Abstract
BACKGROUND: Cancer remains one of the leading global health challenges, with lung cancer (LC), breast cancer (BC), and colorectal cancer (CRC) among the most prevalent and deadly malignancies. The intratumoral microbiota (IM), a distinct microbial ecosystem within tumor tissues, has recently emerged as a potential modulator of carcinogenesis, immune responses, and metastatic progression. However, comparative cross-cancer analyses remain limited. Therefore, this study aimed to compare the IM across these cancer types, with particular emphasis on distinguishing metastatic from non-metastatic malignancies, to identify tumor-specific microbial signatures with potential relevance for biomarker discovery, patient stratification, and microbiota-informed therapeutic strategies. METHODS: We performed 16S rRNA gene sequencing to profile the IM in formalin-fixed, paraffin-embedded (FFPE) samples from 20 BC patients, 20 CRC patients and 15 non-small cell lung cancer (NSCLC) patients. RESULTS: BC samples exhibited the highest genus-level richness, whereas CRC samples showed significantly greater overall alpha diversity, consistent with the microbial complexity of the gut environment. NSCLC samples displayed the most balanced microbial distribution, as reflected by the highest Shannon index value. Stratification by metastatic status revealed distinct microbial signatures: 16 genera were exclusive to metastatic tumors and 49 to non-metastatic ones. In BC specifically, the class Clostridia and the family Burkholderiaceae were enriched in non-metastatic samples, accompanied by functional shifts in pantothenate and coenzyme A biosynthesis, lysine metabolism, and lipid A pathways. Microbial network analysis further revealed differences in ecological community structure and keystone taxa: Streptococcus spp. predominated as hubs in metastatic tumors, whereas Neisseria spp. were central in non-metastatic networks. CONCLUSIONS: Overall, our findings highlight cancer-type and metastasis-specific microbial signatures, supporting a potential role for the IM in tumor progression and offering novel avenues for biomarker discovery and therapeutic targeting.