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As a core functional component of the tumor microenvironment, the regulatory role of intratumoral microbiome in tumorigenesis and progression has become as a frontier research direction in oncology. Microorganisms such as bacteria, fungi, and viruses participate in the regulation of tumor biological mechanisms through multiple pathways, including metabolite secretion, induction of genomic instability, and remodeling of the immune microenvironment; their species composition and abundance characteristics exhibit distinct cancer-type specificity, and their impact on patient prognosis is highly context-dependent. Current detection systems for the intratumoral microbiome mainly encompass in situ detection technologies, metagenomic sequencing, and computational pathology-driven intelligent detection, each with its own advantages and limitations, among which intelligent detection centered on deep learning is gradually overcoming the technical bottlenecks of identifying low-abundance microbial signals, achieving accurate quantification, and resolving spatial distribution. In the future, with the deep integration of three-dimensional pathological imaging, spatial omics, and multi-modal foundation models, intratumoral microbiome research will advance toward the in-depth development of multi-dimensional data integration, providing innovative ideas and technical pathways for elucidating the regulatory mechanisms between microorganisms and the host and for developing precision diagnostic and treatment strategies based on individual microecological characteristics.