Brief Summary: Survivors of early-onset colorectal cancer (diagnosed before age 50) may experience colorectal cancer recurrence several years after curative-intent treatments, but clinical guidelines provide unclear guidance on endoscopic surveillance. This study aims to predict recurrence-free survival and overall survival, in survivors of early-onset colorectal cancer, using a tumor-based molecular assay based on microRNA (ribonucleic acid)

Detailed Description: Colorectal cancer (CRC) once predominantly affected older individuals, but in recent years has witnessed a progressive increase in incidence among young adults. Once rare, early-onset colorectal cancer (EOCRC, that is, a CRC diagnosed before the age of 50) now constitutes 10-15% of all newly diagnosed CRC cases and it stands as the first cause of cancer-related death in young men in the US and the second for young women. In the wake of the increasing incidence, the growing population of EOCRC survivors introduces distinctive clinical challenges. Patients with EOCRC are hypothesized to possess a more biologically active colorectum, susceptible to malignant transformation both earlier in life and later after primary cancer. Indeed, EOCRC survivors encounter an elevated risk of disease recurrence, a risk that may manifest years after primary treatment. These considerations have prompted a trend toward offering more aggressive therapy or endoscopy surveillance, a practice however not substantiated by evidence yet. Scientific societies have also adopted a cautious stance, recognizing the elevated risk while acknowledging the absence of evidence to substantiate an intensified surveillance protocol, which might constitute overtreatment. In this research effort, the investigators will leverage machine learning to predict recurrence-free survival (RFS) and overall survival (OS) in patients cured of EOCRC. The research plan will employ three phases: 1. After a systematic discovery phase, based on small RNA sequencing, the investigators will identify a panel of candidate biomarkers. 2. The investigators will then develop an assay based on reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and train a machine-learning model to predict recurrence-free and overall survival outcomes 3. The investigators will independently validate the assay. This assay is provisionally termed "ENCORE" (Early oNset COlorectal cancer REcurrence) and will be tested for recurrence-free and overall survival outcomes up to ten years after treatment. At the end of this study, this assay will have been developed and validated to help clinical decision-making by predicting both recurrence-free and overall survival in EOCRC survivors.