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Computational Approaches For Biomarker Detection And Precision Therapeutics In Cancers
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Book Synopsis Computational Approaches for Biomarker Detection and Precision Therapeutics in Cancers by : Suman Ghosal
Download or read book Computational Approaches for Biomarker Detection and Precision Therapeutics in Cancers written by Suman Ghosal and published by Frontiers Media SA. This book was released on 2022-04-07 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis 'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine by : Nosheen Masood
Download or read book 'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine written by Nosheen Masood and published by Springer Nature. This book was released on 2020-03-20 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concisely describes the role of omics in precision medicine for cancer therapies. It outlines our current understanding of cancer genomics, shares insights into the process of oncogenesis, and discusses emerging technologies and clinical applications of cancer genomics in prognosis and precision-medicine treatment strategies. It then elaborates on recent advances concerning transcriptomics and translational genomics in cancer diagnosis, clinical applications, and personalized medicine in oncology. Importantly, it also explains the importance of high-performance analytics, predictive modeling, and system biology in cancer research. Lastly, the book discusses current and potential future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.
Book Synopsis 'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine by :
Download or read book 'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine written by and published by . This book was released on 2020 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concisely describes the role of omics in precision medicine for cancer therapies. It outlines our current understanding of cancer genomics, shares insights into the process of oncogenesis, and discusses emerging technologies and clinical applications of cancer genomics in prognosis and precision-medicine treatment strategies. It then elaborates on recent advances concerning transcriptomics and translational genomics in cancer diagnosis, clinical applications, and personalized medicine in oncology. Importantly, it also explains the importance of high-performance analytics, predictive modeling, and system biology in cancer research. Lastly, the book discusses current and potential future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.
Book Synopsis Computational Approaches for Cancer Precision Medicine by : Lindsay C. Stetson
Download or read book Computational Approaches for Cancer Precision Medicine written by Lindsay C. Stetson and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many types of cancer have no proven means of prevention or effective therapies. Precision medicine is an emerging approach for disease treatment that takes into account the biology of the patient in an effort to improve therapeutic outcome. While significant advances have been made in precision medicine when it comes to select cancers such as breast and lung, precision medicine is still not used by clinicians when initiating treatment for most cancer patients. Advances in DNA sequencing and large-scale studies such as The Cancer Genome Atlas (TCGA) have led to a better understanding of the molecular initiators and drivers of cancer, but challenges remain in bringing precision medicine from the bench to the bedside. A major impediment to achieving personalized therapy is the small number of drugs developed to target the proteins encoded by potential driver genes. Additionally, the large numbers of genetic aberrations in cancer discovered through next-generation sequencing have not always translated into actionable drug targets. In this dissertation these two challenges are addressed. First, we demonstrate that data from large-scale pharmacogenomic studies can be computationally mined to create omic signatures of drug response. The benefit of this study is the ability to rapidly and cost-effectively identify drugs and research compounds that can be repositioned or repurposed for use in different cancer types. Additionally, we demonstrate that this approach can successfully identify the precise subgroup of cancer patients that will benefit from a drug treatment based on their unique tumor biology. We then show that proteomics studies completed as part of TCGA can be computationally mined to create protein models predictive of patient survival. The resulting protein signatures can be used by clinicians to identify those patients that are high-risk and should be treated more aggressively or referred to clinical trial. Additionally, proteins that are correlated to patient survival are potential actionable drug targets. Both drug development and clinical trials are expensive; computational approaches such as those described in this dissertation are critical to the cost-effective and timely development of precision medicines.
Book Synopsis Computational Methods for Precision Oncology by : Alessandro Laganà
Download or read book Computational Methods for Precision Oncology written by Alessandro Laganà and published by Springer Nature. This book was released on 2022-03-01 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision medicine holds great promise for the treatment of cancer and represents a unique opportunity for accelerated development and application of novel and repurposed therapeutic approaches. Current studies and clinical trials demonstrate the benefits of genomic profiling for patients whose cancer is driven by specific, targetable alterations. However, precision oncologists continue to be challenged by the widespread heterogeneity of cancer genomes and drug responses in designing personalized treatments. Chapters provide a comprehensive overview of the computational approaches, methods, and tools that enable precision oncology, as well as related biological concepts. Covered topics include genome sequencing, the architecture of a precision oncology workflow, and introduces cutting-edge research topics in the field of precision oncology. This book is intended for computational biologists, bioinformaticians, biostatisticians and computational pathologists working in precision oncology and related fields, including cancer genomics, systems biology, and immuno-oncology.
Book Synopsis Computational Analyses, Methods, and Tools Supporting Cancer Biomarker Identification and Targeted Therapy Development by : Pichai Raman
Download or read book Computational Analyses, Methods, and Tools Supporting Cancer Biomarker Identification and Targeted Therapy Development written by Pichai Raman and published by . This book was released on 2016 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over time, much has been done in attempt to understand the various causes and complex molecular mechanisms of cancer, yet it still represents one of the leading causes of mortality worldwide. Fortunately, cancer therapeutics have evolved, from broad chemotherapies with multiple harsh side effects to molecular missiles which target specific cancer causing genes, leaving a patient's normal cells largely untouched. Similarly, cancer detection strategies and prognosis methods have also advanced, allowing doctors and patients to better manage and control the disease. The main challenge currently is to identify those genes that are specific markers for a particular cancer and can inform prognosis and those that may be "targeted therapies". This can be accomplished most rapidly through the use of large-scale cancer genomic datasets and sophisticated integrative analyses, methods, and tools to detect and prioritize candidate genes and biomarkers. As such, the goal of this work is to develop analyses, methods, and frameworks that benefit the translational research community by identifying and prioritizing genes for biomarker and drug development. Specifically, using integrative approaches on The Cancer Genome Atlas (TCGA) and various datasets from Gene Expression Omnibus (GEO), we perform analyses to identify a marker of survival and Epithelial-mesenchymal transition (EMT) in ovarian serous adenocarcinoma and a 5-gene signature of survival and molecular subtype in pancreatic ductal adenocarcinoma. Additionally, we highlight associated oncogenic pathways and suggest potential therapeutic strategies in these analyses. In order to improve detection of these survival markers we also evaluate a suite of techniques used commonly in the literature for survival analysis and determine best practices when using RNA-Sequencing data. Finally, we develop an application that allows researcher to access cancer 'big data' and apply their experience and domain expertise alongside the application logic of the tool to identify survival markers, therapeutic avenues, and genes that may represent an 'Achilles heel' for a set of tumors. This undertaking involves many different facets of bioinformatics, including statistical methods of analysis, high-performance computing, graph theory, web programming, and UI/UX interaction, as well as domain expertise in cancer target discovery. While there is much activity in the translational cancer informatics domain, the current study adds to the wealth of knowledge and tools in the community and presents another foothold to gain novel insights into this devastating disease.
Book Synopsis Computational Methods in Drug Discovery and Repurposing for Cancer Therapy by : Ganji Purnachandra Nagaraju
Download or read book Computational Methods in Drug Discovery and Repurposing for Cancer Therapy written by Ganji Purnachandra Nagaraju and published by Elsevier. This book was released on 2023-03-22 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about ongoing research as well as computational approaches for drug discovery and repurposing for cancer therapy. The book also provides detailed descriptions about target molecules, pathways, and their inhibitors for easy understanding and applicability. The book discusses tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers, and transcriptome; those are discussed in the context of different cancer types, such as colon, pancreatic, glioblastoma, endometrial, and retinoblastoma, among others. This book is a valuable resource for researchers, students, and members of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor the treatment for cancer patients. - Discusses in silico remodeling of effective phytochemical compounds for discovering improved anticancer agents for substantial/significant cancer therapy - Covers potential tools of bioinformatics that are applied toward discovering new targets by drug repurposing and strategies to cure different types of cancers - Demonstrates the significance of computational and artificial intelligence approaches in anticancer drug discovery - Explores how these various advances can be integrated into a precision and personalized medicine approach that can eventually enhance patient care
Book Synopsis Computational Solutions to Exosomal MicroRNA Biomarker Detection in Pancreatic Cancer by : Thuy Thi Hong An
Download or read book Computational Solutions to Exosomal MicroRNA Biomarker Detection in Pancreatic Cancer written by Thuy Thi Hong An and published by . This book was released on 2021 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pancreatic cancer is the fourth leading cause of cancer death in the United States and the 5-year survival rate is only 5% to 10%. There are only a few non-specific symptoms associated with the early stage cancer, therefore most patients are diagnosed in a late stage. Due to the lack of effective treatments on pancreatic cancer and the fact that the early stage has a 39% 5-year survival rate, the biggest hope to control this disease is early detection. Therefore, discovery of effective and reliable non-invasive biomarkers for early detection of pancreatic cancer has been a major topic in the research field. Very recently, exosomal microRNAs have become promising candidates of diagnostic markers due to the facts that 1) such small non-coding RNA are stably present in the tissue and can get into blood circulation via exosome packaging which protects them from enzymatic degradation; 2) cancer cells, even at their early stages, may secrete up to tenfold more exosomes than normal cells and some disease-associated microRNAs can get into blood stream; 3) circulating exosomal microRNAs may carry early signals of cancers. With the goal to facilitate cancer detection, in this study, we have developed an integrated computational approach that leverages advanced genomics and bioinformatics to identify exosomal microRNAs that can be promising early detection biomarkers in pancreatic cancer. First, we have analyzed large-scale small RNA microarray data collected from the GEO database to identify microRNA candidates that are differentially-expressed in cancer versus healthy control. Then we have explored several classification models to identify the most effective signature of microRNAs that can well differentiate cancer from normal based on the expression profiles. Through a series of comparisons and validations, the support vector machine-based classifier has achieved the best performance among all. A combination of five significantly-expressed microRNAs (hsa-miR-125a-3p, hsa-miR-6893-5p, hsa-miR-125b-1-3p, hsa-miR-6075, and hsa-miR-4294) achieved the best accuracy and AUC of 97.6% and 99.7%, respectively, which is highly promising. In order to explore the molecular determinants in microRNA secretion to further guide the non-invasive biomarker detection in the blood stream, in the second part of this project, we focused on sequence analysis of exosomal microRNAs for motif detection. Particularly, a graph-based motif-finding algorithm previously developed in our lab has been applied for this purpose. As a result, the motif [CUG][AU]G[UG] was found highly enriched in microRNAs associated with cancer exosomes. Knowing such properties is highly useful to guide a more targeted search in contrast to the profiling-based discovery where most of the detected microRNAs are highly abundant but likely disease irrelevant. In summary, our study has presented a new data-driven strategy that can potentially advance the biomedical research in biomarker discovery. Particularly, we have demonstrated that circulating exosomal microRNAs can be used as promising stable non-invasive biomarkers for early diagnosis of pancreatic cancer.
Author :Engineering National Academies of Sciences (and Medicine) Publisher : ISBN 13 :9780309495349 Total Pages :93 pages Book Rating :4.4/5 (953 download)
Book Synopsis Improving Cancer Diagnosis and Care by : Engineering National Academies of Sciences (and Medicine)
Download or read book Improving Cancer Diagnosis and Care written by Engineering National Academies of Sciences (and Medicine) and published by . This book was released on 2020 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Application of Bioinformatics in Cancers by : Chad Brenner
Download or read book Application of Bioinformatics in Cancers written by Chad Brenner and published by MDPI. This book was released on 2019-11-20 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.
Book Synopsis Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease by : Institute of Medicine
Download or read book Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease written by Institute of Medicine and published by National Academies Press. This book was released on 2010-06-25 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many people naturally assume that the claims made for foods and nutritional supplements have the same degree of scientific grounding as those for medication, but that is not always the case. The IOM recommends that the FDA adopt a consistent scientific framework for biomarker evaluation in order to achieve a rigorous and transparent process.
Book Synopsis Proteomic and Metabolomic Approaches to Biomarker Discovery by : Haleem J. Issaq
Download or read book Proteomic and Metabolomic Approaches to Biomarker Discovery written by Haleem J. Issaq and published by Academic Press. This book was released on 2013-05-20 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution. The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis and modeling. This new standard effectively eliminates the differing methodologies used in studies and creates a unified approach. Readers will learn the advantages and disadvantages of the various techniques discussed, as well as potential difficulties inherent to all steps in the biomarker discovery process. A vital resource for biochemists, biologists, analytical chemists, bioanalytical chemists, clinical and medical technicians, researchers in pharmaceuticals, and graduate students, Proteomic and Metabolomic Approaches to Biomarker Discovery provides the information needed to reduce clinical error in the execution of research. - Describes the use of biomarkers to reduce clinical errors in research - Includes techniques from a range of biomarker discoveries - Covers all steps involved in biomarker discovery, from study design to study execution
Book Synopsis Recent Advancements in Biomarkers and Early Detection of Gastrointestinal Cancers by : Pallaval Veera Bramhachari
Download or read book Recent Advancements in Biomarkers and Early Detection of Gastrointestinal Cancers written by Pallaval Veera Bramhachari and published by Springer Nature. This book was released on 2020-07-21 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes various novel biomarkers for the early diagnosis of gastrointestinal (GI) cancers. It also highlights recent advances in understanding the role of molecular markers and biomarkers, such as volatile biomarkers, serum biomarkers, predictive and prognostic molecular markers for the early detection of GI cancers. Further, it discusses novel biomarkers, including circulating microRNAs, serum microRNA and plasma microRNA in GI cancer. The book presents breakthrough technologies like ultra-sensitive nano-chips, nanosensors, nanodevices, biosensors, electrochemical biosensors, optical biosensors, DNA biosensors, synthetic biology devices, and 'omics' technologies for the early diagnosis of gastrointestinal cancer. In addition it examines the potential of genome-wide association studies, big data analytics, computation biology, systems biology, and nanotechnology for early diagnostics and therapeutics for gastrointestinal cancer, with a focus on personalized cancer treatment. The book is a valuable source for researchers and clinicians engaged in detection and diagnosis of gastrointestinal cancers.
Book Synopsis Personalized Medicine in Oncology by : Ari VanderWalde
Download or read book Personalized Medicine in Oncology written by Ari VanderWalde and published by . This book was released on 2022 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowhere is the explosion in comprehensive genomic testing more evident than in oncology. Multiple consensus guidelines now recommend molecular testing as the standard of care for most metastatic tumors. To aid in the advancement of this rapidly changing field, we intend this Special Issue of JPM to focus on technical developments in the genomic profiling of cancer, detail promising somatic alterations that either are, or have a high likelihood of being, relevant in the near future, and to address issues related to the pricing and value of these tests.The last few years have seen the cost of molecular testing decrease by orders of magnitude. In 2018, we saw the first “site-agnostic” drug approvals in cancer (for microsatellite unstable cancer (PD-1 inhibitors) and NTRK-fusions (TRK inhibitors)). Research on targetable mutations, determination of genetic “signatures” that can use multiple individual genes/pathways, development of targeted therapy, and insight into the value of new technology remains at the cutting edge of research in this field. We are soliciting papers that present new technologies to assess predictive biomarkers in cancer, original research (pre-clinical or clinical) that demonstrates promise for particular targeted therapies in cancer, and articles that explore the clinical and financial impacts of this paradigmatic shift in cancer diagnostics and treatment.
Book Synopsis Artificial Intelligence in Medical Imaging by : Erik R. Ranschaert
Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Book Synopsis Next Generation Sequencing by : Jerzy Kulski
Download or read book Next Generation Sequencing written by Jerzy Kulski and published by BoD – Books on Demand. This book was released on 2016-01-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Next generation sequencing (NGS) has surpassed the traditional Sanger sequencing method to become the main choice for large-scale, genome-wide sequencing studies with ultra-high-throughput production and a huge reduction in costs. The NGS technologies have had enormous impact on the studies of structural and functional genomics in all the life sciences. In this book, Next Generation Sequencing Advances, Applications and Challenges, the sixteen chapters written by experts cover various aspects of NGS including genomics, transcriptomics and methylomics, the sequencing platforms, and the bioinformatics challenges in processing and analysing huge amounts of sequencing data. Following an overview of the evolution of NGS in the brave new world of omics, the book examines the advances and challenges of NGS applications in basic and applied research on microorganisms, agricultural plants and humans. This book is of value to all who are interested in DNA sequencing and bioinformatics across all fields of the life sciences.
Book Synopsis Early Detection of Breast Cancer by : S. Brünner
Download or read book Early Detection of Breast Cancer written by S. Brünner and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: The enormous expansion seen over the last decade in the mammo graphic detection of breast cancer lesions, especially the use of screen ing procedures for the early detection of clinically unsuspected tumors, has made it necessary to summarize the experience made by various centers in the world. The 2nd International Copenhagen Symposium on Detection of Breast Cancer afforded an opportunity of gathering scientists from all over the world to discuss the various problems of early breast cancer detection with special reference to screening procedures. This book forms a synthesis of the information presented by leading scientists from many of the world's mammo graphic centers, particularly those in Sweden and the USA. Hence, the reader will have the opportunity to study the outstanding work carried out by various institutes and centers of breast cancer screening. It is our sincere hope that a study of this volume will encourage other scientists to join in the work on screening procedures. S. Brunner B. Langfeldt P. E. Andersen Contents S. A. Feig: 1 Hypothetical Breast Cancer Risk from Mammography S. A. Feig: Benefits and Risks of Mammography 11 R. L. Egan and M. B. McSweeney: Multicentric Breast Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . 28 M. B. McSweeney and R. L. Egan: Breast Cancer in the Younger Patient: A Preliminary Report 36 M. B. McSweeney and R. L. Egan: Bilateral Breast Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . . . . ' 41 N. Bjurstam: The Radiographic Appearance of Normal and Metastatic Axillary Lymph Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 M. Moskowitz, S. A. Feig, C. Cole-Beuglet, S. H.
