Physiologic Determinants of Near-Infrared Spectroscopy-Derived Cerebral and Tissue Oxygen Saturation Measurements in Critically Ill Patients.

OBJECTIVES: Near-infrared spectroscopy (NIRS) is a potentially valuable modality to monitor the adequacy of oxygen delivery to the brain and other tissues in critically ill patients, but little is known about the physiologic determinants of NIRS-derived tissue oxygen saturations. The purpose of this study was to assess the contribution of routinely measured physiologic parameters to tissue oxygen saturation measured by NIRS. DESIGN: An observational sub-study of patients enrolled in the Role of Active Deresuscitation After Resuscitation-2 (RADAR-2) randomized feasibility trial. SETTING: Two ICUs in the United Kingdom. PATIENTS: Patients were recruited for the RADAR-2 study, which compared a conservative approach to fluid therapy and deresuscitation with usual care. Those included in this sub-study underwent continuous NIRS monitoring of cerebral oxygen saturations (SctO2) and quadriceps muscle tissue saturations (SmtO2). INTERVENTION: Synchronized and continuous mean arterial pressure (MAP), heart rate (HR), and pulse oximetry (oxygen saturation, Spo2) measurements were recorded alongside NIRS data. Arterial Paco2, Pao2, and hemoglobin concentration were recorded 12 hourly. Linear mixed effect models were used to investigate the association between these physiologic variables and cerebral and muscle tissue oxygen saturations. MEASUREMENTS AND MAIN RESULTS: Sixty-six patients were included in the analysis. Linear mixed models demonstrated that Paco2, Spo2, MAP, and HR were weakly associated with SctO2 but only explained 7.1% of the total variation. Spo2 and MAP were associated with SmtO2, but together only explained 0.8% of its total variation. The remaining variability was predominantly accounted for by between-subject differences. CONCLUSIONS: Our findings demonstrated that only a small proportion of variability in NIRS-derived cerebral and tissue oximetry measurements could be explained by routinely measured physiologic variables. We conclude that for NIRS to be a useful monitoring modality in critical care, considerable further research is required to understand physiologic determinants and prognostic significance.

Advancing disability-inclusive climate research and action, climate justice, and climate-resilient development.

Globally, more than 1 billion people with disabilities are disproportionately and differentially at risk from the climate crisis. Yet there is a notable absence of climate policy, programming, and research at the intersection of disability and climate change. Advancing climate justice urgently requires accelerated disability-inclusive climate action. We present pivotal research recommendations and guidance to advance disability-inclusive climate research and responses identified by a global interdisciplinary group of experts in disability, climate change, sustainable development, public health, environmental justice, humanitarianism, gender, Indigeneity, mental health, law, and planetary health. Climate-resilient development is a framework for enabling universal sustainable development. Advancing inclusive climate-resilient development requires a disability human rights approach that deepens understanding of how societal choices and actions-characterised by meaningful participation, inclusion, knowledge diversity in decision making, and co-design by and with people with disabilities and their representative organisations-build collective climate resilience benefiting disability communities and society at large while advancing planetary health.

Dual-Hit Strategy for Therapeutic Targeting of Pancreatic Cancer in Patient-Derived Xenograft Tumors.

PURPOSE: Paracrine activation of pro-fibrotic hedgehog (HH) signaling in pancreatic ductal adenocarcinoma (PDAC) results in stromal amplification that compromises tumor drug delivery, efficacy, and patient survival. Interdiction of HH-mediated tumor-stroma crosstalk with smoothened (SMO) inhibitors (SHHi) "primes" PDAC patient-derived xenograft (PDX) tumors for increased drug delivery by transiently increasing vascular patency/permeability, and thereby macromolecule delivery. However, patient tumor isolates vary in their responsiveness, and responders show co-induction of epithelial-mesenchymal transition (EMT). We aimed to identify the signal derangements responsible for EMT induction and reverse them and devise approaches to stratify SHHi-responsive tumors noninvasively based on clinically-quantifiable parameters. EXPERIMENTAL DESIGN: Animals underwent diffusion-weighted magnetic resonance (DW-MR) imaging for measurement of intratumor diffusivity. In parallel, tissue-level deposition of nanoparticle probes was quantified as a marker of vascular permeability/perfusion. Transcriptomic and bioinformatic analysis was employed to investigate SHHi-induced gene reprogramming and identify key "nodes" responsible for EMT induction. RESULTS: Multiple patient tumor isolates responded to short-term SHH inhibitor exposure with increased vascular patency and permeability, with proportionate increases in tumor diffusivity. Nonresponding PDXs did not. SHHi-treated tumors showed elevated FGF drive and distinctly higher nuclear localization of fibroblast growth factor receptor (FGFR1) in EMT-polarized tumor cells. Pan-FGFR inhibitor NVP-BGJ398 (Infigratinib) reversed the SHHi-induced EMT marker expression and nuclear FGFR1 accumulation without compromising the enhanced permeability effect. CONCLUSIONS: This dual-hit strategy of SMO and FGFR inhibition provides a clinically-translatable approach to compromise the profound impermeability of PDAC tumors. Furthermore, clinical deployment of DW-MR imaging could fulfill the essential clinical-translational requirement for patient stratification.

surviveR: a flexible shiny application for patient survival analysis.

Kaplan-Meier (KM) survival analyses based on complex patient categorization due to the burgeoning volumes of genomic, molecular and phenotypic data, are an increasingly important aspect of the biomedical researcher's toolkit. Commercial statistics and graphing packages for such analyses are functionally limited, whereas open-source tools have a high barrier-to-entry in terms of understanding of methodologies and computational expertise. We developed surviveR to address this unmet need for a survival analysis tool that can enable users with limited computational expertise to conduct routine but complex analyses. surviveR is a cloud-based Shiny application, that addresses our identified unmet need for an easy-to-use web-based tool that can plot and analyse survival based datasets. Integrated customization options allows a user with limited computational expertise to easily filter patients to enable custom cohort generation, automatically calculate log-rank test and Cox hazard ratios. Continuous datasets can be integrated, such as RNA or protein expression measurements which can be then used as categories for survival plotting. We further demonstrate the utility through exemplifying its application to a clinically relevant colorectal cancer patient dataset. surviveR is a cloud-based web application available at https://generatr.qub.ac.uk/app/surviveR , that can be used by non-experts users to perform complex custom survival analysis.

Pre- and Post-COVID-19 Outcomes for Israelis With Intellectual and Developmental Disabilities in the Community.

This study is among the first pre-post examinations to explore differences in subjective well-being, adaptive and maladaptive behavior, close relationships, community integration, family members' satisfaction with residential and community living settings, and family contact before and after the COVID-19 outbreak. Participants demonstrated better life satisfaction and adaptive behavior before COVID-19 than after COVID-19. Participants reported closer relationships with family members and peers before COVID-19 and closer relationships with staff members after COVID-19. The findings reveal mixed, although mostly negative, effects of the pandemic on people with intellectual and developmental disabilities in the community in Israel, in accord with extant comparative research.

classifieR a flexible interactive cloud-application for functional annotation of cancer transcriptomes.

BACKGROUND: Transcriptionally informed predictions are increasingly important for sub-typing cancer patients, understanding underlying biology and to inform novel treatment strategies. For instance, colorectal cancers (CRCs) can be classified into four CRC consensus molecular subgroups (CMS) or five intrinsic (CRIS) sub-types that have prognostic and predictive value. Breast cancer (BRCA) has five PAM50 molecular subgroups with similar value, and the OncotypeDX test provides transcriptomic based clinically actionable treatment-risk stratification. However, assigning samples to these subtypes and other transcriptionally inferred predictions is time consuming and requires significant bioinformatics experience. There is no "universal" method of using data from diverse assay/sequencing platforms to provide subgroup classification using the established classifier sets of genes (CMS, CRIS, PAM50, OncotypeDX), nor one which in provides additional useful functional annotations such as cellular composition, single-sample Gene Set Enrichment Analysis, or prediction of transcription factor activity. RESULTS: To address this bottleneck, we developed classifieR, an easy-to-use R-Shiny based web application that supports flexible rapid single sample annotation of transcriptional profiles derived from cancer patient samples form diverse platforms. We demonstrate the utility of the " classifieR" framework to applications focused on the analysis of transcriptional profiles from colorectal (classifieRc) and breast (classifieRb). Samples are annotated with disease relevant transcriptional subgroups (CMS/CRIS sub-types in classifieRc and PAM50/inferred OncotypeDX in classifieRb), estimation of cellular composition using MCP-counter and xCell, single-sample Gene Set Enrichment Analysis (ssGSEA) and transcription factor activity predictions with Discriminant Regulon Expression Analysis (DoRothEA). CONCLUSIONS: classifieR provides a framework which enables labs without access to a dedicated bioinformation can get information on the molecular makeup of their samples, providing an insight into patient prognosis, druggability and also as a tool for analysis and discovery. Applications are hosted online at https://generatr.qub.ac.uk/app/classifieRc and https://generatr.qub.ac.uk/app/classifieRb after signing up for an account on https://generatr.qub.ac.uk .

Molecular Subtyping Resource: a user-friendly tool for rapid biological discovery from transcriptional data.

Generation of transcriptional data has dramatically increased in the past decade, driving the development of analytical algorithms that enable interrogation of the biology underpinning the profiled samples. However, these resources require users to have expertise in data wrangling and analytics, reducing opportunities for biological discovery by 'wet-lab' users with a limited programming skillset. Although commercial solutions exist, costs for software access can be prohibitive for academic research groups. To address these challenges, we have developed an open source and user-friendly data analysis platform for on-the-fly bioinformatic interrogation of transcriptional data derived from human or mouse tissue, called Molecular Subtyping Resource (MouSR). This internet-accessible analytical tool, https://mousr.qub.ac.uk/, enables users to easily interrogate their data using an intuitive 'point-and-click' interface, which includes a suite of molecular characterisation options including quality control, differential gene expression, gene set enrichment and microenvironmental cell population analyses from RNA sequencing. The MouSR online tool provides a unique freely available option for users to perform rapid transcriptomic analyses and comprehensive interrogation of the signalling underpinning transcriptional datasets, which alleviates a major bottleneck for biological discovery. This article has an associated First Person interview with the first author of the paper.

3D Functional Genomics Screens Identify CREBBP as a Targetable Driver in Aggressive Triple-Negative Breast Cancer.

Triple-negative breast cancers (TNBC) are resistant to standard-of-care chemotherapy and lack known targetable driver gene alterations. Identification of novel drivers could aid the discovery of new treatment strategies for this hard-to-treat patient population, yet studies using high-throughput and accurate models to define the functions of driver genes in TNBC to date have been limited. Here, we employed unbiased functional genomics screening of the 200 most frequently mutated genes in breast cancer, using spheroid cultures to model in vivo-like conditions, and identified the histone acetyltransferase CREBBP as a novel tumor suppressor in TNBC. CREBBP protein expression in patient tumor samples was absent in 8% of TNBCs and at a high frequency in other tumors, including squamous lung cancer, where CREBBP-inactivating mutations are common. In TNBC, CREBBP alterations were associated with higher genomic heterogeneity and poorer patient survival and resulted in upregulation and dependency on a FOXM1 proliferative program. Targeting FOXM1-driven proliferation indirectly with clinical CDK4/6 inhibitors (CDK4/6i) selectively impaired growth in spheroids, cell line xenografts, and patient-derived models from multiple tumor types with CREBBP mutations or loss of protein expression. In conclusion, we have identified CREBBP as a novel driver in aggressive TNBC and identified an associated genetic vulnerability in tumor cells with alterations in CREBBP and provide a preclinical rationale for assessing CREBBP alterations as a biomarker of CDK4/6i response in a new patient population. SIGNIFICANCE: This study demonstrates that CREBBP genomic alterations drive aggressive TNBC, lung cancer, and lymphomas and may be selectively treated with clinical CDK4/6 inhibitors.

The pseudo-caspase FLIP(L) regulates cell fate following p53 activation.

p53 is the most frequently mutated, well-studied tumor-suppressor gene, yet the molecular basis of the switch from p53-induced cell-cycle arrest to apoptosis remains poorly understood. Using a combination of transcriptomics and functional genomics, we unexpectedly identified a nodal role for the caspase-8 paralog and only human pseudo-caspase, FLIP(L), in regulating this switch. Moreover, we identify FLIP(L) as a direct p53 transcriptional target gene that is rapidly up-regulated in response to Nutlin-3A, an MDM2 inhibitor that potently activates p53. Genetically or pharmacologically inhibiting expression of FLIP(L) using siRNA or entinostat (a clinically relevant class-I HDAC inhibitor) efficiently promoted apoptosis in colorectal cancer cells in response to Nutlin-3A, which otherwise predominantly induced cell-cycle arrest. Enhanced apoptosis was also observed when entinostat was combined with clinically relevant, p53-activating chemotherapy in vitro, and this translated into enhanced in vivo efficacy. Mechanistically, FLIP(L) inhibited p53-induced apoptosis by blocking activation of caspase-8 by the TRAIL-R2/DR5 death receptor; notably, this activation was not dependent on receptor engagement by its ligand, TRAIL. In the absence of caspase-8, another of its paralogs, caspase-10 (also transcriptionally up-regulated by p53), induced apoptosis in Nutlin-3A-treated, FLIP(L)-depleted cells, albeit to a lesser extent than in caspase-8-proficient cells. FLIP(L) depletion also modulated transcription of canonical p53 target genes, suppressing p53-induced expression of the cell-cycle regulator p21 and enhancing p53-induced up-regulation of proapoptotic PUMA. Thus, even in the absence of caspase-8/10, FLIP(L) silencing promoted p53-induced apoptosis by enhancing PUMA expression. Thus, we report unexpected, therapeutically relevant roles for FLIP(L) in determining cell fate following p53 activation.

ΔNp63γ/SRC/Slug Signaling Axis Promotes Epithelial-to-Mesenchymal Transition in Squamous Cancers.

Purpose: To investigate the regulation of epithelial-to-mesenchymal transition (EMT) in head and neck squamous cell carcinoma (HNSCC) and its importance in tumor invasion.Experimental Design: We use a three-dimensional invasive organotypic raft culture model of human foreskin keratinocytes expressing the E6/E7 genes of the human papilloma virus-16, coupled with bioinformatic and IHC analysis of patient samples to investigate the role played by EMT in invasion and identify effectors and upstream regulatory pathways.Results: We identify SNAI2 (Slug) as a critical effector of EMT-activated downstream of TP63 overexpression in HNSCC. Splice-form-specific depletion and rescue experiments further identify the ΔNp63γ isoform as both necessary and sufficient to activate the SRC signaling axis and SNAI2-mediated EMT and invasion. Moreover, elevated SRC levels are associated with poor outcome in patients with HNSCC in The Cancer Genome Atlas dataset. Importantly, the effects on EMT and invasions and SNAI2 expression can be reversed by genetic or pharmacologic inhibition of SRC.Conclusions: Overexpression of ΔNp63γ modulates cell invasion by inducing targetable SRC-Slug-evoked EMT in HNSCC, which can be reversed by inhibitors of the SRC signaling. Clin Cancer Res; 24(16); 3917-27. ©2018 AACR.