Abstract

630 Background: Although overall incidence of colorectal cancer is declining, the incidence for young patients (age < 50) with colon cancer is increasing. Reasons for this rise are unclear. Understanding clinical and molecular differences between younger and older cohorts can help guide both patient education strategies and future research into the mechanisms of this phenomenon. Methods: A retrospective analysis of patients diagnosed with colon cancer between 2008 and 2015 who underwent molecular tumor profiling via next-gen sequencing of 26 commonly mutated genes at the University of Colorado. Data collected by chart review includes demographic, pathologic, treatment course, and outcomes. Age group cutoffs for data analysis were set at < 50, 50-65, and > 65 based on screening guidelines and average age of diagnosis Results: We evaluated a total of 242 patients, stage I (n = 1), stage II (n = 65), stage III (n = 68), stage IV (n = 105). Mean age was 59.5 (range 27 to 89). A higher percentage of younger patients were non-smokers (77% of youngest cohort vs 46% of oldest cohort, p < 0.001) and had a non-significant trend towards male gender (youngest cohort 63.8% male, oldest cohort 43.4% male, p = 0.065). Younger patients had similar body mass index (BMI) compared to older patients (BMI 27 vs 25.7, p = 0.35). Younger patients had higher rates of rectal cancer (42% vs 21%, p = 0.01) and lower rates of proximal/right sided colon cancer (20% vs 46.5%, p = 0.014). Younger patients also had lower rates of MSI-H tumors (8% vs 14%, p = 0.01). Finally, younger patients had significantly lower rates of APC (43.1% vs 69.3%, p = 0.009) and BRAF (3.5% vs 19.7%, p = 0.004) mutations. Conclusions: Younger patients ( < 50 years old) with colorectal cancer had lower rates of tobacco use and no difference in obesity rates compared to older patients. In addition, although APC and BRAF mutations were lower in younger patients, there were no mutations that were more prevalent in the young cohort. Therefore, further research into lifestyle factors (specific diet/exercise patterns) or alternative molecular mechanisms are needed.

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