Cancer research is an ever-evolving field, driven by the pressing need to understand and combat a disease that remains a leading cause of morbidity and mortality worldwide. The molecular complexity of cancer, with its vast inter-individual and inter-tumor variability, has presented significant challenges in diagnosis and treatment. The introduction of high-throughput OMICS technologies—such as genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics—has revolutionized our comprehension of the intricate biological dimensions of cancer. These integrative approaches are pivotal in unraveling the complexities of tumor heterogeneity, molecular signatures, immune interactions, and therapeutic resistance mechanisms, driving new waves of innovation in research and treatment strategies.

This Research Topic aims to serve as a comprehensive platform showcasing the latest advancements in the application of OMICS technologies to cancer biology. The goal is to highlight original research, reviews, and perspectives that elucidate the role of integrative OMICS in identifying novel biomarkers, understanding tumor progression, and informing therapeutic decisions. By fostering interdisciplinary dialogue among experimental biologists, clinicians, computational scientists, and bioinformaticians, this collection seeks to push the boundaries of how molecular data inform clinical outcomes in oncology. Topics of interest include, but are not limited to, the classification and prognosis of cancer subtypes, the signaling role of noncoding RNAs, biomarker discovery through proteogenomics, and the connection of metabolism to therapy response.

To gather further insights within the expansive domain of OMICS in cancer research, we welcome articles addressing, but not limited to, the following themes:

- Multi-OMICS integration in cancer subtype classification and prognosis

- The role of transcriptomics and noncoding RNAs (miRNA, lncRNA, circRNA) in cancer signaling

- Proteogenomic approaches for biomarker discovery and drug target validation

- Metabolomic and lipidomic profiling in tumor metabolism and therapy response

- Single-cell and spatial OMICS to resolve tumor microenvironment complexity

- Epigenomic alterations and their translational relevance

- The use of Artificial Intelligence and machine learning in OMICS data interpretation

- OMICS-guided approaches in immuno-oncology and precision medicine

We invite submissions in the form of Original Research articles, Reviews, and Perspectives, providing a global platform for cutting-edge contributions in shaping future paradigms of cancer diagnosis, prognosis, and therapy grounded in integrative OMICS science.

Are you interested in contributing a manuscript to this Research Topic?

Integrative OMICS Approaches in Cancer Biology: From Molecular Mechanisms to Precision Medicine