Identification, validation and biological characterisation of novel glioblastoma tumour microenvironment subtypes: implications for precision immunotherapy.

BACKGROUND: New precision medicine therapies are urgently required for glioblastoma (GBM). However, to date, efforts to subtype patients based on molecular profiles have failed to direct treatment strategies. We hypothesised that interrogation of the GBM tumour microenvironment (TME) and identification of novel TME-specific subtypes could inform new precision immunotherapy treatment strategies. MATERIALS AND METHODS: A refined and validated microenvironment cell population (MCP) counter method was applied to >800 GBM patient tumours (GBM-MCP-counter). Specifically, partition around medoids (PAM) clustering of GBM-MCP-counter scores in the GLIOTRAIN discovery cohort identified three novel patient clusters, uniquely characterised by TME composition, functional orientation markers and immune checkpoint proteins. Validation was carried out in three independent GBM-RNA-seq datasets. Neoantigen, mutational and gene ontology analysis identified mutations and uniquely altered pathways across subtypes. The longitudinal Glioma Longitudinal AnalySiS (GLASS) cohort and three immunotherapy clinical trial cohorts [treatment with neoadjuvant/adjuvant anti-programmed cell death protein 1 (PD-1) or PSVRIPO] were further interrogated to assess subtype alterations between primary and recurrent tumours and to assess the utility of TME classifiers as immunotherapy biomarkers. RESULTS: TMEHigh tumours (30%) displayed elevated lymphocyte, myeloid cell immune checkpoint, programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 transcripts. TMEHigh/mesenchymal+ patients featured tertiary lymphoid structures. TMEMed (46%) tumours were enriched for endothelial cell gene expression profiles and displayed heterogeneous immune populations. TMELow (24%) tumours were manifest as an 'immune-desert' group. TME subtype transitions upon recurrence were identified in the longitudinal GLASS cohort. Assessment of GBM immunotherapy trial datasets revealed that TMEHigh patients receiving neoadjuvant anti-PD-1 had significantly increased overall survival (P = 0.04). Moreover, TMEHigh patients treated with adjuvant anti-PD-1 or oncolytic virus (PVSRIPO) showed a trend towards improved survival. CONCLUSIONS: We have established a novel TME-based classification system for application in intracranial malignancies. TME subtypes represent canonical 'termini a quo' (starting points) to support an improved precision immunotherapy treatment approach.

Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis.

Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake.

Pembrolizumab in soft-tissue sarcomas with tertiary lymphoid structures: a phase 2 PEMBROSARC trial cohort.

Immune checkpoint inhibitors (ICIs) show limited clinical activity in patients with advanced soft-tissue sarcomas (STSs). Retrospective analysis suggests that intratumoral tertiary lymphoid structures (TLSs) are associated with improved outcome in these patients. PEMBROSARC is a multicohort phase 2 study of pembrolizumab combined with low-dose cyclophosphamide in patients with advanced STS (NCT02406781). The primary endpoint was the 6-month non-progression rate (NPR). Secondary endpoints included objective response rate (ORR), progression-free survival (PFS), overall survival (OS) and safety. The 6-month NPR and ORRs for cohorts in this trial enrolling all comers were previously reported; here, we report the results of a cohort enrolling patients selected based on the presence of TLSs (n = 30). The 6-month NPR was 40% (95% confidence interval (CI), 22.7-59.4), so the primary endpoint was met. The ORR was 30% (95% CI, 14.7-49.4). In comparison, the 6-month NPR and ORR were 4.9% (95% CI, 0.6-16.5) and 2.4% (95% CI, 0.1-12.9), respectively, in the all-comer cohorts. The most frequent toxicities were grade 1 or 2 fatigue, nausea, dysthyroidism, diarrhea and anemia. Exploratory analyses revealed that the abundance of intratumoral plasma cells (PCs) was significantly associated with improved outcome. These results suggest that TLS presence in advanced STS is a potential predictive biomarker to improve patients' selection for pembrolizumab treatment.

Individual milk fatty acids are potential predictors of enteric methane emissions from dairy cows fed a wide range of diets: Approach by meta-analysis.

There is a need to quantify methane (CH4) emissions with alternative methods. For the past decade, milk fatty acids (MFA) could be used as proxies to predict CH4 emissions from dairy cows because of potential common rumen biochemical pathways. However, equations have been developed based on a narrow range of diets and with limited data. The objectives of this study were to (1) construct a set of empirical models based on individual data of CH4 emissions and MFA from a large number of lactating dairy cows fed a wide range of diets; (2) further increase the models' level of complexity (from farm to research level) with additional independent variables such as dietary chemical composition (organic matter, neutral detergent fiber, crude protein, starch, and ether extract), dairy performance (milk yield and composition), and animal characteristics (days in milk or body weight); and (3) evaluate the performance of the developed models on independent data sets including measurements from individual animals or average measurements of groups of animals. Prediction equations based only on MFA [C10:0, iso C17:0 + trans-9 C16:1,cis-11 C18:1, and trans-11,cis-15 C18:2 for CH4 production (g/d); iso C16:0, cis-11 C18:1, trans-10 C18:1, and cis-9,cis-12 C18:2 for CH4 yield (g/kg of dry matter intake, DMI); and iso C16:0, cis-15 C18:1, and trans-10 + trans-11 C18:1 for CH4 intensity (g/kg of milk)] had a root mean squared error of 65.1 g/d, 2.8 g/kg of DMI, and 2.9 g/kg of milk, respectively, whereas complex equations that additionally used DMI, dietary neutral detergent fiber, ether extract, days in milk, and body weight had a lower root mean squared error of 46.6 g/d, 2.6 g/kg of DMI, and 2.7 g/kg of milk, respectively). External evaluation with individual or mean data not used for equation development led to variable results. When evaluations were performed using individual cow data from an external data set, accurate predictions of CH4 production (g/d) were obtained using simple equations based on MFA. Better performance was observed on external evaluation with individual data for the simple equation of CH4 production (g/d, based on MFA), whereas better performance was observed on external evaluation mean data for the simple equation of CH4 yield (g/kg of DMI). The performance of evaluation of the models is dependent on the domain of validity of the evaluation data sets used (individual or mean).

Effects of starch-rich or lipid-supplemented diets that induce milk fat depression on rumen biohydrogenation of fatty acids and methanogenesis in lactating dairy cows.

Optimizing milk production efficiency implies diets allowing low methane (CH4) emissions and high dairy performance. We hypothesize that nature of energy (starch v. lipids) and lipid supplement types (monounsaturated fatty acid (MUFA) v. polyunsaturated fatty acid (PUFA) mitigate CH4 emissions and can induce low milk fat content via different pathways. The main objective of this experiment was to study the effects of starch-rich or lipid-supplemented diets that induce milk fat depression (MFD) on rumen biohydrogenation (RBH) of unsaturated fatty acids (FA) and enteric CH4 emissions in dairy cows. Four multiparous lactating Holstein cows (days in milk=61±11 days) were used in a 4×4 Latin square design with four periods of 28 days. Four dietary treatments, three of which are likely to induce MFD, were based (dry matter basis) on 56% maize silage, 4% hay and 40% concentrates rich in: (1) saturated fatty acid (SFA) from Ca salts of palm oil (PALM); (2) starch from maize grain and wheat (MFD-Starch); (3) MUFA (cis-9 C18:1) from extruded rapeseeds (MFD-RS); and (4) PUFA (C18:2n-6) from extruded sunflower seeds (MFD-SF). Intake and milk production were measured daily. Milk composition and FA profile, CH4 emissions and total-tract digestibility were measured simultaneously when animals were in open-circuit respiration chambers. Fermentation parameters were analysed from rumen fluid samples taken before feeding. Dry matter intake, milk production, fat and protein contents, and CH4 emissions were similar among the four diets. We observed a higher milk SFA concentration with PALM and MFD-Starch, and lower milk MUFA and trans-10 C18:1 concentrations in comparison to MFD-RS and MFD-SF diets, while trans-11 C18:1 remained unchanged among diets. Milk total trans FA concentration was greater for MFD-SF than for PALM and MFD-Starch, with the value for MFD-RS being intermediate. Milk C18:3n-3 content was higher for MFD-RS than MFD-SF. The MFD seems more severe with MFD-SF and MFD-RS than PALM and MFD-Starch diets, because of a decrease in milk SFA concentration and a stronger shift from trans-11 C18:1 to trans-10 C18:1 in milk. The MFD-SF diet increased milk trans FA (+60%), trans-10 C18:1 (+31%), trans-10,cis-12 CLA (+27%) and PUFA (+36%) concentrations more than MFD-RS, which explains the numerically lowest milk fat yield and indicates that RBH pathways of PUFA differ between these two diets. Maize silage-based diets rich in starch or different unsaturated FA induced MFD with changes in milk FA profiles, but did not modify CH4 emissions.

Effects of carbohydrate type or bicarbonate addition to grass silage-based diets on enteric methane emissions and milk fatty acid composition in dairy cows.

The aim of the study was to compare the effect of fiber- or starch-rich diets based on grass silage, supplemented or not with bicarbonate, on CH4 emissions and milk fatty acid (FA) profile in dairy cows. The experiment was conducted as a 4 × 4 Latin square design with a 2 × 2 factorial arrangement: carbohydrate type [starch- or fiber-rich diets with dietary starch level of 23.1 and 5.9% on a dry matter basis, respectively], without or with bicarbonate addition [0 and 1% of the dry matter intake, respectively]. Four multiparous lactating Holstein cows were fed 4 diets with 42% grass silage, 8% hay, and 50% concentrate in 4 consecutive 4-wk periods: (1) starch-rich diet, (2) starch-rich diet with bicarbonate, (3) fiber-rich diet, and (4) fiber-rich diet with bicarbonate. Intake and milk production were measured daily and milk composition was measured weekly; CH4 emission and total-tract digestibility were measured simultaneously (5 d, wk 4) when animals were in open-circuit respiration chambers. Sensors continuously monitored rumen pH (3 d, wk 4), and fermentation parameters were analyzed from rumen fluid samples taken before feeding (1 d, wk 3). Cows fed starch-rich diets had less CH4 emissions (on average, -18% in g/d; -15% in g/kg of dry matter intake; -19% in g/kg of milk) compared with fiber-rich diets. Carbohydrate type did not affect digestion of nutrients, except starch, which increased with starch-rich diets. The decrease in rumen protozoa number (-36%) and the shift in rumen fermentation toward propionate at the expense of butyrate for cows fed the starch-rich diets may be the main factor in reducing CH4 emissions. Milk of cows fed starch-rich diets had lower concentrations in trans-11 C18:1, sum of cis-C18, cis-9,trans-11 conjugated linoleic acid (CLA), and sum of CLA, along with greater concentration of some minor isomers of CLA and saturated FA in comparison to the fiber-rich diet. Bicarbonate addition did not influence CH4 emissions or nutrient digestibility regardless of the carbohydrate type in the diet. Rumen pH increased with bicarbonate addition, whereas other rumen parameters and milk FA composition were almost comparable between diets. Feeding dairy cows a starch-rich diet based on grass silage helps to limit the negative environmental effect of ruminants, but does not lead to greater milk nutritional value because milk saturated FA content is increased.

Effects of phytase supplementation on phosphorus retention in broilers and layers: a meta-analysis.

Phytase, a widely used feed additive in poultry diets, increases P availability and subsequently reduces inorganic-P supplementation and P-excretion. Phytase supplementation effect on P-retention in poultry has been investigated, but the effect sizes were highly variable. The present study's objective was to conduct several meta-analyses to quantitatively summarize the phytase effect on P-retention in broilers and layers. Data from 103 and 26 controlled experiments testing the phytase effect on P-retention were included in 2 separate meta-analyses for broilers and layers, respectively. The mean difference calculated by subtracting the means of P-retention for the control group from the phytase-supplemented group was chosen as an effect size estimate. Between-study variability (heterogeneity) of mean difference was estimated using random-effect models and had a significant effect (P < 0.01) in both broilers and layers. Therefore, random-effect models were extended to mixed-effect models to explain heterogeneity and obtain final phytase effect size estimates. Available dietary and bird variables were included as fixed effects in the mixed-effect models. The final broiler mixed-effect model included phytase dose and Ca-to-total-P ratio (Ca:tP), explaining 15.6% of the heterogeneity. Other variables such as breed might further explain between-study variance. Broilers consuming control diets were associated with 48.4% P-retention. Exogenous phytase supplementation at 1,039 FTU/kg of diet increased P-retention by 8.6 percentage units on average. A unit increase of phytase dose and Ca:tP from their means further increased P-retention. For layers, the final mixed-effect models included dietary Ca, age, and experimental period length. The variables explained 65.9% of the heterogeneity. Layers receiving exogenous phytase at 371 FTU/kg were associated with a 5.02 percentage unit increase in P-retention. A unit increase in dietary Ca from its mean increased P-retention, whereas an increase in the experiment length and layer's age decreased P-retention. Phytase supplementation had a significant positive effect on P-retention in both broilers and layers, but effect sizes across studies were significantly heterogeneous due to differences in Ca contents, experiment length, bird age, and phytase dose.