About this Research Topic
Cancer is an extremely complex disease and for organ-specific cancers it can be challenging to identify the key factors and then link their mechanistic contributions to the range of growth and spread with the ongoing events in the body. Systems biology offers possibilities to study cancer as a systematic disease, and tackle one important challenge at a time. In this regard, engagement of research scientists with varied backgrounds allow for innovative thought process that is essential for understanding and investigating the big picture.
This Research Topic aims to provide a platform for innovative approaches and treatments of cancer. This topic invites research scientists to share the novel ways of not only early detection of the key cancer players but also in how to target and eliminate them while keeping the rest of the body safe and healthy.
We invite manuscripts related to (but not limited to) the following innovations in this field:
• Analysis of the genetic and epigenetic changes in single cells, providing insights into the heterogeneity of cancer cells and their microenvironment.
• Network analysis, studying the interactions between genes and proteins involved in cancer development and progression
• Machine learning applications, used to analyze large datasets and predict the outcome of cancer treatments, and to develop personalized treatment plans for cancer patients.
• Immunotherapy, that uses the body's own immune system to fight cancer, such as CAR-T cell therapy and checkpoint inhibitors.
• Organoid models, 3D cultures of cancer cells that closely mimic the structure and function of tumors in the body, and can be used to study the biology of cancer and test potential treatments.
• Multi-omics, involving the integration of data from multiple omics platforms, such as genomics, transcriptomics, proteomics, and metabolomics to provide a comprehensive view of cancer biology.
• Spatial transcriptomics, which allows for the analysis of gene expression patterns within the context of tissue architecture, providing insights into the spatial organization of cancer cells and their microenvironment.
Topic Editor Kazim Y. Arga is co-founder and director of Cellformatics Biotechnology Inc. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
This Research Topic aims to provide a platform for innovative approaches and treatments of cancer. This topic invites research scientists to share the novel ways of not only early detection of the key cancer players but also in how to target and eliminate them while keeping the rest of the body safe and healthy.
We invite manuscripts related to (but not limited to) the following innovations in this field:
• Analysis of the genetic and epigenetic changes in single cells, providing insights into the heterogeneity of cancer cells and their microenvironment.
• Network analysis, studying the interactions between genes and proteins involved in cancer development and progression
• Machine learning applications, used to analyze large datasets and predict the outcome of cancer treatments, and to develop personalized treatment plans for cancer patients.
• Immunotherapy, that uses the body's own immune system to fight cancer, such as CAR-T cell therapy and checkpoint inhibitors.
• Organoid models, 3D cultures of cancer cells that closely mimic the structure and function of tumors in the body, and can be used to study the biology of cancer and test potential treatments.
• Multi-omics, involving the integration of data from multiple omics platforms, such as genomics, transcriptomics, proteomics, and metabolomics to provide a comprehensive view of cancer biology.
• Spatial transcriptomics, which allows for the analysis of gene expression patterns within the context of tissue architecture, providing insights into the spatial organization of cancer cells and their microenvironment.
Topic Editor Kazim Y. Arga is co-founder and director of Cellformatics Biotechnology Inc. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
Keywords: Systems approach, Network analysis, Single-cell sequencing, Cancer biomarkers, Cancer targets, Multi-Omics, Immunotherapy, Machine learning, Artificial intelligence
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
