CRCpred: An AI-ML tool for colorectal cancer prediction using gut microbiome

Colorectal cancer (CRC) is a leading cause of death worldwide. A plethora of research shows the alteration of the gut microbiome and the association of bacterial taxa with CRC. Gaining insights into the health status through microbiome-based diagnosis is a rapidly growing area of research. Many studies have utilized machine learning (ML) to leverage gut microbial dysbiosis for CRC screening, yet most have been limited by their training data and algorithms. Here, using 1728 publicly available metagenomic samples from 11 studies across eight countries, we developed a web-based tool, "CRCpred," employing ML and deep learning-based hybrid algorithms for CRC prediction. The XGBoost algorithm demonstrated the highest performance, achieving an average area under the curve (AUC) of 0.90 on the test and 0.91 on the validation datasets. Our results highlight the utility of CRCpred in predicting CRC and healthy status using gut bacterial species relative abundance profile. CRCpred is publicly available at https://metabiosys.iiserb.ac.in/crcpred.