Diagnosis of childhood febrile illness using a multi-class blood RNA molecular signature

Background: Appropriate treatment and management of children presenting with fever depend on accurate and timely diagnosis, but current diagnostic tests lack sensitivity and specificity and are frequently too slow to inform initial treatment. As an alternative to pathogen detection, host gene expression signatures in blood have shown promise in discriminating several infectious and inflammatory diseases in a dichotomous manner. However, differential diagnosis requires simultaneous consideration of multiple diseases. Here, we show that diverse infectious and inflammatory diseases can be discriminated by the expression levels of a single panel of genes in blood. Methods: A multi-class supervised machine-learning approach, incorporating clinical consequence of misdiagnosis as a ‘‘cost’’ weighting, was applied to a whole-blood transcriptomic microarray dataset, incorporating 12 publicly available datasets, including 1,212 children with 18 infectious or inflammatory diseases. The transcriptional panel identifiedwas further validated in a new RNA sequencing dataset comprising 411 febrile children. Findings: We identified 161 transcripts that classified patients into 18 disease categories, reflecting individual causative pathogen and specific disease, as well as reliable prediction of broad classes comprising bacterial infection, viral infection, malaria, tuberculosis, or inflammatory disease. The transcriptional panel was validated in an independent cohort andbenchmarked against existingdichotomousRNA signatures. Conclusions: Our data suggest that classification of febrile illness can be achieved with a single blood sample and opens the way for a new approach for clinical diagnosis. Funding: European Union’s Seventh Framework no. 279185; Horizon2020 no. 668303 PERFORM; Wellcome Trust (206508/Z/17/Z); Medical Research Foundation (MRF-160-0008-ELP-KAFO-C0801); NIHR Imperial BRC

Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain

A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We present a set of integrated experiments that investigate the effects of common genetic variability on DNA methylation and mRNA expression in four human brain regions each from 150 individuals (600 samples total). We find an abundance of genetic cis regulation of mRNA expression and show for the first time abundant quantitative trait loci for DNA CpG methylation across the genome. We show peak enrichment for cis expression QTLs to be approximately 68,000 bp away from individual transcription start sites; however, the peak enrichment for cis CpG methylation QTLs is located much closer, only 45 bp from the CpG site in question. We observe that the largest magnitude quantitative trait loci occur across distinct brain tissues. Our analyses reveal that CpG methylation quantitative trait loci are more likely to occur for CpG sites outside of islands. Lastly, we show that while we can observe individual QTLs that appear to affect both the level of a transcript and a physically close CpG methylation site, these are quite rare. We believe these data, which we have made publicly available, will provide a critical step toward understanding the biological effects of genetic variation

Establishment and characterization of a new human pancreatic adenocarcinoma cell line with high metastatic potential to the lung

<p>Abstract</p> <p>Background</p> <p>Pancreatic cancer is still associated with devastating prognosis. Real progress in treatment options has still not been achieved. Therefore new models are urgently needed to investigate this deadly disease. As a part of this process we have established and characterized a new human pancreatic cancer cell line.</p> <p>Methods</p> <p>The newly established pancreatic cancer cell line PaCa 5061 was characterized for its morphology, growth rate, chromosomal analysis and mutational analysis of the K-<it>ras</it>, EGFR and p53 genes. Gene-amplification and RNA expression profiles were obtained using an Affymetrix microarray, and overexpression was validated by IHC analysis. Tumorigenicity and spontaneous metastasis formation of PaCa 5061 cells were analyzed in pfp^-/-/rag2^-/-mice. Sensitivity towards chemotherapy was analysed by MTT assay.</p> <p>Results</p> <p>PaCa 5061 cells grew as an adhering monolayer with a doubling time ranging from 30 to 48 hours. M-FISH analyses showed a hypertriploid complex karyotype with multiple numerical and unbalanced structural aberrations. Numerous genes were overexpressed, some of which have previously been implicated in pancreatic adenocarcinoma (GATA6, IGFBP3, IGFBP6), while others were detected for the first time (MEMO1, RIOK3). Specifically highly overexpressed genes (fold change > 10) were identified as EGFR, MUC4, CEACAM1, CEACAM5 and CEACAM6. Subcutaneous transplantation of PaCa 5061 into pfp^-/-/rag2^-/-mice resulted in formation of primary tumors and spontaneous lung metastasis.</p> <p>Conclusion</p> <p>The established PaCa 5061 cell line and its injection into pfp^-/-/rag2^-/-mice can be used as a new model for studying various aspects of the biology of human pancreatic cancer and potential treatment approaches for the disease.</p

Imaging biomarker roadmap for cancer studies.

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.Development of this roadmap received support from Cancer Research UK and the Engineering and Physical Sciences Research Council (grant references A/15267, A/16463, A/16464, A/16465, A/16466 and A/18097), the EORTC Cancer Research Fund, and the Innovative Medicines Initiative Joint Undertaking (grant agreement number 115151), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution

Imaging biomarker roadmap for cancer studies.

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.Development of this roadmap received support from Cancer Research UK and the Engineering and Physical Sciences Research Council (grant references A/15267, A/16463, A/16464, A/16465, A/16466 and A/18097), the EORTC Cancer Research Fund, and the Innovative Medicines Initiative Joint Undertaking (grant agreement number 115151), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution

Investigation of inter- and intraspecies variation through genome sequencing of Aspergillus section Nigri

Aspergillus section Nigri comprises filamentous fungi relevant to biomedicine, bioenergy, health, and biotechnology. To learn more about what genetically sets these species apart, as well as about potential applications in biotechnology and biomedicine, we sequenced 23 genomes de novo, forming a full genome compendium for the section (26 species), as well as 6 Aspergillus niger isolates. This allowed us to quantify both inter-and intraspecies genomic variation. We further predicted 17,903 carbohydrateactive enzymes and 2,717 secondary metabolite gene clusters, which we condensed into 455 distinct families corresponding to compound classes, 49% of which are only found in single species. We performed metabolomics and genetic engineering to correlate genotypes to phenotypes, as demonstrated for the metabolite aurasperone, and by heterologous transfer of citrate production to Aspergillus nidulans. Experimental and computational analyses showed that both secondary metabolism and regulation are key factors that are significant in the delineation of Aspergillus species.Peer reviewe

Wnt signalling modulates transcribed-ultraconserved regions in hepatobiliary cancers

Objective Transcribed-ultraconserved regions (T-UCR) are long non-coding RNAs which are conserved across species and are involved in carcinogenesis. We studied T-UCRs downstream of the Wnt/β-catenin pathway in liver cancer. Design Hypomorphic Apc mice (Apcfl/fl) and thiocetamide (TAA)-treated rats developed Wnt/β-catenin dependent hepatocarcinoma (HCC) and cholangiocarcinoma (CCA), respectively. T-UCR expression was assessed by microarray, real-time PCR and in situ hybridisation. Results Overexpression of the T-UCR uc.158− could differentiate Wnt/β-catenin dependent HCC from normal liver and from β-catenin negative diethylnitrosamine (DEN)-induced HCC. uc.158− was overexpressed in human HepG2 versus Huh7 cells in line with activation of the Wnt pathway. In vitro modulation of β-catenin altered uc.158− expression in human malignant hepatocytes. uc.158− expression was increased in CTNNB1-mutated human HCCs compared with non-mutated human HCCs, and in human HCC with nuclear localisation of β-catenin. uc.158− was increased in TAA rat CCA and reduced after treatment with Wnt/β-catenin inhibitors. uc.158− expression was negative in human normal liver and biliary epithelia, while it was increased in human CCA in two different cohorts. Locked nucleic acid-mediated inhibition of uc.158− reduced anchorage cell growth, 3D-spheroid formation and spheroid-based cell migration, and increased apoptosis in HepG2 and SW1 cells. miR-193b was predicted to have binding sites within the uc.158− sequence. Modulation of uc.158− changed miR-193b expression in human malignant hepatocytes. Co-transfection of uc.158− inhibitor and anti-miR-193b rescued the effect of uc.158− inhibition on cell viability. Conclusions We showed that uc.158− is activated by the Wnt pathway in liver cancers and drives their growth. Thus, it may represent a promising target for the development of novel therapeutics

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Diagnosis of childhood febrile illness using a multi-class blood RNA molecular signature.

BackgroundAppropriate treatment and management of children presenting with fever depend on accurate and timely diagnosis, but current diagnostic tests lack sensitivity and specificity and are frequently too slow to inform initial treatment. As an alternative to pathogen detection, host gene expression signatures in blood have shown promise in discriminating several infectious and inflammatory diseases in a dichotomous manner. However, differential diagnosis requires simultaneous consideration of multiple diseases. Here, we show that diverse infectious and inflammatory diseases can be discriminated by the expression levels of a single panel of genes in blood.MethodsA multi-class supervised machine-learning approach, incorporating clinical consequence of misdiagnosis as a "cost" weighting, was applied to a whole-blood transcriptomic microarray dataset, incorporating 12 publicly available datasets, including 1,212 children with 18 infectious or inflammatory diseases. The transcriptional panel identified was further validated in a new RNA sequencing dataset comprising 411 febrile children.FindingsWe identified 161 transcripts that classified patients into 18 disease categories, reflecting individual causative pathogen and specific disease, as well as reliable prediction of broad classes comprising bacterial infection, viral infection, malaria, tuberculosis, or inflammatory disease. The transcriptional panel was validated in an independent cohort and benchmarked against existing dichotomous RNA signatures.ConclusionsOur data suggest that classification of febrile illness can be achieved with a single blood sample and opens the way for a new approach for clinical diagnosis.FundingEuropean Union's Seventh Framework no. 279185; Horizon2020 no. 668303 PERFORM; Wellcome Trust (206508/Z/17/Z); Medical Research Foundation (MRF-160-0008-ELP-KAFO-C0801); NIHR Imperial BRC