Limber pine (Pinus flexilis James) genetic map constructed by exome-seq provides insight into the evolution of disease resistance and a genomic resource for genomics-based breeding.

Limber pine (Pinus flexilis) is a keystone species of high-elevation forest ecosystems of western North America, but some parts of the geographic range have high infection and mortality from the non-native white pine blister rust caused byCronartium ribicola. Genetic maps can provide essential knowledge for understanding genetic disease resistance as well as local adaptation to changing climates. Exome-seq was performed to construct high-density genetic maps in two seed families. Composite maps positioned 9612 unigenes across 12 linkage groups (LGs). Syntenic analysis of genome structure revealed that the majority of orthologs were positional orthologous genes (POGs) with localization on homologousLGs among conifer species. Gene ontology (GO) enrichment analysis showed relatively fewer constraints forPOGs with putative roles in adaptation to environments and relatively more conservation forPOGs with roles in basic cell function and maintenance. The mapped genes included 639 nucleotide-binding site leucine-rich repeat genes (NBS-LRRs), 290 receptor-like protein kinase genes (RLKs), and 1014 genes with potential roles in the defense response and induced systemic resistance to attack by pathogens. Orthologous loci for resistance to rust pathogens were identified and were co-positioned with multiple members of theR gene family, revealing the evolutionary pressure acting upon them. This high-density genetic map provides a genomic resource and practical tool for breeding and genetic conservation programs, with applications in genome-wide association studies (GWASs), the characterization of functional genes underlying complex traits, and the sequencing and assembly of the full-length genomes of limber pine and relatedPinus species.

Pineoblastoma segregates into molecular sub-groups with distinct clinico-pathologic features: a Rare Brain Tumor Consortium registry study.

Pineoblastomas (PBs) are rare, aggressive pediatric brain tumors of the pineal gland with modest overall survival despite intensive therapy. We sought to define the clinical and molecular spectra of PB to inform new treatment approaches for this orphan cancer. Tumor, blood, and clinical data from 91 patients with PB or supratentorial primitive neuroectodermal tumor (sPNETs/CNS-PNETs), and 2 pineal parenchymal tumors of intermediate differentiation (PPTIDs) were collected from 29 centres in the Rare Brain Tumor Consortium. We used global DNA methylation profiling to define a core group of PB from 72/93 cases, which were delineated into five molecular sub-groups. Copy number, whole exome and targeted sequencing, and miRNA expression analyses were used to evaluate the clinico-pathologic significance of each sub-group. Tumors designated as group 1 and 2 almost exclusively exhibited deleterious homozygous loss-of-function alterations in miRNA biogenesis genes (DICER1, DROSHA, and DGCR8) in 62 and 100% of group 1 and 2 tumors, respectively. Recurrent alterations of the oncogenic MYC-miR-17/92-RB1 pathway were observed in the RB and MYC sub-group, respectively, characterized by RB1 loss with gain of miR-17/92, and recurrent gain or amplification of MYC. PB sub-groups exhibited distinct clinical features: group 1-3 arose in older children (median ages 5.2-14.0 years) and had intermediate to excellent survival (5-year OS of 68.0-100%), while Group RB and MYC PB patients were much younger (median age 1.3-1.4 years) with dismal survival (5-year OS 37.5% and 28.6%, respectively). We identified age < 3 years at diagnosis, metastatic disease, omission of upfront radiation, and chr 16q loss as significant negative prognostic factors across all PBs. Our findings demonstrate that PB exhibits substantial molecular heterogeneity with sub-group-associated clinical phenotypes and survival. In addition to revealing novel biology and therapeutics, molecular sub-grouping of PB can be exploited to reduce treatment intensity for patients with favorable biology tumors.

Rapid, economical diagnostic classification of ATRT molecular subgroup using NanoString nCounter platform.

Background: Despite genomic simplicity, recent studies have reported at least 3 major atypical teratoid rhabdoid tumor (ATRT) subgroups with distinct molecular and clinical features. Reliable ATRT subgrouping in clinical settings remains challenging due to a lack of suitable biological markers, sample rarity, and the relatively high cost of conventional subgrouping methods. This study aimed to develop a reliable ATRT molecular stratification method to implement in clinical settings. Methods: We have developed an ATRT subgroup predictor assay using a custom genes panel for the NanoString nCounter System and a flexible machine learning classifier package. Seventy-one ATRT primary tumors with matching gene expression array and NanoString data were used to construct a multi-algorithms ensemble classifier. Additional validation was performed using an independent gene expression array against the independently generated dataset. We also analyzed 11 extra-cranial rhabdoid tumors with our classifier and compared our approach against DNA methylation classification to evaluate the result consistency with existing methods. Results: We have demonstrated that our novel ensemble classifier has an overall average of 93.6% accuracy in the validation dataset, and a striking 98.9% accuracy was achieved with the high-prediction score samples. Using our classifier, all analyzed extra-cranial rhabdoid tumors are classified as MYC subgroups. Compared with the DNA methylation classification, the results show high agreement, with 84.5% concordance and up to 95.8% concordance for high-confidence predictions. Conclusions: Here we present a rapid, cost-effective, and accurate ATRT subgrouping assay applicable for clinical use.

Molecular subgrouping of atypical teratoid/rhabdoid tumors-a reinvestigation and current consensus.

BACKGROUND: Atypical teratoid/rhabdoid tumors (ATRTs) are known to exhibit molecular and clinical heterogeneity even though SMARCB1 inactivation is the sole recurrent genetic event present in nearly all cases. Indeed, recent studies demonstrated 3 molecular subgroups of ATRTs that are genetically, epigenetically, and clinically distinct. As these studies included different numbers of tumors, various subgrouping techniques, and naming, an international working group sought to align previous findings and to reach a consensus on nomenclature and clinicopathological significance of ATRT subgroups. METHODS: We integrated various methods to perform a meta-analysis on published and unpublished DNA methylation and gene expression datasets of ATRTs and associated clinicopathological data. RESULTS: In concordance with previous studies, the analyses identified 3 main molecular subgroups of ATRTs, for which a consensus was reached to name them ATRT-TYR, ATRT-SHH, and ATRT-MYC. The ATRT-SHH subgroup exhibited further heterogeneity, segregating further into 2 subtypes associated with a predominant supratentorial (ATRT-SHH-1) or infratentorial (ATRT-SHH-2) location. For each ATRT subgroup we provide an overview of its main molecular and clinical characteristics, including SMARCB1 alterations and pathway activation. CONCLUSIONS: The introduction of a common classification, characterization, and nomenclature of ATRT subgroups will facilitate future research and serve as a common ground for subgrouping patient samples and ATRT models, which will aid in refining subgroup-based therapies for ATRT patients.

Tissue specificity of in vitro drug sensitivity.

Objectives: We sought to investigate the tissue specificity of drug sensitivities in large-scale pharmacological studies and compare these associations to those found in drug clinical indications. Materials and Methods: We leveraged the curated cell line response data from PharmacoGx and applied an enrichment algorithm on drug sensitivity values' area under the drug dose-response curves (AUCs) with and without adjustment for general level of drug sensitivity. Results: We observed tissue specificity in 63% of tested drugs, with 8% of total interactions deemed significant (false discovery rate <0.05). By restricting the drug-tissue interactions to those with AUC > 0.2, we found that in 52% of interactions, the tissue was predictive of drug sensitivity (concordance index > 0.65). When compared with clinical indications, the observed overlap was weak (Matthew correlation coefficient, MCC = 0.0003, P > .10). Discussion: While drugs exhibit significant tissue specificity in vitro, there is little overlap with clinical indications. This can be attributed to factors such as underlying biological differences between in vitro models and patient tumors, or the inability of tissue-specific drugs to bring additional benefits beyond gold standard treatments during clinical trials. Conclusion: Our meta-analysis of pan-cancer drug screening datasets indicates that most tested drugs exhibit tissue-specific sensitivities in a large panel of cancer cell lines. However, the observed preclinical results do not translate to the clinical setting. Our results suggest that additional research into showing parallels between preclinical and clinical data is required to increase the translational potential of in vitro drug screening.