Research Topic

Using Cancer ‘omics' to Understand Cancer

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The proliferation and increasing accessibility of technologies that generate massive sets of omics (genomics, transcriptomics, epigenomics, proteomics, etc.) data carry great appeal. They promise to provide a robust foundation for the advancement of a systems-level understanding of the basic biological ...

The proliferation and increasing accessibility of technologies that generate massive sets of omics (genomics, transcriptomics, epigenomics, proteomics, etc.) data carry great appeal. They promise to provide a robust foundation for the advancement of a systems-level understanding of the basic biological principles and processes that underlie the heterogeneous group of diseases we refer collectively as “cancer”. Insights gained from omics research is critical to precision medicine in relation to its involvement in cancer prevention, early detection, and treatment intervention. This proposal aims to assemble a series of review articles dealing with various omics fields and connect it with articles addressing cancer risk factors.

We welcome articles addressing the following topics:

1. Genomics: why genomic research is critical to understand the biology of cancer
2. Epigenomics: how large-scale methylation and chromatin modifications affect carcinogenesis
3. Proteomics: proteomics and its role in cancer research
4. Biomarkers and big data: screening large datasets to identify early cancer, select the appropriate therapeutic intervention, and monitor clinical outcomes
5. Single cell RNA-Sequencing analysis (scRNA-seq): high throughput scRNA-seq technology provides an accurate assessment of tumor heterogeneity which is essential for the development of effective therapies
6. Statistics & cancer omics - problems associated with handling a large amount of data and multiple testing in clinical trials and observational studies, and how to address these issues
7. High-performance computing: application of New Cloud technologies to study cancer genomics
8. Genomic screening for inherited cancer risk and over-diagnosis at the genetic level
9. The use of ‘Artificial Intelligence’ in cancer research
10. Transcriptomics and genomics
11. Noncoding RNA as a biomarker for cancer risk assessment


Keywords: Omics, big data, genetics, cancer risk, biomarkers


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.

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