Table_1_Comparison of Microbiota in Patients Treated by Surgery or Chemotherapy by 16S rRNA Sequencing Reveals Potential Biomarkers for Colorectal Cancer Therapy.XLS
Colorectal cancer (CRC) is the third most diagnosed cancer worldwide due to its high difficulty in early diagnosis, high mortality rate and short life span. Recent publications have demonstrated the involvement of the commensal gut microbiota in the initiation, progression and chemoresistance of CRC. However, this microbial community has not been explored within CRC patients after anti-cancer treatments. To this end, we performed next generation sequencing-based metagenomic analysis to determine the composition of the microbiota in CRC patients after anti-cancer treatments. The microbial 16S rRNA genes were analyzed from a total of 69 fecal samples from four clinical groups, including healthy individuals, CRC patients, and CRC patients treated with surgery or chemotherapy. The findings suggested that surgery greatly reduced the bacterial diversity of the microbiota in CRC patients. Moreover, Fusobacterium nucleatum were shown to confer chemoresistance during CRC therapy, and certain bacterial strains or genera, such as the genus Sutterella and species Veillonella dispar, were specifically associated with CRC patients who were treated with chemotherapeutic cocktails, suggesting their potential relationships with chemoresistance. These candidate bacterial genera or strains may have the ability to enhance the dosage response to conventional chemotherapeutic cocktails or reduce the side effects of these cocktails. A combination of common CRC risk factors, such as age, gender and BMI, identified in this study improved our understanding of the microbial community and its compositional variation during anti-cancer treatments. However, the underlying mechanisms of these microbial candidates remain to be investigated in animal models. Taken together, the findings of this study indicate that fecal microbiome-based approaches may provide additional methods for monitoring and optimizing anti-cancer treatments.