BACKGROUND. Understanding the integrated immunogenomic landscape of advanced prostate cancer (APC) could impact stratified treatment selection.METHODS. Defective mismatch repair (dMMR) status was determined by either loss of mismatch repair protein expression on IHC or microsatellite instability (MSI) by PCR in 127 APC biopsies from 124 patients (Royal Marsden [RMH] cohort); MSI by targeted panel next-generation sequencing (MSINGS) was then evaluated in the same cohort and in 254 APC samples from the Stand Up To Cancer/Prostate Cancer Foundation (SU2C/PCF). Whole exome sequencing (WES) data from this latter cohort were analyzed for pathogenic MMR gene variants, mutational load, and mutational signatures. Transcriptomic data, available for 168 samples, was also performed.RESULTS. Overall, 8.1% of patients in the RMH cohort had some evidence of dMMR, which associated with decreased overall survival. Higher MSINGS scores associated with dMMR, and these APCs were enriched for higher T cell infiltration and PD-L1 protein expression. Exome MSINGS scores strongly correlated with targeted panel MSINGS scores (r = 0.73, P < 0.0001), and higher MSINGS scores associated with dMMR mutational signatures in APC exomes. dMMR mutational signatures also associated with MMR gene mutations and increased immune cell, immune checkpoint, and T cell–associated transcripts. APC with dMMR mutational signatures overexpressed a variety of immune transcripts, including CD200R1, BTLA, PD-L1, PD-L2, ADORA2A, PIK3CG, and TIGIT.CONCLUSION. These data could impact immune target selection, combination therapeutic strategy selection, and selection of predictive biomarkers for immunotherapy in APC.FUNDING. We acknowledge funding support from Movember, Prostate Cancer UK, The Prostate Cancer Foundation, SU2C, and Cancer Research UK.
Background:Limited data exist regarding the correlation between MRI tumour regression grade (mrTRG) and pathological TRG (pTRG) in rectal cancer.Methods:mrTRG and pTRG were compared in rectal cancer patients from two phase II trials (EXPERT and EXPERT-C). The agreement between radiologist and pathologist was assessed with the weighted κ test while the Kaplan–Meier method was used to estimate survival outcomes.Results:One hundred ninety-one patients were included. Median time from completion of neoadjuvant treatment to pre-operative MRI and surgery was 4.1 weeks (interquartile range (IQR): 3.7–4.7) and 6.6 weeks (IQR: 5.9–7.6), respectively. Fair agreement was found between mrTRG and pTRG when regression was classified according to standard five-tier systems (κ=0.24) or modified three-tier systems (κ=0.25). Sensitivity and specificity of mrTRG 1–2 (complete/good radiological regression) for the prediction of pathological complete response was 74.4% (95% CI: 58.8–86.5) and 62.8% (95% CI: 54.5–70.6), respectively. Survival outcomes of patients with intermediate pathological regression (pTRG 2) were numerically better if complete/good regression was also observed on imaging (mrTRG 1–2) compared to poor regression (mrTRG 3–5) (5-year recurrence-free survival 76.9% vs 65.9%, P=0.18; 5-year overall survival 80.6% vs 68.8%, P=0.22).Conclusions:The agreement between mrTRG and pTRG is low and mrTRG cannot be used as a surrogate of pTRG. Further studies are warranted to assess the ability of mrTRG to identify pathological complete responders for the adoption of non-operative management strategies and to provide complementary prognostic information to pTRG for better risk-stratification after surgery.
BackgroundEnvironmental, social and individual factors influence eating patterns, which in turn affect the risk of many chronic diseases. This study aimed to estimate associations between environmental factors and the consumption of fruit and vegetables among adults in a Brazilian urban context.MethodsData from the surveillance system for risk factors for chronic diseases (VIGITEL) of Brazilian Ministry of Health were used. A cross-sectional telephone survey (VIGITEL – 2008–2010) was carried out with 5826 adults in the urban area of Belo Horizonte. Individual variables were collected. The frequency of fruit and vegetables consumption was assessed from number of servings, weekly frequency and an intake score was calculated. Georeferenced variables were used to characterize the food environment. The density of healthy food outlets (stores specialized in selling fruit and vegetables), unhealthy food outlets (bars, snack bars and food trucks/trailers) and the neighborhood family income were investigated and associated with fruit and vegetables intake score. Weighted multilevel linear regression was used to evaluate the associations between the environment variables and the fruit and vegetables intake score.ResultsHigher fruit and vegetables intake scores were observed in neighborhoods with higher density of healthy food outlets and higher income. Lower scores were observed in neighborhood with higher density of unhealthy food outlets. These associations were adjusted by individual variables such as gender, age, physical activity, sugar sweetened beverages consumption, education level and smoking.DiscussionThe food environment might explain some of the socioeconomic disparities with respect to healthy food intake and health outcomes. Healthy food stores are less common in socially disadvantaged neighborhoods, and therefore, healthy foods such as fruits and vegetables are less available or are of a lower quality in lower income areas.ConclusionFood environment characteristics and neighborhood socioeconomic level had significant associations with fruit and vegetable intake score. These are initial findings that require further investigation within the middle income world populations and the role of the environment with respect to both healthy and unhealthy food acquisition and intake.
This study’s aim was to characterize the food environment of Brazilian public and private schools. This was a national school-based cross-sectional study with 1,247 schools - among which 81.09% were public and 18.91% were private - in 124 Brazilian municipalities. The data originated from the Questionnaire on Aspects of the School Environment, used in the Study of Cardiovascular Risk in Adolescents (ERICA) in 2013 and 2014. Data analysis was conducted in 2017. The chi-square test was used to compare proportions. A greater proportion of public schools offered school meals (98.15%) in comparison to private schools (8.07%) (p < 0.001). The internal sale of food and beverages was more prevalent in private schools (97.75% vs. 45.06%, p < 0.001). Also, sale and advertisement of processed and ultra-processed foods (sodas, cookies, savory snacks, sandwiches and pizza), as well as the presence of vending machines for industrialized products (18.02% vs. 4%) (p < 0.001) were more common in private schools. Street vendors at the school gate or surroundings were identified in 41.32% of the public schools and 47.75% of the private schools (p > 0.05). These findings reveal the predominance of obesogenic environments mainly in private schools, and can contribute to the design of Brazilian public policies to promote a healthy school food environment.
Context
The presence of retail food establishments around schools can be a potentiating or protective factor for overweight in students, depending on access to these places as well as types of foods available therein. The hypothesis for this study was that a greater density and proximity of retail food establishments around schools influence the weight of students.
Objective
To systematically review the available observational literature on the association between retail food establishments around schools and the occurrence of overweight and obesity in schoolchildren and adolescents.
Data Sources
Observational studies were searched in the MEDLINE, EMBASE, and SCOPUS databases published until May 2019.
Data Extraction
Two independent reviewers extracted relevant data.
Data Analysis
Data on the 31 included studies were summarized with narrative synthesis according to meta-analyses of observational studies in epidemiology, exploring the type of food establishments around schools and analyzing qualitatively the impact of proximity or density on overweight and obesity rates.
Conclusion
Of the 31 articles, a direct association between proximity or density of establishments (mainly fast food restaurants, convenience stores, grocery stores) around schools and overweight and obesity in children and adolescents were found in 14 studies. However, authors of 13 papers found no association and inverse association was presented in 4 papers. The studies presented different methods of classification, location, and analysis of retail food establishments, making it difficult to conclude the real influence that the presence of these establishments near schools have on the nutritional status of children and adolescents. Therefore, future studies should consider the use of longitudinal designs and standardized analysis of the food environment around schools to better understand this food environment and its influence on health-related behaviors.
Previously, we classified colorectal cancers (CRCs) into five CRCAssigner (CRCA) subtypes with different prognoses and potential treatment responses, later consolidated into four consensus molecular subtypes (CMS). Here we demonstrate the analytical development and validation of a custom NanoString nCounter platform-based biomarker assay (NanoCRCA) to stratify CRCs into subtypes. To reduce costs, we switched from the standard nCounter protocol to a custom modified protocol. The assay included a reduced 38-gene panel that was selected using an in-house machine-learning pipeline. We applied NanoCRCA to 413 samples from 355 CRC patients. From the fresh frozen samples (n = 237), a subset had matched microarray/RNAseq profiles (n = 47) or formalin-fixed paraffin-embedded (FFPE) samples (n = 58). We also analyzed a further 118 FFPE samples. We compared the assay results with the CMS classifier, different platforms (microarrays/RNAseq) and gene-set classifiers (38 and the original 786 genes). The standard and modified protocols showed high correlation (> 0.88) for gene expression. Technical replicates were highly correlated (> 0.96). NanoCRCA classified fresh frozen and FFPE samples into all five CRCA subtypes with consistent classification of selected matched fresh frozen/FFPE samples. We demonstrate high and significant subtype concordance across protocols (100%), gene sets (95%), platforms (87%) and with CMS subtypes (75%) when evaluated across multiple datasets. Overall, our NanoCRCA assay with further validation may facilitate prospective validation of CRC subtypes in clinical trials and beyond.
The findings reinforce the need for public policies that promote equality in the food environments of the city. Also, further investigations into the influence of the presence of supermarkets on the nutritional status of children and adolescents are required.
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