The correlation between the microbiome and the occurrence and progression of CRC has received increasing attention, but determining how microbes influence cancer susceptibility and progression remains a challenge. Data from cross-sectional epidemiological studies, unbiased microbiome analyses of stool and colorectal tissue, and preclinical models reveal specific taxonomic and bacterial factors . In addition, the role of gut flora in the host can also affect the degree of differentiation or malignancy of CRC in the process of cancer. Metagenomic analysis of stool samples from patients with CRC revealed bacteria closely associated with the development of CRC, and these bacteria included Bacteroides fragilis, Fusobacterium nucleatum, Porphyromonas asaccharolytica, Parvimonas micra, Prevotella intermedia, Alistipes finegoldii, and Thermanaerovibrio acidaminovorans [15, 16]. Molecular mechanisms that drive tumorigenesis have been elucidated, including bacterial membrane proteins or secretory molecules that interact with human cancer cells. However, for most gut bacteria, whether they enhance or inhibit the growth of cancer cells remains unknown . At the same time, how gut bacterial disorders systematically affect the process and mechanism of the EMT in host CRC cells remains unclear. Abd-EI-Raouf et al.  studied the effect of bacteria on tumor cells after in vitro infection of bladder cancer cells by Escherichia coli and found that bacteria enhanced the EMT effect and improved the migration ability of cells. Studies have shown that Clostridium nucleatum can promote the EMT in oral squamous cell carcinoma by regulating the lncRNA MIR4435-2HG\/miR-296-5p\/Akt2\/SNAI1 signaling pathway, thus enhancing cell migration . Lu et al.  proposed that the effector protein OspB, which is delivered by Shigella, affects cell proliferation by activating mTORC1, and that mTORC1 is the main regulator of cell growth. Studies have found that bifidobacteria may enhance the proliferation ability of colon epithelial cells by generating specific extracellular protein structure scaffolds to promote growth . Therefore, whether gut bacteria can promote or inhibit the poor differentiation process of CRC and its possible mechanism are worth studying.
There have been many studies on the relationship between bacteria and tumors, and our research had similar findings. Bifidobacterium reduced cancer cell proliferation by inhibiting growth factor signaling and inducing mitochondria mediated apoptosis, and reduced chemical/immunological/radiotherapy side effects by inhibiting proinflammatory cytokines . The research showed that the abundance of Megamonas in the gut microbiota of patients with cachexia was reduced, and the abundance of Megamonas was significantly different from the non-cachexia group, and it was possible that the disturbance of this microbiota was related to the later stage . Erysipelotrichaceae_UCG_003 was one of the main butyric acid-producing bacteria. The abundance of Erysipelotrichaceae_UCG-003 in healthy group was significantly higher than that in lung cancer group, and it was negatively correlated with glycerol and phospholipid metabolism . This negative correlation may be one of the ways to regulate metabolism and tumor development in vivo. In a research of the microbiota before and after chemotherapy, the abundance of Actinomyces in stool after chemotherapy increased to 2.5 times that before chemotherapy. Actinomyces in the gut may have a positive clinical outcome in CRC patients, and Actinomyces may inhibit tumor growth . Oscillospiraceae showed a relationship with metabolic disorders. In the intestinal microorganisms of patients with high uric acid, Oscillospiraceae was significantly reduced, and Oscillospiraceae may be related to uric acid metabolism . However, there are few studies on the correlation between bacteria and the degree of pathological differentiation. We first reported that characteristic gut bacteria of poorly differentiated CRC were Bifidobacterium, norank_f__Oscillospiraceae, Eisenbergiella, etc., and the characteristic gut bacteria of moderately differentiated CRC were Megamonas, Erysipelotrichaceae_UCG-003, Actinomyces, etc. At present, the differentiation degree of CRC is rarely analyzed with gut bacteria, and poor differentiation is an important manifestation of more invasive CRC. In the present study, certain clinical samples were included to screen and analyze the bacterial characteristics of CRC tumor differentiation. The differences in intestinal microbiota from the perspective of pathological characteristics of CRC were explored, and the relationship between intestinal microbiota and biological behavior of CRC were studied. The study will provide a direction for the further research with strong innovations.
The association between poor differentiation of CRC and gut bacteria was significant. Dysbiosis of gut microbiota and subsequent inappropriate immune responses can lead to susceptibility to chronic inflammation, which contributes to the development of disease and cancer. Microorganisms may contribute to genetic and epigenetic changes through the production of superoxide radicals and genotoxins, as well as toll-like receptor-mediated oncogenic pathway induction . The structural changes of gut bacteria and CRC differentiation may be mutually reinforcing. The increase in the number of specific microorganisms and the decrease in beneficial bacteria may increase the risk of poor differentiation of CRC and promote more invasive CRC. In addition, the poor differentiation state of CRC may also interfere with the intestinal microbiota structure, induce intestinal microbiota disorder, and further increase the probability of malignancy. Recently, Helicobacter hepaticus was found to increase tumor invasion by cytotoxic lymphocytes in mouse models, and this method can inhibit tumor growth . This indicated that the differential microorganisms screened out in this study can become potential targets for the prevention or treatment of poor differentiation of CRC.
In addition, it was found that bacteria were correlated with each other through an intragroup correlation. Therefore, it is possible that different bacteria may participate in or assist each other in promoting or inhibiting the poor differentiation of CRC. In the follow-up study, microbial sequencing of poorly differentiated CRC is likely to find that the bacteria are consistent with those found in this study.
We further constructed a prediction model for poor differentiation of CRC based on differential gut bacteria, The research screened out important characteristic gut microbes, including Pseudoramibacter, Megamonas and Bifidobacterium. Liao et al.  established a kNN classification model based on the clinicopathological information and protein expression profile analysis of CRC, which predicted the degree of tumor differentiation of CRC with high accuracy (P ≤ 0.001, receiver-operator characteristics-ROC-error, 0.171). The expression of related genes, such as HER3 and insulin receptor substrate 1, was found to be a predictive target of the degree of CRC differentiation [34, 35]. Metabolites from gut microbes also play an important role. Symbiotic microbial factors are short-chain fatty acids, such as butyrate, which reduce the growth of normal intestinal stem cells and a range of cancer-derived cell lines . The potential role of gut bacterial metabolites in CRC differentiation was not considered in this study. This may be one of the problems of this research experiment. At the same time, gut bacteria are affected by dietary habits, drug use and other factors, so the impact on the results of this analysis is inevitable. In the present study, the MiSeq platform was used for the second-generation sequencing of 16S rRNA V1-V4 region. Our research design began in 2018, and the third-generation sequencing technologies, such as NanoPore, were immature at that time. Third-generation sequencing can make the length of sequencing up to about 10 kb, and do not need PCR enrichment sequence, can be directly sequenced, third-generation sequencing can solve the problem of information loss and base mismatch. Long-read platforms will provide us with a direction in the further research. Vuik et al.  found that poorly differentiated CRCs were more common in the younger group by recruiting 6400 subjects. Pereira et al.  analyzed the pathological features of CRC in different groups of age and showed that poorly differentiated tumors was most common in young CRC patients. The results showed that the age difference existed in the moderately and poorly differentiated groups. In future studies, the age-related differential bacteria could be further analyzed. At the same time, the sample size of this study is insufficient, which also limits the applicability of the research results. In the future, multicenter studies are needed to further verify whether these microbiota can be used as promoting factors for the development of CRC, and to further find the link between these microbiota and the development of CRC.