Cancer genomics has illuminated a wide spectrum of genes and core molecular processes contributing to human malignancy. Still, the genetic and molecular basis of many cancers remains only partially explained. Genetic predisposition accounts for 5-10% of cancer diagnoses 1,2 and genetic events cooperating with known somatic driver events are poorly understood. Analyzing established cancer predisposition genes in medulloblastoma (MB), a malignant childhood brain tumor, we recently identified pathogenic germline variants that account for 5% of all MB patients 3 . Here, by extending our previous analysis to include all protein-coding genes, we discovered and replicated rare germline loss-of-function (LoF) variants across Elongator Complex Protein 1 (ELP1) on 9q31.3 in 15% of pediatric MB SHH cases, thus implicating ELP1 as the most common MB predisposition gene and increasing genetic predisposition to 40% for pediatric MB SHH . Inheritance was verified based on parent-offspring and pedigree analysis, which identified two families with a history of pediatric MB. ELP1-associated MBs were restricted to the molecular SHHα subtype 4 and were characterized by universal biallelic inactivation of ELP1 due
Long non-coding RNAs are involved in biological processes throughout the cell including the nucleus, chromatin and cytosol. However, most lncRNAs remain unannotated and functional annotation of lncRNAs is difficult due to their low conservation and their tissue and developmentally specific expression. LncRNA subcellular localization is highly informative regarding its biological function, although it is difficult to discover because few prediction methods currently exist. While protein subcellular localization prediction is a well-established research field, lncRNA localization prediction is a novel research problem. We developed DeepLncRNA, a deep learning algorithm which predicts lncRNA subcellular localization directly from lncRNA transcript sequences. We analyzed 93 strand-specific RNA-seq samples of nuclear and cytosolic fractions from multiple cell types to identify differentially localized lncRNAs. We then extracted sequence-based features from the lncRNAs to construct our DeepLncRNA model, which achieved an accuracy of 72.4%, sensitivity of 83%, specificity of 62.4% and area under the receiver operating characteristic curve of 0.787. Our results suggest that primary sequence motifs are a major driving force in the subcellular localization of lncRNAs.
Pineoblastoma is a rare embryonal tumor of childhood that is conventionally treated with highdose craniospinal irradiation (CSI). Multi-dimensional molecular evaluation of pineoblastoma and associated intertumoral heterogeneity is lacking. Herein, we report outcomes and molecular features of children with pineoblastoma from two multi-center, risk-adapted trials (SJMB03 for patients ≥3 years; SJYC07 for patients <3 years) complemented by a non-protocol institutional cohort. The clinical cohort consisted of 58 patients with histologically diagnosed pineoblastoma (SJMB03=30; SJYC07=12; non-protocol=16, including 12 managed with SJMB03-like therapy). The SJMB03 protocol comprised risk-adapted CSI (average-risk=23.4 Gy, high-risk=36 Gy) with radiation boost to the primary site and adjuvant chemotherapy. The SJYC07 protocol consisted of induction chemotherapy, consolidation with focal radiation (intermediate-risk) or chemotherapy (high-risk), and metronomic maintenance therapy. The molecular cohort comprised 43 pineal parenchymal tumors profiled by DNA methylation array (n=43), whole-exome sequencing (n=26), and RNA-sequencing (n=16). Respective 5-year progression-free survival rates for patients with average-risk or high-risk disease on SJMB03 or SJMB03-like therapy were 100% and 56.5±10.3% (P=0.007); respective 2-year progression-free survival rates for those with intermediate-risk or high-risk disease on SJYC07 were 14.3±13.2% and 0% (P=0.375). Of patients with average-risk disease treated with SJMB03/SJMB03-like therapy, 17/18 survived without progression. DNAmethylation analysis revealed four clinically relevant pineoblastoma subgroups: PB-A, PB-B, PB-B-like, and PB-FOXR2. Pineoblastoma subgroups differed in age at diagnosis, propensity for metastasis, cytogenetics, and clinical outcomes. Alterations in the miRNA-processing pathway genes DICER1, DROSHA, and DGCR8 were recurrent and mutually exclusive in PB-B and PB-B-like subgroups; PB-FOXR2 samples universally overexpressed the FOXR2 proto-oncogene.Our findings suggest superior outcome amongst older children with average-risk pineoblastoma treated with reduced-dose CSI. The identification of biologically and clinically distinct pineoblastoma subgroups warrants consideration of future molecularly-driven treatment protocols for this rare pediatric brain tumor entity.Liu et al.
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