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The age of DHP and how pupfish colonized Devils Hole have always been a topic of interest. Recently, two different publications (Martin, Crawford, Turner, & Simons, & Saglam et al., ) tackled this issue using genomic data sets and demographic models but came to widely different conclusions. In their comment, Martin and Hohne () argue that our results (Saglam et al., ) were misleading because we used inappropriate calibration information and biased a priori assumptions. They then re-analysed our data using a "biologically informed" mutation rate prior and concluded that our data support a much younger age of DHP (12.6 kya) as opposed to 60 kya reported in our study. Below we will summarize why their arguments do not hold up and explore some of the inconsistencies between their claims and what was actually presented in our study. Furthermore, we will demonstrate their re-analyses provide no new information compared to what was presented in our original manuscript and reinforce our estimate of a 60 kya divergence of DHP as outweighing competing hypotheses.

We thank the authors for their thought-provoking comments on our paper. Most of the commentators agree that soil organic carbon (SOC) sequestration is important for improving the quality of soil, however they argue that we have overstated the potential of soil carbon sequestration. We welcome the comments and appreciate that the issue of SOC sequestration has always been somewhat factious (Schlesinger, 2000). We shall address the significance of the quantity “4 per mille”, reported sequestration rates, the limitation of carbon sequestration with time, and nutrient requirements. We clarify that our paper (Minasny et al., 2017) mainly deals with potentials for the 20 countries and regions, where SOC sequestration can also be seen as a way to improving the resilience of the soil to future climate change, that is, improving adaptation rather than mitigation. We believe that in some parts of the world where food security is threatened, the benefit of soil carbon management for adaptation should be stressed more than for mitigation. This is the reason why the 4 per mille initiative explicitly includes food security (Chabbi et al., 2017; Soussana et al., 2015). We need to add that the “4 per mille Soils for Food Security and Climate” initiative is just one of many national and global initiatives on SOC sequestration for mitigating climate change. The Intergovernmental Technical Panel on Soils (ITPS) of the Global Soil Partnership (GSP) discussed incorporating the topic of SOC in the IPCC Assessment Report (ARs), from AR6 onwards. The IPCC has also put a focus on soil in their upcoming special report “Climate Change and Land” (http://www.ipcc.ch/report/sr2/). The recent FAO Global Symposium (GSOC17) assembled experts engaged in FAO, GSP and its ITPS, IPCC, UNCCD-SPI and WMO activities to work together for the common goal of appropriate SOC management as part of overall sustainable soil management within the climate change mitigation and adaptation, sustainable development, Land Degradation Neutrality (LDN) and food security agendas (http://www.fao.org/about/meetings/soil-organic-carbon-symposium/en/). The Global Research Alliance on Agricultural Greenhouse Gases (GRA) focused on opportunities to reduce agricultural greenhouse gas emissions and increase soil carbon sequestration while still helping to meet food security objectives (http://globalresearchalliance.org/about/). The Common Agriculture Policy in the EU is currently being revised to include the potential use of SOC as an indicator. The 4 per mille initiative was launched at COP21, where the Paris Agreement was adopted, and one of the main aims of the Paris Agreement is to stop the planet from warming an additional two Celsius degrees. The two-degree target, although suggested by scientists through modelling work, was chosen more for political and pragmatic reasons whereby countries could agree on a target that they could work towards (Tollefson, 2015). And of course, there are many scientific critiques of this target (Knutti et al., 2016). Similarly, the 4 per mille initiative comes from a politically-driven aspiration, and our paper (Minasny et al., 2017) is a response to such an aspiration, to seek and outline possibilities based on current knowledge. The important concept is that soil and agriculture are part of the solution, and it is an interim and evidence-based solution that we can implement. Now we shall respond to each of the commentaries.

PURPOSE Multi-omics data integration captures tumor characteristics at multiple scales [i.e., microscopic (genomics and epigenetics), macroscopic (radiomics), clinical manifestation], provides a more comprehensive assessment of patient’s risk, and facilitates personalized therapies. In this work, we investigated the synergistic value of such multiple data sources for risk stratification and prediction of overall survival in IDH-wildtype glioblastoma tumors. METHODS Quantitative conventional and deep radiomics were extracted from pre-operative multi-parametric structural MRI (T1, T1Gd, T2, T2-FLAIR) of 501 patients with newly diagnosed glioblastoma. 389/501 and 112/501 patients formed our discovery and replication cohorts, respectively. Conventional radiomics were extracted from CaPTk, and deep radiomics from a pre-trained VGG-19 model. Multivariate SVM classification was performed on the discovery cohort to stratify patients in high, medium, and low-risk groups, using recursive feature elimination and 5-fold cross-validation. This model was independently tested on the replication cohort, and a radiomic-based survival prediction index (SPIradiomics) was calculated for each patient. Multi-stage integration of omics data, i.e., clinical (age, gender, extent of resection (EOR)), SPIradiomics, epigenetics (MGMT promoter methylation), and genomics (27 clinically relevant gene mutations via next-generation sequencing (NGS)), was performed using multivariate Cox proportional hazards (Cox-PH) model for stratification of the risk in the replication cohort. RESULTS Cox-PH modeling resulted in a concordance index (c-index) of 0.65 (95% CI:0.6–0.7) for clinical data, 0.67 (95% CI:0.62–0.72) for clinical and epigenetics, 0.70 (95% CI:0.65–0.75) for clinical and radiomics, 0.72 (95% CI:0.68–0.77) for clinical, epigenetics, and radiomics, and 0.75 (95% CI:0.71 – 0.78) for the multi-omics combination of all data; highlighting the added value of each layer of information in prediction of the patient’s risk. CONCLUSION Our results reinforce the synergistic value of integrated diagnostic methods for improving risk assessment of patients with glioblastoma that may pave the path towards a more personalized treatment planning.

PURPOSE Intratumor heterogeneity is frequent in glioblastoma (GB), giving rise to the tumor’s resistance to standard therapies and, ultimately, poorer clinical outcomes. Yet heterogeneity is often not quantified when assessing the genomic or methylomic profile of a tumor, when a single tissue sample is analyzed. This study proposes a novel approach to non-invasively characterize heterogeneity across glioblastoma using deep learning analysis MRI scans, using MGMT promoter methylation (MGMTpm) as a test-case, and validates the imaging-derived heterogeneity maps with MGMTpm heterogeneity measured via multiple tissue samples. METHODS Multi-parametric MRI (mpMRI) scans (T1, T1-Gd, T2, T2-FLAIR) of 181 patients with newly diagnosed glioblastoma, who underwent surgical tumor resection and had MGMT methylation assessment results, were retrospectively collected. We trained a 5-fold cross-validated deep convolutional neural network with six convolutional layers for a discovery cohort of 137 patients by placing overlapping regional patches over the whole tumor on mpMRI scans to capture spatial heterogeneity of MGMTpm status in different regions within the tumor. Our approach effectively hypothesized that despite heterogeneity in the training examples, dominant imaging patterns would be captured by deep learning. Trained model was independently applied to an unseen replication cohort of 44 patients, with multiple tissue specimens chosen from different spatial regions within the tumor, allowing us to compare imaging- and tissue-based MGMTpm estimates. RESULTS Our model yielded AUC of 0.75 (95% CI: 0.65–0.79) for global MGMT status prediction, which reflected the heterogeneity in MGMTpm, but also that a dominant imaging pattern of MGMT methylation seemed to emerge. In methylated patients with multiple tissue samples, a significant Pearson's correlation coefficient of 0.64 (p< 0.05) was found between imaging-based heterogeneity maps and MGMTpm heterogeneity. CONCLUSION A novel method based on mpMRI and deep neural networks yielded imaging-based heterogeneity maps that strongly associated with intratumor molecular heterogeneity in MGMT promoter methylated tumors.

BACKGROUND A therapeutic approach for chimeric antigen receptor T (CART) cell therapy in glioblastoma is targeting the epidermal growth factor receptor variant III (EGFRvIII), present in approximately 30% of glioblastomas. While earlier research demonstrated that phenotypic and genotypic characteristics in patient T cells and CART product may predict therapeutic success for hematologic malignancies, no study has investigated such determinants for clinical response in glioblastoma. METHODS We analyzed apheresis and infusion products for patients in the first-in-human trial of EGFRvIII-directed CART for recurrent glioblastoma (NCT02209376, n=9). Inherent T cell phenotypes were characterized by flow cytometry assay using a panel of 27 markers. Clinical response was quantified via engraftment in peripheral circulation and time-on-trial (ToT). RESULTS Mean area under the curve (AUC) peripheral CART engraftment for the study period was 213 log10 copies/μg (SD=173) and mean ToT was 134 days (SD=173). For the CAR+/CD4+ population in the infusion product, PD1 positivity was positively associated with AUC engraftment (r=0.753, P=0.012) and ToT (r=0.800, P=0.010). On immune checkpoint inhibitor analysis, CTLA-4, TIM3, and LAG3 did not exhibit significant associations with AUC engraftment or ToT. For activation markers, PD1/GRZB (r=0.794, P=0.011) and PD1/HLA-DR (r=0.769, P=0.016) were directly associated with ToT. PD1/GRZB was also predictive of AUC engraftment (r=0.794, P=0.011). For the CAR+/CD8+ population, PD1 positivity correlated with elevated AUC engraftment (r=0.639, P=0.047). In the CAR-/CD4+ population, PD1 remained positively correlated with AUC engraftment (r=0.690, P=0.027) and ToT (r=0.726, P=0.027). No significant associations were observed for apheresis products. CONCLUSION PD1 in CART infusion products predicted peripheral engraftment and ToT in recurrent glioblastoma. Double-positive cells for PD1 and activation markers also displayed a positive correlation, suggesting PD1 highlights a population of activated CAR T cells. Further characterization of predictors of EGFRvIII-directed CART treatment efficacy may improve selection of patients and starting T cell populations for clinical expansion.

PURPOSE Glioblastomas display significant heterogeneity on the molecular level, typically harboring several co-occurring mutations, which likely contributes to failure of molecularly targeted therapeutic approaches. Radiogenomics has emerged as a promising tool for in vivo characterization of this heterogeneity. We derive radiogenomic signatures of four mutations via machine learning (ML) analysis of multiparametric MRI (mpMRI) and evaluate them in the presence and absence of other co-occurring mutations. METHODS We identified a retrospective cohort of 359 IDH-wildtype glioblastoma patients, with available pre-operative mpMRI (T1, T1Gd, T2, T2-FLAIR) scans and targeted next generation sequencing (NGS) data. Radiomic features, including morphologic, histogram, texture, and Gabor wavelet descriptors, were extracted from the mpMRI. Multivariate predictive models were trained using cross-validated SVM with LASSO feature selection to predict mutation status in key driver genes, EGFR, PTEN, TP53, and NF1. ML models and spatial population atlases of genetic mutations were generated for stratification of the tumors (1) with co-occurring mutations versus wildtypes, (2) with exclusive mutations in each driver gene versus the tumors without any mutations in the pathways associated with these genes. RESULTS ML models yielded AUCs of 0.75 (95%CI:0.62-0.88) / 0.87 (95%CI:0.70-1) for co-occurring / exclusive EGFR mutations, 0.69 (95%CI:0.58-0.80) / 0.80 (95%CI:0.61-0.99) for co-occurring / exclusive PTEN mutations, and 0.77 (95%CI:0.65-0.88) / 0.86 (95%CI:0.69-1) for co-occurring / exclusive TP53 cases. Spatial atlases revealed a predisposition of left temporal lobe for NF1 and right frontotemporal region for TP53 in mutually exclusive tumors, which was not observed in the co-occurring mutation atlases. CONCLUSION Our results suggest the presence of distinct radiogenomic signatures of several glioblastoma mutations, which become even more pronounced when respective mutations do not co-occur with other mutations. These in vivo signatures can contribute to pre-operative stratification of patients for molecular targeted therapies, and potentially longitudinal monitoring of mutational changes during treatment.

PURPOSE Understanding the molecular underpinnings of imaging signatures of glioblastoma can provide insights into the biologic basis of tumor formation and progression as well as in vivo surrogate markers of molecular events driving the tumor’s phenotype. Through machine learning (ML), this study demonstrates that distinct imaging subtypes of glioblastoma are related to specific molecular alterations. METHODS Pre-operative multi-parametric MRI (T1, T2, T1CE, T2-FLAIR, DSC-MRI, DTI-MRI) of 669 IDH-wildtype subjects with glioblastoma were retrospectively collected and radiomic features, including descriptors of morphology, intensity, histogram, and texture, were extracted. Imaging subtypes were identified by a feature selection and clustering approach. Genomic markers, obtained using next generation sequencing (NGS) panel of 27 key glioblastoma genes, were available in 358/669 patients. Canonical correlation analysis (CCA) was conducted within each imaging subtype between the selected imaging features and genetic variables to seek maximum correlations between combinations of variables in imaging and genomic sets, and hence elucidate the molecular drivers of respective subtypes. RESULTS Three distinct imaging subtypes were identified by clustering on 50 selected features, representing characteristics of morphology, tumor neo-angiogenesis (DSC-derived features), and cellular density (DTI-derived features). These subtypes yielded differentiable overall survival based on Kaplan-Meier analysis. The canonical coefficients of each subtype revealed the distinction of the underlying genomic characteristics: one exhibited frequently mutated [ARID2, NTRK1], another subtype showed increased frequency of mutation in [ATRX, EGFR, PIK3R1], while the third was associated with all these genes and [NF1, PIK3CA, RB1], additionally. CONCLUSION We derived three distinct radiomic MRI subtypes for glioblastoma that highly correlate with the patients' survival and molecular genetic characteristics. Investigating the relationship between imaging and genomic information may enable identification of molecularly- and phenotypically-consistent tumor subtypes, which would offer non-invasive approaches for characterizing heterogeneity of glioblastoma, further facilitating patient stratification and treatment planning.

PURPOSE Multi-parametric MRI based radiomic signatures have highlighted the promise of artificial intelligence (AI) in neuro-oncology. However, inter-institution heterogeneity hinders generalization to data from unseen clinical institutions. To this end, we formulated the ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium for glioblastoma. Here, we seek non-invasive generalizable radiomic signatures from routine clinically-acquired MRI for prognostic stratification of glioblastoma patients. METHODS We identified a retrospective cohort of 606 patients with near/gross total tumor resection ( >90%), from 13 geographically-diverse institutions. All pre-operative structural MRI scans (T1,T1-Gd,T2,T2-FLAIR) were aligned to a common anatomical atlas. An automatic algorithm segmented the whole tumors (WTs) into 3 sub-compartments, i.e., enhancing (ET), necrotic core (NC), and peritumoral T2-FLAIR signal abnormality (ED). The combination of ET+NC defines the tumor core (TC). Quantitative radiomic features were extracted to generate our AI model to stratify patients into short- (< 14mts) and long-survivors ( >14mts). The model trained on 276 patients from a single institution was independently validated on 330 unseen patients from 12 left-out institutions, using the area-under-the-receiver-operating-characteristic-curve (AUC). RESULTS Each feature individually offered certain (limited but reproducible) value for identifying short-survivors: 1) TC closer to lateral ventricles (AUC=0.62); 2) larger ET/brain (AUC=0.61); 3) larger TC/brain (AUC=0.59); 4) larger WT/brain (AUC=0.55); 5) larger ET/WT (AUC=0.59); 6) smaller ED/WT (AUC=0.57); 7) larger ventricle deformations (AUC=0.6). Integrating all features and age, through a multivariate AI model, resulted in higher accuracy (AUC=0.7; 95% C.I.,0.64-0.77). CONCLUSION Prognostic stratification using basic radiomic features is highly reproducible across diverse institutions and patient populations. Multivariate integration yields relatively more accurate and generalizable radiomic signatures, across institutions. Our results offer promise for generalizable non-invasive in vivo signatures of survival prediction in patients with glioblastoma. Extracted features from clinically-acquired imaging, renders these signatures easier for clinical translation. Large-scale evaluation could contribute to improving patient management and treatment planning. *Indicates equal authorship.

Radiopharmaceuticals that incorporate radioactive iodine in combination with single‐photon emission computed tomography imaging play a key role in nuclear medicine, with applications in drug development and disease diagnosis. Despite this importance, there are relatively few general methods for the incorporation of radioiodine into small molecules. This work reports a rapid air‐ and moisture‐stable ipso‐iododeboronation procedure that uses NIS in the non‐toxic, green solvent dimethyl carbonate. The fast reaction and mild conditions of the gold‐catalysed method led to the development of a highly efficient process for the radiolabelling of arenes, which constitutes the first example of an application of homogenous gold catalysis to selective radiosynthesis. This was exemplified by the efficient synthesis of radiolabelled meta‐[125I]iodobenzylguanidine, a radiopharmaceutical that is used for the imaging and therapy of human norepinephrine transporter‐expressing tumours.

Summary: A number of mitochondrial diseases arise from single-nucleotide variant (SNV) accumulation in multiple mitochondria. Here, we present a method for identification of variants present at the single-mitochondrion level in individual mouse and human neuronal cells, allowing for extremely high-resolution study of mitochondrial mutation dynamics. We identified extensive heteroplasmy between individual mitochondrion, along with three high-confidence variants in mouse and one in human that were present in multiple mitochondria across cells. The pattern of variation revealed by single-mitochondrion data shows surprisingly pervasive levels of heteroplasmy in inbred mice. Distribution of SNV loci suggests inheritance of variants across generations, resulting in Poisson jackpot lines with large SNV load. Comparison of human and mouse variants suggests that the two species might employ distinct modes of somatic segregation. Single-mitochondrion resolution revealed mitochondria mutational dynamics that we hypothesize to affect risk probabilities for mutations reaching disease thresholds. : Morris et al. use independent sequencing of multiple individual mitochondria from mouse and human brain cells to show high pervasiveness of mutations. The mutations are heteroplasmic within single mitochondria and within and between cells. These findings suggest mechanisms by which mutations accumulate over time, resulting in mitochondrial dysfunction and disease. Keywords: single mitochondrion, single cell, human neuron, mouse neuron, single-nucleotide variation

Social connectedness is critical to older adults' well-being, but is defined inconsistently and its determinants and outcomes have not been comprehensively described. The current scoping review mapped the definitions, determinants, and outcomes of social connectedness for older adults. By identifying the conceptual features described in most articles, social connectedness was defined as: the opposite of loneliness, a subjective evaluation of the extent to which one has meaningful, close, and constructive relationships with others (i.e., individuals, groups, and society). Social connectedness is operationalized into: (a) caring about others and feeling cared about by others, and (b) feeling of belonging to a group or community. One's social network and life satisfaction were the most frequently proposed determinant and outcome, respectively. This review resulted in a clear definition of social connectedness and comprehensive description of its possible determinants and outcomes. This clarity will support the development of interventions to enhance social connectedness for older adults. [ Journal of Gerontological Nursing, 43 (7), 43–52.]

Therapeutic resistance remains a persistent challenge for patients with malignant tumors. Here, we reveal that endothelial cells (ECs) acquire transformation into mesenchymal stem cell (MSC)–like cells in glioblastoma (GBM), driving tumor resistance to cytotoxic treatment. Transcriptome analysis by RNA sequencing (RNA-seq) revealed that ECs undergo mesenchymal transformation and stemness-like activation in GBM microenvironment. Furthermore, we identified a c-Met-mediated axis that induces β-catenin phosphorylation at Ser(675) and Wnt signaling activation, inducing multidrug resistance–associated protein-1(MRP-1) expression and leading to EC stemness-like activation and chemoresistance. Last, genetic ablation of β-catenin in ECs overcome GBM tumor resistance to temozolomide (TMZ) chemotherapy in vivo. Combination of Wnt inhibition and TMZ chemotherapy eliminated tumor-associated ECs, inhibited GBM growth, and increased mouse survival. These findings identified a cell plasticity–based, microenvironment-dependent mechanism that controls tumor chemoresistance, and suggest that targeting Wnt/β-catenin–mediated EC transformation and stemness activation may overcome therapeutic resistance in GBM.

Background The context of care provided in long-term care homes is changing, as an increasing number of older adults are entering long-term care with advance stages of illness and higher care needs. Long-term care homes are quickly becoming the place of death for an increasing number of older adults, despite recent literature identifying inadequate and suboptimal levels of end-of-life care. Within long-term care, healthcare assistants represent 60%-70% of the unregulated workforce and provide 70%-90% of the direct care to residents. Research indicates that a high level of uncertainty exists surrounding the role of healthcare assistants in end-of-life care, with numerous studies reporting the role of healthcare assistants to be 'unclear' with varying levels of responsibilities and autonomy. Objective The purpose of this scoping review was to explore healthcare assistants' experiences and perspectives of their role in end-of-life care in long-term care. Methods We applied Arksey and O'Malley's methodological framework, with recommendations from Levac and colleagues' guiding principles. Electronic databases and the grey literature were searched for relevant articles. Search concepts included end-of-life care and healthcare assistants. Articles were included in this review if they explored healthcare assistants' experiences or perspectives of providing end-of-life care in long-term care. The peaceful end of life theory by Ruland and Moore (1998) was used to organise data extraction and analysis. Results A total of n = 15 articles met the inclusion criteria. The most predominant role-required behaviours reported by healthcare assistants were as follows: psychosocial support to significant others, knows the resident's care wishes and physical care with respect and dignity. The most predominant extra-role behaviours reported by healthcare assistants were as follows: becoming emotionally involved, acting as extended family and ensuring residents do not die alone. Conclusions Findings from this review expanded the concept of end-of-life care by illustrating the role-required and extra-role behaviours healthcare assistants perform when providing end-of-life care in long-term care. Implications for practice Findings from this scoping review highlight the numerous behaviours healthcare assistants perform outside their role description in order to provide end-of-life care to dying residents in long-term care. These findings could inform policymakers and managers of long-term care homes.

Malignant solid tumors are characterized by aberrant vascularity that fuels the formation of an immune-hostile microenvironment and induces resistance to immunotherapy. Vascular abnormalities may be driven by pro-angiogenic pathway activation and genetic reprogramming in tumor endothelial cells (ECs). Here, our kinome-wide screening of mesenchymal-like transcriptional activation in human glioblastoma (GBM)-derived ECs identifies p21-activated kinase 4 (PAK4) as a selective regulator of genetic reprogramming and aberrant vascularization. PAK4 knockout induces adhesion protein re-expression in ECs, reduces vascular abnormalities, improves T cell infiltration and inhibits GBM growth in mice. Moreover, PAK4 inhibition normalizes the tumor vascular microenvironment and sensitizes GBM to chimeric antigen receptor–T cell immunotherapy. Finally, we reveal a MEF2D/ZEB1- and SLUG-mediated mechanism by which PAK4 reprograms the EC transcriptome and downregulates claudin-14 and VCAM-1 expression, enhancing vessel permeability and reducing T cell adhesion to the endothelium. Thus, targeting PAK4-mediated EC plasticity may offer a unique opportunity to recondition the vascular microenvironment and strengthen cancer immunotherapy. Fan and colleagues report that inhibition of PAK4 normalizes the tumor vascular microenvironment and sensitizes glioblastomas to CAR-T cell immunotherapy.

Background Plasma cell-free DNA (cfDNA) concentration is lower in glioblastoma (GBM) compared to other solid tumors, which can lead to low circulating tumor DNA (ctDNA) detection. In this study, we investigated the relationship between multimodality magnetic resonance imaging (MRI) and histopathologic features with plasma cfDNA concentration and ctDNA detection in patients with treatment-naive GBM. Methods We analyzed plasma cfDNA concentration, MRI scans, and tumor histopathology from 42 adult patients with newly diagnosed GBM. Linear regression analysis was used to examine the relationship of plasma cfDNA concentration before surgery to imaging and histopathologic characteristics. In a subset of patients, imaging and histopathologic metrics were also compared between patients with and without a detected tumor somatic mutation. Results Tumor volume with elevated (>1.5 times contralateral white matter) rate transfer constant (Kep, a surrogate of blood–brain barrier [BBB] permeability) was independently associated with plasma cfDNA concentration (P = .001). Histopathologic characteristics independently associated with plasma cfDNA concentration included CD68+ macrophage density (P = .01) and size of tumor vessels (P = .01). Patients with higher (grade ≥3) perivascular CD68+ macrophage density had lower volume transfer constant (Ktrans, P = .01) compared to those with lower perivascular CD68+ macrophage density. Detection of at least 1 somatic mutation in plasma cfDNA was associated with significantly lower perivascular CD68+ macrophages (P = .01). Conclusions Metrics of BBB disruption and quantity and distribution of tumor-associated macrophages are associated with plasma cfDNA concentration and ctDNA detection in GBM patients. These findings represent an important step in understanding the factors that determine plasma cfDNA concentration and ctDNA detection.

BACKGROUND There is a lack of data on the use of direct-acting antivirals (DAA) on the risk of death and tumoral recurrence in patients with hepatitis C virus (HCV) and hepatocellular carcinoma (HCC) listed for liver transplantation (LT). We aimed to assess the impact of antiviral treatment on mortality and HCC recurrence patients with HCC-HCV. METHODS This was a retrospective multicenter study of patients with HCC-HCV listed for LT from 2005 to 2015. Patients were divided according to the antiviral treatment received after HCC diagnosis: DAA, interferon (IFN), or no antiviral. Intention-to-treat overall survival and HCC recurrence incidence were compared by the Kaplan-Meier method. Multivariable regression analysis was performed to identify risk factors for outcomes. RESULTS A total of 1012 HCV-HCC patients were listed for LT during the study period. The median follow-up was 4.0 (interquartile range = 2.3-6.7) years. Mortality was 5.6 (95% confidence interval [CI], 4.3-7.2), 13.1 (95% CI, 11.0-15.7), and 6.2 (95% CI, 5.4-7.2) deaths per 100 person-year among patients treated with DAA, IFN, and antiviral naive, respectively (P < 0.001). Of the 875 HCV-HCC transplant recipients, the 5-year recurrence-free survival was 93.4%, 84.8%, 73.9% for the pre-LT DAA, pre-LT IFN, and antiviral naive groups, respectively (P < 0.001). After multivariable regression, the use of pre-LT DAA was not associated to risk of recurrence (hazard ratio = 0.44 [95% CI, 0.19-1.00]). Post-LT DAA was not related to increased risk of recurrence (hazard ratio = 0.62 [95% CI, 0.33-1.16]). CONCLUSIONS In this multicenter intent-to-treat study, DAA therapy was not found to be a risk factor for mortality or HCC recurrence after adjusting for potential confounders.

Accurate methods for tracking individuals are crucial to the success of fisheries and aquaculture management. Management of migratory salmonid populations, which are important for the health of many economies, ecosystems, and indigenous cultures, is particularly dependent on data gathered from tagged fish. However, the physical tagging methods currently used have many challenges including cost, variable marker retention, and information limited to tagged individuals. Genetic tracking methods combat many of the problems associated with physical tags, but have their own challenges including high cost, potentially difficult marker design, and incompatibility of markers across species. Here we show the feasibility of a new genotyping method for parent-based tagging (PBT), where individuals are tracked through the inherent genetic relationships with their parents. We found that Rapture sequencing, a combination of restriction-site associated DNA and capture sequencing, provides sufficient data for parentage assignment. Additionally, the same capture bait set, which targets specific restriction-site associated DNA loci, can be used for both Rainbow Trout Oncorhynchus mykiss and Chinook Salmon Oncorhynchus tshawytscha. We input 248 single nucleotide polymorphisms from 1,121 samples to parentage assignment software and compared parent-offspring relationships of the spawning pairs recorded in a hatchery. Interestingly, our results suggest sperm contamination during hatchery spawning occurred in the production of 14% of offspring, further confirming the need for genetic tagging in accurately tracking individuals. PBT with Rapture successfully assigned progeny to parents with a 98.86% accuracy with sufficient genetic data. Cost for this pilot study was approximately $3 USD per sample. As costs vary based on the number of markers used and individuals sequenced, we expect that when implemented at a large-scale, per sample costs could be further decreased. We conclude that Rapture PBT provides a cost-effective and accurate alternative to the physical coded wire tags, and other genetic-based methods.

Chimeric antigen receptor (CAR)-engineered T cells have demonstrated remarkable success in the treatment of B cell malignancies. FDA approval of these therapies represents a watershed moment in the development of therapies for cancer. Despite the successes of the last decade, many patients will unfortunately not experience durable responses to CAR therapy. Emerging research has shed light on the biology responsible for these failures, and further highlighted the hurdles to broader success. Here, we review the recent research identifying how interactions between cancer cells and engineered immune cells result in resistance to CAR therapies.

Recent work has highlighted the tumor microenvironment as a central player in cancer. In particular, interactions between tumor and immune cells may help drive the development of brain tumors such as glioblastoma multiforme (GBM). Despite significant research into the molecular classification of glioblastoma, few studies have characterized in a comprehensive manner the immune infiltrate in situ and within different GBM subtypes.In this study, we use an unbiased, automated immunohistochemistry-based approach to determine the immune phenotype of the four GBM subtypes (classical, mesenchymal, neural and proneural) in a cohort of 98 patients. Tissue Micro Arrays (TMA) were stained for CD20 (B lymphocytes), CD5, CD3, CD4, CD8 (T lymphocytes), CD68 (microglia), and CD163 (bone marrow derived macrophages) antibodies. Using automated image analysis, the percentage of each immune population was calculated with respect to the total tumor cells. Mesenchymal GBMs displayed the highest percentage of microglia, macrophage, and lymphocyte infiltration. CD68+ and CD163+ cells were the most abundant cell populations in all four GBM subtypes, and a higher percentage of CD163+ cells was associated with a worse prognosis. We also compared our results to the relative composition of immune cell type infiltration (using RNA-seq data) across TCGA GBM tumors and validated our results obtained with immunohistochemistry with an external cohort and a different method. The results of this study offer a comprehensive analysis of the distribution and the infiltration of the immune components across the four commonly described GBM subgroups, setting the basis for a more detailed patient classification and new insights that may be used to better apply or design immunotherapies for GBM.

Chicken have a considerable impact in South American rural household economy as a source of animal protein (eggs and meat) and a major role in cultural manifestations (e.g. cockfighting, religious ceremonies, folklore). A large number of phenotypes and its heterogeneity are representative to the rusticity of the environments (from arid to tropical rain forest and high altitude) and agricultural systems (highly industrialized to subsistence agriculture). This heterogeneity also represents the successive introduction of domestic chicken into this subcontinent, which some consider predating Columbus arrival to South America. In this study, we have used next-generation sequencing of restriction site associated DNA to scan for genome-wide variation across 145 South American chicken representing local populations from six countries of South America (Colombia, Brazil, Ecuador, Peru, Bolivia, and Chile). After quality control, the genotypes of 122,801 single nucleotide polymorphisms (SNPs) were used to assess the genomic diversity and interpopulation genetic relationship between those populations and their potential sources. The estimated population genetic diversity displayed the gamefowl has the least diverse population (θπ=0.86; θS=0.70). This population is also the most divergent (FST=0.11) among the South American populations. The allele-sharing analysis and the admixture analysis revealed that the current diversity displayed by these populations resulted from multiple admixture events with a strong influence of the modern commercial egg-layer chicken (ranging between 44 to 79%) . It also revealed an unknown genetic component that is mostly present in the Easter Island population that is also present in local chicken populations from the South American Pacific fringe.

Glioblastoma treatment options remain limited due to its aggressive and invasive nature. It is increasingly appreciated that molecular heterogeneity between tumors and within tumors likely contributes to the lack of therapeutic advances. To maintain the inherent heterogeneity of glioblastoma, we employed a novel method to rapidly culture glioblastoma organoids (GBOs) directly from neurosurgical resection. GBOs are routinely generated around two weeks following initial resection. Comprehensive histologic and sequencing analyses demonstrated similarity to primary tumors. Leveraging clinical molecular and sequencing data, selected GBOs were treated with radiation/temozolamide and targeted inhibitor therapies. The effect on proliferation was measured by the percentage of KI67+ cells and gene set enrichment (GSEA) analysis was performed to compare the pre-treated expression signature amongst responsive and non-responsive tumors. Treatment of organoids with radiation/temozolamide led to a decrease in the percentage of KI67+ cells in four of eight patient-derived organoid lines with some evidence of correlative radiographic response Gene sets associated with radiation response and TNF signaling were enriched in radiation/temozolamide sensitive GBOs. GBO response to EGFR inhibition via gefitinib treatment was specific to EGFR altered tumors, whose expression also enriched for EGF signaling pathway expression. Two GBOs had downstream NF1 mutations that responded to the MEK inhibitor trametinib. On GSEA, gene expression of NF1 mutated GBOs enriched for RAS signaling. One GBO line was found to have a PI3K mutation and responded dramatically to mTOR inhibition via everolimus. Dichotomous efficacy of MEK and mTOR inhibition was also noted by tumor-specific changes in GBO diameter following treatment. This novel culturing method of GBOs maintains intertumoral and intratumoral heterogeneity and allows for therapeutic testing within two weeks of neurosurgical resection. As clinical sequencing because increasingly prevalent, GBOs may become a valuable tool to functionally test mutation-specific treatment strategies in a patient-specific manner within a clinically relevant time frame.

BACKGROUND This study builds on the results of the University of Pennsylvania sponsored phase I study of a single peripheral infusion of chimeric antigen receptor (CAR) T cells targeting epidermal growth factor receptor variant III (EGFRvIII) in recurrent glioblastoma (GBM) (NCT02209376). A dose of 5x108 CART-EGFRvIII cells was safe, and the cells were able to expand in the host and reach the GBM tumor in the brain. In addition, there was no cross-reactivity of CART-EGFRvIII cells with wild-type EGFR normally expressed by human tissues. Some patients required tumor resection after CAR T cell infusion. In situ evaluation of the tumor microenvironment demonstrated increased and robust expression of inhibitory molecules, such as programmed death-ligand 1 (PD-L1), compared to pre–CART-EGFRvIII tumor specimens. Therefore, we hypothesized that using a combination of CART-EGFRvIII cells and a PD-1 inhibitor would improve the outcome of the treatment. METHODS This single-center study (NCT03726515) has a single-arm, open-label, phase 1 design and will enroll 7 patients with newly diagnosed, O6-methylguanine-methyltransferase (MGMT)-unmethylated, EGFRvIII+ GBM. Following maximal safe tumor resection, patients receive a short course of adjuvant radiation with a total dose of 40 Gy administered in 15 fractions. Peripheral IV infusions of 2x108 CART-EGFRvIII cells and 200mg pembrolizumab begin 2–3 weeks after completing radiation therapy. Thereafter, subjects receive CART-EGFRvIII cells + pembrolizumab in 3-week cycles for up to 3 infusions of CART-EGFRvIII cells and 4 infusions of pembrolizumab. The primary endpoint of the study is the safety and tolerability of administering multiple infusions of CART-EGFRvIII cells in combination with pembrolizumab, as measured by the occurrence of study-related adverse events. Secondary endpoints include overall survival, progression-free survival, and objective response rate. PROGRESS: At 5 June 2019, 2 patients have been enrolled and treated on study.

High grade glioma is the most common malignant primary brain tumor. Despite the best available therapy, the median survival is limited. Chimeric antigen receptor (CAR)-T cells effectively attack target positive tumor cells, demonstrating a promising possible treatment. Based on our previous clinical and pre-clinical studies, we utilized epidermal growth factor receptor variant III (EGFRvIII) and interleukin 13 receptor subunit alpha 2 (IL13Rα2) targeting single-chain variable fragments (scFvs) to generate bi-specific tandem CAR T cells and bi-specific parallel CAR T cells to decrease the potential of antigen escape and tumor recurrence. 5, 10, 15 or 20 flexible amino acids were utilized to link scFvs in tandem CARs. Ribosomal “skipping” 2A peptides were utilized to generate parallel CAR T cells. Flow-based IL13Rα2 staining on glioma stem cells (GSCs) showed 7 out 11 cases positive (64%) heterogeneous intratumoral expression. Tandem CAR T cells and parallel CAR T cells upregulated CD69 expression (P< 0.0001), generated IFNγ, interleukin 2 and TNFα (P< 0.0001), as well as exhibiting cytotoxic activity (P< 0.0001) when compared against un-transduced T cells, in co-culture with either single- or double-target positive GSCs. There was no significant difference between different lengths of linker in tandem CAR T cells. Parallel CAR T cells generated a larger cytokine response (P< 0.0001) and more effectively killed target positive cells (P< 0.05) than tandem CAR T cells. In summary, glioma associated target expression is heterogeneous in GSCs. Multivalent tandem CAR T cells and parallel CAR T cells effectively respond to target expressing tumor cells. The function of tandem CAR T cells is not relative with the length of linker. Parallel CAR T cells are a more promising strategy in generating gene modified multivalent targeting T cells.

This paper argues that international sport organizations may be able to use value congruity in order to assess the effect of their current corporate social responsibility strategy and develop better relationships with their consumers. Six studies (n = 1197) conducted in the United States and France before and after the 2016 and 2018 Olympic Games revealed that brand-based value congruity (BBVC) has a significant positive influence on relationship quality, which is consistent with other measures of self-congruity from the literature. The model demonstrated cross-cultural invariance. The Olympic Games influenced some of the direct and indirect effects of BBVC without significantly affecting the model.

Purpose: The clinical utility of plasma cell-free DNA (cfDNA) has not been assessed prospectively in patients with glioblastoma (GBM). We aimed to determine the prognostic impact of plasma cfDNA in GBM, as well as its role as a surrogate of tumor burden and substrate for next-generation sequencing (NGS). Experimental Design: We conducted a prospective cohort study of 42 patients with newly diagnosed GBM. Plasma cfDNA was quantified at baseline prior to initial tumor resection and longitudinally during chemoradiotherapy. Plasma cfDNA was assessed for its association with progression-free survival (PFS) and overall survival (OS), correlated with radiographic tumor burden, and subjected to a targeted NGS panel. Results: Prior to initial surgery, GBM patients had higher plasma cfDNA concentration than age-matched healthy controls (mean 13.4 vs. 6.7 ng/mL, P < 0.001). Plasma cfDNA concentration was correlated with radiographic tumor burden on patients' first post-radiation magnetic resonance imaging scan (ρ = 0.77, P = 0.003) and tended to rise prior to or concurrently with radiographic tumor progression. Preoperative plasma cfDNA concentration above the mean (>13.4 ng/mL) was associated with inferior PFS (median 4.9 vs. 9.5 months, P = 0.038). Detection of ≥1 somatic mutation in plasma cfDNA occurred in 55% of patients and was associated with nonstatistically significant decreases in PFS (median 6.0 vs. 8.7 months, P = 0.093) and OS (median 5.5 vs. 9.2 months, P = 0.053). Conclusions: Plasma cfDNA may be an effective prognostic tool and surrogate of tumor burden in newly diagnosed GBM. Detection of somatic alterations in plasma is feasible when samples are obtained prior to initial surgical resection.

Two ways to get tangled? Neurodegeneration in Alzheimer's disease dementia is associated with neurofibrillary tangles composed of aggregated tau protein. Darwich et al. describe an additional form of autosomal-dominant dementia with neurofibrillary tangles linked to a hypomorph mutation in valosin-containing protein (VCP). VCP was found to disaggregate pathologic tau, and the hypomorph mutation increased tau accumulation in cells and mice. These findings highlight the role of protein turnover in maintaining neuronal health and suggest that VCP may provide a therapeutic target for Alzheimer's disease. Science , this issue p. eaay8826

Introduction: Gliosarcoma (GS) is a rare, malignant mixed tumor of the central nervous system with a median survival of approximately 13 months across multiple studies. Although the value of the extent of resection (EOR) has been confirmed as a prognostic survival factor in glioblastoma, no such association has been defined for GS. The goal of this study was to establish an association between EOR and survival and to determine if a threshold of resection exists for which a survival benefit is conferred in GS. Methods: The authors identified 11 patients with histologically confirmed GS between January 2005 and January 2015, treated at the Hospital of the University of Pennsylvania. Clinical, radiographic, and outcome data were retrospectively reviewed. Volumetric analysis was completed using semi-automated segmentation to measure the change in contrast-enhancing material based on preoperative T1-contrast (T1c) and postoperative T1 & T1c magnetic resonance imaging (MRI) scans. A log-rank test was completed to confirm an association between EOR and survival, and a series of Kaplan-Meier curves were constructed to determine an EOR threshold. Univariate Cox proportional hazards model (CPHM) followed by multivariate CPHM was also completed to evaluate associations between the prognostic clinical and immunohistochemistry variables under consideration. Results: Extent of resection categories were defined as gross total resection (GTR >95%), subtotal resection (STR 90%-95%), and partial resection (PR

BACKGROUND Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represent the effects of treatment, or pseudo-progression (PsP). We hypothesize that quantitative machine learning analysis of clinically acquired multiparametric magnetic resonance imaging (mpMRI) can identify subvisual imaging characteristics to provide robust, noninvasive imaging signatures that can distinguish true progression (TP) from PsP. METHODS We evaluated independent discovery (n = 40) and replication (n = 23) cohorts of glioblastoma patients who underwent second resection due to progressive radiographic changes suspicious for recurrence. Deep learning and conventional feature extraction methods were used to extract quantitative characteristics from the mpMRI scans. Multivariate analysis of these features revealed radiophenotypic signatures distinguishing among TP, PsP, and mixed response that compared with similar categories blindly defined by board-certified neuropathologists. Additionally, interinstitutional validation was performed on 20 new patients. RESULTS Patients who demonstrate TP on neuropathology are significantly different (P

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults and carries a dismal prognosis. Significant challenges in the care of patients with GBM include marked vascular heterogeneity and arteriovenous (AV) shunting, which results in tumor hypoxia and inadequate delivery of systemic treatments to reach tumor cells. In this study, we investigated the utility of different MR perfusion techniques to detect and quantify arteriovenous (AV) shunting and tumor hypoxia in patients with GBM. Macrovascular shunting was present in 33% of subjects, with the degree of shunting ranging from (37–60%) using arterial spin labeling perfusion. Among the dynamic susceptibility contrast-enhanced perfusion curve features, there were a strong negative correlation between hypoxia score, DSC perfusion curve recovery slope (r = −0.72, P = 0.018) and angle (r = −0.73, P = 0.015). The results of this study support the possibility of using arterial spin labeling and pattern analysis of dynamic susceptibility contrast-enhanced MR Imaging for evaluation of arteriovenous shunting and tumor hypoxia in glioblastoma.

Molecular profiling of glioblastoma has revealed complex cytogenetic, epigenetic, and molecular abnormalities that are necessary for diagnosis, prognosis, and treatment. Our neuro-oncology group has developed a data-driven, institutional consensus guideline for efficient and optimal workup of glioblastomas based on our routine performance of molecular testing. We describe our institution’s testing algorithm, assay development, and genetic findings in glioblastoma, to illustrate current practices and challenges in neuropathology related to molecular and genetic testing. We have found that coordination of test requisition, tissue handling, and incorporation of results into the final pathologic diagnosis by the neuropathologist improve patient care. Here, we present analysis of O 6 -methylguanine-DNA-methyltransferase promoter methylation and next-generation sequencing results of 189 patients, obtained utilizing our internal processes led by the neuropathology team. Our institutional pathway for neuropathologist-driven molecular testing has streamlined the management of glioblastoma samples for efficient return of results for incorporation of genomic data into the pathological diagnosis and optimal patient care.

When incipient species meet in secondary contact, natural selection can rapidly reduce costly reproductive interactions by directly targeting reproductive traits. This process, called reproductive character displacement (RCD), leaves a characteristic pattern of geographic variation where divergence of traits between species is greater in sympatry than allopatry. However, because other forces can also cause similar patterns, care must be given in separating pattern from process. Here we show how the phylo-comparative method together with genomic data can be used to evaluate evolutionary processes at the population level in closely related species. Using this framework, we test the role of RCD in speciation of two cricket species endemic to Anatolian mountains by quantifying patterns of character displacement, rates of evolution and adaptive divergence. Our results show differing patterns of character displacement between species for reproductive vs. non-reproductive characters and strong patterns of asymmetric divergence. We demonstrate diversification results from rapid divergence of reproductive traits towards multiple optima under the dual influence of strong drift and selection. These results present the first solid evidence for RCD in Anatolian mountains, quantify the amount of drift and selection necessary for RCD to lead to speciation, and demonstrate the utility of phylo-comparative methods for quantifying evolutionary parameters at the population level.

Cattle have recurrent follicular waves every 7-10 days in most physiological situations; an FSH increase is associated with emergence of the wave and LH pulse frequency determines the fate of the dominant follicle. To control oestrus with hormones it is necessary to ensure that either induced corpus luteum regression or the termination of a progestogen treatment coincides with the selection of the dominant follicle during the wave, to give a precise onset of oestrus and high fertility. The exogenous administration of progesterone or progestagen blocks the normal turnover of the dominant follicle once the corpus luteum regresses. Thus, the effects of duration of dominance of the preovulatory follicle on onset of oestrus and fertility were examined. The variation in onset of oestrus was reduced but occurred 5-9 h later after 4 versus 8 days of dominance; pregnancy rate was also affected with dominance periods of 2-4, 4-8 and > 10 days resulting in 0, 10-15% or 20-50% reduction in pregnancy rates, respectively. The necessity for short duration of dominance of the preovulatory follicle means that to ensure high fertility the follicular wave needs to be regulated when using hormones to control oestrus. Two approaches were examined, namely the use of GnRH or oestradiol at time of progesterone intravaginal releasing device insertion. The effect of 250 micrograms of synthetic GnRH on the fate of an existing follicle wave was to ovulate the dominant follicle (20/20 cows) and a new wave emerged 1.6 +/- 0.3 days later; however, there was no effect of GnRH on the wave if administered before dominant follicle selection. The effect of oestradiol concentrations on suppression of FSH in ovariectomized heifers showed that increasing oestradiol to 10-15 pg ml-1 caused a 37 +/- 6.9% decrease in FSH for 24 h, with a subsequent increase to pretreatment values by 57 +/- 13 h. In cyclic heifers, increasing oestradiol to > 10 pg ml-1 in conjunction with progesterone treatment at emergence of the first wave of the cycle affected the current follicle wave by either preventing dominant follicle selection or decreasing diameter of the dominant follicle, without consistently affecting the interval to new wave emergence. Increase of oestradiol after dominance, however, delayed new wave emergence by 2-5 days. A better understanding of the hormonal control of follicle waves will lead to development of improved hormonal regimens to control oestrus sufficiently to give high pregnancy rates to a single AI without recourse to detection of oestrus.

© 2019 Elsevier B.V. Objective: Corpus callosum (CC) involvement is a poor prognostic factor in patients with glioblastoma (GBM). The purpose of this study was to determine whether diffusion tensor imaging (DTI) can quantify occult tumor infiltration in the CC and predict the overall survival in GBM patients. Methods: Forty-eight patients with pathologically proven GBM and 17 normal subjects were included in this retrospective study. Patients were divided into four groups based on CC invasion and overall survival: long survivors without CC invasion; short survivors without CC invasion; long survivors with CC invasion; short survivors with CC invasion. All patients underwent DTI at 3T MRI scanner. Fractional anisotropy (FA) and mean diffusivity (MD) values were measured from genu, mid-body, and splenium of the CC. The mean values of these parameters were compared between different groups and Kaplan Meier curves were used for prediction of overall survival. Results: Patients with short survival and CC invasion had the lowest FA values (0.64 ± 0.05) from the CC compared with other groups (p < 0.05). Receiver operator characteristic curve (ROC) analysis indicated that a FA cutoff value of 0.70 was the best predictor for overall survival with an area under the curve (AUC) of 0.77, sensitivity 1, specificity 0.59. Kaplan-Meier survival curves demonstrated that the mean survival time was significantly longer for patients with high FA (>0.70) compared with those with low FA (

Glioblastoma (GBM) is the most prevalent and lethal primary brain tumor, which carries a poor prognosis due to a high level of therapeutic resistance and rate of tumor recurrence. Underlying this aggressive behavior is extraordinary genomic and cellular heterogeneity, conferring numerous avenues for treatment escape and refractory growth. This work leverages single cell genomic analyses to link somatic mutations to transcriptomic signatures within the native tumor tissue. We implemented a three-stage pipeline to perform the following tasks: variant calling, machine learning (ML) classification, and biological pathway analysis. Somatic variants were called from smart-seq based scRNA-seq data and filtered based on predicted lethality, reference in cancer mutation databases e.g. COSMIC, and population prevalence. In the second stage, the genotyped cells and normalized gene expression profiles were pre-processed using differential gene expression, and input into ML classifiers trained on the task of predicting mutation status. The utilized ML models included a Support Vector Machine and Ridge Classifier and were selected based on performance and interpretability. The efficacy of the models was evaluated using the AUC-ROC metric across multiple dataset partitions. The output of this stage was a set of “important genes” identified using the learned ML model weights. In the third stage, the sets of identified genes were subsampled and analyzed using the g:Profiler API to identify significant biological pathways. The analysis was performed on 2 datasets containing 677 samples from 5 patients and 1091 samples from 4 patients. The EGFRvIII mutation was used to validate the performance of the methodology due to its prevalence in primary GBM tumors. The mutation was detected in 17 single-cell samples. The ML models both produced a mean AUC-ROC of 0.93 [0.92, 094], and the classifiers identified NPM1, TCEA1, PPIA, SUMO2, among other genes, to be of significance. The individual genes have functions involving cell cycle regulation and protein folding, while the identified biological pathways associated with gene subsets were linked to ribonuclease activity and transcription factor post-transcriptional modifications. The ML component was applied to an additional dataset containing cell samples from 4 patients and correctly identified the 2 patients positive for EGFRvIII. The larger analysis identified point mutations in EGFR, TP53, and ATRX, and the classifiers exhibited AUC-ROC metrics ranging from 0.94 [0.93, 0.94] to 0.99 [0.99, 1.0]. Overall, we developed and employed a pipeline to link somatic variants with their gene expression signatures at the single cell level, identified biological pathways for further examination and established a ML classifier that can be applied to high-throughput scRNA-seq methods that lack the transcript coverage of the variant loci. Citation Format: Christopher Streiffer, Daniel Zhang, Ryan Salinas, Steven Brem, Donald O'Rourke, Zev Binder, Han-Chiao Isaac Chen, Hongjun Song. Identifying the transcriptomic signatures of mutational heterogeneity in GBM using single cell genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2203.

PURPOSE Differentiation of true tumor progression from pseudoprogression (PsP) is a major unmet need in patients with glioblastoma (GBM). [18F]Fluciclovine is a synthetic amino acid PET radiotracer that is FDA approved in the setting of biochemical recurrence in prostate cancer. The aim of this study was to assess the value of [18F]Fluciclovine PET in differentiation of true tumor progression and PsP in post-treatment of glioblastoma. METHODS 15 patients with GBM with new contrast-enhancing lesions or lesions showing increased enhancement (>25% increase) on standard MRI after completion of radiation underwent 60-minutes dynamic [18F]Fluciclovine PET imaging. Patients subsequently (within 1 week) underwent resection of the enhancing lesion and the tumor percentage vs treatment-related changes were quantified on histopathology. Patients were considered true tumor progression if tumor represented ≥ 50% of the resected specimen and considered PsP if treatment-related changes represented ≥70% of the resected specimen. Summed 30- to 40-minute post-injection PET images were used to measure SUVpeak, SUVmax, and 50% threshold SUVmean. RESULTS 10 patients with true tumor progression and 5 patients with PsP were included. Patients who demonstrated true tumor progression had significantly higher SUVpeak compared to patients with PsP (5.3±1.4 vs 3.1± 0.9, p=0.002, AUC=0.92, p DISCUSSION Our preliminary results indicated that [18F]Fluciclovine PET imaging can accurately differentiate true tumor progression from PsP. Further studies are required to confirm these promising early results and determine the optimal criteria for interpreting [18F]Fluciclovine PET to distinguish PsP from true tumor progression.

Investigation of human CNS disease and drug effects has been hampered by the lack of a system that enables single-cell analysis of live adult patient brain cells. We developed a culturing system, based on a papain-aided procedure, for resected adult human brain tissue removed during neurosurgery. We performed single-cell transcriptomics on over 300 cells, permitting identification of oligodendrocytes, microglia, neurons, endothelial cells, and astrocytes after 3 weeks in culture. Using deep sequencing, we detected over 12,000 expressed genes, including hundreds of cell-type-enriched mRNAs, lncRNAs and pri-miRNAs. We describe cell-type- and patient-specific transcriptional hierarchies. Single-cell transcriptomics on cultured live adult patient derived cells is a prime example of the promise of personalized precision medicine. Because these cells derive from subjects ranging in age into their sixties, this system permits human aging studies previously possible only in rodent systems.

The extent of ochratoxin A (OTA) contamination of domestically produced foods sold across Canada was determined from 2009 to 2014 with sampling and testing occurring each fiscal year. Cereal-based, fruit-based, and soy-based food samples (n = 6,857) were analyzed. Almost half of the samples (3,200; 47%) did not contain detectable concentrations of OTA. The remaining 3,657 samples contained OTA at 0.040 to 631 ng/g. Wheat, oats, milled products of other grains (such as rye and buckwheat), and to a lesser extent corn products and their derived foods were the most significant potential sources of OTA exposure for the Canadian population. Wine, grape juice, soy products, beer, dairy-based infant formula, and licorice candy were not significant contributors to OTA consumption. Spices had the highest OTA concentrations; but because so little is ingested, these foods are not considered to be a significant source of OTA. In contrast, infant formulas and cereals can be important dietary sources of OTA. Infant cereals containing oats and infant formulas containing soy had detectable concentrations of OTA, some of which exceeded the proposed Canadian guidelines. The prevalence and concentrations of OTA in major crops (wheat, corn, and oats) varied widely across years. Because these foods were purchased at retail stores, no information was available on the OTA concentrations in the raw materials, the storage conditions before purchase of the samples, or the origin of the ingredients (may include blends of raw materials from different years and/or different geographical regions of Canada); therefore, impact of these factors could not be assessed. Overall, 2.3% of the samples exceeded the proposed Canadian OTA regulatory limits and 2.7% exceeded the current European Union (EU) OTA regulatory limits. These results are consistent with a Health Canada exposure assessment published in 2010, despite the inclusion of a wider range of products and confirm the safety of foods widely available across Canada.

Many soil science laboratories are now equipped with technology platforms in portable visible near infrared (vis-NIR) and X-ray fluorescence (XRF) spectrometers. These technologies have complementary capabilities, where XRF is known to accurately measure the soil's inorganic element concentration, and vis-NIR has the ability to estimate the soil's organic component and mineralogy suites. In this study data mining was used to estimate soil properties from the vis-NIR spectra, and in a novel way from the XRF spectral data. The prediction outcomes were combined into a single prediction outcome, using formal methods called model averaging procedures. Combining model outcomes derived from spectra using model averaging techniques improves or maintains the prediction status (as ratio of performance to inter-quartile distance) of vis-NIR and XRF models for a wide range of soil properties of agronomic importance. Overall, the relative improvement in %RMSE ranged from 4 to 44%. Weight preference in model averaging was related to the inference of soil chemical and physical properties from vis-NIR and XRF spectra. For example, the weights preference the vis-NIR predictions for soil pH, soil carbon (C), clay, and XRF predictions for most of the elemental soil properties. Based on both the relative improvement in RMSE and RPIQ status, model averaging was found to be suitable for soil pH, soil C (soil organic C (SOC) and total C (TC)), soil texture (sand and clay), CEC and total elements K, Mg, Co, Cr and Mn. Optimum prediction performance for total elements Cu and Zn is achieved by XRF alone. The unreliable RPIQ status for total elements P, S, Mo, Se and exchangeable Ca, Mg, K, and Na derived from vis-NIR and XRF predictions in this study did not improve with model averaging. Overall, Granger-Ramanathan averaging produced similar or better outcomes compared to variance weighted averaging. This model averaging approach is more simple to compute requiring only to fit a simple multiple linear regression model, unlike the VWA approach in which the weighting is estimated for each soil property, and thus in the interests of parsimony is recommended as the model averaging technique to be adopted as protocol. More conventional use of portable XRF in soil analysis is to employ the elemental concentrations measured by the XRF device to predict other soil properties, generally applying multiple linear regression models. When XRF is used in a conventional way to determine elemental concentrations it was demonstrated to be highly reliable for elemental concentrations present in high concentrations, but predictions of elemental content derived from XRF spectra was more effective for elements present in low concentrations. This in turn reduces the capacity of XRF elemental concentrations to be used in the prediction of other soil properties by inference.

Proposed legislation to secure and maintain soil quality in Europe has generated interest surrounding how best to characterize soil geochemistry, and how to assess and monitor soil contamination. Visible-near infrared (vis-NIR), mid-infrared (MIR), and portable X-ray fluorescence (pXRF) spectroscopy can reduce time and cost associated with new soil monitoring programs. Before becoming deployable, accuracy of these techniques needs to be quantified. This study investigated potential of these techniques to characterize a full suite of soil geochemistry (40 elements), pH, and soil organic carbon (SOC) in a diverse set of agricultural soils from the Irish National Soil Database (NSDB) archive. Cubist models were employed to assess goodness of fit from spectrally derived estimates of each soil property. Then a model ensemble, or model averaging, approach was tested to examine if combining model outcomes of either vis-NIR or MIR with pXRF could improve accuracy of soil property prediction. In total, 15 of the 42 soil properties could be predicted to a good accuracy status using individual spectral methods, mostly achieved by MIR and pXRF. Combining model outcomes of vis-NIR or MIR with pXRF resulted in a positive improvement, increasing the number of soil properties that could be predicted from 15 to 25. Most notably is the large number of trace elements (As, Cd, Co, Cu, Hg, Mn, Ni, and Zn) predicted to good or reasonable accuracy. It was concluded that the synergistic use of vis-NIR, MIR, and pXRF spectral methods is well placed as a tool to permit large scale routine soil monitoring.

Objectives Research into the lived experiences of long-term care residents with dementia has identified perceived conflict, and its impact on sadness, as priorities for quality of life from the perspectives of people with dementia. However, whether and to what extent perceived conflict and sadness are associated has not been previously tested in this population. This study tested the associations between perceived conflicts with staff, family or friends and co-residents and their experience of sadness, and whether cognitive impairment or functional dependence modified these associations. Methods The study design was cross-sectional, correlational retrospective. Participants were 5001 residents of 613 long-term care facilities in Ontario, Canada with moderate and severe dementia. Clinical administrative data collected from 2012 to 2013 using the Resident Assessment Instrument 2.0 were used to measure the person's perception of conflicts with family/friends, staff, or co-residents, as well as verbal and non-verbal indicators of sadness. Hypotheses were tested using logistic regression, with cluster correction. Results Sadness (adjusting for age, sex, family/friend contact, pain, cognitive impairment, and functional dependence) was positively associated with perceived conflicts with family or friends (OR 1.91; 95% CI 1.26–2.88; p = 0.002) and staff (OR 1.51; 95% CI 1.07–2.13; p = 0.020). These associations did not differ depending on the level of cognitive impairment or functional dependence. The association between co-resident conflict and sadness was statistically significant for people with moderate (OR 2.02; 95% CI 1.45–2.82; p Conclusion Long-term care residents with dementia who perceive conflict with others require support to maintain high quality relationships, particularly with family and friends. Future research should rigorously assess the modifiability of perceived conflict for people with moderate and severe dementia, and whether interventions to ameliorate perceived conflict result in decreased sadness and improved quality of life.

Aberrant vascularization is a hallmark of cancer progression and treatment resistance. Here, we have shown that endothelial cell (EC) plasticity drives aberrant vascularization and chemoresistance in glioblastoma multiforme (GBM). By utilizing human patient specimens, as well as allograft and genetic murine GBM models, we revealed that a robust endothelial plasticity in GBM allows acquisition of fibroblast transformation (also known as endothelial mesenchymal transition [Endo-MT]), which is characterized by EC expression of fibroblast markers, and determined that a prominent population of GBM-associated fibroblast-like cells have EC origin. Tumor ECs acquired the mesenchymal gene signature without the loss of EC functions, leading to enhanced cell proliferation and migration, as well as vessel permeability. Furthermore, we identified a c-Met/ETS-1/matrix metalloproteinase–14 (MMP-14) axis that controls VE-cadherin degradation, Endo-MT, and vascular abnormality. Pharmacological c-Met inhibition induced vessel normalization in patient tumor–derived ECs. Finally, EC-specific KO of Met inhibited vascular transformation, normalized blood vessels, and reduced intratumoral hypoxia, culminating in suppressed tumor growth and prolonged survival in GBM-bearing mice after temozolomide treatment. Together, these findings illustrate a mechanism that controls aberrant tumor vascularization and suggest that targeting Endo-MT may offer selective and efficient strategies for antivascular and vessel normalization therapies in GBM, and possibly other malignant tumors.

Objectives The aim of this study was to investigate gender-based differences in nuclear cardiology practice globally, with a particular focus on laboratory volume, radiation dose, protocols, and best practices. Background It is unclear whether gender-based differences exist in radiation exposure for nuclear cardiology procedures. Methods In a large, multicenter, observational, cross-sectional study encompassing 7,911 patients in 65 countries, radiation effective dose was estimated for each examination. Patient-level best practices relating to radiation exposure were compared between genders. Analysis of covariance was used to determine any difference in radiation exposure according to gender, region, and the interaction between gender and region. Linear, logistic, and hierarchical regression models were developed to evaluate gender-based differences in radiation exposure and laboratory adherence to best practices. The study also included the United Nations Gender Inequality Index and Human Development Index as covariates in multivariable models. Results The proportion of myocardial perfusion imaging studies performed in women varied among countries; however, there was no significant correlation with the Gender Inequality Index. Globally, mean effective dose for nuclear cardiology procedures was only slightly lower in women (9.6 ± 4.5 mSv) than in men (10.3 ± 4.5 mSv; p Conclusions Despite significant worldwide variation in best practice use and radiation doses from nuclear cardiology procedures, only small differences were observed between genders worldwide. Regional variations noted in myocardial perfusion imaging use and radiation dose offer potential opportunities to address gender-related differences in delivery of nuclear cardiology care.

Immunotherapy, including chimeric antigen receptor (CAR) T cell therapy, has yielded major advancements for a number of hard-to-treat cancers; however, its transformative potential has yet to be realized in glioblastoma (GBM). Clinical studies of EGFRvIII targeted CAR T cell therapy have indicated that tumor heterogeneity, immune microenvironment, and adaptive responses to treatment may play important roles in limiting overall efficacy. We sought to examine comprehensively the dynamic molecular landscape of CAR T cell therapy in GBM using patient-derived GBM organoids (GBOs), a newly established laboratory model of inter- and intra- tumoral heterogeneity. Especially advantageous in these studies, GBOs preserve the intrinsic composition of somatic mutations, transcriptomic states, and non-neoplastic cells that contribute to the tumor microenvironment. Complementing the complexity of this biological system, we constructed an integrated single-cell multi-omics platform to interrogate gene expression, cell surface protein expression, somatic variants, and TCR sequences all from the same cell. Co-culture of GBOs and EGFRvIII targeted CAR T cells led to rapid T cell activation with concomitant upregulation of cytokine response gene programs in both antigen-positive and antigen-negative tumor cells. The adaptive tumor response also included expression of immune checkpoint receptor (ICR) ligands, such as PD-L1. At later time points, T cells transitioned into a dysfunctional or exhausted state, as characterized by increased cell surface expression of inhibitory receptors, such as PD-1, and decreased markers of effector activity despite the presence of antigen. Interestingly, CAR T cell therapy not only led to changes in immune-related pathways and tumor microenvironment, but it also induced shifts in tumor cell states with the depletion of an oligodendrocyte precursor cell-like state and corresponding enrichment in an astrocyte-like state. This finding suggests that EGFRvIII targeted CAR T cell therapy may leverage intrinsic cellular plasticity to induce differentiation-like effects in the surviving tumor cells.

Introduction: Glioblastoma (GBM) is malignant and aggressive brain tumor with a median overall survival of 14.6 months, despite the development of new treatments. Chimeric Antigen Receptor (CAR) modified T cells are powerful new class of immune based therapies that have shown a high rate of long term durable response in CD19 expressing B-cell malignancies. However, this success has yet to be translated to solid tumors, in part due to a lack of surface antigens specifically expressed on tumor cells while not present on normal tissue and an immunosuppressive tumor microenvironment. Approximately 60% of GBMs contain a mutation, rearrangement, splicing alteration, and/or amplification of EGFR. Investigation of 411 GBM patient samples from University of Pennsylvania identified EGFR amplification in 38% of cases and EGFRvIII in 25% of cases and most common oncogenic missense mutations in extracellular domain (ECD) A289D/T/V, R108G/K, and G598V in 12-13% of cases. ECD missense mutations are associated with increased invasiveness aided by ligand independent activation of receptor and decreased patient survival compared to patients that are wild type EGFR at R108, A289 and G59V locus. Methods: We generated two structurally different CARs by fusing the scFv of mAb806 to 4-1BB and Killer immunoglobulin like receptor (KIR) co-stimulatory domains. mAb806 recognizes a conformationally exposed epitope of wild-type EGFR when it is overexpressed on tumor cells or in the presence of oncogenic mutations such as EGFRvIII. We tested in vitro cytolytic activity of 806-EGFR-CART cells against U87-MG (expressing low levels of EGFR) and U87-MG EGFR (U87-MG parental cell line transduced with EGFR wild type for amplified background) cell lines. These lines were engineered to ectopically express targeted EGFR-ECD missense mutations and EGFRvIII. Results: Both 4-1BB and KIR based EGFR806 CAR T cells specifically lysed tumor cells, proliferated, and secreted cytokines when co-cultured with target-expressing cell lines. To test exclusive specificity of EGFR806 CART to targeted mutations, K562 cells were transduced with EGFR-ECD mutations and co-cultured with 4-1BB and KIR CART cells. While the EGFR806 lysed K562 cells expressing wild type EGFR, EGFR-ECD Mutants, and EGFRvIII, it did not demonstrate any activity against K562-Parental cells. Unlike EGFR-specific cetuximab based CAR, EGFR-806CART cells did not kill EGFR wild type expressing fetal brain astrocytes and keratinocytes in vitro. We further evaluated the in vivo efficacy of CARs in NSG mice by injecting U87-MG, U87-MG EGFR and U87-MG EGFR expressing EGFRvIII subcutaneously and assessed tumor burden and mice survival. Though both 4-1BB and KIR based EGFR806 CART cells control tumor growth, KIR based CAR outperformed 4-1BB based CAR in terms of tumor burden and improved mice survival. Conclusion: Though our CART clinical trial for EGFRvIII positive recurrent GBM patients demonstrated CART therapy is safe and CART cells are able to successfully traffic to regions of active GBM, antigen loss and tumor heterogeneity resulted in limited therapeutic success. Broad specificity of EGFR806 CART cells to Amplified EGFR, EGFRvIII and EGFR-ECD mutants gives us the potential to clear various forms of EGFR. The enhanced anti-tumor efficacy by KIR based CAR in vivo setting provides us with additional therapeutic options for GBM. Citation Format: Radhika Thokala, Zev Binder, Yibo Yin, Michael Milone, Donald M. Orourke. High affinity chimeric antigen receptors with cross reactivity to clinically relevant EGFR mutated proteins [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6596.

To understand potential immune system alterations in glioblastoma patients and provide a foundation for immunotherapy, we profiled intra tumoral leucocytes from newly diagnosed de novo patients as well as patients with recurrent tumor using high dimensional CyTOF. All recurrent patients underwent standard-of-care therapy, including surgical resection, concurrent temozolomide and radiotherapy, and adjuvant temozolomide. We used two immune profiling panels: a broad profiling panel that includes 45 phenotypic markers that together permit the identification and enumeration of the main innate and adaptive immune cell subsets in humans, and a deep profiling panel that includes 45 features focused on T cell phenotype and biology. We report in both de novo and recurrent tumors a predominant infiltration by CD11b+CD14+ monocytes (43.6±13%. of CD45+ cells). These monocytes displayed an immunomodulatory M2 profile (CD163+HLA-DR-/+CD80-CD86-/+). The adaptive compartment was sparse and dominated by alpha beta T cells, although some mucosal associated invariant T cells and gamma delta T cells were also present. T cells were both conventional T cells and regulatory T cells. The latter tended to be more abundant in the de novo as compared to recurrent tumors (22.8±17.9% of CD4+ T cells in de novo vs 12.9±12.5% in recurrent tumors, P=0.09). Conventional T cells were mostly CD27-CD45RA- effectors, with high expression of PD1 (69.9±17.6% of CD8+ T cells). Using high dimensional approaches, we confirmed that this high expression of PD1 reflects T cell exhaustion, as defined by co-expression of other inhibitory receptors such as Tim3, CTLA-4 and LAG-3. Exhausted T cells typically co-expressed PD1 and CD39 in the de novo tumors, and this pattern was less often observed in recurrent tumors (63.4±22.84% of CD8+ T cells in de novo vs 46.3±14.5% in recurrent tumors, P=0.03). Together, our results highlight the potential issue of a substandard T cell compartment at the time of GBM diagnosis. We are now investigating the mechanisms underlying these observations, as well as their impact on T cell immunity of the patients, as well as current immunotherapy strategies. Our studies should provide a foundation for improving therapy in glioblastoma patients. Citation Format: Cécile Alanio, Zev A. Binder, Donald M. O'Rourke, E. John Wherry. Deep immune profiling of de novo and recurrent glioblastoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-356.

Meningiomas are the most common primary brain tumor of adults. The majority are benign (WHO grade I), with a mostly indolent course; 20% of them (WHO grade II and III) are, however, considered aggressive and require a more complex management. WHO grade II and III tumors are heterogeneous and, in some cases, can develop from a prior lower grade meningioma, although most arise de novo. Mechanisms leading to progression or implicated in de novo grade II and III tumorigenesis are poorly understood. RNA-seq was used to profile the transcriptome of grade I, II, and III meningiomas and to identify genes that may be involved in progression. Bioinformatic analyses showed that grade I meningiomas that progress to a higher grade are molecularly different from those that do not. As such, we identify GREM2, a regulator of the BMP pathway, and the snoRNAs SNORA46 and SNORA48, as being significantly reduced in meningioma progression. Additionally, our study has identified several novel fusion transcripts that are differentially present in meningiomas, with grade I tumors that did not progress presenting more fusion transcripts than all other tumors. Interestingly, our study also points to a difference in the tumor immune microenvironment that correlates with histopathological grade. Electronic supplementary material The online version of this article (10.1186/s40478-019-0690-x) contains supplementary material, which is available to authorized users.

2508 Background: Due to significant interpatient heterogeneity, survival outcomes vary widely in patients with GBM. Novel prognostic biomarkers are needed. We aimed to determine the prognostic impact of baseline plasma cfDNA concentration in patients with GBM. Methods: We analyzed 84 patients with newly diagnosed GBM and at least 7 months of follow-up time. The first 41 patients comprised a previously published derivation cohort (Bagley, Clin Cancer Res 2020). The subsequent 43 patients served as an independent validation cohort. cfDNA was extracted from plasma collected prior to initial surgical resection and quantified by qPCR for a 115 bp amplicon of the human ALU repeat element. Receiver operating characteristic (ROC) curve analysis was used in the derivation cohort to (1) assess the accuracy of plasma cfDNA concentration for predicting progression-free survival status at 7 months (PFS-7), a landmark based on the median PFS for newly diagnosed GBM (Stupp, N Engl J Med 2005), and (2) derive the optimal cutoff for dichotomizing patients into high- and low-cfDNA groups. In the validation cohort, logistic regression was used to measure the association of plasma cfDNA concentration (high vs. low) with PFS-7, adjusted for age, isocitrate dehydrogenase ( IDH) 1/2 mutational status, 0-6-methylguanine-methyltransferase ( MGMT) methylation, extent of resection, and performance status. Multivariate Cox regression was used for overall survival (OS) analysis. Results: In the derivation cohort, the optimal cutoff for plasma cfDNA was 25.0 ng/mL (area under the curve [AUC] = 0.663), with inferior PFS and OS in patients with cfDNA above this cutoff (PFS, median 4.9 vs. 9.5 months, log-rank p = 0.001; OS, median 8.5 vs. 15.5 months, log-rank p = 0.03). In the validation cohort, baseline plasma cfDNA concentration over the cutoff was independently associated with a lower likelihood of being alive and progression-free at 7 months (adjusted OR 0.13, 95% CI 0.02 – 0.75, p = 0.02). OS was also worse in in the validation cohort in patients with high plasma cfDNA (adjusted HR 3.0, 95% CI 1.1 – 8.0, p = 0.03). Conclusions: In patients with newly diagnosed GBM, high baseline plasma cfDNA concentration is associated with worse survival outcomes independent of other prognostic factors. Further validation in a larger, multicenter study is warranted.

e22015 Background: We evaluated spatially-resolved protein profiling of longitudinal tumor specimens derived from two patients with metastatic melanoma who progressed on sequential therapies including targeted therapy (TT) and immune checkpoint blockade (ICB) therapy targeting T cell-surface antigens (CTLA-4 and PD-1). The purpose of this study was to identify molecular determinants of resistance to sequential TT and ICB therapies. Methods: We performed multiplexed and multidimensional spatial protein profiling using NanoString’s GeoMx Digital Spatial Profiling (DSP) platform and single-cell level imaging analysis with Cyclic Immunofluorescence (CycIF) to simultaneously determine dynamic changes in tumor intrinsic signaling pathways and immune response in the tumor microenvironment (TME). Results: The first patient presented with a BRAFV600E-positive brain metastasis. This patient was sequentially treated with ipilimumab (Ipi), the combination of dabrafenib and trametinib, and pembrolizumab (Pembro) and progressed despite of high expression of CD56 NK cell after all treatments. In addition, CycIF analysis revealed drug resistance in a subpopulation of cells that had continued activation of mTOR (pS6) and EGFR pathways. The second patient presented with dermal metastases on the flank with NRASQ61K mutation. This patient was sequentially treated with Pembo, Talimogene Laherparepvec, the combination of Ipi plus nivolumab, and two different investigational agents combined with Pembro. This patient displayed stable disease (SD) on Pembro but eventually progressed on the subsequent therapies. DSP analysis demonstrated CD68/CD40 myeloid cell infiltrates as well as HLA-DR and CD44 in the TME after the last treatment. CycIF analysis revealed dynamic changes in tumoral characteristics including DNA damage and proliferation during treatment. Furthermore, the analysis suggested that there might be a resistant subpopulation in the last tumor biopsy, which is in line with progression of the disease. Conclusions: In this study, we conducted detailed analyses on serial specimens from two patients to precisely define the spatial distribution of immune responses and cancer signaling pathways. The findings propose that concurrent proteomics analysis and immune monitoring of longitudinal tumor biopsies can be informative in clinical evaluation in order to identify salvage therapies to overcome drug resistance.

The LACE+ index (Length of stay, Acuity of admission, Charlson Comorbidity Index score, and Emergency department [ED] visits in the past 6 months) is a tool used to predict 30-day readmissions. We sought to examine this predictive tool in patients undergoing brain tumor surgery.Admissions and readmissions for patients undergoing craniotomy for supratentorial neoplasm at a single multihospital academic medical center were analyzed. All brain tumor cases for which the patient was alive at 30 days after surgery were included (n = 352). Simple logistic regression analyses were used to assess the ability of the LACE+ index and subsequent single variables to accurately predict the outcome measures of 30-day readmission, reoperation, and ED visit. Analysis of the model's or variable's discrimination was determined by the receiver operating characteristic curve as represented by the C-statistic.The sample included admissions for craniotomy for supratentorial neoplasm (n = 352). Assessment of the LACE+ index demonstrates a 1.02× increased odds of 30-day readmission for every 1-unit increase in LACE+ score (P = 0.031, CI = 1.00-1.03). Despite this, analysis of the receiver operating characteristic curve indicates that LACE+ index has poor specificity in predicting 30-day readmission (C-statistic = 0.58). A 1-unit increase in LACE+ score also predicts a 0.98× reduction in odds of home discharge (P0.001, CI = 0.97-0.99, C-statistic = 0.70). But LACE+ index does not predict 30-day reoperation (P = 0.945) or 30-day ED visits (P = 0.218).The results of this study demonstrate that the LACE+ index is not yet suitable as a prediction model for 30-day readmission in a brain tumor population.