 6.5% (21/325), RET in 0.6% (2/325), and ROS1 in 0.3% (1/325). CONCLUSIONS: This study successfully used a RNA-based single assay for the simultaneous analysis of ALK, RET, and ROS1 fusions employing routine biopsies from Brazilian patients lung adenocarcinoma allowing an extensive molecular testing for actionable rearrangements contributing to guide clinical strategies.