Swift: primary data analysis for the Illumina Solexa sequencing platform

Motivation: Primary data analysis methods are of critical importance in second generation DNA sequencing. Improved methods have the potential to increase yield and reduce the error rates. Openly documented analysis tools enable the user to understand the primary data, this is important for the optimization and validity of their scientific work

Psychometric evaluation of the Problem Areas in Diabetes (PAID) survey in Southern, rural African American women with Type 2 diabetes

<p>Abstract</p> <p>Background</p> <p>The Problem Areas in Diabetes (PAID) survey is a measure of diabetes-related stress for which reported use has been in largely Caucasian populations. Our purpose was to assess the psychometric properties of the PAID in Southern rural African American women with Type 2 diabetes.</p> <p>Methods</p> <p>A convenience sample of African American women (N = 131) ranging from 21–50 years of age and diagnosed with Type 2 diabetes were recruited for a survey study from two rural Southern community health centers. Participants completed the PAID, Center for Epidemiological Studies-Depression Scale (CES-D), and the Summary of Diabetes Self-Care Activities Scale (SDSCA). Factor analysis, Cronbach's coefficient alpha, and construct validation facilitated psychometric evaluation.</p> <p>Results</p> <p>A principle component factor analysis of the PAID yielded two factors, 1) a lack of confidence subscale, and 2) a negative emotional consequences subscale. The Lack of Confidence and Negative Emotional Consequences subscales, but not the overall PAID scale, were associated with glycemic control and body mass index, respectively. Relationships with measures of depression and diabetes self-care supported construct validity of both subscales. Both subscales had acceptable (alpha = 0.85 and 0.94) internal consistency measures.</p> <p>Conclusion</p> <p>A psychometrically sound two-factor solution to the PAID survey is identified in Southern, rural African American women with Type 2 diabetes. Lack of confidence in and negative emotional consequences of diabetes self-care implementation provide a better understanding of determinants of glycemic control and weight than an aggregate of the two scales.</p

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

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

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

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

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

SARS-CoV-2 RNA detected in blood products from patients with COVID-19 is not associated with infectious virus

Background: Laboratory diagnosis of SARS-CoV-2 infection (the cause of COVID-19) uses PCR to detect viral RNA (vRNA) in respiratory samples. SARS-CoV-2 RNA has also been detected in other sample types, but there is limited understanding of the clinical or laboratory significance of its detection in blood. Methods: We undertook a systematic literature review to assimilate the evidence for the frequency of vRNA in blood, and to identify associated clinical characteristics. We performed RT-PCR in serum samples from a UK clinical cohort of acute and convalescent COVID-19 cases (n=212), together with convalescent plasma samples collected by NHS Blood and Transplant (NHSBT) (n=462 additional samples). To determine whether PCR-positive blood samples could pose an infection risk, we attempted virus isolation from a subset of RNA-positive samples. Results: We identified 28 relevant studies, reporting SARS-CoV-2 RNA in 0-76% of blood samples; pooled estimate 10% (95%CI 5-18%). Among serum samples from our clinical cohort, 27/212 (12.7%) had SARS-CoV-2 RNA detected by RT-PCR. RNA detection occurred in samples up to day 20 post symptom onset, and was associated with more severe disease (multivariable odds ratio 7.5). Across all samples collected ≥28 days post symptom onset, 0/494 (0%, 95%CI 0-0.7%) had vRNA detected. Among our PCR-positive samples, cycle threshold (ct) values were high (range 33.5-44.8), suggesting low vRNA copy numbers. PCR-positive sera inoculated into cell culture did not produce any cytopathic effect or yield an increase in detectable SARS-CoV-2 RNA. Conclusions: vRNA was detectable at low viral loads in a minority of serum samples collected in acute infection, but was not associated with infectious SARS-CoV-2 (within the limitations of the assays used). This work helps to inform biosafety precautions for handling blood products from patients with current or previous COVID-19

Integrated Molecular Characterization of Uterine Carcinosarcoma

SummaryWe performed genomic, epigenomic, transcriptomic, and proteomic characterizations of uterine carcinosarcomas (UCSs). Cohort samples had extensive copy-number alterations and highly recurrent somatic mutations. Frequent mutations were found in TP53, PTEN, PIK3CA, PPP2R1A, FBXW7, and KRAS, similar to endometrioid and serous uterine carcinomas. Transcriptome sequencing identified a strong epithelial-to-mesenchymal transition (EMT) gene signature in a subset of cases that was attributable to epigenetic alterations at microRNA promoters. The range of EMT scores in UCS was the largest among all tumor types studied via The Cancer Genome Atlas. UCSs shared proteomic features with gynecologic carcinomas and sarcomas with intermediate EMT features. Multiple somatic mutations and copy-number alterations in genes that are therapeutic targets were identified

Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH -Mutant Molecular Profiles

Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance

Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma

SummaryWe report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine