TP53, ATRX alterations, and low tumor mutation load feature IDH-wildtype giant cell glioblastoma despite exceptional ultra-mutated tumors

Background: Giant cell glioblastoma (gcGBM) is a rare morphological variant of IDH-wildtype (IDHwt) GBM that occurs in young adults and have a slightly better prognosis than "classic" IDHwt GBM. Methods: We studied 36 GBMs, 14 with a histopathological diagnosis of gcGBM and 22 with a giant cell component. We analyzed the genetic profile of the most frequently mutated genes in gliomas and assessed the tumor mutation load (TML) by gene-targeted next-generation sequencing. We validated our findings using The Cancer Genome Atlas (TCGA) data. Results: p53 was altered by gene mutation or protein overexpression in all cases, while driver IDH1, IDH2, BRAF, or H3F3A mutations were infrequent or absent. Compared to IDHwt GBMs, gcGBMs had a significant higher frequency of TP53, ATRX, RB1, and NF1 mutations, while lower frequency of EGFR amplification, CDKN2A deletion, and TERT promoter mutation. Almost all tumors had low TML values. The high TML observed in only 2 tumors was consistent with POLE and MSH2 mutations. In the histopathological review of TCGA IDHwt, TP53-mutant tumors identified giant cells in 37% of the cases. Considering our series and that of the TCGA, patients with TP53-mutant gcGBMs had better overall survival than those with TP53wt GBMs (log-rank test, P < .002). Conclusions: gcGBMs have molecular features that contrast to "classic" IDHwt GBMs: unusually frequent ATRX mutations and few EGFR amplifications and CDKN2A deletions, especially in tumors with a high number of giant cells. TML is frequently low, although exceptional high TML suggests a potential for immune checkpoint therapy in some cases, which may be relevant for personalized medicine

Achieving social and ecological goals of coastal management through integrated monitoring

Successful resource management relies on an understanding of the complex relationships between social and natural systems and their governance (Berkes et al., 2016). Taken together these interacting systems have been described as part of a social?ecological system (SES). Here, natural system refers to the biological and physical (biophysical) system and is used interchangeably with ecological system or ecosystem. Social system is used to characterize the interactions within and among human communities and their institutions, particularly those related to resource governance. The SES framework was developed to explain the many complexities of these relationships, but also to characterize what contexts and processes could help improve the management of natural resources (Ostrom, 2009). More specifically, SES has been defined as 'a system that includes societal (human) and ecological (biophysical) subsystems in mutual interactions' (Harrington et al., 2010) or a system 'where social and ecological systems are mutually dependent' (Fidel, Kliskey, Alessa, & Sutton, 2014). Management is most successful when it maximizes the benefits that natural resources provide to people and human stewardship of the environment. To date, limited evidence linking conservation and natural resource management interventions to human well?being exists (McKinnon et al., 2016). Monitoring must adapt to capture this complexity, and in particular, focus sharply on the interactions and interdependencies of natural and social systems. In the sustainability sciences, when monitoring is part of adaptive management, the purpose is to track ecosystem change over time, assess management implementation, and evaluate how well objectives were achieved (Kendall & Moore, 2012). Natural resource managers have monitored the biophysical status of ecosystems for decades; however, monitoring social systems has not been as well defined nor have the links between biophysical and social systems been adequately addressed (Wongbusarakum & Heenan, 2018). While conceptual frameworks for SES have advanced (Ostrom, 2009), practical approaches are needed to examine human–environment interactions in different contexts and specific scales (Fleischman et al., 2014; Kittinger, Finkbeiner, Glazier, & Crowder, 2012). Integration of monitoring efforts may enhance the understanding of human?derived benefits from natural systems and improve natural resource management

Life and death of a sewage treatment plant recorded in a coral skeleton δ15N record

We investigated the potential of coral skeleton δ15N (CS-δ15N) records for tracking anthropogenic-N sources in coral reef ecosystems. We produced a 56 yr-long CS-δ15N record (1958–2014) from a reef flat in Guam that has been exposed to varying 1) levels of sewage treatment 2) population density, and 3) land use. Increasing population density (from < 30 to 300 ind·km− 2) and land use changes in the watershed resulted in a ~ 1‰ enrichment of the CS-δ15N record until a sewage treatment plant (STP) started operation in 1975. Then, CS-δ15N stabilized, despite continued population density and land use changes. Based on population and other considerations, a continued increase in the sewage footprint might have been expected over this time. The stability of CS-δ15N, either contradicts this expectation, or indicates that the impacts on the outer reef at the coring site were buffered by the mixing of reef water with the open ocean