Food items contributing most to variation in antioxidant intake; A cross-sectional study among Norwegian women

Background Fruit and vegetable intake has been found to reduce the risk of cardiovascular disease, certain types of cancer and diabetes mellitus. It is possible that antioxidants play a large part in this protective effect. However, which foods account for the variation in antioxidant intake in a population is not very clear. We used food frequency data from a population-based sample of women to identify the food items that contributed most to the variation in antioxidant intake in Norwegian diet. Methods We used data from a study conducted among participants in the Norwegian Breast Cancer Screening Program (NBCSP), the national program which invites women aged 50–69 years to mammographic screening every 2 years. A subset of 6514 women who attended the screening in 2006/2007 completed a food frequency questionnaire (FFQ). Daily intake of energy, nutrients and antioxidant intake were estimated. We used multiple linear regression analysis to capture the variation in antioxidant intake. Results The mean (SD) antioxidant intake was 23.0 (8.5) mmol/day. Coffee consumption explained 54% of the variation in antioxidant intake, while fruits and vegetables explained 22%. The twenty food items that contributed most to the total variation in antioxidant intake explained 98% of the variation in intake. These included different types of coffee, tea, red wine, blueberries, walnuts, oranges, cinnamon and broccoli. Conclusions In this study we identified a list of food items which capture the variation in antioxidant intake among these women. The major contributors to dietary total antioxidant intake were coffee, tea, red wine, blueberries, walnuts, oranges, cinnamon and broccoli. These items should be assessed in as much detail as possible in studies that wish to capture the variation in antioxidant intake

A comprehensive framework for analysis of microRNA sequencing data in metastatic colorectal cancer

Although microRNAs (miRNAs) contribute to all hallmarks of cancer, miRNA dysregulation in metastasis remains poorly understood. The aim of this work was to reliably identify miRNAs associated with metastatic progression of colorectal cancer (CRC) using novel and previously published nextgeneration sequencing (NGS) datasets generated from 268 samples of primary (pCRC) and metastatic CRC (mCRC; liver, lung and peritoneal metastases) and tumor adjacent tissues. Differential expression analysis was performed using a meticulous bioinformatics pipeline, including only bona fide miRNAs, and utilizing miRNA-tailored quality control and processing. Five miRNAs were identified as upregulated at multiple metastatic sites Mir-210 3p, Mir191 5p, Mir-8-P1b 3p [mir-141–3p], Mir-1307 5p and Mir-155 5p. Several have previously been implicated in metastasis through involvement in epithelial-tomesenchymal transition and hypoxia, while other identified miRNAs represent novel findings. The use of a publicly available pipeline facilitates reproducibility and allows new datasets to be added as they become available. The set of miRNAs identified here provides a reliable starting-point for further research into the role of miRNAs in metastatic progression

GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome

Background: Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. Findings: We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Conclusions: Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no.This work was supported by the Research Council of Norway (under grant agreements 221580, 218241, and 231217/F20), by the Norwegian Cancer Society (under grant agreements 71220’PR-2006-0433 and 3485238-2013), and by the South-Eastern Norway Regional Health Authority (under grant agreement 2014041).Peer Reviewe

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Omics analyses in peritoneal metastasis-utility in the management of peritoneal metastases from colorectal cancer and pseudomyxoma peritonei: a narrative review

High-throughput “-omics” analysis may provide a broader and deeper understanding of cancer biology to define prognostic and predictive biomarkers and identify novel therapy targets. In this review we provide an overview of studies where the peritoneal tumor component of peritoneal metastases from colorectal cancer (PM-CRC) and pseudomyxoma peritonei (PMP) were analyzed. Most of the available data was derived from DNA mutation analysis, but a brief review of findings from transcriptomic and protein expression analysis was also performed. Studies reporting genomic analysis of peritoneal tumor samples from 1,779 PM-CRC and 623 PMP cases were identified. The most frequently mutated genes in PM-CRC were KRAS, APC, SMAD4, BRAF, and PIK3CA, while in PMP KRAS, GNAS, FAT4, TGFBR1, TP53 and SMAD3/4 mutations were most commonly identified. Analyses were performed by single-gene analyses and to some extent targeted next-generation sequencing, and a very limited amount of broad explorative data exists. The investigated cohorts were typically small and heterogeneous with respect to the methods used and to the reporting of clinical data. This was even more apparent regarding transcriptomic and protein data, as the low number of cases examined and quality of clinical data would not support firm conclusions. Even for the most frequently mutated genes, the results varied greatly; for instance, KRAS mutations were reported at frequencies between 20–57% in PM-CRC and 38–100% in PMP. Such variation could be caused by random effects in small cohorts, heterogeneity in patient selection, or sensitivity of applied technology. Although a large number of samples have been subjected to analysis, cross-study comparisons are difficult to perform, and combined with small cohorts and varying quality and detail of clinical information, the observed variation precludes useful interpretation in a clinical context. Although omics data in theory could answer questions to aid management decisions in PM-CRC and PMP, the existing data does not presently support clinical implementation. With the necessary technologies being generally available, the main challenge will be to obtain sufficiently large, representative cohorts with adequate clinical data and standardized reporting of results. Importantly, studies where the focus is specifically on peritoneal disease are needed, where the study designs are aligned with clearly defined research questions to allow robust conclusions. Such studies are highly warranted if patients with PM-CRC and PMP are to derive benefit from recent advances in precision cancer medicine

The rainfall plot: its motivation, characteristics and pitfalls

Background A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. Results We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. Conclusions This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage

Experimental Treatment of Mucinous Peritoneal Metastases Using Patient-Derived Xenograft Models

Mucinous peritoneal metastases (PM) generally respond poorly to systemic treatment, and there is a clear unmet need for new treatment strategies to improve survival and quality of life for patients with PM. In this work, the growth inhibitory effect of five drugs (oxaliplatin (OXA; 5 mg/kg), irinotecan (IRI; 60 mg/kg), cabazitaxel (CBZ; 15 or 30 mg/kg), regorafenib (REG; 10, 30 or 60 mg/kg), and capecitabine (CAP; 359 or 755 mg/kg) was investigated in three orthotopic patient-derived xenograft models that mimic mucinous PM. Drugs were administered intraperitoneally (i.p.) as monotherapy weekly for 4 weeks (OXA, IRI), as one single i.p. injection (CBZ), or orally (REG, CAP) daily 5 of 7 days per week for four weeks, and i.p. tumor growth and survival were monitored and compared between treatment groups. The i.p. administered drugs (OXA, IRI, CBZ) had the strongest growth inhibitory effect, with OXA being most efficacious, completely inhibiting tumor growth in the majority of the animals. CBZ and IRI also strongly inhibited tumor growth, but with more variation in efficacy between the models. A moderate reduction in tumor growth was observed in all models treated with REG, while CAP had little to no growth inhibitory effect. Targeted next-generation-sequencing has identified mutational profiles typically associated with PM (mutations in KRAS, GNAS, and BRAF oncogenes), supporting the representativeness of the models. The results presented in this work support the continued exploration of i.p. treatment protocols for PM, with OXA remaining and CBZ emerging as particularly interesting candidates for further studies

Peptide vaccine targeting mutated GNAS: A potential novel treatment for pseudomyxoma peritonei

Background Pseudomyxoma peritonei (PMP) is a rare, slow-growing abdominal cancer with no efficacious treatment options in non-resectable and recurrent cases. Otherwise, rare activating mutations in the GNAS oncogene are remarkably frequent in PMP and the mutated gene product, guanine nucleotide-binding protein α subunit (Gsα), is a potential tumor neoantigen, presenting an opportunity for targeting by a therapeutic cancer vaccine. Methods Tumor and blood samples were collected from 25 patients undergoing surgery for PMP (NCT02073500). GNAS mutation analysis was performed by next-generation targeted sequencing or digital droplet PCR. Responses to stimulation with Gsα mutated (point mutations R201H and R201C) 30 mer peptides were analyzed in peripheral blood T cells derived from patients with PMP and healthy donors. Fresh PMP tumor samples were analyzed by mass cytometry using a panel of 35 extracellular markers, and cellular subpopulations were clustered and visualized using the visual stochastic network embedding analysis tool. Results GNAS mutations were detected in 22/25 tumor samples (88%; R201H and R201C mutations detected in 16 and 6 cases, respectively). Strong T cell proliferation against Gsα mutated peptides was observed in 18/24 patients with PMP. Mass cytometry analysis of tumor revealed infiltration of CD3 +T cells in most samples, with variable CD4+:CD8 + ratios. A large proportion of T cells expressed immune checkpoint molecules, in particular programmed death receptor-1 and T cell immunoreceptor with Ig and ITIM, indicating that these T cells were antigen experienced. Conclusion These findings point to the existence of a pre-existing immunity in patients with PMP towards mutated Gsα, which has been insufficient to control tumor growth, possibly because of inhibition of antitumor T cells by upregulation of immune checkpoint molecules. The results form a rationale for exploring peptide vaccination with Gsα peptides in combination with immune checkpoint inhibiton as a possible curative treatment for PMP and other GNAS mutated cancers

T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases

Background - Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite-stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumor-infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T-cell infiltration in CLM using T-cell receptor (TCR) repertoire sequencing. Eighty-five resected CLMs from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T-cell fractions were calculated, repertoire clonality was analyzed based on Hill evenness curves, and TCR sequence convergence was assessed using network analysis. Results - Increased T-cell fractions (10.6% vs. 6.3%) were detected in CLMs exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT-exposed tumors independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence. Conclusions - TCR repertoire sequencing can be used to quantify T-cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T-cell clonal expansion in CLM in a clinical context

Additional file 1 of The rainfall plot: its motivation, characteristics and pitfalls

Supplementary material. The file includes two definitions. The first defines how to formally provide a rainfall plot for the whole genome. The second defines how to discretize a whole genome rainfall plot (how to formally transform values in order to fit a grid). (PDF 32 kb