Microbial Biomarkers for Colorectal Cancer Identified with Random Forest Model

Colorectal cancer (CRC) is one of the most common cancers and a leading cause of cancer-related death. Gut microbiota are part of a complex microbe-based ecosystem of the human body, and changes in the microbiota can lead to a variety of diseases. All currently used CRC detection methods, including endoscopy, guaiac-based fecal occult blood test and fecal immunochemical test, have many limitations. Therefore, establishing novel screening methods which are accurate, inexpensive and non-invasive is indicated. Random forest models, as a superiority machine learning model, are increasingly used in research to select biomarkers. In this review, we summarized progressions of the diagnoses of CRC based on the random forest model of gut microbiota. We concluded that some cancer-associated bacteria in gut microbiota could be used as biomarkers for detecting early CRC. We also aimed to discuss how to select possible markers of colorectal diseases based on gut microbiota using the random forest model.