Molecular characterization of colorectal adenoma and colorectal cancer via integrated genomic transcriptomic analysis

IntroductionColorectal adenoma can develop into colorectal cancer. Determining the risk of tumorigenesis in colorectal adenoma would be critical for avoiding the development of colorectal cancer; however, genomic features that could help predict the risk of tumorigenesis remain uncertain. MethodsIn this work, DNA and RNA parallel capture sequencing data covering 519 genes from colorectal adenoma and colorectal cancer samples were collected. The somatic mutation profiles were obtained from DNA sequencing data, and the expression profiles were obtained from RNA sequencing data. ResultsDespite some similarities between the adenoma samples and the cancer samples, different mutation frequencies, co-occurrences, and mutually exclusive patterns were detected in the mutation profiles of patients with colorectal adenoma and colorectal cancer. Differentially expressed genes were also detected between the two patient groups using RNA sequencing. Finally, two random forest classification models were built, one based on mutation profiles and one based on expression profiles. The models distinguished adenoma and cancer samples with accuracy levels of 81.48% and 100.00%, respectively, showing the potential of the 519-gene panel for monitoring adenoma patients in clinical practice. ConclusionThis study revealed molecular characteristics and correlations between colorectal adenoma and colorectal cancer, and it demonstrated that the 519-gene panel may be used for early monitoring of the progression of colorectal adenoma to cancer.

Automated summary

This study collected DNA and RNA sequencing data from colorectal adenoma and colorectal cancer samples, and found different mutation frequencies and exclusive patterns in the mutation profiles between adenoma and cancer patients, as well as differentially expressed genes. Two random forest classification models were built based on mutation profiles and expression profiles, and achieved high accuracy in distinguishing adenoma and cancer samples, suggesting the potential of the 519-gene panel for monitoring adenoma patients in clinical practice.