319 research outputs found

    Carriage of Haemophilus influenzae in Cape Town children

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    Little is known about the epideIDiology of Haemophilus influenzae infections in South Africa. This study was designed to determine the prevalence, serotype distribution, antimicrobial susceptibility pattern and effect of age and hospitalisation on the carriage of H. influenzae in 322 Cape Town children.The overall and type b specific carriage rates in normal children (N =107) were 45,8% and 4,7% respectively. The yield following nasopharyngeal culture was twice that following throat culture (P < 0,001). Children hospitalised with tuberculosis (N =62) had significantly greater carriage rates, 66,1% and 37,1% respectively (P =0,02). Institutionalised mentally handicapped children (N =77) and children with tuberculosis attending an outpatient clinic (N =76) had lower carriage rates (P < 0,02). Antimicrobial resistance was a major problem only in children hospitalised with tuberculosis (rifampicin 100%, penicillin 43,9%, erythromycin 85,4%, co-trimoxazole 82,9%). This universal resistance to rifampicin has not been reported previously. There was no difference in the mean age of children with positive or negative cultures, with the exception of those hospitalised with tuberculosis. In this group children infected with type b were much younger (mean 19,7 months) than those with other and non-typeableinfections (32,1 months) and the non-infected(50,1 months) (P =0,04). Duration of hospitalisation or outpatient therapy in the patients with tuberculosis did not influence carriage rates.We conclude that carriage of H. influenzae in normal children is similar to that reported from other countries and that carriage, particularly of type b, in children hospitalised with tuberculosis was of significance and probably contributed to an outbreak of multi-resistant invasive H. influenzae disease in this group

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data

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    Background: A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening. / Methods: United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3–T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups. / Results: The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age. / Conclusions: PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS. / Impact: Personalized genetic risk assessments could inform prostate cancer screening decisions

    An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

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    It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes

    Global Patterns of Prostate Cancer Incidence, Aggressiveness, and Mortality in Men of African Descent

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    Prostate cancer (CaP) is the leading cancer among men of African descent in the USA, Caribbean, and Sub-Saharan Africa (SSA). The estimated number of CaP deaths in SSA during 2008 was more than five times that among African Americans and is expected to double in Africa by 2030. We summarize publicly available CaP data and collected data from the men of African descent and Carcinoma of the Prostate (MADCaP) Consortium and the African Caribbean Cancer Consortium (AC3) to evaluate CaP incidence and mortality in men of African descent worldwide. CaP incidence and mortality are highest in men of African descent in the USA and the Caribbean. Tumor stage and grade were highest in SSA. We report a higher proportion of T1 stage prostate tumors in countries with greater percent gross domestic product spent on health care and physicians per 100,000 persons. We also observed that regions with a higher proportion of advanced tumors reported lower mortality rates. This finding suggests that CaP is underdiagnosed and/or underreported in SSA men. Nonetheless, CaP incidence and mortality represent a significant public health problem in men of African descent around the world
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