An emerging consensus regarding the triangle relationship between tumor, immune cells, and microbiomes is the immune-oncology-microbiome (IOM) axis, which stipulates that microbiomes can act as a discrete enabling (or disabling) characteristic that broadly influence the acquisition of certain hallmarks of cancer, i.e., a set of functional capabilities acquired by human cells during carcinogenesis and progression to malignant tumors. Specifically, it has been postulated that polymorphic microbiomes can either induce or inhibit some of the hallmark capacities (particularly, immune evasions) via their intersecting with two other enabling characteristics (genome instability and mutation, and tumor promoting inflammation). The net effects of the microbiomes can be either protective or deleterious effects on cancer development, malignant progression, and therapy responses. Nevertheless, there is not yet a mechanistic interpretation for IOM, especially regarding intratumoral microbiomes. Here, we propose to interpret the observed relationships, in which microbiomes can be complicit, bystanders, or in rare cases, oncomicrobes or foes, to either cancer cells or immune cells, possibly depend on specific microbial taxon, with the AKP (Anna Karenina principle)--that all heathy tissue microbiomes should be similar, and tumor microbiomes should be dissimilar with each other, in analogy with Leo Tolstoy's aphorism that "all happy families look alike; each unhappy family is unhappy in its own way." Given potentially double-sword nature of microbes, both AKP and anti-AKP should exist in the IOM axis. We test the AKP with microbiome datasets of 20+ cancer types from the TCGA database and find that the ratio of AKP/anti-AKP is about 3:1.

The authors have declared no competing interest.

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Availability of datasets The datasets reanalyzed in this article is publicly available from the Online Supplementary Information of the following publication: Poore, GD, E Kopylova, Q Zhu, R Knight (2020). Microbiome analyses of blood and tissues suggest cancer diagnostic approach. Nature 579, 567-574. https://doi.org/10.1038/s41586-020-2095-1