The microbiota is present in many parts of the human body and plays essential roles. The most typical case is the occurrence and development of cancer. Pancreatic cancer (PC), one of the most aggressive and lethal types of cancer, has recently attracted the attention of researchers. Recent research has revealed that the microbiota regulates PC carcinogenesis via an altered immune response. Specifically, the microbiota, in several sites, including the oral cavity, gastrointestinal tract, and pancreatic tissue, along with the numerous small molecules and metabolites it produces, influences cancer progression and treatment by activating oncogenic signaling, enhancing oncogenic metabolic pathways, altering cancer cell proliferation, and triggering chronic inflammation that suppresses tumor immunity. Diagnostics and treatments based on or in combination with the microbiota offer novel insights to improve efficiency compared with existing therapies.

Radiation enteritis (RE) is a severe, dose-limiting complication of cancer radiotherapy that affects the therapeutic outcomes of patients and their quality of life. Current risk assessments primarily rely on physical dosimetry. However, this approach inherently ignores the substantial individual variability in radiation susceptibility, creating an urgent clinical need for personalized predictive tools. Emerging evidence suggests that the gut microbiota plays a central role in RE pathogenesis. Ionizing radiation can cause rapid and profound changes in intestinal ecological structure by reducing the number of beneficial microbes while increasing that of harmful pathogens; these factors interact to exacerbate damage to the mucosal barrier and the ongoing inflammatory response. This review synthesizes the multifaceted role the gut microbiome plays in RE, uniquely emphasizing its clinical translational value. Baseline microbial signatures and dynamic multi-omics data, particularly specific taxa and metabolites of the gut microbiota, emerged as powerful predictive biomarkers. These biological signals could inform risk stratification; however, large-scale clinical validation is required. Moreover, integrating microbiome data into machine learning algorithms represents an exploratory approach for toxicity prediction. Crucially, the evaluation of microbiota-targeted therapies reveals an expanding landscape of preclinical and early-phase clinical research. Future interventions may expand beyond conventional probiotics and fecal microbiota transplantation to include experimental therapies such as rationally designed consortia and engineered biotherapeutics. Finally, a strategic roadmap is proposed, utilizing large-scale longitudinal cohorts, high-resolution spatial transcriptomics, and explainable artificial intelligence. These advances may support the transition toward proactive microbiome-guided management strategies.