About this Research Topic
The acquisition of cancer hallmarks requires molecular alterations at multiple levels. Numerous attempts have been made to untangle the molecular mechanisms of carcinogenesis using single-omics approaches. While these single-omics approaches have contributed towards the identification of cancer-specific mutations, epigenetic alterations, and molecular subtyping of tumors, they lack the resolving-power to establish the causal relationship between molecular alterations and the phenotypic manifestation of cancer hallmarks. In contrast, the multi-omics approaches involving the interrogation of the cancer cells/tissues from multiple aspects have the potential to unveil the intricate molecular mechanism underlying different phenotypic manifestations of cancer. Moreover, multi-omics approaches can be used to dissect the cellular response to chemo- or immunotherapy as well as discover molecular candidates with diagnostic/prognostic value. This topic will focus on the applications of different multi-omics and systems biology approaches in the field of cancer research and discuss how these approaches are shaping the field of personalized oncomedicine.
The complexity of mammalian cells is driven by the heritable genome constrained by epigenetic mechanisms to regulate the expression of genes in different cellular contexts. Altered gene expression eventually re-shapes the proteome abundance that is necessary for cellular functionality in altered cellular states. Alteration in the epigenetic, transcriptomic, and proteomic landscape enables the cancer cells to acquire the necessary functions to acquire cancer hallmarks. The phenotypic consequence of an altered cellular state such as cancerous transformation is essentially reflected by changes in different omics levels. Therefore interrogation of cancer cells at multi-omics levels is required to understand the link between molecular signatures and cancer phenotypes.
The genome-wide modulation of gene expression by epigenomic alterations can be investigated through the integration of high-throughput data, such as chromatin accessibility, DNA occupancy, methylation expression, etc. In contrast to the NGS-based techniques, mass spectrometry has become the method of choice for proteome analyses.
Although the concept of multi-omics is well established, some aspects of multi-omics data integration in cancer context remain unresolved (e.g., whether a concordant or discordant relationship between multi-omics datasets exists in cancer). Moreover, how this intricate relationship evolves from healthy tissue to cancer remains poorly understood and could be investigated in this collection. Finally, similarities as well as differences across different cancer types could also be considered in the light of multi-omics integration. Through this special collection we seek to understand the mechanisms that underlie the altered relationship among different omics levels in cancer cells/tissues.
This Research Topic invites Original Research and Review articles that will focus on harnessing the full potential of multi-omics studies to integrate alterations that often take place at various regulatory layers in cancer. Topics of interest include, but are not limited to, interrogation of cancer cells in multiple omics levels (genomics, epigenomics, transcriptomics, epitranscriptomic, proteomics, and metabolomics) and systems biology approaches. We would like to encourage harnessing the omics databases to analyze multi-omics data for different cancers. We are particularly interested in manuscripts that cover the following subtopics:
● Integration of two or more omics data in cancer context
● Investigation of concordant and discordant correlation between omics levels
● Identifying molecular signatures based on omics data
● Integration of omics data to stratify cancer patients
● Identification of biomarkers and therapeutic targets based on omics analyses
● Understanding cancer hallmarks thorough systems biology
The complexity of mammalian cells is driven by the heritable genome constrained by epigenetic mechanisms to regulate the expression of genes in different cellular contexts. Altered gene expression eventually re-shapes the proteome abundance that is necessary for cellular functionality in altered cellular states. Alteration in the epigenetic, transcriptomic, and proteomic landscape enables the cancer cells to acquire the necessary functions to acquire cancer hallmarks. The phenotypic consequence of an altered cellular state such as cancerous transformation is essentially reflected by changes in different omics levels. Therefore interrogation of cancer cells at multi-omics levels is required to understand the link between molecular signatures and cancer phenotypes.
The genome-wide modulation of gene expression by epigenomic alterations can be investigated through the integration of high-throughput data, such as chromatin accessibility, DNA occupancy, methylation expression, etc. In contrast to the NGS-based techniques, mass spectrometry has become the method of choice for proteome analyses.
Although the concept of multi-omics is well established, some aspects of multi-omics data integration in cancer context remain unresolved (e.g., whether a concordant or discordant relationship between multi-omics datasets exists in cancer). Moreover, how this intricate relationship evolves from healthy tissue to cancer remains poorly understood and could be investigated in this collection. Finally, similarities as well as differences across different cancer types could also be considered in the light of multi-omics integration. Through this special collection we seek to understand the mechanisms that underlie the altered relationship among different omics levels in cancer cells/tissues.
This Research Topic invites Original Research and Review articles that will focus on harnessing the full potential of multi-omics studies to integrate alterations that often take place at various regulatory layers in cancer. Topics of interest include, but are not limited to, interrogation of cancer cells in multiple omics levels (genomics, epigenomics, transcriptomics, epitranscriptomic, proteomics, and metabolomics) and systems biology approaches. We would like to encourage harnessing the omics databases to analyze multi-omics data for different cancers. We are particularly interested in manuscripts that cover the following subtopics:
● Integration of two or more omics data in cancer context
● Investigation of concordant and discordant correlation between omics levels
● Identifying molecular signatures based on omics data
● Integration of omics data to stratify cancer patients
● Identification of biomarkers and therapeutic targets based on omics analyses
● Understanding cancer hallmarks thorough systems biology
Keywords: Multi-omics, cancer, systems biology
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