Bacteria living inside tumors can influence how cancer grows and responds to treatment, but the field has been hampered by controversy over the reliability of the data. Our study provides a much-needed road map for researchers. We rigorously tested the massive Cancer Genome Atlas data set and developed a statistical framework to separate true biological signals from random noise. We discovered that many widely reported links are statistically unreliable and likely false leads. Importantly, our framework successfully pinpoints trustworthy signals. We used it to identify a specific bacterium, Streptococcus anginosus, and proved in the lab that it makes oral cancer cells grow faster and spread. Our publicly available Multi-Omics and Microbiome Associations in Cancer 2 (MOMAC2) web portal now allows scientists to use these reliability-graded findings to accelerate robust cancer microbiome research.
Ma et al. (Wed,) studied this question.