ABSTRACT
An ongoing change in legislation means decision-makers in Aotearoa New Zealand need to incorporate 'matauranga' (Maori knowledge/knowledge system) in central and local government legislation and strategy. This paper develops a 'te ao Maori' (Maori worldview) disaster risk reduction (DRR) framework for non-Maori decision-makers to guide them through this process. This 'interface framework' will function as a Rosetta Stone between the 'two worlds'. It intends to help central and local officials trained in Western knowledge-based disciplines by translating standard DRR concepts into a te ao Maori DRR framework. It draws on previous work examining Maori DRR thinking to create a novel framework that can help these stakeholders when they are converting higher-level theoretical insights from matauranga Maori into more practical 'on the ground' applications. This type of interface is essential: while Indigenous knowledge's utility is increasingly recognised nationally and internationally, a gap remains between this acknowledgement and its practical and applied integration into emergency management legislation and strategy.
Subject(s)
Disaster Planning , Risk Reduction Behavior , Humans , Decision Making , Disaster Planning/organization & administration , Disasters , Maori People , New ZealandSubject(s)
Awards and Prizes , Faculty, Medical , Humans , Academic Medical Centers , Pediatrics/educationABSTRACT
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.
ABSTRACT
Despite decades of research, mechanisms by which co-transcriptional alternative splicing events are targeted to the correct genomic locations to drive cell fate decisions remain unknown. By combining structural and molecular approaches, we define a new mechanism by which an essential transcription factor (TF) targets co-transcriptional splicing through physical and functional interaction with RNA and RNA binding proteins (RBPs). We show that an essential TF co-transcriptionally regulates sex-specific alternative splicing by directly interacting with a subset of target RNAs on chromatin and modulating the dynamics of hnRNPA2 homolog nuclear splicing condensates.
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Rhabdoid tumor predisposition syndrome type-1 (RTPS1) is characterized by germline pathogenic variants in SMARCB1 and development of INI1-deficient rhabdoid tumors in early childhood. Due to its poor prognosis, the risk of subsequent tumor development and the impact of surveillance at later ages are poorly understood. We retrospectively reviewed individuals referred to the Cancer Genetics Program at The Hospital for Sick Children for SMARCB1 genetic testing and/or surveillance for RTPS1. In addition, to explore characteristics of late-onset tumors in RTPS1, a literature review was conducted. Of eighty-three individuals (55 probands and 28 family members), 12 probands and 4 family members were genetically confirmed with RTPS1. Four pediatric probands with RTPS1 underwent surveillance. An additional three individuals, including one patient with 22q11.2 distal deletion without history of tumor, one patient with negative genetic testing results but clinically diagnosed with RTPS1, and one sibling identified through cascade testing, underwent surveillance. Three patients with RTPS1 developed tumors between the ages of 9 and 17, including malignant rhabdoid tumors (N = 3), schwannomas (N = 4), and epithelioid malignant peripheral nerve sheath tumor (N = 1). Three of these lesions were asymptomatically detected by surveillance. A literature review revealed 17 individuals with RTPS1 who developed INI1-deficient tumors after age five. Individuals with RTPS1 remain at elevated risk for developing INI1-deficient tumors after the peak age of rhabdoid tumor in early childhood. Extension of surveillance beyond 5 years of age could lead to improved survival and reduced morbidity for these patients, and prospective evaluation of revised approaches will be important.
ABSTRACT
BACKGROUND: Atypical Teratoid Rhabdoid Tumor (ATRT) is a rare, devastating, and largely incurable pediatric brain tumor. Although recent studies have uncovered three molecular subgroups of ATRTs with distinct disease patterns, and signaling features, the therapeutic profiles of ATRT subgroups remain incompletely elucidated. METHODS: We examined the effect of 465 kinase inhibitors on a panel of ATRT subgroup-specific cell lines. We then applied multi-omics analyses to investigate the underlying molecular mechanism of kinase inhibitor efficacy in ATRT subgroups. RESULTS: We observed that ATRT cell lines are broadly sensitive to inhibitors of the PI3K and MAPK signaling pathways, as well as CDKs, AURKA/B kinases, and PLK1. We identified two classes of multi-kinase inhibitors (MKIs) predominantly targeting receptors tyrosine kinase (RTKs) including PDGFR and EGFR/ERBB2 in MYC/TYR ATRT cells. The PDGFRB inhibitor, Dasatinib, synergistically affected MYC/TYR ATRT cell growth when combined with broad-acting PI3K and MAPK pathway inhibitors, including Rapamycin and Trametinib. We observed that MYC/TYR ATRT cells were also distinctly sensitive to various inhibitors of ERBB2 signaling. Transcriptional, H3K27Ac ChIPSeq, ATACSeq, and HiChIP analyses of primary MYC/TYR ATRTs revealed ERBB2 expression which correlated with differential methylation and activation of a distinct enhancer element by DNA looping. Significantly, we show the brain penetrant EGFR/ERBB2 inhibitor, Afatinib, specifically inhibited in vitro and in vivo growth of MYC/TYR ATRT cells. CONCLUSIONS: Taken together our studies suggest combined treatments with PDGFR and ERBB2-directed TKIs with inhibitors of the PI3K and MAPK pathways as an important new therapeutic strategy for the MYC/TYR subgroup of ATRTs.
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Pineal parenchymal tumors are rare neoplasms for which evidence-based treatment recommendations are lacking. These tumors vary in biology, clinical characteristics, and prognosis, requiring treatment that ranges from surgical resection alone to intensive multimodal antineoplastic therapy. Recently, international collaborative studies have shed light on the genomic landscape of these tumors, leading to refinement in molecular-based disease classification in the 5th edition of the World Health Organization (WHO) classification of tumors of the central nervous system. In this review, we summarize the literature on diagnostic and therapeutic approaches, and suggest pragmatic recommendations for the clinical management of patients presenting with intrinsic pineal region masses including parenchymal tumors (pineocytoma, pineal parenchymal tumor of intermediate differentiation, and pineoblastoma), pineal cyst, and papillary tumors of the pineal region.