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Journal articles on the topic 'Bioinformatics and biostatistics'
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1
Brenner, Chad. "Applications of Bioinformatics in Cancer." Cancers 11, no. 11 (October 24, 2019): 1630. http://dx.doi.org/10.3390/cancers11111630.
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Ahmed, S. Ejaz. "New Frontiers of Biostatistics and Bioinformatics." Technometrics 63, no. 3 (July 3, 2021): 441–42. http://dx.doi.org/10.1080/00401706.2021.1945333.
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Molenberghs, Geert. "Biometry, Biometrics, Biostatistics, Bioinformatics, ... , Bio-X." Biometrics 61, no. 1 (March 2005): 1–9. http://dx.doi.org/10.1111/j.0006-341x.2005.040831.x.
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Cardinali, G., F. Maraziti, and S. Selvi. "Electrophoretic data classification for phylogenetics and biostatistics." Bioinformatics 19, no. 16 (October 31, 2003): 2163–65. http://dx.doi.org/10.1093/bioinformatics/btg294.
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Suprun, Maria, and Mayte Suárez-Fariñas. "PlateDesigner: a web-based application for the design of microplate experiments." Bioinformatics 35, no. 9 (October 9, 2018): 1605–7. http://dx.doi.org/10.1093/bioinformatics/bty853.
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Abstract Summary In biological assays, systematic variability, known as a batch effect, can often confound the effects of true biological conditions and has been well documented for a variety of high-throughput technologies. In microplate-based multiplex experiments, such as Luminex or OLINK assays, researchers need to consider both position and plate effects. Those effects can be easily accounted for if the experiments are properly designed, which includes randomization of the samples across multiple experimental runs. However, doing the ad hoc randomization becomes challenging when handling multiple samples. PlateDesigner is the first web-based application that provides randomization for microplate experiments, ensuring that the main principles of the experimental design, such as grouping samples from the same biological units and balancing the distribution of experimental conditions, are applied. Creating randomizations with PlateDesigner is simple and the results can be exported in a variety of formats, and easily integrated with microplate readers and statistical analysis software. Availability and implementation PlateDesigner is written in R/Shiny and is hosted online by the Center of Biostatistics at the Icahn School of Medicine at Mount Sinai. This application is freely available at platedesigner.net.
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Iqbal, Muhammad Shahid, Waqas Ahmad, Roohallah Alizadehsani, Sadiq Hussain, and Rizwan Rehman. "Breast Cancer Dataset, Classification and Detection Using Deep Learning." Healthcare 10, no. 12 (November 29, 2022): 2395. http://dx.doi.org/10.3390/healthcare10122395.
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Incorporating scientific research into clinical practice via clinical informatics, which includes genomics, proteomics, bioinformatics, and biostatistics, improves patients’ treatment. Computational pathology is a growing subspecialty with the potential to integrate whole slide images, multi-omics data, and health informatics. Pathology and laboratory medicine are critical to diagnosing cancer. This work will review existing computational and digital pathology methods for breast cancer diagnosis with a special focus on deep learning. The paper starts by reviewing public datasets related to breast cancer diagnosis. Additionally, existing deep learning methods for breast cancer diagnosis are reviewed. The publicly available code repositories are introduced as well. The paper is closed by highlighting challenges and future works for deep learning-based diagnosis.
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Dang, Sanjeena, and Nathalie Vialaneix. "Cutting Edge Bioinformatics and Biostatistics Approaches Are Bringing Precision Medicine and Nutrition to a New Era." Lifestyle Genomics 11, no. 2 (2018): 73–76. http://dx.doi.org/10.1159/000494131.
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Turck, Christoph W., Tytus D. Mak, Maryam Goudarzi, Reza M. Salek, and Amrita K. Cheema. "The ABRF Metabolomics Research Group 2016 Exploratory Study: Investigation of Data Analysis Methods for Untargeted Metabolomics." Metabolites 10, no. 4 (March 27, 2020): 128. http://dx.doi.org/10.3390/metabo10040128.
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Lack of standardized applications of bioinformatics and statistical approaches for pre- and postprocessing of global metabolomic profiling data sets collected using high-resolution mass spectrometry platforms remains an inadequately addressed issue in the field. Several publications now recognize that data analysis outcome variability is caused by different data treatment approaches. Yet, there is a lack of interlaboratory reproducibility studies that have looked at the contribution of data analysis techniques toward variability/overlap of results. The goal of our study was to identify the contribution of data pre- and postprocessing methods on metabolomics analysis results. We performed urinary metabolomics from samples obtained from mice exposed to 5 Gray of external beam gamma rays and those exposed to sham irradiation (control group). The data files were made available to study participants for comparative analysis using commonly used bioinformatics and/or biostatistics approaches in their laboratories. The participants were asked to report back the top 50 metabolites/features contributing significantly to the group differences. Herein we describe the outcome of this study which suggests that data preprocessing is critical in defining the outcome of untargeted metabolomic studies.
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Wei, Jiamin, Hongbo Wei, Yuxuan Xing, Bin Wang, Lu Han, Liang Tong, and Ying Zhou. "Statistical detecting of genes associated with PIK3C2B on lung disease." BIO Web of Conferences 59 (2023): 03011. http://dx.doi.org/10.1051/bioconf/20235903011.
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Statistical gene detection plays an important role in biostatistics and bioinformatics. So far, many gene loci associated with human complex disease have been found by statistical methods. However, it is difficult to find all the mutation genes that are associated with a certain disease. Researchers need to detect more associated genes aiming at a disease so that human will conquer the disease one day. In this paper, we considered a real and big data set and study the detection problem of genes associated with the PIK3C2B gene on lung disease. 168 significant genes associated with the PIK3C2B gene were detected at nominal significance level 0.001 by using statistical multiple testing method. The detected genes will provide some reference to further study the function of the PIK3C2B gene to lung disease for biologists and medical scientists.
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Chirilă, Monica-Emilia, and Søren M. Bentzen. "In Pursuit of Meaningfulness in the Biomedical Literature – Notes from a Scrap Booklet." Journal of Medical and Radiation Oncology 3, no. 2 (October 1, 2023): 85–90. http://dx.doi.org/10.53011/jmro.2023.02.11.
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"guestProfessor Søren M. Bentzen is the Director of the Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, USA, and he is also an Adjunct Professor of Radiobiology and Medical Physics, University of Copenhagen, Denmark. Dr. Bentzen received a Master of Sciences in physics and mathematics, a PhD in medical image analysis, and he is a doctor of medical science in quantitative clinical radiobiology. He was one of the leaders of the Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) initiative, and serves as a member of the Pediatric Normal Tissue Effects in the Clinic (PENTEC) steering committee. He was also a member of the American Society for Radiation Oncology (ASTRO) Task Forces to develop evidence-based guidelines on the appropriate fractionation for whole breast irradiation and for localized prostate cancer. He has served as chair or member of 17 (seven currently active) Independent Data and Safety Monitoring Committees or Trial Steering Committees and as co-chair for Translational Research for two Radiation Therapy Oncology Group (RTOG) phase III trials. He has published more than 500 original papers and book chapters, has presented >370 invited lectures, and he currently serves on 10 international cancer journal editorial boards. His main research interests include bioeffect modeling; biomathematics; applied biostatistics; clinical trial design; evidence-based medicine; late effects of radiotherapy; clinical radiobiology; integration of data from genomics, proteomics, and molecular imaging into novel therapeutic"
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Tasić, Srdjan, and Irena Tasić. "THE APPLICATION OF BIOINFORMATICS IN THE MOLECULAR CHARACTERIZATION OF Bacillus licheniformis." Knowledge International Journal 28, no. 4 (December 10, 2018): 1367–70. http://dx.doi.org/10.35120/kij28041367s.
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Bioinformatics is the application of information technology in biology and includes the processes of gathering, processing and analysing experimental results. Bioinformatics now entails the creation and advancement of databases, algorithms, computational and statistical techniques, and theory to solve formal and practical problems arising from the management and analysis of biological data. Computers are necessary in microbiology because the manual comparison of multiple sequences has become unpractical. The research subject was the characterisation of the strain ST51 isolated from the thermal water well in Vranjska Banja, south eastern Serbia. Molecular characterisation of these three strains was performed by analysis of the tuf gene, which encodes the elongation factor Tu. The DNA sequences were compared to those deposited in GenBank. data bases using the BLAST program (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastn). The biochemical characterisation was performed using the API 50 CHB system (bioMerieux) and APIWEB TM software Ver. 4.1. The molecular characterisation of the strain ST51 proved the highest level of similarity to the strain Bacillus licheniformis marked as ATCC 14580 (99% identical). The biochemical characterization confirmed that the strain ST51 belongs to the species Bacillus licheniformis.Given that all the conducted analyses yielded a substantial number of data, they were processed and compared using biostatistics methods and tools in order to achieve the highest probability of resulted taxonomic classification. Modern research contributes to the analysis of a significant number of variables which is why considerably more statistical analyses are involved in their interpretation and presentation. Our results indicate that different methods are needed for proper determination and characterisation of isolates/strains. Regarding taxonomy, molecular methods are the most precise, while for physiological specificity biochemical methods are more reliable.
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Choi, Dongseok, Srilakshmi M. Sharma, Sirichai Pasadhika, Zhixin Kang, Christina A. Harrington, Justine R. Smith, Stephen R. Planck, and James T. Rosenbaum. "Application of Biostatistics and Bioinformatics Tools to Identify Putative Transcription Factor-Gene Regulatory Network of Ankylosing Spondylitis and Sarcoidosis." Communications in Statistics - Theory and Methods 38, no. 18 (September 21, 2009): 3326–38. http://dx.doi.org/10.1080/03610920902898472.
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Ogino, Shuji, Jonathan A. Nowak, Tsuyoshi Hamada, Danny A. Milner, and Reiko Nishihara. "Insights into Pathogenic Interactions Among Environment, Host, and Tumor at the Crossroads of Molecular Pathology and Epidemiology." Annual Review of Pathology: Mechanisms of Disease 14, no. 1 (January 24, 2019): 83–103. http://dx.doi.org/10.1146/annurev-pathmechdis-012418-012818.
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Evidence indicates that diet, nutrition, lifestyle, the environment, the microbiome, and other exogenous factors have pathogenic roles and also influence the genome, epigenome, transcriptome, proteome, and metabolome of tumor and nonneoplastic cells, including immune cells. With the need for big-data research, pathology must transform to integrate data science fields, including epidemiology, biostatistics, and bioinformatics. The research framework of molecular pathological epidemiology (MPE) demonstrates the strengths of such an interdisciplinary integration, having been used to study breast, lung, prostate, and colorectal cancers. The MPE research paradigm not only can provide novel insights into interactions among environment, tumor, and host but also opens new research frontiers. New developments—such as computational digital pathology, systems biology, artificial intelligence, and in vivo pathology technologies—will further transform pathology and MPE. Although it is necessary to address the rarity of transdisciplinary education and training programs, MPE provides an exemplary model of integrative scientific approaches and contributes to advancements in precision medicine, therapy, and prevention.
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Schmidt, Julian C., Bonnie V. Dougherty, Richard D. Beger, Dean P. Jones, Michael A. Schmidt, and William B. Mattes. "Metabolomics as a Truly Translational Tool for Precision Medicine." International Journal of Toxicology 40, no. 5 (September 11, 2021): 413–26. http://dx.doi.org/10.1177/10915818211039436.
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Metabolomics is unique among omics technologies in being applicable to metabolism and toxicity studies broadly across organisms (e.g., humans, other mammals, model organisms, and even bacteria) and across biological materials (e.g., blood, urine, saliva, biopsy, and stool), including cultured cells and subcellular fractions. Metabolomics can be used to characterize biologic response patterns in humans as well as to support mechanistic studies in model systems and ex vivo studies. A broad range of resources are available, including publicly accessible data repositories (e.g., Metabolomics Workbench), tools for biostatistics and bioinformatics (e.g., MetaboAnalyst), metabolite identification (e.g., Metlin), and pathway analysis (e.g., Kyoto Encyclopedia of Genes and Genomes). Thus, metabolomics is more than a promise of the future; metabolomics is already available as a translational approach to facilitate precision medicine. This ACT Symposium review will contain an introduction to metabolomics in toxicity studies followed by sections on translational metabolic networks, translational metabolite biomarkers of acetaminophen-induced acute liver injury, translational framework using high-resolution metabolomics for integrated pharmacokinetics and pharmacodynamics, and precision medicine applications: extracting actionable targets from untargeted metabolomics data following one year in space.
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Marini, Federico, and Harald Binder. "Development of Applications for Interactive and Reproducible Research: a Case Study." Genomics and Computational Biology 3, no. 1 (October 31, 2016): 39. http://dx.doi.org/10.18547/gcb.2017.vol3.iss1.e39.
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For a proper understanding of the organization and regulation of gene expression, the computational analysis is an essential component of the scientific workflow, and this is particularly true in the fields of biostatistics and bioinformatics. Interactivity and reproducibility are two highly relevant features to consider when adopting or designing a tool, and often they can not be provided simultaneously.In this work, we address the issue of developing a framework that can provide interactive analysis, in order to allow experimentalists to fully exploit advanced software tools, as well as reproducibility as an internal validation of the analysis steps, by providing the underlying code and data in such a way that enables the re-creation of the results, and also constitutes a didactic tool for the life scientist.We illustrate this paradigm with the help of the R/Bioconductor package pcaExplorer, designed as a practical companion for interactive and reproducible exploratory data analysis for high dimensional data (e.g. RNA-seq), and highlight some of the features that are provided in the software.
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Lee, Po-Lei, Yuri Shelepin, and Teen-Hang Meen. "Introduction to a New Journal: International Journal of Clinical Medicine and Bioengineering." International Journal of Clinical Medicine and Bioengineering 1, no. 1 (March 20, 2021): 1–2. http://dx.doi.org/10.35745/ijcmb2021v01.01.0001.
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Clinical medicine is the branch of medicine about the practice of how clinical physicians carry on patients to promote health and cure illness. In contrast to traditional clinical medicine performs diagnosis and treatment on human subjects simply through direct observation, biostatistics, and clinical examination. The progress in recent medical technologies have provided more effective and efficient ways for physicians to treat patients. Scientists employ interdisciplinary knowledge, such as thermodynamics [1], kinetics [2], biocatalysts [3], biomechanics [4], bioinformatics [5], gene therapy [6], bioreactor design [7], fluid mechanics [8], bioelectronics [9], tissue engineering [10], computing technologies [11–13], and medical imaging technologies [14], in order to bridge applied sciences and clinical medicine. The necessity of medical technology prompts the emergence of bioengineering which gathers scientists, engineers and clinical physicians to resolve difficult clinical medicine problems, especially the issues of new clinical diseases and health threatens that we have never faced before. Researches in bioengineering field comprehensively develop usable and eligible medical devices, including diagnostic equipment, biocompatible materials, wearable devices, neurological stimulation devices, and surgical instruments. In order to discover new technologies for clinical medicine, we created a new journal: International Journal of Clinical Medicine and Bioengineering.
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Gonçalves, Emanuel, and Julio Saez-Rodriguez. "Cyrface: An interface from Cytoscape to R that provides a user interface to R packages." F1000Research 2 (September 19, 2013): 192. http://dx.doi.org/10.12688/f1000research.2-192.v1.
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There is an increasing number of software packages to analyse biological experimental data in the R environment. In particular, Bioconductor, a repository of curated R packages, is one of the most comprehensive resources for bioinformatics and biostatistics. The use of these packages is increasing, but it requires a basic understanding of the R language, as well as the syntax of the specific package used. The availability of user graphical interfaces for these packages would decrease the learning curve and broaden their application. Here, we present a Cytoscape plug-in termed Cyrface that allows Cytoscape plug-ins to connect to any function and package developed in R. Cyrface can be used to run R packages from within the Cytoscape environment making use of a graphical user interface. Moreover, it links the R packages with the capabilities of Cytoscape and its plug-ins, in particular network visualization and analysis. Cyrface’s utility has been demonstrated for two Bioconductor packages (CellNOptR and DrugVsDisease), and here we further illustrate its usage by implementing a workflow of data analysis and visualization. Download links, installation instructions and user guides can be accessed from the Cyrface homepage (http://www.ebi.ac.uk/saezrodriguez/cyrface/).
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Porazinska, Dorota L., Matthew J. Morgan, John M. Gaspar, Leon N. Court, Christopher M. Hardy, and Mike Hodda. "Discrimination of Plant-Parasitic Nematodes from Complex Soil Communities Using Ecometagenetics." Phytopathology® 104, no. 7 (July 2014): 749–61. http://dx.doi.org/10.1094/phyto-08-13-0236-r.
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Many plant pathogens are microscopic, cryptic, and difficult to diagnose. The new approach of ecometagenetics, involving ultrasequencing, bioinformatics, and biostatistics, has the potential to improve diagnoses of plant pathogens such as nematodes from the complex mixtures found in many agricultural and biosecurity situations. We tested this approach on a gradient of complexity ranging from a few individuals from a few species of known nematode pathogens in a relatively defined substrate to a complex and poorly known suite of nematode pathogens in a complex forest soil, including its associated biota of unknown protists, fungi, and other microscopic eukaryotes. We added three known but contrasting species (Pratylenchus neglectus, the closely related P. thornei, and Heterodera avenae) to half the set of substrates, leaving the other half without them. We then tested whether all nematode pathogens—known and unknown, indigenous, and experimentally added—were detected consistently present or absent. We always detected the Pratylenchus spp. correctly and with the number of sequence reads proportional to the numbers added. However, a single cyst of H. avenae was only identified approximately half the time it was present. Other plant-parasitic nematodes and nematodes from other trophic groups were detected well but other eukaryotes were detected less consistently. DNA sampling errors or informatic errors or both were involved in misidentification of H. avenae; however, the proportions of each varied in the different bioinformatic pipelines and with different parameters used. To a large extent, false-positive and false-negative errors were complementary: pipelines and parameters with the highest false-positive rates had the lowest false-negative rates and vice versa. Sources of error identified included assumptions in the bioinformatic pipelines, slight differences in primer regions, the number of sequence reads regarded as the minimum threshold for inclusion in analysis, and inaccessible DNA in resistant life stages. Identification of the sources of error allows us to suggest ways to improve identification using ecometagenetics.
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Kossida, Sophia. "Introduction into Systems Biology: Basics of Proteomics, Bioinformatics, Biostatistics & Integration of Data Generated by these Fields, Athens, Greece, 26-30 September 2011." EMBnet.journal 17, no. 1 (April 12, 2011): 4. http://dx.doi.org/10.14806/ej.17.1.199.
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Gonçalves, Emanuel, Franz Mirlach, and Julio Saez-Rodriguez. "Cyrface: An interface from Cytoscape to R that provides a user interface to R packages." F1000Research 2 (July 1, 2014): 192. http://dx.doi.org/10.12688/f1000research.2-192.v2.
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There is an increasing number of software packages to analyse biological experimental data in the R environment. In particular, Bioconductor, a repository of curated R packages, is one of the most comprehensive resources for bioinformatics and biostatistics. The use of these packages is increasing, but it requires a basic understanding of the R language, as well as the syntax of the specific package used. The availability of user graphical interfaces for these packages would decrease the learning curve and broaden their application. Here, we present a Cytoscape app termed Cyrface that allows Cytoscape apps to connect to any function and package developed in R. Cyrface can be used to run R packages from within the Cytoscape environment making use of a graphical user interface. Moreover, it can link R packages with the capabilities of Cytoscape and its apps, in particular network visualization and analysis. Cyrface’s utility has been demonstrated for two Bioconductor packages (CellNOptR and DrugVsDisease), and here we further illustrate its usage by implementing a workflow of data analysis and visualization. Download links, installation instructions and user guides can be accessed from the Cyrface’s homepage (http://www.ebi.ac.uk/saezrodriguez/cyrface/) and from the Cytoscape app store (http://apps.cytoscape.org/apps/cyrface).
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Dedov, I. I., N. G. Mokrysheva, M. V. Shestakova, P. Y. Volchkov, A. Y. Mayorov, O. Yu Rebrova, V. O. Barysheva, et al. "The prospects for the creation of the National Center for Personalized Medicine of Endocrine Diseases." Problems of Endocrinology 67, no. 1 (February 12, 2021): 13–19. http://dx.doi.org/10.14341/probl12730.
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The National Medical Research Center for Endocrinology (NMRCE) received the right to implement the development program of the World-class Research Centre “The National Center for personalized medicine of endocrine diseases” (NMCPMED). The objective of the NMCPMED will be not only the creation of a system of personalized treatment, but also the training of new specialists for medicine. Fundamental researches, carried out on the basis of the already existing institutes and laboratories of the NMRCE will be expanded by creating new laboratories of the NCPMED created de novo in accordance with the approved project. This article introduces the reader to the most important laboratories that would be created in NCPMED. These are laboratories of general, molecular and population genetics, bioinformatics, pharmacogenomics, microbiota, genome editing, mathematical and digital technologies, non-invasive technologies for the diagnosis of endocrinopathies, cellular technologies, artificial intelligence and a fundamentally new laboratory of metabolic visualization and radioteranostics. The authors hope that readers of one of the main journals for endocrinologists in our country will actively participate in the implementation of NMRCE, as both young and experienced talented researchers will have a chance to be a part of the Centre. To realize the ambitious implementation plans for the achievements of the Centre, it is necessary to radically change the worldview of the doctors in our country, to train them in a new way, and to expand the structure of the Center’s team by increasing the number of specialists in medical genetics, transcriptomics, biostatistics and bioinformatics, working at the intersection of experimental and clinical endocrinology, and ensuring the transit of innovative technologies into clinical practice. New laboratories of the World-Class Research Center, will become the place of routine work of a new generation of doctors, who possess not only the basics of clinical work, but also the skills of fundamental researches that will allow them to significantly improve the methods of diagnosis and treatment.
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Pusek, Susan, Beth Knudson, Joel Tsevat, Cecilia M. Patino, David D. Chaplin, David H. Ingbar, Jason G. Umans, Joan Nagel, and Rebecca D. Jackson. "Personalized training pathways for translational science trainees: Building on a framework of knowledge, skills, and abilities across the translational science spectrum." Journal of Clinical and Translational Science 4, no. 2 (February 19, 2020): 102–7. http://dx.doi.org/10.1017/cts.2019.445.
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AbstractBackground:In order to conduct translational science, scientists must combine domain-specific expertise with knowledge on how to identify and cross translational hurdles, and insights on positioning discoveries for the next translational stage. Expert educators from the Clinical and Translational Science Awards (CTSA) Consortium identified 97 knowledge, skills, and abilities (KSAs) important to include in training programs for translational scientists. To assist educators and trainees to use these KSAs, a conceptual model called “Personalized Pathways” was developed that prioritizes KSAs based on trainee background, research area, or phenotype, and expertise on the research team.Purpose:To understand how CTSA educators prioritize specific KSAs when developing personalized training plans for different translational phenotypes and to identify areas of similarity and difference across phenotypes.Methods:A web-based, cross-sectional survey of CTSA educators was done. For a selected phenotype, respondents recommended one of four levels of mastery for each of the 97 KSAs. Results were tabulated by frequency, weighted by importance, and divided into tertiles representing high, middle, and lower priority KSAs. Agreement across phenotypes was compared using Krippendorff’s alpha.Results:Ten KSAs were high training priority for Preclinical, Clinical, and Community-Engaged phenotypes. These address research methods, responsible conduct of research, team building, and communicating research results. Nine KSAs were in the next tertile for priority reflecting KSAs in biostatistics, bioinformatics, regulatory precepts, and translating implications of research findings.Conclusion:A smaller set of KSAs can be prioritized for training Preclinical-, Clinical-, and Community-Engaged researchers. Future work should explore this approach for other phenotypes.
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Akpalu, Albert, Fred Stephen Sarfo, Bruce Ovbiagele, Rufus Akinyemi, Mulugeta Gebregziabher, Reginald Obiako, Lukman Owolabi, et al. "Phenotyping Stroke in Sub-Saharan Africa: Stroke Investigative Research and Education Network (SIREN) Phenomics Protocol." Neuroepidemiology 45, no. 2 (2015): 73–82. http://dx.doi.org/10.1159/000437372.
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Background: As the second leading cause of death and the leading cause of adult-onset disability, stroke is a major public health concern particularly pertinent in Sub-Saharan Africa (SSA), where nearly 80% of all global stroke mortalities occur, and stroke burden is projected to increase in the coming decades. However, traditional and emerging risk factors for stroke in SSA have not been well characterized, thus limiting efforts at curbing its devastating toll. The Stroke Investigative Research and Education Network (SIREN) project is aimed at comprehensively evaluating the key environmental and genomic risk factors for stroke (and its subtypes) in SSA while simultaneously building capacities in phenomics, biobanking, genomics, biostatistics, and bioinformatics for brain research. Methods: SIREN is a transnational, multicentre, hospital and community-based study involving 3,000 cases and 3,000 controls recruited from 8 sites in Ghana and Nigeria. Cases will be hospital-based patients with first stroke within 10 days of onset in whom neurovascular imaging will be performed. Etiological and topographical stroke subtypes will be documented for all cases. Controls will be hospital- and community-based participants, matched to cases on the basis of gender, ethnicity, and age (±5 years). Information will be collected on known and proposed emerging risk factors for stroke. Study Significance: SIREN is the largest study of stroke in Africa to date. It is anticipated that it will shed light on the phenotypic characteristics and risk factors of stroke and ultimately provide evidence base for strategic interventions to curtail the burgeoning burden of stroke on the sub-continent.
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Wrensch, Margaret, James L. Fisher, Judith A. Schwartzbaum, Melissa Bondy, Mitchel Berger, and Kenneth D. Aldape. "The molecular epidemiology of gliomas in adults." Neurosurgical Focus 19, no. 5 (November 2005): 1–11. http://dx.doi.org/10.3171/foc.2005.19.5.6.
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In this paper the authors highlight recent findings from molecular epidemiology studies of glioma origin and prognosis and suggest promising paths for future research. The reasons for variation in glioma incidence according to time period of diagnosis, sex, age, ancestry and ethnicity, and geography are poorly understood, as are factors that affect prognosis. High-dose therapeutic ionizing irradiation and rare mutations in highly penetrant genes associated with certain rare syndromes—the only two established causes of glioma—can be called upon to explain few cases. Both familial aggregation of gliomas and the inverse association of allergies and immune-related conditions with gliomas have been shown consistently, but the explanations for these associations are inadequately developed or unknown. Several bio-markers do predict prognosis, but only evaluation of loss of 1p and 19q in oligodendroglial tumors are incorporated in clinical practice. Ongoing research focuses on classifying homogeneous groups of tumors on the basis of molecular markers and identifying inherited polymorphisms that may influence survival or risk. Because most cases of glioma have yet to furnish either an environmental or a genetic explanation, the greatest potential for discovery may lie in genomic studies in conjunction with continued evaluation of environmental and developmental factors. Large sample sizes and multidisciplinary teams with expertise in neuropathology, genetics, epidemiology, functional genomics, bioinformatics, biostatistics, immunology, and neurooncology are required for these studies to permit exploration of potentially relevant pathways and modifying effects of other genes or exposures, and to avoid false-positive findings. Improving survival rates for patients harboring astrocytic tumors will probably require many randomized clinical trials of novel treatment strategies.
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Dana, Dibyendu, Satishkumar Gadhiya, Luce St. Surin, David Li, Farha Naaz, Quaisar Ali, Latha Paka, et al. "Deep Learning in Drug Discovery and Medicine; Scratching the Surface." Molecules 23, no. 9 (September 18, 2018): 2384. http://dx.doi.org/10.3390/molecules23092384.
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The practice of medicine is ever evolving. Diagnosing disease, which is often the first step in a cure, has seen a sea change from the discerning hands of the neighborhood physician to the use of sophisticated machines to use of information gleaned from biomarkers obtained by the most minimally invasive of means. The last 100 or so years have borne witness to the enormous success story of allopathy, a practice that found favor over earlier practices of medical purgatory and homeopathy. Nevertheless, failures of this approach coupled with the omics and bioinformatics revolution spurred precision medicine, a platform wherein the molecular profile of an individual patient drives the selection of therapy. Indeed, precision medicine-based therapies that first found their place in oncology are rapidly finding uses in autoimmune, renal and other diseases. More recently a new renaissance that is shaping everyday life is making its way into healthcare. Drug discovery and medicine that started with Ayurveda in India are now benefiting from an altogether different artificial intelligence (AI)—one which is automating the invention of new chemical entities and the mining of large databases in health-privacy-protected vaults. Indeed, disciplines as diverse as language, neurophysiology, chemistry, toxicology, biostatistics, medicine and computing have come together to harness algorithms based on transfer learning and recurrent neural networks to design novel drug candidates, a priori inform on their safety, metabolism and clearance, and engineer their delivery but only on demand, all the while cataloging and comparing omics signatures across traditionally classified diseases to enable basket treatment strategies. This review highlights inroads made and being made in directed-drug design and molecular therapy.
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Knitz, Michael W., Thomas E. Bickett, Laurel B. Darragh, Shilpa Bhatia, Benjamin Van Court, Miles Piper, Sarah Douglas, and Sana D. Karam. "Sexual dimorphism and the effect of therapeutic low-dose estrogen in head and neck squamous cell carcinoma." Journal of Immunology 208, no. 1_Supplement (May 1, 2022): 63.10. http://dx.doi.org/10.4049/jimmunol.208.supp.63.10.
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Abstract Differences between males and females have been identified in a variety of immune-related diseases. Generally, females show stronger immune responses, but also present a higher incidence of auto immune disease. Reasons for this have not been concretely identified but estrogen is believed to be a main driver of sex-dependent differences in biological behavior of disease and response to therapy. Using castration, oophorectomy, and estrogen rescue experiments in various preclinical head and neck squamous cell carcinoma (HNSCC) models, we identify estrogen as a regulator of immune response to treatment. The effect of estrogen is dose-dependent, as higher doses fail to demonstrate the beneficial effects of low dose estrogen. This response is dependent on regulatory T cells and dendritic cells, as knockout of these cell types eliminates the disparity between male and female responses. We also identified estrogen receptor beta agonists as a potential therapeutic strategy providing similar treatment benefit as low dose estrogen, reversing the effects of oophorectomy and stimulating cytotoxic T cell function. Survival analysis from HNSCC patients provided correlational validation of the potential benefit of estrogen as it demonstrates increased overall survival in younger women. Our data implicate low dose estrogen as a potential therapeutic strategy to enhance response to immunotherapy. Sana D. Karam is funded by the NIDCR (R01 DE028529-01, R01 DE028282-01) and Colorado Head and Neck Cancer SPORE and receives funding from Astra Zeneca, Genentech, and Ionis. This study was partly supported by the National Institutes of Health P30CA046934 Cancer Center Support Grant, including the Bioinformatics and Biostatistics Shared Resource Core, the Cancer Center Flow Cytometry Shared Resource, and the Genomics and Microarray Shared Resource at the University of Colorado. This study was also partly supported by the Cancer League of Colorado.
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Wichmann, H. E. "Genetic Epidemiology in Germany." Methods of Information in Medicine 44, no. 04 (2005): 584–89. http://dx.doi.org/10.1055/s-0038-1634011.
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Summary Objectives: Genetic epidemiology investigates the role of genetic factors and their interaction with environmental factors (in a broad meaning) for the occurrence of diseases in human populations. Its aim is to undest-and the influence of genetics on the development of dis-eases, their course and the clinical implications, with the final goal to improve prevention, diagnostics and therapy. Methods: Originally genetic epidemiology was understood as a specialized discipline with the main focus on family-based studies. The extraordinary development of genetics in the last decades – with respect of the understanding of the meaning of genes for human health, as well as by the availability of cost-effective high throughput methods in the lab, has opened enormous opportunities to study genetic factors. Now, genetic epidemiology and genetic statistics have a much broader application. In addition, access to large samples of patients or from the population is needed. This can be realized via biobanks. Results: Large biobanks with 500,000 or more patients or participants from the general population are being established or planned in the UK, Japan or the US. However, in Germany only two smaller activities are ongoing, KORA-gen in the south and POPGEN in the north. Possibilities to reach larger numbers, based on existing cohorts or disease networks are discussed. Ethical boundary conditions have to be taken into account, which seem to improve due to the Opinion of the German National Ethics Council on Biobanks for Research. Furthermore, the activities of the German centers for Genetic Epidemiological Methods (GEMs) as research and support units for genetic statistics and epidemiological methodology are described. Conclusions: Genetic epidemiology is based strongly on interdisciplinary collaboration and includes basics of genetics, elements of molecular biology to identify genes, population genetics, clinical medicine, and methodological disciplines as epidemiology, biostatistics and bioinformatics. In Germany the situation for this type of patient-based research has recently improved due to the National Genome Research Network (NGFN).
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Nandikolmath, Dattaniranjan, Rupesh Samanchi, Barsha Rana, and Aruna Hallikeri. "Using R Programming for Somatoploting." International Journal of Kinanthropometry 4, no. 1 (April 30, 2024): 50–61. http://dx.doi.org/10.34256/ijk2417.
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Introduction: Anthropometry is a technique employed to evaluate body dimensions and ratios by examining body length, width, circumference, and skinfold thickness. It is cost-effective, uncomplicated, and easily transportable, and it may be used in diverse industries. Somatotyping is a primary method used to classify the human physique based on three main components: endomorphy, mesomorphy, and ectomorphy. Heath and Carter established and modified the standards of somatotype, which continue to be employed for global measurements. Several software tools have been created for somatoploting, including SAS/GRAPH, Houcine, Orhan, and machine-learning models. Nevertheless, most of these tools are not open-source, resulting in laborious manual enumeration and hindering the accurate representation of differences among groups. A functional, open-source, precise tool is required to categorise somatotypes of extensive sample sizes and illustrate their differences. Method: R programming is a powerful and versatile programme language, particularly popular in statistical computing and graphics. It is widely used in various fields, like biostatistics, bioinformatics, and financial market analysis. R incorporates original programming concepts like object-oriented programming, which users can use transparently. This paper introduces how to use R programming as a tool for somatoploting, introduces the code for somatoploting, inserts x and y data, and executes the program to get a somatochart. It uses anthropometric data of 34 school-going students collected in Shindikurbet, Karnataka, aged between 10 and 12 years, collected through ISAK protocol guidelines to develop somatotypes and further plot them. Result: The paper holistically demonstrates using R programming to plot somatotypes in a 2-D Somatochart. Using this process, the reader can develop high-quality somatocharts in image or PDF formats. Conclusion: This study explores using R programming, an open-source software, for somatoploting and generating somatocharts. This method aids in understanding complex information, fact-explaining, and guiding action in various fields. It offers accessible data processing, analysis, and presentation, making implementing and saving budgets for students, researchers, and institutions easy. Further research could be conducted to make the code easier to use in Excel sheets or mobile applications.
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Rossetti, Renata, Leticia Tordesillas, Matthew Beatty, Yian Ann Chen, Dongliang Du, Amod Sarnaik, Shari Pilon-Thomas, and Daniel Abate-Daga. "195 Stimulation of tumor infiltrating B-cells improves ex-vivo TIL expansion for melanoma immunotherapy." Journal for ImmunoTherapy of Cancer 9, Suppl 2 (November 2021): A206. http://dx.doi.org/10.1136/jitc-2021-sitc2021.195.
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BackgroundThe immunogenic nature of melanoma has been exploited for the development of adoptive transfer of ex-vivo expanded tumor infiltrating lymphocytes (TIL). This adoptive cell transfer therapy has overall response rates of around 50%. Multiple factors may determine the quality of the TIL product including components of the tumor microenvironment. B-cells are frequently found in melanoma metastasis, and display signs of antigen experience. Recently, B-cell tumor infiltration has been associated with improved clinical responses to immune checkpoint inhibitors,1 2 but their role in TIL therapy remains unexplored. Considering the potential role of B cells, we aim to develop strategies to enhance the quality of TIL products through B-cell stimulation during ex-vivo TIL expansion.MethodsWe stimulated melanoma infiltrating B-cells using human recombinant CD40L on the first day of ex-vivo TIL expansion. Thirteen samples were expanded from melanoma tumor single cell suspensions, in high dose IL-2 alone (standard protocol), or in high dose IL-2 plus CD40L. After up to four weeks of expansion, the TIL phenotype was analyzed by flow cytometry.ResultsThe expansion success rate from the frozen tumor digests was 69% (95% CI: 38.6–90.9%) in the CD40L treatment condition compared to 23% with the standard protocol. Also, TILs cultured in the presence of CD40L expanded to higher numbers than with the standard protocol (P = 0.02). Interestingly, most of the samples expanded with CD40L had a significant increase in the percentage of CD4+ T cells (P = 0.03), but not to the detriment of the absolute number of CD8+ T cells. Treatment with CD40L increased the percentage of effector memory-like T cells (P = 0.03) and of CD39- CD69- T cells (P < 0.05), which were recently associated with response to TIL therapy.3ConclusionsThis preliminary work demonstrates that the stimulation with CD40L at the initiation of TIL culture leads to enhanced TIL expansion and an increase in CD4+ T cells with an effector memory-like and stem-like phenotype. Our group and others have previously described cases of patients who had tumor regression after receiving TIL therapy that were predominantly CD4+ T cells, suggesting that expansion of the CD4+ TIL repertoire may enhance TIL therapy.4AcknowledgementsThis work has been supported in part by the Flow Cytometry, Genomics and Biostatistics and Bioinformatics Core Facilities at Moffitt Cancer Center, an NCI designated Comprehensive Cancer Center (P30-CA076292). We acknowledge Moffitt’s Melanoma Center of Excellence for the financial support.ReferencesCabrita R, Lauss M, Sanna A. Tertiary lymphoid structures improve immunotherapy and survival in melanoma. Nature 2020;577:561–565.Petitprez F, de Reynies A, Keung EZ. B cells are associated with survival and immunotherapy response in sarcoma. Nature 2020;577:556–560.Krishna S, Lowery FJ, Copeland AR. Stem-like CD8 T cells mediate response of adoptive cell immunotherapy against human cancer. Science 2020;370:1328–1334.Friedman KM, Prieto PA, Devillier LE. Tumor-specific CD4+ melanoma tumor-infiltrating lymphocytes. J Immunother 2012;35:400–408.Ethics ApprovalThe study was approved by Advarra IRB, approval number MCC20559.
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Markowitz, Joseph, Zachary Abrams, Naduparambil Jacob, Xiaoli Zhang, John Hassani, Nicholas Latchana, Lai Wei, et al. "MicroRNA profiling of patient plasma for clinical trials using bioinformatics and biostatistical approaches." OncoTargets and Therapy Volume 9 (September 2016): 5931–41. http://dx.doi.org/10.2147/ott.s106288.
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Martini, Dylan, Julie Shabto, Subir Goyal, Yuan Liu, T. Anders Olsen, Sean Evans, Benjamin Magod, et al. "45 Body composition as a predictive and prognostic biomarker in advanced urothelial carcinoma (UC) patients treated with immune checkpoint inhibitors (ICI)." Journal for ImmunoTherapy of Cancer 8, Suppl 3 (November 2020): A47—A48. http://dx.doi.org/10.1136/jitc-2020-sitc2020.0045.
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BackgroundSeveral immune checkpoint inhibitors (ICI) have been approved for the treatment of advanced urothelial carcinoma (UC). There are limited predictive biomarkers for UC patients treated with ICI. In this study, we investigated the association between body composition and clinical outcomes in ICI-treated advanced UC patients.MethodsWe conducted a retrospective analysis of 70 ICI-treated advanced UC patients at Winship Cancer Institute from 2015–2020. Inclusion criteria was available computed tomography (CT) scans within 2 months of ICI-initiation. Baseline CT images were collected at mid-L3 and muscle and fat compartments were segmented using SliceOMatic v5.0 (TomoVision). The density of subcutaneous fat, inter-muscular fat, visceral fat, and skeletal muscle (SM) were measured and converted to indices by dividing by height(m)2 (SFI, IFI, VFI and SMI, respectively). Attenuated SM mean (Hounsfield Units) was also collected. Myosteatosis was calculated by IFI/SMI*100%. Gender-specific optimal cuts were used to dichotomize patients as high or low for each variable using OS as the primary outcome. A prognostic body composition risk score was created based on the beta coefficient from the multivariable Cox model (MVA) following best-subset variable selection. Our body composite risk score was SMI + 2*SM mean + VFI and patients were categorized as high (0–1), intermediate (2–3), or low-risk (4). Comparison of OS and PFS between the risk groups was performed via Kaplan-Meier method and Log-rank test. Concordance statistics (C-statistics) were used to quantify the discriminatory magnitude of the predictive model.ResultsMost patients (70%) were male and more than one-quarter (26%) had an ECOG PS ≥ 2. The majority received ICI in the second (46%) or third-line (21%) setting. Body composite poor-risk patients had significantly shorter OS (HR: 6.18, p<0.001), PFS (HR: 5.91, p<0.001), and lower chance at CB (OR: 0.02, p=0.004) compared to low-risk group in MVA (table 1). Patients with low myosteatosis had significantly longer OS (HR: 0.35, p=0.002), PFS (HR: 0.32, p<0.001), and higher chance at CB (OR: 20.47, p=0.034) compared to high myosteatosis patients in MVA. The C-statistics for our body composition risk group and myosteatosis analyses were higher than BMI for all clinical outcomes (table 2). High and intermediate-risk patients had significantly shorter OS and PFS compared to low-risk patients per Kaplan-Meier estimation (figure 1).Abstract 45 Table 1MVA* of association between risk groups and myosteatosis with clinical outcomesAbstract 45 Table 2Comparison of C-statistics between body composition risk groups, myosteatosis and BMIAbstract 45 Figure 1Kaplan-Meier curves of association between body composition risk groups and overall survival (OS, top panel) and progression-free survival (PFS, bottom panel)ConclusionsBody composition variables such as SMI, SM mean, VFI and myosteatosis may be predictive of clinical outcomes in ICI-treated advanced UC patients. Larger, prospective studies are warranted to validate this hypothesis-generating data.AcknowledgementsResearch reported in this publication was supported in part by the Biostatistics and Bioinformatics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.Trial RegistrationNot applicableEthics ApprovalThis retrospective study was approved by the Emory University Institutional Review Board.ConsentNot applicableReferencesNot applicable
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Rossetti, Renata Ariza Marques, Leticia Tordesillas, Matthew Beatty, Dongliang Du, Yian Ann Chen, Amod Sarnaik, Shari Pilon-Thomas, and Daniel Abate-Daga. "Abstract 4055: CD40L stimulates melanoma infiltrating B cells and enhances ex vivo TIL expansion." Cancer Research 83, no. 7_Supplement (April 4, 2023): 4055. http://dx.doi.org/10.1158/1538-7445.am2023-4055.
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Abstract Adoptive transfer of tumor infiltrating lymphocytes (TIL) is a feasible and effective therapy for melanoma and lung cancer[1,2]. Multiple factors may determine the quality of the TIL product including components of the tumor microenvironment. In this work, we analyzed the role of melanoma infiltrating B cells in the context of TIL expansion based on their documented association with response to other types of immunotherapies[3]. We stimulated melanoma infiltrating B cells using human recombinant CD40L on the first day of ex-vivo TIL expansion. Samples were expanded from cryopreserved melanoma tumor single cell suspensions, in high dose IL-2 alone (standard protocol), or in high dose IL-2 plus CD40L. After 48h, analysis of activation markers on the CD40-expressing cells by flow cytometry was performed. For further investigation of the changes induced by CD40L stimulation, TIL expansion cultures (+/- CD40L) were analyzed using scRNA-seq (10X Genomics Chromium NextGEM Single Cell 5’ v2 and V(D)J Reagent kits; Illumina NovaSeq 6000 instrument with S4 sequencing flow cell) at 48h of culture (n=7 patients). The TIL expansion success rate was 68% with the CD40L treatment condition compared to 36% with the standard protocol. TILs cultured in the presence of CD40L expanded to on average three times more than with the standard protocol (P ≤ 0.01). Treatment with CD40L increased the percentage of CD39- CD69- T cells (P ≤ 0.05). Within the tumor digests, a higher percentage of B cells, including switched memory B cells (CD27+ IgD− ), was associated with successful TIL expansion (P=0.04). scRNA-seq analysis demonstrated different clustering patterns within the B cell compartment based on culture conditions. No clear partition was observed for other cell types, including the myeloid compartment. B cells displayed 126 DEGs associated to CD40L addition, CCL22, CD83, EBI3 and CD58 were among the upregulated genes in the CD40L-treated B cells. Other cell types experienced minimal to no change in transcriptomic profiles. B cell clusters were sub-classified based on CD27 and IgD expression[4], showing a predominance of naïve and switched memory B cells. Our results show that higher presence of B cells within tumors is associated with better TIL expansion, suggesting an interplay between T and B cells, and providing rationale for the design of improved TIL expansion protocols based on B cell stimulation with CD40L. This work has been supported in part by the Flow Cytometry, Genomics and Biostatistics and Bioinformatics Core Facilities at Moffitt Cancer Center, an NCI designated Comprehensive Cancer Center (P30-CA076292). We acknowledge Moffitt’s Melanoma Center of Excellence and the Mark Foundation for the financial support. [1] Sarnaik, A.A. et al. JCO 39, 2656-2666 (2021). [2] Creelan, B. et al. Nat Med 27, 1410-1418 (2021). [3] Cabrita, R. et al. Nature 577, 561-565 (2020). [4] Sanz, I. et al. Front Immunol 10, 2458 (2019). Citation Format: Renata Ariza Marques Rossetti, Leticia Tordesillas, Matthew Beatty, Dongliang Du, Yian Ann Chen, Amod Sarnaik, Shari Pilon-Thomas, Daniel Abate-Daga. CD40L stimulates melanoma infiltrating B cells and enhances ex vivo TIL expansion. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4055.
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Ambrogi, Federico, and Thomas H. Scheike. "Penalized estimation for competing risks regression with applications to high-dimensional covariates." Biostatistics 17, no. 4 (April 26, 2016): 708–21. http://dx.doi.org/10.1093/biostatistics/kxw017.
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High-dimensional regression has become an increasingly important topic for many research fields. For example, biomedical research generates an increasing amount of data to characterize patients' bio-profiles (e.g. from a genomic high-throughput assay). The increasing complexity in the characterization of patients' bio-profiles is added to the complexity related to the prolonged follow-up of patients with the registration of the occurrence of possible adverse events. This information may offer useful insight into disease dynamics and in identifying subset of patients with worse prognosis and better response to the therapy. Although in the last years the number of contributions for coping with high and ultra-high-dimensional data in standard survival analysis have increased (Witten and Tibshirani, 2010. Survival analysis with high-dimensional covariates. Statistical Methods in Medical Research19(1), 29–51), the research regarding competing risks is less developed (Binder and others, 2009. Boosting for high-dimensional time-to-event data with competing risks. Bioinformatics25(7), 890–896). The aim of this work is to consider how to do penalized regression in the presence of competing events. The direct binomial regression model of Scheike and others (2008. Predicting cumulative incidence probability by direct binomial regression. Biometrika95(1), 205–220) is reformulated in a penalized framework to possibly fit a sparse regression model. The developed approach is easily implementable using existing high-performance software to do penalized regression. Results from simulation studies are presented together with an application to genomic data when the endpoint is progression-free survival. An R function is provided to perform regularized competing risks regression according to the binomial model in the package timereg (Scheike and Martinussen, 2006. Dynamic Regression models for survival data. New York: Springer), available through CRAN.
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Sekelska, Izsakova, Kubosova, Tilandyova, Csekes, Kuchova, Hyblova, et al. "Result of Prospective Validation of the Trisomy Test® for the Detection of Chromosomal Trisomies." Diagnostics 9, no. 4 (October 2, 2019): 138. http://dx.doi.org/10.3390/diagnostics9040138.
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Noninvasive prenatal testing (NIPT) is one of the most common prenatal screening tests used worldwide. Trisomy Test® belongs to NIPT tests based on low-coverage whole-genome sequencing. In our prospective study, 7279 samples of pregnant women collected during approximately two years were analyzed. In this cohort, 117 positive cases for trisomies 21, 18, and 13 were reported. An in-house designed bioinformatic pipeline and proprietary biostatistical approach was used for the detection of trisomies. The pooled sensitivity and specificity of our test reached 99.12% and 99.94%, respectively. The proportion of repeatedly uninformative results after repeated blood draws was 1.11%. Based on the presented results, we can confirm that the Trisomy Test® is fully comparable with other commercial NIPT tests available worldwide.
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Shyr, Yu. "WS-05-02: Biostatistical and bioinformatics approaches in high dimensional data derived from high throughput assays: a consumer guide." Journal of Thoracic Oncology 2, no. 8 (August 2007): S292—S293. http://dx.doi.org/10.1097/01.jto.0000283069.00949.c1.
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Strafella, Claudia, Valeria Errichiello, Valerio Caputo, Gianluca Aloe, Federico Ricci, Andrea Cusumano, Giuseppe Novelli, Emiliano Giardina, and Raffaella Cascella. "The Interplay between miRNA-Related Variants and Age-Related Macular Degeneration: EVIDENCE of Association of MIR146A and MIR27A." International Journal of Molecular Sciences 20, no. 7 (March 29, 2019): 1578. http://dx.doi.org/10.3390/ijms20071578.
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The complex interplay among genetic, epigenetic, and environmental variables is the basis for the multifactorial origin of age-related macular degeneration (AMD). Previous results highlighted that single nucleotide polymorphisms (SNPs) of CFH, ARMS2, IL-8, TIMP3, SLC16A8, RAD51B, VEGFA, and COL8A1 were significantly associated with the risk of AMD in the Italian population. Given these data, this study aimed to investigate the impact of SNPs in genes coding for MIR146A, MIR31, MIR23A, MIR27A, MIR20A, and MIR150 on their susceptibility to AMD. Nine-hundred and seventy-six patients with exudative AMD and 1000 controls were subjected to an epigenotyping analysis through real-time PCR and direct sequencing. Biostatistical and bioinformatic analysis was performed to evaluate the association with susceptibility to AMD. These analyses reported that the SNPs rs11671784 (MIR27A, G/A) and rs2910164 (MIR146A, C/G) were significantly associated with AMD risk. Interestingly, the bioinformatic analysis showed that MIR27A and MIR146A take part in the angiogenic and inflammatory pathways underlying AMD etiopathogenesis. Thus, polymorphisms within the pre-miRNA sequences are likely to affect their functional activity, especially the interaction with specific targets. Therefore, our study represents a step forward in the comprehension of the mechanisms leading to AMD onset and progression, which certainly include the involvement of epigenetic modifications.
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Graves, Keonte J., Colin Reily, Hemant K. Tiwari, Vinodh Srinivasasainagendra, William Evan Secor, Jan Novak, and Christina A. Muzny. "Identification of Trichomonas vaginalis 5-Nitroimidazole Resistance Targets." Pathogens 12, no. 5 (May 10, 2023): 692. http://dx.doi.org/10.3390/pathogens12050692.
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Trichomonas vaginalis is the most common non-viral sexually transmitted infection. 5-nitroimidazoles are the only FDA-approved medications for T. vaginalis treatment. However, 5-nitroimidazole resistance has been increasingly recognized and may occur in up to 10% of infections. We aimed to delineate mechanisms of T. vaginalis resistance using transcriptome profiling of metronidazole (MTZ)-resistant and sensitive T. vaginalis clinical isolates. In vitro, 5-nitroimidazole susceptibility testing was performed to determine minimum lethal concentrations (MLCs) for T. vaginalis isolates obtained from women who had failed treatment (n = 4) or were successfully cured (n = 4). RNA sequencing, bioinformatics, and biostatistical analyses were performed to identify differentially expressed genes (DEGs) in the MTZ-resistant vs. sensitive T. vaginalis isolates. RNA sequencing identified 304 DEGs, 134 upregulated genes and 170 downregulated genes in the resistant isolates. Future studies with more T. vaginalis isolates with a broad range of MLCs are needed to determine which genes may represent the best alternative targets in drug-resistant strains.
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Kraboth, Zoltan, Bence Galik, Marton Tompa, Bela Kajtar, Peter Urban, Attila Gyenesei, Attila Miseta, and Bernadette Kalman. "DNA CpG methylation in sequential glioblastoma specimens." Journal of Cancer Research and Clinical Oncology 146, no. 11 (August 10, 2020): 2885–96. http://dx.doi.org/10.1007/s00432-020-03349-w.
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Abstract Purpose Glioblastoma is the most aggressive form of brain tumors. A better understanding of the molecular mechanisms leading to its evolution is essential for the development of treatments more effective than the available modalities. Here, we aim to identify molecular drivers of glioblastoma development and recurrence by analyzing DNA CpG methylation patterns in sequential samples. Methods DNA was isolated from 22 pairs of primary and recurrent formalin-fixed, paraffin-embedded glioblastoma specimens, and subjected to reduced representation bisulfite sequencing. Bioinformatic analyses were conducted to identify differentially methylated sites and pathways, and biostatistics was used to test correlations among clinical and pathological parameters. Results Differentially methylated pathways likely involved in primary tumor development included those of neuronal differentiation, myelination, metabolic processes, synapse organization and endothelial cell proliferation, while pathways differentially active during glioblastoma recurrence involved those associated with cell processes and differentiation, immune response, Wnt regulation and catecholamine secretion and transport. Conclusion DNA CpG methylation analyses in sequential clinical specimens revealed hypomethylation in certain pathways such as neuronal tissue development and angiogenesis likely involved in early tumor development and growth, while suggested altered regulation in catecholamine secretion and transport, Wnt expression and immune response contributing to glioblastoma recurrence. These pathways merit further investigations and may represent novel therapeutic targets.
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Rebollo-Hernanz, Miguel, Yolanda Aguilera, Alicia Gil-Ramírez, Vanesa Benítez, Silvia Cañas, Cheyenne Braojos, and Maria A. Martin-Cabrejas. "Biorefinery and Stepwise Strategies for Valorizing Coffee By-Products as Bioactive Food Ingredients and Nutraceuticals." Applied Sciences 13, no. 14 (July 19, 2023): 8326. http://dx.doi.org/10.3390/app13148326.
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Coffee production generates significant amounts of by-products, posing challenges for waste management in the industry. Recent research has revealed that coffee by-products are rich in bioactive compounds suitable to produce functional food ingredients and nutraceuticals. In this review, we explore biorefinery strategies for extracting and utilizing bioactive compounds from coffee by-products, including the production of bio-based chemicals and materials, as well as the extraction of phenolic compounds, antioxidants, and dietary fiber for food applications. We propose a stepwise approach for the development of functional food ingredients and nutraceuticals from coffee by-products, covering the identification of needs, comprehensive characterization, in vitro and in vivo research, unraveling the mechanism of action, food and nutraceutical formulation, sensory analysis, shelf-life stability, scale-up, randomized control trials, and biostatistics and bioinformatic integration. Additionally, we discuss the market potential, regulatory issues, and technological innovation surrounding the commercialization of coffee by-product-based products. Emphasizing the importance of regulatory compliance and sustainability in the coffee industry, this review highlights the potential of coffee by-products to be transformed from waste into valuable functional food ingredients and nutraceuticals, offering a promising avenue for waste reduction and promoting sustainability in the coffee industry.
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Zaragoza-Infante, Laura, Andreas Agathangelidis, Valentin Junet, Nikos Pechlivanis, Triantafylia Koletsa, Alessio Bruscaggin, Zadie Davis, et al. "Distinct Modes of Ongoing Antigen Interactions Shape Intraclonal Dynamics in Splenic Marginal Zone Lymphoma." Blood 138, Supplement 1 (November 5, 2021): 1330. http://dx.doi.org/10.1182/blood-2021-148722.
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Abstract Almost one-third of all splenic marginal zone lymphoma (SMZL) cases express B cell receptor immunoglobulin (BcR IG) encoded by the IGHV1-2*04 gene. Such cases display a distinctive profile of genomic aberrations (e.g. higher incidence of NOTCH2 and KLF2 mutations) and a more aggressive clinical course compared to SMZL cases utilizing other IGHV genes. Such skewing of the BcR IG gene repertoire implicates antigen selection in SMZL ontogeny. Although the supportive evidence is compelling, it mostly derives from low-throughput approaches, which are inherently limited in their capacity to capture the complexity of the BcR IG gene repertoire. This hinders the comprehensive assessment of the subclonal architecture of SMZL that could offer insight into the dynamics of antigen-IG interactions. Here, we sought to overcome this limitation through a high-throughput immunogenetic investigation of SMZL, focusing on the detailed characterization of somatic hypermutation (SHM) and intraclonal diversification (ID) profiles. Our study included 22 cases utilizing the IGHV1-2*04 gene and 36 cases utilizing other IGHV genes. IGHV-IGHD-IGHJ (IGH) gene rearrangements were PCR-amplified and libraries were sequenced on the Illumina MiSeq platform. Data was analyzed with the IMGT/HighV-QUEST and TRIP software as well as a novel bioinformatics/biostatistics pipeline. Clonotypes were defined as unique combinations of a given IGHV gene+VH CDR3 amino acid (aa) sequence. Only IGH gene rearrangement sequences assigned to the dominant clonotypes of each case were assessed. In detail, all nucleotide variants (nt vars, i.e. all sequences clustered in the same dominant clonotype yet displaying distinct SHM profiles) were identified and further analyzed. Starting from the most abundant nt var, a network was built representing its connections with all other nt vars. For this analysis, we introduce the terms 'most relevant pathway' (MRP) corresponding to the pathway including connected nt vars with the highest total number of IGH sequences; and 'longest mutational pathways' (LMP) corresponding to the pathways with the highest number of nt vars (Fig. 1). Different graph metrics assessed the impact of ID in different SMZL subgroups: the first one focuses on the 'most relevant pathway' and quantifies SHM convergence [ratio of the total number of IGH sequences corresponding to the nt vars of this pathway to the number of IGH sequences in the most abundant nt var]; while the second refers to the length of the 'longest mutational pathways'. Cases lacking additional connected nt vars [length of the LMP=1; 3 IGHV1-2*04 cases and 4 non-IGHV1-2*04 cases] were excluded. Consequently, the analysis included 19 IGHV1-2*04 cases and 32 non-IGHV1-2*04 cases. Significant differences were noted in the SHM and ID profiles between groups; the IGHV1-2*04 group had significantly (p<0.01) higher convergence values ranging from 0.009 to 1.243 (median: 0.102), as opposed to the non-IGHV1-2*04 group (range: 0.002-1.13, median: 0.014), overall suggesting that stronger selective pressures act in SMZL cases expressing the IGHV1-2*04 versus others. Moreover, IGHV1-2*04 cases displayed significantly (p<0.01) longer mutational pathways (length range: 2-6, median: 3) compared to the other group (range: 2-5, median: 2), alluding to more pronounced ID arising due to ongoing SHM. Finally, all mutations leading to aa changes were analyzed in the context of ID networks. More recurrent aa mutations were identified amongst cases with higher levels of convergence. For instance, the VH FR2 M39I change, one of the most prominent recurrent SHMs in the IGHV1-2*04 group, was found in the most abundant nt var in 13/19 IGHV1-2*04 cases, while it was identified in nt vars with extra mutations in another 3 cases. Of interest, it was present at the end of the mutational pathways in these 16 cases, whilst in the other group it was present only in one case using the IGHV1-2*02 gene, and absent in the rest (p<0.01). In conclusion, in the first large-scale high-throughput immunogenetic analysis of SMZL we provide strong evidence for more pronounced antigenic pressure in cases utilizing IGHV1-2*04 versus other IGHV genes. Our findings highlight a unique subclonal architecture for IGHV1-2*04 SMZL and corroborate the hypothesis that this group may represent a distinct molecular variant of SMZL. Figure 1 Figure 1. Disclosures Rossi: Abbvie: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Verastem: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Cellestia: Honoraria, Research Funding. Chatzidimitriou: Janssen: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Stamatopoulos: Janssen: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding.
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Karousi, Paraskevi, Pinelopi I. Artemaki, Christina D. Sotiropoulou, Spyridon Christodoulou, Andreas Scorilas, and Christos K. Kontos. "Identification of Two Novel Circular RNAs Deriving from BCL2L12 and Investigation of Their Potential Value as a Molecular Signature in Colorectal Cancer." International Journal of Molecular Sciences 21, no. 22 (November 23, 2020): 8867. http://dx.doi.org/10.3390/ijms21228867.
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The utility of circular RNAs (circRNAs) as molecular biomarkers has recently emerged. However, only a handful of them have already been studied in colorectal cancer (CRC). The purpose of this study was to identify new circRNAs deriving from BCL2L12, a member of the BCL2 apoptosis-related family, and investigate their potential as biomarkers in CRC. Total RNA extracts from CRC cell lines and tissue samples were reversely transcribed. By combining PCR with divergent primers and nested PCR followed by Sanger sequencing, we were able to discover two BCL2L12 circRNAs. Subsequently, bioinformatical tools were used to predict the interactions of these circRNAs with microRNAs (miRNAs) and RNA-binding proteins (RBPs). Following a PCR-based pre-amplification, real-time qPCR was carried out for the quantification of each circRNA in CRC samples and cell lines. Biostatistical analysis was used to assess their potential prognostic value in CRC. Both novel BCL2L12 circRNAs likely interact with particular miRNAs and RBPs. Interestingly, circ-BCL2L12-2 expression is inversely associated with TNM stage, while circ-BCL2L12-1 overexpression is associated with shorter overall survival in CRC, particularly among TNM stage II patients. Overall, we identified two novel BCL2L12 circRNAs, one of which can further stratify TNM stage II patients into two subgroups with substantially distinct prognosis.
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Pang, Ronald TK, Terence CW Poon, KC Allen Chan, Nelson LS Lee, Rossa WK Chiu, Yu-Kwan Tong, Ronald MY Wong, et al. "Serum Proteomic Fingerprints of Adult Patients with Severe Acute Respiratory Syndrome." Clinical Chemistry 52, no. 3 (March 1, 2006): 421–29. http://dx.doi.org/10.1373/clinchem.2005.061689.
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Abstract Background: Severe acute respiratory syndrome (SARS) is an emerging infectious disease caused by a new coronavirus strain, SARS-CoV. Specific proteomic patterns might be present in serum in response to the infection and could be useful for early detection of the disease. Methods: Using surface-enhanced laser desorption/ionization (SELDI) ProteinChip technology, we profiled and compared serum proteins of 39 patients with early-stage SARS infection and 39 non-SARS patients who were suspected cases during the SARS outbreak period. Proteomic patterns associated with SARS were identified by bioinformatic and biostatistical analyses. Features of interest were then purified and identified by tandem mass spectrometry. Results: Twenty proteomic features were significantly different between the 2 groups. Fifteen were increased in the SARS group, and 5 were decreased. Their concentrations were correlated with 2 or more clinical and/or biochemical variables. Two were correlated with the SARS-CoV viral load. Hierarchical clustering analysis showed that a majority of the SARS patients (95%) had similar serum proteomic profiles and identified 2 subgroups with poor prognosis. ROC curve analysis identified individual features as potential biomarkers for SARS diagnosis (areas under ROC curves, 0.733–0.995). ROC curve areas were largest for an N-terminal fragment of complement C3c α chain (m/z 28 119) and an internal fragment of fibrinogen α-E chain (m/z 5908). Immunoglobulin κ light chain (m/z 24 505) positively correlated with viral load. Conclusions: Specific proteomic fingerprints in the sera of adult SARS patients could be used to identify SARS cases early during onset with high specificity and sensitivity.
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Nakamura, Aurélie, Olivier François, and Johanna Lepeule. "Epigenetic Alterations of Maternal Tobacco Smoking during Pregnancy: A Narrative Review." International Journal of Environmental Research and Public Health 18, no. 10 (May 11, 2021): 5083. http://dx.doi.org/10.3390/ijerph18105083.
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In utero exposure to maternal tobacco smoking is the leading cause of birth complications in addition to being associated with later impairment in child’s development. Epigenetic alterations, such as DNA methylation (DNAm), miRNAs expression, and histone modifications, belong to possible underlying mechanisms linking maternal tobacco smoking during pregnancy and adverse birth outcomes and later child’s development. The aims of this review were to provide an update on (1) the main results of epidemiological studies on the impact of in utero exposure to maternal tobacco smoking on epigenetic mechanisms, and (2) the technical issues and methods used in such studies. In contrast with miRNA and histone modifications, DNAm has been the most extensively studied epigenetic mechanism with regard to in utero exposure to maternal tobacco smoking. Most studies relied on cord blood and children’s blood, but placenta is increasingly recognized as a powerful tool, especially for markers of pregnancy exposures. Some recent studies suggest reversibility in DNAm in certain genomic regions as well as memory of smoking exposure in DNAm in other regions, upon smoking cessation before or during pregnancy. Furthermore, reversibility could be more pronounced in miRNA expression compared to DNAm. Increasing evidence based on longitudinal data shows that maternal smoking-associated DNAm changes persist during childhood. In this review, we also discuss some issues related to cell heterogeneity as well as downstream statistical analyses used to relate maternal tobacco smoking during pregnancy and epigenetics. The epigenetic effects of maternal smoking during pregnancy have been among the most widely investigated in the epigenetic epidemiology field. However, there are still huge gaps to fill in, including on the impact on miRNA expression and histone modifications to get a better view of the whole epigenetic machinery. The consistency of maternal tobacco smoking effects across epigenetic marks and across tissues will also provide crucial information for future studies. Advancement in bioinformatic and biostatistics approaches is key to develop a comprehensive analysis of these biological systems.
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Mathlouthi, Nour El Houda, Imen Belguith, Mariem Yengui, Hamadou Oumarou Hama, Jean-Christophe Lagier, Leila Ammar Keskes, Ghiles Grine, and Radhouane Gdoura. "The Archaeome’s Role in Colorectal Cancer: Unveiling the DPANN Group and Investigating Archaeal Functional Signatures." Microorganisms 11, no. 11 (November 10, 2023): 2742. http://dx.doi.org/10.3390/microorganisms11112742.
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Background and Aims: Gut microbial imbalances are linked to colorectal cancer (CRC), but archaea’s role remains underexplored. Here, using previously published metagenomic data from different populations including Austria, Germany, Italy, Japan, China, and India, we performed bioinformatic and statistical analysis to identify archaeal taxonomic and functional signatures related to CRC. Methods: We analyzed published fecal metagenomic data from 390 subjects, comparing the archaeomes of CRC and healthy individuals. We conducted a biostatistical analysis to investigate the relationship between Candidatus Mancarchaeum acidiphilum (DPANN superphylum) and other archaeal species associated with CRC. Using the Prokka tool, we annotated the data focusing on archaeal genes, subsequently linking them to CRC and mapping them against UniprotKB and GO databases for specific archaeal gene functions. Results: Our analysis identified enrichment of methanogenic archaea in healthy subjects, with an exception for Methanobrevibacter smithii, which correlated with CRC. Notably, CRC showed a strong association with archaeal species, particularly Natrinema sp. J7-2, Ferroglobus placidus, and Candidatus Mancarchaeum acidiphilum. Furthermore, the DPANN archaeon exhibited a significant correlation with other CRC-associated archaea (p < 0.001). Functionally, we found a marked association between MvhB-type polyferredoxin and colorectal cancer. We also highlighted the association of archaeal proteins involved in the biosynthesis of leucine and the galactose metabolism process with the healthy phenotype. Conclusions: The archaeomes of CRC patients show identifiable alterations, including a decline in methanogens and an increase in Halobacteria species. MvhB-type polyferredoxin, linked with CRC and species like Candidatus Mancarchaeum acidiphilum, Natrinema sp. J7-2, and Ferroglobus placidus emerge as potential archaeal biomarkers. Archaeal proteins may also offer gut protection, underscoring archaea’s role in CRC dynamics.
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García, Mireia Saladrigas, Mario Durán, Jaume Coma, José Francisco Pérez, and Susana María Martín-Orúe. "97 An insight into the piglet’s microbial colonization evolution: From birth towards weaning." Journal of Animal Science 98, Supplement_3 (November 2, 2020): 28–29. http://dx.doi.org/10.1093/jas/skaa054.051.
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Abstract The aim of the present study was to explore the evolution of piglet gut microbiota from birth to weaning. Moreover, it was hypothesized that different farm environments could condition this process. Two farms, distinct in their use of antibiotics, and 10 litters per farm were selected. A total of 100 fecal samples were obtained from the same pig of each litter on d2, d7, d14 and d21 of lactation and d14 after weaning. The DNA was extracted by using the PSP® Spin Stool DNA Kit and sequencing of the 16S rRNA gene (V3-V4 region) performed by Illumina MiSeq Platform. Bioinformatics and biostatistical analysis were performed with QIIME and the open-source software R v3.5.3. (phyloseq package). Alpha diversity was strongly affected by age (P< 0.001), with an increasing richness of species through time. Beta diversity decreased after weaning (P< 0.001), suggesting a convergent evolution among individuals. Regarding the structure of the microbiota, a clear clustering of the samples according to age was observed (P< 0.001). A progressive decrease was observed as the piglets aged for Clostridiaceae, Enterobacteriaceae, Fusobacteriaceae, Pasteurellaceae and Streptococcaceae (P< 0.001). In contrast, Lachnospiraceae (P=0.003), Lactobacillaceae (P=0.003) and Veillonellaceae (P=0.025) increased along the d7–d14 period, but decreased afterwards. Campylobacteraceae, Erysipelotrichaceae, Ruminococcaceae (P< 0.001) and Prevotellaceae (P=0.005) gradually increased with age reflecting the change from a milk-oriented microbiome towards a butyrate-producing one. Regarding the impact of the farm, differences in species richness were found and also a distinct microbial structure (ANOSIM: P=0.025) associated to changes in some particular taxonomic groups. In conclusion, during the transition from birth to weaning, the pig microbiota showed a relevant succession of microbial groups towards a more stable ecosystem better adapted to the dry feed. In this relevant early-age process differences between farms seems to have a limited impact.
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Torner, James, Beth R. Knudson, and Kimberly Dukes. "2234 Developing the future translational science workforce at the University of Iowa." Journal of Clinical and Translational Science 2, S1 (June 2018): 53–54. http://dx.doi.org/10.1017/cts.2018.203.
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OBJECTIVES/SPECIFIC AIMS: To evaluate the extent to which the curriculum delivered via an innovative program, the Early Scholars Certificate in Clinical and Translational Science (CCTS) at the University of Iowa (UI), develops a translational science workforce pipeline by increasing awareness of and interest in translational science as a career goal for highly prepared undergraduates. METHODS/STUDY POPULATION: The CCTS’s objective is to increase the awareness of the philosophy and tools of translational science and to incorporate critical evaluation and self-appraisal of the translational aspects of a scholar’s own research. CCTS is a 16-semester-hour (sh) academic certificate program introducing translational science concepts and careers to undergraduate students. The CCTS is a selective program with requirements including a minimum GPA, minimum sh completed, completion of course prerequisites, and already engaged and supported by mentored research. The curriculum includes electives in the area of their research interests (6 sh); graduate level Epidemiology (3 sh); Biostatistics (3 sh); and 2 core Translational Research courses (4 sh total). The first core course, an Introduction to Translational Research, is a survey course providing students the opportunity to learn how translational research is conceived and developed. It is designed to instruct the student how to interpret their research in a translational T1 to T4 paradigm. The program’s capstone course, Practicum in Translational Research, provides undergraduate students the opportunity to address how their research experience translates into clinical practice. Student’s spend the majority of this course’s contact hours in a shadowing experience with a clinician in the area of their research. Students reflect on this shadowing experience and its relevance to their academic and professional goals. The students also spend time developing skills in peer review—not only learning to provide constructive feedback to other research professionals, but also how to receive and integrate the feedback. The course includes a mock research fair where both UI faculty and classmates provide feedback that is later integrated into their capstone projects—a poster presentation at the UI Carver College of Medicine Research Fair as well as a final translational paper. As part of the ongoing evaluation of the program and graduates, we examined the participant data, the course satisfaction with content, the change in understanding of translational science, and the intention to incorporate translational science into research and career goals. We also conducted course evaluation surveys and qualitative analysis of a focus group and interviews. RESULTS/ANTICIPATED RESULTS: Since 2015, the CCTS program has introduced translational science curriculum to 20 undergraduate participants (men/woman 40%/60%; 5% Hispanic or Latino; 15% Center for Diversity and Enrichment Eligible). Areas of academic interest include: biology, genetics, engineering, bioinformatics, biochemistry, neuroscience, psychology, and microbiology. Graduates of the Certificate and degree program to date (n=8) have gone onto: Fullbright awards (1), medical school/Masters in public health (1), combined MD/PhD programs (2), biomedical PhD program (1), or currently work in translational science positions in industry (2). In questionnaire and focus group results, we found that in general, students reported increased understanding of the translational spectrum and felt the certificate program helped them clarify their educational or career goals. Data from both the focus group and the questionnaire demonstrate that students are strongly positive about the program in general, including its quality, faculty and guest speakers, structure, goals, opportunities, personality, and personnel. All students highly valued many elements of the program and each course, and particularly the opportunity for clinical shadowing. Among the questionnaire findings for 2016–17, all students (100%) rated program quality “excellent,” and 7 of 8 (87.5%) “strongly agreed” that they better understood translational science, that they saw themselves continuing in translational science research after graduation, and they were better able to communicate how their lab research fits within the translational spectrum. In each case 1 of 8 “agreed.” Participants also generally felt that their career goals had been affirmed or realigned, and that they were better able to communicate the meaning of translational science to multiple audiences. Responses on changes to career aspirations and plans were mixed, and are ambiguous. Questionnaire Item 4, “My UI curricular and/or co-curricular plans changed as a result of the CCTS program,” which had mixed responses, asked specifically about the CCTS program as a reason for change, but it is not clear if, whether, or how the program specifically wants to change curricular plans. In the focus group, students reported using their individual shadowing and lab experience in determining preferences and intentions about future career choices (e.g., whether or not to apply to medical school and/or pursue basic science research). Participants perceived the shadowing experience, complementing or contrasting their lab research, as particularly relevant in deciding about their future careers. Other themes that emerged from the focus group and/or open section of the questionnaire demonstrate the impact of various course elements on participants’ understanding of translational science and potential careers, including: quality of instruction, program and course content (including guest speakers, the shadowing experience, and the poster development process); the exposure to a range of possibilities along the translational spectrum and the expansion of ideas about what research could look like; the value of connections (to faculty, researchers and clinicians, and other CCTS students and alumni); the attributes of the cohort; and the “personality” of the program and personnel. DISCUSSION/SIGNIFICANCE OF IMPACT: Developing a pipeline for translational science workforce development has been problematic because a lack of the understanding of the need of translational research and a structuring a time efficient program for early career clinical and basic scholars. Undergraduates making critical decisions about educational paths and career goals and plans may not be aware of opportunities in translational science or the type of choices they need to make to prepare for such opportunities. Our data demonstrates that CCTS was an effective way of introducing translational science concepts and career paths to undergraduate students and potentially a powerful way to encourage them to consider these career paths. Participants in our program improved their knowledge of the field and expressed interest and intention to incorporate translational science training into their career plans. However, improvements can be made in the CCTS program. Additionally, CTSAs should consider ways to incorporate findings like these into a wider sphere of training to help develop and strengthen a translational science workforce for the future. The exposure to a variety of translational science career possibilities and specialties was important to students. Based on both focus group discussion and questionnaire data, a few students did expand slightly their sense of career possibilities, but the larger benefit may be their concrete experiences that validate or solidify their interests, making them more skilled at talking about and supporting their career goals on applications and in interviews. Shadowing did not always encourage students to go into clinical medicine, but often solidified interests or leanings students already had, giving them a more grounded basis for refining their decisions. For some students, shadowing a clinician confirmed ideas of being a physician; for others, it steered them away from it. Some now found ethical challenges, bureaucracy, or emotional challenges daunting or newly necessary to consider before focusing on clinical careers. This may be just what students need at this point, and emphasizes for them the relation between different kinds of research and application within translational science. Our evaluation suggests that CCTS contributes to academic choices for career development and additionally can help attract highly skilled students into TS research, including students of color. Future work to evaluate CCTS impact on graduates’ career outcomes will inform the translational research direction and content. In terms of program design, it could be useful to build in multiple opportunities for students to understand the diversity of translational science careers and provide students more exposure to different possibilities in clinical and translational work.
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Willey, James C., Erin Crawford, Daniel J. Craig, Joshua Xu, Nathan Haseley, Jennifer Lococo, and Tom Morrison. "Abstract 529: SNAQ-SEQ™: Use of synthetic internal standards in conjunction with poisson exact test to call variants in contrived circulating tumor DNA specimens." Cancer Research 82, no. 12_Supplement (June 15, 2022): 529. http://dx.doi.org/10.1158/1538-7445.am2022-529.
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Abstract Background: Targeted next generation sequencing (NGS) analysis of circulating tumor (ct) DNA promises to significantly advance targeted therapy and potentially early diagnosis of cancer. However, targeted NGS has poor accuracy for calling known variants with VAF below 0.5%. The goal of this study from the FDA-Sequencing and Quality Control Phase 2 (SEQC2) consortium was to develop and validate bioinformatic and biostatistical methods that enable incorporation of synthetic competitive internal standards (IS) in targeted NGS analysis of actionable tumor mutations. Methods: A synthetic IS spike-in was designed for each actionable mutation target, suitable for use in NGS following targeted PCR or hybrid-capture enrichment and either with unique molecular index (UMI) or non-UMI library preparation. Contrived ctDNA reference samples developed by the SEQC2 consortium containing actionable mutations at known variant allele fraction were used. An aliquot of each sample was mixed with a mixture of IS. Following Illumina TST170 enrichment and library preparation, each library was sequenced, then native template (NT) sequences were separated from IS sequences bioinformatically. In SNAQ-SEQ™ analysis, Poisson Exact Test (PET) analysis was used to calculate the statistical difference between each sample library NT variant VAF and respective IS variant VAF. Analysis was based on NT variant count and position coverage (i.e., copies recovered in library preparation) and IS count and position coverage. PET performed an exact test of a simple null hypothesis about the ratio between two rate parameters in Poisson distribution. Results: Stochastic sampling effect on IS error detection was minimized by ensuring an IS/NT ratio of 2.5 or greater. Under the specified conditions, in which a minimum of two NT variant observations were required for a call, the IS was able to estimate NGS background error for each sample when a minimum IS:NT ratio of 2.5:1 was used. Without use of IS information, the Illumina pipeline called 73% (41/56) of known TP variants in the 0.1% - 0.3% VAF range. In contrast, SNAQ-SEQ™ analysis (PET analysis of IS and NT information) increased TP detection sensitivity to 86% (48/56), for a 13% increase in sensitivity, with no false positives. Conclusion: Following mixture of contrived ctDNA reference samples with IS, PET analysis enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position, in each sample. Using this SNAQ-SEQ™ analysis, true positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity. SNAQ-SEQ™ provides QC that is already standard operating procedure in clinical laboratories for analysis by high pressure liquid chromatography and mass spectrometry. Citation Format: James C. Willey, Erin Crawford, Daniel J. Craig, Joshua Xu, Nathan Haseley, Jennifer Lococo, Tom Morrison. SNAQ-SEQ™: Use of synthetic internal standards in conjunction with poisson exact test to call variants in contrived circulating tumor DNA specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 529.
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Nakamura, Kota, Souvick Roy, Zhongxu Zhu, Eunsung Jun, Haiyong Han, Ruben M. Munoz, Satoshi Nishiwada, et al. "Abstract 3389: An exosomal miRNA-based liquid biopsy signature for the noninvasive early detection of pancreatic ductal adenocarcinoma." Cancer Research 82, no. 12_Supplement (June 15, 2022): 3389. http://dx.doi.org/10.1158/1538-7445.am2022-3389.
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Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second leading cause of cancer-related deaths in the United States by 2030. Most of the PDAC patients are diagnosed with advanced disease, and less than 20% of patients are resectable at the time of diagnosis. The current imaging tools and blood markers (e.g. CA 19-9), are inadequate for early disease detection due to their poor specificity and sensitivity. This highlights the need to develop robust, noninvasive biomarkers for early detection of PDAC. While a large body of literature supports the use of cell-free miRNAs (cf-miRNAs) as potential diagnostic biomarkers in cancer, their tumor specificity is often debatable. Given the emerging evidence that exosomal cargo is a more robust representation of individual tumor types, in this study we sought to explore the diagnostic potential of cf-miRNAs along with exosomal miRNAs (exo-miRNAs), to establish a non-invasive miRNA signature for the early detection of PDAC. Methods: As part of the NCI’s Pancreatic Cancer Detection Consortium (PCDC) funded project, in this study, small RNA-sequencing was performed in exosome and cell-free (cf) samples from a cohort of 57 PDAC cases and 57 non-disease controls. Using rigorous bioinformatic and biostatistical approaches, we prioritized a panel of cf- and exo-miRNAs and evaluated its diagnostic performance in the sequencing-based discovery and validation cohorts. Subsequently, the performance of the discovered miRNA panel was validated using qRT-PCR assays in an independent clinical validation cohort of PDAC patients and non-disease controls (n=48/each group). The results were examined by ROC curve analysis to determine the diagnostic power of the biomarker panel individually and in combination for their ability to discriminate PDAC from controls. Results: The genomewide transcriptomic analyses led to the identification of a panel of 13 cf-miRNA and 17 exo-miRNA candidates. Sequencing validation in an independent cohort revealed that a combined panel of cf and exo-miRNAs exhibited an area under curve (AUC) of 0.89. Subsequent risk score analysis demonstrated that our biomarker signature was also robust in the identification of PDAC patients with early-stage cancers (stage I & II) vs. controls (p <0.001). Moreover, when we combined the miRNA biomarker panel with CA19-9 values, the diagnostic performance was significantly superior when compared to the biomarker panel alone. Finally, the validation efforts in clinical cohorts by qRT-PCR revealed that the combined miRNA panel yielded an impressive accuracy with an AUC of 0.91, and a sensitivity of 0.88 and specificity of 0.87. Conclusions: In conclusion, we report a novel, exosome-based miRNA signature for the early detection of patients with PDAC; which could potentially improve early-detection efforts for this fatal malignancy. Citation Format: Kota Nakamura, Souvick Roy, Zhongxu Zhu, Eunsung Jun, Haiyong Han, Ruben M. Munoz, Satoshi Nishiwada, Geeta Sharma, Derek Cridebring, Frederic Zenhausern, Seungchan Kim, Denise Roe, Sourat Darabi, In Woong Han, Douglas Evans, Suguru Yamada, Michael Demure, Scott A. Celinski, Erkut Borazanci, Susan Tsai, John Bolton, Yasuhiro Kodera, Joon Oh Park, Song Cheol Kim, Xin Wang, Daniel Von Hoff, Ajay Goel. An exosomal miRNA-based liquid biopsy signature for the noninvasive early detection of pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3389.
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Al-Obaide, Mohammed A. Ibrahim, Abdel-Salam G. Abdel-Salam, Nisreen DaifAllah AL-Hmoud, Hayfa H. Hassani, and J. P. Verma. "Editorial: Bioinformatics and Biostatistics Applications in Tobacco Smoking Research." Frontiers in Public Health 6 (December 11, 2018). http://dx.doi.org/10.3389/fpubh.2018.00366.
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Jose, Ameijeiras-Alonso, and Christophe Ley. "Sine-skewed toroidal distributions and their application in protein bioinformatics." Biostatistics, October 2, 2020. http://dx.doi.org/10.1093/biostatistics/kxaa039.
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Summary In the bioinformatics field, there has been a growing interest in modeling dihedral angles of amino acids by viewing them as data on the torus. This has motivated, over the past years, new proposals of distributions on the torus. The main drawback of most of these models is that the related densities are (pointwise) symmetric, despite the fact that the data usually present asymmetric patterns. This motivates the need to find a new way of constructing asymmetric toroidal distributions starting from a symmetric distribution. We tackle this problem in this article by introducing the sine-skewed toroidal distributions. The general properties of the new models are derived. Based on the initial symmetric model, explicit expressions for the shape and dependence measures are obtained, a simple algorithm for generating random numbers is provided, and asymptotic results for the maximum likelihood estimators are established. An important feature of our construction is that no extra normalizing constant needs to be calculated, leading to more flexible distributions without increasing the complexity of the models. The benefit of employing these new sine-skewed toroidal distributions is shown on the basis of protein data, where, in general, the new models outperform their symmetric antecedents.