Cutting Edge Artificial Intelligence, Spatial Transcriptomics and Proteomics Approaches to Analyze Cancer
- 1st Edition, Volume 163 - September 12, 2024
- Imprint: Academic Press
- Editors: Paul B. Fisher, Kenneth D. Tew, Esha Madan, Rajan Gogna
- Language: English
- Hardback ISBN:9 7 8 - 0 - 4 4 3 - 2 9 6 5 0 - 5
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 9 6 5 1 - 2
Cutting Edge Artificial Intelligence, Spatial Transcriptomics and Proteomics Approaches to Analyze Cancer, Volume 163 in the Advances in Cancer Research series, highlights ne… Read more
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- Contains contributions that have been carefully selected based on their vast experience and expertise on the subject
- Includes updated, in-depth, and critical discussions of available information, giving the reader a unique opportunity to learn
- Encompasses a broad view of the topics at hand
Academic, government and industrial sectors
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Preface
- Chapter One: Deep learning-based multimodal spatial transcriptomics analysis for cancer
- Abstract
- 1 Introduction
- 2 Core concepts of multimodal spatial transcriptomics
- 3 Deep learning approaches in multimodal spatial transcriptomics
- 4 Impact of multimodal spatial transcriptomics on cancer diagnostics and therapeutics
- 5 Challenges, future outlook, and ethical considerations
- 6 Conclusion
- References
- Chapter Two: Data enhancement in the age of spatial biology
- Abstract
- 1 Introduction
- 2 Data enhancement by integrating other sequencing modalities for ST data
- 3 Data enhancement by integrating tissue image data for ST data
- 4 Data enhancement by synthetic data
- 5 Perspectives
- References
- Chapter Three: Current computational methods for spatial transcriptomics in cancer biology
- Abstract
- 1 Introduction
- 2 Overview of spatial transcriptomics techniques
- 3 Application of spatial transcriptomics for cancer study
- 4 Discussion
- Acknowledgments
- References
- Chapter Four: Applications of spatial transcriptomics and artificial intelligence to develop integrated management of pancreatic cancer
- Abstract
- 1 Introduction
- 2 Overview of cancer
- 3 Spatial transcriptomics
- 4 Artificial intelligence
- 5 Spatial transcriptomics contribution to understanding the heterogeneity of pancreatic cancer tumors
- 6 The use of Artificial Intelligence to diagnose and define pancreatic cancer therapy
- 7 Conclusions
- Acknowledgments
- References
- Chapter Five: Advancing cancer therapeutics: Integrating scalable 3D cancer models, extracellular vesicles, and omics for enhanced therapy efficacy
- Abstract
- 1 Introduction
- 2 Beyond 2D: exploring the potential of 3D models in cancer research
- 3 Leveraging omics technologies for robust validation and application of 3D cancer models
- 4 Beyond cells: extracellular vesicles as drug delivery systems for targeted cancer therapy
- 5 Conclusions and future perspectives
- Acknowledgments
- References
- Further reading
- Chapter Six: Crosstalk between tumor and microenvironment: Insights from spatial transcriptomics
- Abstract
- 1 Introduction
- 2 Cancer heterogeneity and landscape
- 3 Spatial transcriptomics and insights
- 4 Evolution of tumor
- 5 Tumor microenvironment (TME)
- 6 Integrating ST and scRNA-seq
- 7 Challenges and future directions
- Acknowledgments
- References
- Chapter Seven: Modular formation of in vitro tumor models for oncological research/therapeutic drug screening
- Abstract
- 1 Introduction
- 2 Why do we need 3D tumor models?
- 3 Challenges with traditional tissue engineering strategies to form tumorous tissues
- 4 Application of modular strategy for tumor model formation
- 5 Future perspective and concluding remarks
- Acknowledgment
- References
- Chapter Eight: Unraveling the complexity: Advanced methods in analyzing DNA, RNA, and protein interactions
- Abstract
- 1 Introduction
- 2 Intramolecular DNA-DNA and RNA-RNA interactions
- 3 Intermolecular DNA-RNA interactions
- 4 Conclusion
- Acknowledgments
- References
- Chapter Nine: Multi-omics based artificial intelligence for cancer research
- Abstract
- 1 Introduction
- 2 Artificial intelligence and machine learning
- 3 Omics techniques
- 4 Application of AI and multi-omics in cancer research
- 5 Multi-omics integration
- 6 Challenges
- References
- Edition: 1
- Volume: 163
- Published: September 12, 2024
- Imprint: Academic Press
- No. of pages: 370
- Language: English
- Hardback ISBN: 9780443296505
- eBook ISBN: 9780443296512
PF
Paul B. Fisher
Paul B. Fisher, MPh, PhD, FNAI, Professor and Chairman, Department of Human and Molecular Genetics, Director, VCU Institute of Molecular Medicine Thelma Newmeyer Corman Chair in Cancer Research in the VCU Massey Cancer Center, VCU, School of Medicine, Richmond, VA, and Emeritus Professor, Columbia University, College of Physicians & Surgeons, New York, NY. Dr. Fisher is among the top 10% of NIH funded investigators over the past 35-years, published approximately 625 papers and reviews, and has 55 issued patents. He pioneered novel gene/discovery approaches (subtraction hybridization), developed innovative therapeutic approaches (Cancer Terminator Viruses), presented numerous named and distinguished lectures, founded several start-up companies, was Virginia Outstanding Scientist of 2014 and elected to the National Academy of Inventors in 2018. Dr. Fisher is a prominent nationally and internationally recognized cancer research scientist focusing on understanding the molecular and biochemical basis of cancer development and progression to metastasis and using this garnered information to develop innovative approaches for diagnosing and treating cancer. He discovered and patented novel genes and gene promoters relevant to cancer growth control, differentiation and apoptosis. His discoveries include the first cloning of p21 (CDK inhibitor), human polynucleotide phosphorylase, mda-9/syntenin (a pro-metastatic gene), mda-5 and mda-7/IL-24, which has shown promising clinical activity in Phase I/II clinical trials in patients with advanced cancers. Dr. Fisher alsohas a documented track record as a successful seasoned entrepreneur. He was Founder and Director of GenQuest Incorporated, a functional genomics company, which merged with Corixa Corporation in 1998, traded on NASDAQ and was acquired by GlaxoSmithKline in 2006. He discovered the cancer-specific PEG-Prom, which is the core technology of Cancer Targeting Systems (CTS, Inc.), a Virginia/Maryland-based company (at Johns Hopkins Medical Center) focusing on imaging and therapy (“theranostics”) of metastatic cancer (2014) by Drs. Fisher and Martin G. Pomper. He co-founded InVaMet Therapeutics (IVMT) and InterLeukin Combinatorial Therapies (ILCT) with Dr. Webster K. Cavenee (UCSD) (2017/2018).
Affiliations and expertise
Department of Human and Molecular Genetics, VCU Institute of Molecular Medicine, VCU Massey Cancer Center, Virginia Commonwealth University, School of Medicine, Virginia, USAKT
Kenneth D. Tew
Professor & Chairman, Dept of Cell & Molecular Pharmacology John C. West Chair of Cancer Research, Medical University of South Carolina, USA
The Tew laboratory maintains an interest in using redox pathways as a platform to develop therapeutic strategies through drug discovery/development and biomarker identification. We interrogate how reactive oxygen and nitrogen species (ROS/RNS) impact cancer cells and develop novel drugs that impact on glutathione based pathways. Our research efforts have been integral to studies that have identified glutathione S-transferases (GST) as important in drug resistance, catalytic detoxification and as arbiters of kinase-mediated cell signaling events. In addition, we have been instrumental in defining how GSTP contributes to the process by which cells respond to ROS by selective addition of glutathione to specific protein clusters, so called S-glutathionylation. Each of these research areas has had broad impact on a number of cancer disciplines. Moreover, we have also been seminally involved in the Phase I to III clinical testing of three oncology drugs, Telcyta, Telintra and NOV-002. Other ongoing translational efforts have produced two ongoing clinical trials to measure the effectiveness of serum S-glutathionylated serine proteinase inhibitors as possible biomarkers for exposure to hydrogen peroxide mouthwashes and radiation.
Affiliations and expertise
Professor and Chairman, Department of Cell and Molecular Pharmacology John C. West Chair of Cancer Research, Medical University of South Carolina, USARG
Rajan Gogna
Dr. Rajan Gogna is an assistant professor at the School of Medicine Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA.
Affiliations and expertise
School of Medicine Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USARead Cutting Edge Artificial Intelligence, Spatial Transcriptomics and Proteomics Approaches to Analyze Cancer on ScienceDirect