Proteomics, Tumor Microbiome, and AI: Emerging Clinical Applications in Oncology

The intersection of oncology, microbiology, and computational sciences has significantly advanced our understanding of cancer. Recent years have witnessed a surge in studies exploring the profound impact of the tumor microbiome on cancer initiation, progression, and therapeutic response. Meanwhile, proteomics has illuminated complex protein networks and signaling pathways that govern tumor biology. While both fields individually contribute valuable insights, a comprehensive approach that integrates proteomic and microbiome data remains relatively untapped. Ongoing debates concern the causal relationships and mechanistic interactions within the tumor microenvironment, and there is a pressing need to decipher these components to identify actionable biomarkers and therapeutic targets. Notably, artificial intelligence (AI) has recently emerged as a powerful tool, accelerating the discovery process by enabling more nuanced analyses of high-dimensional datasets in both proteomics and microbiome research within cancer.

This Research Topic aims to showcase state-of-the-art advances at the interface of proteomics, tumor microbiome studies, and AI-driven analytics within the context of oncology. It seeks to blend these disciplines by soliciting research that leverages computational power to unravel complex biological systems, ultimately driving innovation in cancer diagnostics, prognostics, and therapies. The main objectives are to elucidate the synergies between tumor-associated microbes and host proteomic landscapes, identify novel clinical biomarkers, and translate data-driven insights into practical applications for personalized medicine.

Addressing the emerging landscape of omics-driven and computational cancer research, this Research Topic will not only focus on mechanistic studies, but also on translational and clinical implications. Submissions are limited to research that bridges at least two of the three areas—proteomics, tumor microbiome, or AI—with clear relevance to cancer biology or medicine. We welcome articles addressing, but not limited to, the following themes:

- Multi-omics integration (proteomics and microbiome) for tumor profiling

- AI-empowered biomarker discovery and validation in oncology

- Novel computational approaches for analyzing cancer-associated microbial datasets

- The functional role of the tumor microbiome in modulating host proteome and cancer progression

- Translational studies aiming at clinical applications (e.g., diagnosis, prognosis, therapeutic response prediction)

- Cross-talk between the tumor microbiome and proteome in immuno-oncology

- Ethical or technical challenges of deploying AI in cancer microbiome and proteomics workflows