The goal of this project was to identify comorbidities and genes associated with Colorectal cancer (CRC) – the third most common cancer in the United States and the second leading cause of cancer death. The comorbidities of CRC were studied by designing a novel comorbidity network model based on the State Inpatient Database (SID) for the state of California, the records in which were collected under the Healthcare Cost and Utilization Project (HCUP). Ranked lists of comorbidities and comorbidity networks were created, and the prevalence of comorbidities in different stages of CRC was determined. The comorbidity lists were utilized for text mining of PubMed and DisGeNET in order to extract genes associated with CRC. The results of the comorbidity network analyses indicated which comorbidities of CRC are highly expected. The discovered genes could be used to recruit more individuals who would benefit from genetic consultations. The identified associations between the comorbidities, CRC, and shared genes can have important implications on early discovery, and prognosis of CRC.