About this Research Topic
The 21st century has witnessed the emergence of numerous technological innovations such as individualized and single-cell multi-omics technologies, artificial intelligence (AI) and development of innovative algorithms that are currently being applied to big data sciences to study biological systems. These technologies can be further extended to other systems to allow cellular state reprogramming, for example via synthetic biology.
It is time to rethink and expand research to decode immunologic complex systems in cancer by incorporating these cutting-edge technological innovations. For instance, how knowledge gained from systems biology approaches, AI, and other disciplines including stem cell and synthetic biology can be harnessed to enhance the development of immunotherapy options, in particular the development of individualized medicine to modulate immunity in specific cancer patients and ultimately improve outcomes and treatment efficacy.
This Research Topic aims at highlighting cutting-edge technologies that have been revolutionizing the field of immunology paving the way to systems cancer immunology. We welcome submissions of Original Research, Review, Mini-Review, Opinion, Methods and Perspective articles focusing on the following topics:
• Use of AI tools (support vector machine, random forest, deep neural networks, etc.), systems biology and network biology approaches to uncover genetic and molecular factors that affect immune interactions and their potential in modulating the efficacy of cancer immunotherapy;
• Studies on single cell imaging or single cell sequencing and their intersections to chart cell-cell interactions and tissue mapping to define tumor microenvironments and immune cells subpopulations amenable to therapeutic intervention;
• Synthetic biology tools including genome editing technologies such as CRISPR-based tools that are capable to generate novel biological phenotypes in immune cells to better combat cancer such as modulation of signaling and impact on tumor microenvironment.
Dr. Jin Zhang is scientific cofounder of CellOrigin Inc.. The other Topic Editors declare no competing interests with regard to the Research Topic subject.
It is time to rethink and expand research to decode immunologic complex systems in cancer by incorporating these cutting-edge technological innovations. For instance, how knowledge gained from systems biology approaches, AI, and other disciplines including stem cell and synthetic biology can be harnessed to enhance the development of immunotherapy options, in particular the development of individualized medicine to modulate immunity in specific cancer patients and ultimately improve outcomes and treatment efficacy.
This Research Topic aims at highlighting cutting-edge technologies that have been revolutionizing the field of immunology paving the way to systems cancer immunology. We welcome submissions of Original Research, Review, Mini-Review, Opinion, Methods and Perspective articles focusing on the following topics:
• Use of AI tools (support vector machine, random forest, deep neural networks, etc.), systems biology and network biology approaches to uncover genetic and molecular factors that affect immune interactions and their potential in modulating the efficacy of cancer immunotherapy;
• Studies on single cell imaging or single cell sequencing and their intersections to chart cell-cell interactions and tissue mapping to define tumor microenvironments and immune cells subpopulations amenable to therapeutic intervention;
• Synthetic biology tools including genome editing technologies such as CRISPR-based tools that are capable to generate novel biological phenotypes in immune cells to better combat cancer such as modulation of signaling and impact on tumor microenvironment.
Dr. Jin Zhang is scientific cofounder of CellOrigin Inc.. The other Topic Editors declare no competing interests with regard to the Research Topic subject.
Keywords: single-cell; multi-omics; systems immunology; immunology; big data, cancer immunology
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