Ornithine Decarboxylase Antizyme Induces Hypomethylation of Genome DNA and Histone H3 Lysine 9 Dimethylation (H3K9me2) in Human Oral Cancer Cell Line

Background: Methylation of CpG islands of genome DNA and lysine residues of histone H3 and H4 tails regulates gene transcription. Inhibition of polyamine synthesis by ornithine decarboxylase antizyme-1 (OAZ) in human oral cancer cell line resulted in accumulation of decarboxylated S-adenosylmethionine (dcSAM), which acts as a competitive inhibitor of methylation reactions. We anticipated that accumulation of dcSAM impaired methylation reactions and resulted in hypomethylation of genome DNA and histone tails. Methodology/Principal Findings: Global methylation state of genome DNA and lysine residues of histone H3 and H4 tails were assayed by Methylation by Isoschizomers (MIAMI) method and western blotting, respectively, in the presence or absence of OAZ expression. Ectopic expression of OAZ mediated hypomethylation of CpG islands of genome DNA and histone H3 lysine 9 dimethylation (H3K9me2). Protein level of DNA methyltransferase 3B (DNMT3B) and histone H3K9me specific methyltransferase G9a were down-regulated in OAZ transfectant. Conclusions/Significance: OAZ induced hypomethylation of CpG islands of global genome DNA and H3K9me2 by down-regulating DNMT3B and G9a protein level. Hypomethylation of CpG islands of genome DNA and histone H3K9me2 is a potent mechanism of induction of the genes related to tumor suppression and DNA double strand break repair

Quantitative measurement of airway dimensions using ultra-high resolution computed tomography

Background: Quantitative measurement of airway dimensions using computed tomography (CT) is performed in relatively larger airways due to the limited resolution of CT scans. Nevertheless, the small airway is an important pathological lesion in lung diseases such as chronic obstructive pulmonary disease (COPD) and asthma. Ultra-high resolution scanning may resolve the smaller airway, but its accuracy and limitations are unclear. Methods: Phantom tubes were imaged using conventional (512 × 512) and ultra-high resolution (1024 × 1024 and 2048 × 2048) scans. Reconstructions were performed using the forward-projected model-based iterative reconstruction solution (FIRST) algorithm in 512 × 512 and 1024 × 1024 matrix scans and the adaptive iterative dose reduction 3D (AIDR-3D) algorithm for all scans. In seven subjects with COPD, the airway dimensions were measured using the 1024 × 1024 and 512 × 512 matrix scans. Results: Compared to the conventional 512 × 512 scan, variations in the CT values for air were increased in the ultra-high resolution scans, except in the 1024×1024 scan reconstructed through FIRST. The measurement error of the lumen area of the tube with 2-mm diameter and 0.5-mm wall thickness (WT) was minimal in the ultra-high resolution scans, but not in the conventional 512 × 512 scan. In contrast to the conventional scans, the ultra-high resolution scans resolved the phantom tube with ≥ 0.6-mm WT at an error rate of < 11%. In seven subjects with COPD, the WT showed a lower value with the 1024 × 1024 scans versus the 512 × 512 scans. Conclusions: The ultra-high resolution scan may allow more accurate measurement of the bronchioles with smaller dimensions compared with the conventional scan

Epigenomic Diversity of Colorectal Cancer Indicated by LINE-1 Methylation in a Database of 869 Tumors

Background: Genome-wide DNA hypomethylation plays a role in genomic instability and carcinogenesis. LINE-1 (L1 retrotransposon) constitutes a substantial portion of the human genome, and LINE-1 methylation correlates with global DNA methylation status. LINE-1 hypomethylation in colon cancer has been strongly associated with poor prognosis. However, whether LINE-1 hypomethylators constitute a distinct cancer subtype remains uncertain. Recent evidence for concordant LINE-1 hypomethylation within synchronous colorectal cancer pairs suggests the presence of a non-stochastic mechanism influencing tumor LINE-1 methylation level. Thus, it is of particular interest to examine whether its wide variation can be attributed to clinical, pathologic or molecular features.Design Utilizing a database of 869 colorectal cancers in two prospective cohort studies, we constructed multivariate linear and logistic regression models for LINE-1 methylation (quantified by Pyrosequencing). Variables included age, sex, body mass index, family history of colorectal cancer, smoking status, tumor location, stage, grade, mucinous component, signet ring cells, tumor infiltrating lymphocytes, CpG island methylator phenotype (CIMP), microsatellite instability, expression of TP53 (p53), CDKN1A (p21), CTNNB1 (β-catenin), PTGS2 (cyclooxygenase-2), and FASN, and mutations in KRAS, BRAF, and PIK3CA. Results: Tumoral LINE-1 methylation ranged from 23.1 to 90.3 of 0-100 scale (mean 61.4; median 62.3; standard deviation 9.6), and distributed approximately normally except for extreme hypomethylators [LINE-1 methylation < 40; N = 22 (2.5%), which were far more than what could be expected by normal distribution]. LINE-1 extreme hypomethylators were significantly associated with younger patients (p = 0.0058). Residual plot by multivariate linear regression showed that LINE-1 extreme hypomethylators clustered as one distinct group, separate from the main tumor group. The multivariate linear regression model could explain 8.4% of the total variability of LINE-1 methylation (R-square = 0.084). Multivariate logistic regression models for binary LINE-1 hypomethylation outcomes (cutoffs of 40, 50 and 60) showed at most fair predictive ability (area under receiver operator characteristics curve < 0.63). Conclusions: LINE-1 extreme hypomethylators appear to constitute a previously-unrecognized, distinct subtype of colorectal cancers, which needs to be confirmed by additional studies. Our tumor LINE-1 methylation data indicate enormous epigenomic diversity of individual colorectal cancers

Epigenomic diversity of colorectal cancer indicated by LINE-1 methylation in a database of 869 tumors

<p>Abstract</p> <p>Background</p> <p>Genome-wide DNA hypomethylation plays a role in genomic instability and carcinogenesis. LINE-1 (L1 retrotransposon) constitutes a substantial portion of the human genome, and LINE-1 methylation correlates with global DNA methylation status. LINE-1 hypomethylation in colon cancer has been strongly associated with poor prognosis. However, whether LINE-1 hypomethylators constitute a distinct cancer subtype remains uncertain. Recent evidence for concordant LINE-1 hypomethylation within synchronous colorectal cancer pairs suggests the presence of a non-stochastic mechanism influencing tumor LINE-1 methylation level. Thus, it is of particular interest to examine whether its wide variation can be attributed to clinical, pathologic or molecular features.</p> <p>Design</p> <p>Utilizing a database of 869 colorectal cancers in two prospective cohort studies, we constructed multivariate linear and logistic regression models for LINE-1 methylation (quantified by Pyrosequencing). Variables included age, sex, body mass index, family history of colorectal cancer, smoking status, tumor location, stage, grade, mucinous component, signet ring cells, tumor infiltrating lymphocytes, CpG island methylator phenotype (CIMP), microsatellite instability, expression of TP53 (p53), CDKN1A (p21), CTNNB1 (β-catenin), PTGS2 (cyclooxygenase-2), and FASN, and mutations in <it>KRAS, BRAF</it>, and <it>PIK3CA</it>.</p> <p>Results</p> <p>Tumoral LINE-1 methylation ranged from 23.1 to 90.3 of 0-100 scale (mean 61.4; median 62.3; standard deviation 9.6), and distributed approximately normally except for extreme hypomethylators [LINE-1 methylation < 40; N = 22 (2.5%), which were far more than what could be expected by normal distribution]. LINE-1 extreme hypomethylators were significantly associated with younger patients (p = 0.0058). Residual plot by multivariate linear regression showed that LINE-1 extreme hypomethylators clustered as one distinct group, separate from the main tumor group. The multivariate linear regression model could explain 8.4% of the total variability of LINE-1 methylation (R-square = 0.084). Multivariate logistic regression models for binary LINE-1 hypomethylation outcomes (cutoffs of 40, 50 and 60) showed at most fair predictive ability (area under receiver operator characteristics curve < 0.63).</p> <p>Conclusions</p> <p>LINE-1 extreme hypomethylators appear to constitute a previously-unrecognized, distinct subtype of colorectal cancers, which needs to be confirmed by additional studies. Our tumor LINE-1 methylation data indicate enormous epigenomic diversity of individual colorectal cancers.</p

Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis

Background: Previous approaches to defining subtypes of colorectal carcinoma (CRC) and other cancers based on transcriptomes have assumed the existence of discrete subtypes. We analyze gene expression patterns of colorectal tumors from a large number of patients to test this assumption and propose an approach to identify potentially a continuum of subtypes that are present across independent studies and cohorts. Results: We examine the assumption of discrete CRC subtypes by integrating 18 published gene expression datasets and \u3e3700 patients, and contrary to previous reports, find no evidence to support the existence of discrete transcriptional subtypes. Using a meta-analysis approach to identify co-expression patterns present in multiple datasets, we identify and define robust, continuously varying subtype scores to represent CRC transcriptomes. The subtype scores are consistent with established subtypes (including microsatellite instability and previously proposed discrete transcriptome subtypes), but better represent overall transcriptional activity than do discrete subtypes. The scores are also better predictors of tumor location, stage, grade, and times of disease-free survival than discrete subtypes. Gene set enrichment analysis reveals that the subtype scores characterize T-cell function, inflammation response, and cyclin-dependent kinase regulation of DNA replication. Conclusions: We find no evidence to support discrete subtypes of the CRC transcriptome and instead propose two validated scores to better characterize a continuity of CRC transcriptomes

Predictive and Prognostic Roles of BRAF Mutation in Stage III Colon Cancer: Results from Intergroup Trial CALGB 89803

Alterations in the RAS-RAF-MAP2K (MEK)-MAPK signaling pathway are major drivers in colon and rectal carcinogenesis. In colorectal cancer, BRAF mutation is associated with microsatellite instability (MSI), and typically predicts inferior prognosis. We examined the effect of BRAF mutation on survival and treatment efficacy in patients with stage III colon cancer

TGFBR2 and BAX Mononucleotide Tract Mutations, Microsatellite Instability, and Prognosis in 1072 Colorectal Cancers

Mononucleotide tracts in the coding regions of the TGFBR2 and BAX genes are commonly mutated in microsatellite instability-high (MSI-high) colon cancers. The receptor TGFBR2 plays an important role in the TGFB1 (transforming growth factor-β, TGF-β) signaling pathway, and BAX plays a key role in apoptosis. However, a role of TGFBR2 or BAX mononucleotide mutation in colorectal cancer as a prognostic biomarker remains uncertain.We utilized a database of 1072 rectal and colon cancers in two prospective cohort studies (the Nurses' Health Study and the Health Professionals Follow-up Study). Cox proportional hazards model was used to compute mortality hazard ratio (HR), adjusted for clinical, pathological and molecular features including the CpG island methylator phenotype (CIMP), LINE-1 methylation, and KRAS, BRAF and PIK3CA mutations. MSI-high was observed in 15% (162/1072) of all colorectal cancers. TGFBR2 and BAX mononucleotide mutations were detected in 74% (117/159) and 30% (48/158) of MSI-high tumors, respectively. In Kaplan-Meier analysis as well as univariate and multivariate Cox regression analyses, compared to microsatellite stable (MSS)/MSI-low cases, MSI-high cases were associated with superior colorectal cancer-specific survival [adjusted HR, 0.34; 95% confidence interval (CI), 0.20-0.57] regardless of TGFBR2 or BAX mutation status. Among MSI-high tumors, TGFBR2 mononucleotide mutation was associated with CIMP-high independent of other variables [multivariate odds ratio, 3.57; 95% CI, 1.66-7.66; p = 0.0011].TGFBR2 or BAX mononucleotide mutations are not associated with the patient survival outcome in MSI-high colorectal cancer. Our data do not support those mutations as prognostic biomarkers (beyond MSI) in colorectal carcinoma

Comprehensive Biostatistical Analysis of CpG Island Methylator Phenotype in Colorectal Cancer Using a Large Population-Based Sample

The CpG island methylator phenotype (CIMP) is a distinct phenotype associated with microsatellite instability (MSI) and BRAF mutation in colon cancer. Recent investigations have selected 5 promoters (CACNA1G, IGF2, NEUROG1, RUNX3 and SOCS1) as surrogate markers for CIMP-high. However, no study has comprehensively evaluated an expanded set of methylation markers (including these 5 markers) using a large number of tumors, or deciphered the complex clinical and molecular associations with CIMP-high determined by the validated marker panel. METHOLODOLOGY/PRINCIPAL FINDINGS: DNA methylation at 16 CpG islands [the above 5 plus CDKN2A (p16), CHFR, CRABP1, HIC1, IGFBP3, MGMT, MINT1, MINT31, MLH1, p14 (CDKN2A/ARF) and WRN] was quantified in 904 colorectal cancers by real-time PCR (MethyLight). In unsupervised hierarchical clustering analysis, the 5 markers (CACNA1G, IGF2, NEUROG1, RUNX3 and SOCS1), CDKN2A, CRABP1, MINT31, MLH1, p14 and WRN were generally clustered with each other and with MSI and BRAF mutation. KRAS mutation was not clustered with any methylation marker, suggesting its association with a random methylation pattern in CIMP-low tumors. Utilizing the validated CIMP marker panel (including the 5 markers), multivariate logistic regression demonstrated that CIMP-high was independently associated with older age, proximal location, poor differentiation, MSI-high, BRAF mutation, and inversely with LINE-1 hypomethylation and beta-catenin (CTNNB1) activation. Mucinous feature, signet ring cells, and p53-negativity were associated with CIMP-high in only univariate analysis. In stratified analyses, the relations of CIMP-high with poor differentiation, KRAS mutation and LINE-1 hypomethylation significantly differed according to MSI status.Our study provides valuable data for standardization of the use of CIMP-high-specific methylation markers. CIMP-high is independently associated with clinical and key molecular features in colorectal cancer. Our data also suggest that KRAS mutation is related with a random CpG island methylation pattern which may lead to CIMP-low tumors

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries