Computational Driven Understanding Of The Regulatory Mechanisms Of The Breast Cancer Transcriptome And Its Implications For Drug Treatment
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Computational Driven Understanding Of The Regulatory Mechanisms Of The Breast Cancer Transcriptome And Its Implications For Drug Treatment
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Author : Shujun Huang
language : en
Publisher:
Release Date : 2021
Computational Driven Understanding Of The Regulatory Mechanisms Of The Breast Cancer Transcriptome And Its Implications For Drug Treatment written by Shujun Huang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Breast cancer (BC) is the most commonly diagnosed cancer and the major cause of cancer mortality among women worldwide. As a heterogenous disease, BC can be divided into four major molecular subtypes: luminal A, luminal B, HER2-enriched, and triple negative breast cancer (TNBC). The TNBC subtype shows the shortest survival time among the four groups and lacks effective targeted therapeutic strategies. Different BC subtypes display different transcriptome profiles. However, the dysregulated pathways and transcriptional regulators underlying the gene expression profiles of different BC subtypes have yet to be fully elucidated. Current research is investigating the dysregulated genes in BC with the aim to identify potential gene targets for BC while overlooking the fact these genes are often part of a pathway. Moreover, among the multi-omics data, gene expression profiles have been shown to be the most informative data for developing anti-cancer drug response prediction models in silico. But these models typically were developed with individual genes. Therefore, this thesis aimed to explore the breast cancer transcriptome with a focus on the TNBC subtype to address three major questions: 1) exploring the regulatory mechanisms driving the unique expression pattern of different BC subtypes; 2) identifying compounds that could affect the expression pattern of the top dysregulated pathways in BC; and 3) developing a drug response prediction model by using BC pathway activity profiles inferred from the transcriptome profiles. To address the first question, we collected the multi-omics data of BC samples from The Cancer Genome Atlas (TCGA) dataset, including gene expression, DNA methylation, copy number variation (CNV) and microRNA (miRNA) profiles, the transcription factor (TF)-binding data from TRRUST v2.0, and the miRNA-binding data from starBase v3.0. Using these data, the Lasso regression-based integrative analysis identified 25, 20, 15 and 24 key regulators for luminal A, luminal B, HER2-enriched and TNBC subtypes, respectively. A further look at the TNBC regulators found that many of them are regulating the FOXM1 (i.e., PID_FOXM1_PATHWAY) and PPARA (i.e., BIOCARTA_PPARA_PATHWAY) pathways. To address the second question, we focused on the FOXM1 and PPARA pathways. Using the Connectivity Map (CMAP) database, which provides drug-induced gene expression changes in MCF7 cell lines, we investigated how different compounds change the activity and expression pattern of the two pathways. Nineteen drugs (such as 5109870, MG-132, MG-262, celastrol, resveratrol, and cephaeline) were identified to decrease the FOXM1 pathway activity scores and reverse the FOXM1 pathway expression pattern while 13 drugs (such as cephaeline, pararosaniline, cycloheximide, monensin, wortmannin, and raloxifene) were identified to increase the PPARA pathway activity scores and reverse the PPARA pathway expression pattern. It may be of interest to validate these compounds experimentally. To address the third question, we collected the baseline gene expression profiles of 49 BC cell lines along with IC50 values of these cell lines to 220 drugs from the Genomics of Drug Sensitivity in Cancer (GDSC) dataset. Using these data, we developed a multiple-layer cell line-drug response network (ML-CDN2) by integrating a one-layer cell line similarity network based on the pathway activity profiles and a three-layer drug similarity network based on three types of drug information. ML-CDN2 demonstrated good prediction performance, with the Pearson correlation coefficient between the observed and predicted IC50 values for all cell line-drug pairs of 0.873. Moreover, the ML-CDN2 model could be used to predict the drug response for new BC cell line samples or new BC patient-derived samples. This thesis demonstrated the transcriptional regulators underlying the transcriptome profiles in different BC subtypes. Moreover, this thesis demonstrated the implications of the BC transcriptome in drug treatment by identifying the drugs to modulate the two dysregulated pathways in BC and developing the anti-cancer drug response prediction model for BC by incorporating the transcriptome profiles.
Deep Learning For Cancer Diagnosis
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Author : Utku Kose
language : en
Publisher: Springer Nature
Release Date : 2020-09-12
Deep Learning For Cancer Diagnosis written by Utku Kose and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-12 with Technology & Engineering categories.
This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.
Personalized Medicine In Oncology
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Author : Ari VanderWalde
language : en
Publisher: Mdpi AG
Release Date : 2022-01-25
Personalized Medicine In Oncology written by Ari VanderWalde and has been published by Mdpi AG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-25 with categories.
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.
Systems Biology Of Cancer
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Author : Sam Thiagalingam
language : en
Publisher: Cambridge University Press
Release Date : 2015-04-09
Systems Biology Of Cancer written by Sam Thiagalingam and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-09 with Mathematics categories.
An overview of the current systems biology-based knowledge and the experimental approaches for deciphering the biological basis of cancer.
Prediction And Explanation In Biomedicine Using Network Based Approaches
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Author : Alessio Martino
language : en
Publisher: Frontiers Media SA
Release Date : 2022-10-12
Prediction And Explanation In Biomedicine Using Network Based Approaches written by Alessio Martino and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-12 with Medical categories.
Precision Cancer Medicine
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Author : Sameek Roychowdhury
language : en
Publisher: Springer Nature
Release Date : 2020-01-02
Precision Cancer Medicine written by Sameek Roychowdhury and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-02 with Medical categories.
Genomic sequencing technologies have augmented the classification of cancer beyond tissue of origin and towards a molecular taxonomy of cancer. This has created opportunities to guide treatment decisions for individual patients with cancer based on their cancer’s unique molecular characteristics, also known as precision cancer medicine. The purpose of this text will be to describe the contribution and need for multiple disciplines working together to deliver precision cancer medicine. This entails a multi-disciplinary approach across fields including molecular pathology, computational biology, clinical oncology, cancer biology, drug development, genetics, immunology, and bioethics. Thus, we have outlined a current text on each of these fields as they work together to overcome various challenges and create opportunities to deliver precision cancer medicine. As trainees and junior faculty enter their respective fields, this text will provide a framework for understanding the role and responsibility for each specialist to contribute to this team science approach.
Evolution Of Translational Omics
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Author : Institute of Medicine
language : en
Publisher: National Academies Press
Release Date : 2012-09-13
Evolution Of Translational Omics written by Institute of Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-13 with Science categories.
Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.
Drug Repurposing In Cancer Therapy
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Author : Kenneth K.W. To
language : en
Publisher: Academic Press
Release Date : 2020-07-29
Drug Repurposing In Cancer Therapy written by Kenneth K.W. To and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-29 with Science categories.
Drug Repurposing in Cancer Therapy: Approaches and Applications provides comprehensive and updated information from experts in basic science research and clinical practice on how existing drugs can be repurposed for cancer treatment. The book summarizes successful stories that may assist researchers in the field to better design their studies for new repurposing projects. Sections discuss specific topics such as in silico prediction and high throughput screening of repurposed drugs, drug repurposing for overcoming chemoresistance and eradicating cancer stem cells, and clinical investigation on combination of repurposed drug and anticancer therapy. Cancer researchers, oncologists, pharmacologists and several members of biomedical field who are interested in learning more about the use of existing drugs for different purposes in cancer therapy will find this to be a valuable resource. Presents a systematic and up-to-date collection of the research underpinning the various drug repurposing approaches for a quick, but in-depth understanding on current trends in drug repurposing research Brings better understanding of the drug repurposing process in a holistic way, combining both basic and clinical sciences Encompasses a collection of successful stories of drug repurposing for cancer therapy in different cancer types
Steroid Receptors In Breast Cancer
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Author :
language : en
Publisher:
Release Date : 1983
Steroid Receptors In Breast Cancer written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Breast categories.
The Physics Of Cancer
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Author : Caterina A. M. La Porta
language : en
Publisher: Cambridge University Press
Release Date : 2017-04-20
The Physics Of Cancer written by Caterina A. M. La Porta and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-20 with Science categories.
An introduction to the emerging field of cancer physics, integrating cancer biology with approaches from theoretical and applied physics.