About this Research Topic
Proteomics is playing an increasingly significant role in investigating molecular mechanisms that govern oncogenesis and is being widely used in the quest for early-stage biomarkers and novel therapeutic targets. Understanding complex signaling mechanisms mediated by various post-translational modifications including phosphorylation, glycosylation, ubiquitylation and ADP ribosylation is an area where proteomics could have the greatest impact. Proteomics can, therefore, help dissect molecular mechanisms, functional roles of proteins, receptors and signaling pathways involved in cancer.
Proteome stability and dynamics are known to regulate metastatic stages of cancer. Protein-protein interactions, protein-DNA/RNA interactions, and protein-lipid interactions are all important in understanding macromolecular complexes involved in cancer progression. Proteome profiles can ultimately help in the selection of treatment for individual patients. It is an excellent tool for gaining insight into the mode of action of several current and under-trial drugs, natural products, peptides, monoclonal antibodies, activation of cancer suppressor genes and enables repurposing of drugs. High throughput and quantitative proteomics approaches including label-free and label-based quantification methods (SILAC, ITRAQ, TMT, etc.) have the potential to identify proteins of interest including putative biomarkers and therapeutic targets. In addition, an analysis of cancer proteome data combined with other multi-omics data including metabolomics, transcriptomics, genomics, and molecular imaging can provide a more comprehensive understanding of cancer progression.
Overall, proteomics has proved invaluable in the investigation of various biomedical research questions in cancer and beyond. In this Research Topic, we would like to include Original Research and Review articles focusing on:
1. Cancer biomarkers: Biomarkers for early diagnosis, prognosis and drug response.
2. Post-translational modifications: Phosphorylation, N‑glycosylation, O‑GlcNAcylation, Acetylation, Ubiquitylation, ADP-Ribosylation etc.
3. Protein-protein interactions and drug mechanism of action.
4. Signaling pathways and molecular mechanisms that regulate tumorigenesis.
5. Protein Quantifications: label Free / label based quantitation.
6. Structure and function of proteins in cancer progression.
7. Proteome dynamics and metastasis.
Proteome stability and dynamics are known to regulate metastatic stages of cancer. Protein-protein interactions, protein-DNA/RNA interactions, and protein-lipid interactions are all important in understanding macromolecular complexes involved in cancer progression. Proteome profiles can ultimately help in the selection of treatment for individual patients. It is an excellent tool for gaining insight into the mode of action of several current and under-trial drugs, natural products, peptides, monoclonal antibodies, activation of cancer suppressor genes and enables repurposing of drugs. High throughput and quantitative proteomics approaches including label-free and label-based quantification methods (SILAC, ITRAQ, TMT, etc.) have the potential to identify proteins of interest including putative biomarkers and therapeutic targets. In addition, an analysis of cancer proteome data combined with other multi-omics data including metabolomics, transcriptomics, genomics, and molecular imaging can provide a more comprehensive understanding of cancer progression.
Overall, proteomics has proved invaluable in the investigation of various biomedical research questions in cancer and beyond. In this Research Topic, we would like to include Original Research and Review articles focusing on:
1. Cancer biomarkers: Biomarkers for early diagnosis, prognosis and drug response.
2. Post-translational modifications: Phosphorylation, N‑glycosylation, O‑GlcNAcylation, Acetylation, Ubiquitylation, ADP-Ribosylation etc.
3. Protein-protein interactions and drug mechanism of action.
4. Signaling pathways and molecular mechanisms that regulate tumorigenesis.
5. Protein Quantifications: label Free / label based quantitation.
6. Structure and function of proteins in cancer progression.
7. Proteome dynamics and metastasis.
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