Early detection of cancer combined with effective treatment improves survival and quality of life. Freenome is using a type of artificial intelligence, called machine learning, to identify patterns of cell-free biomarkers in the blood to detect cancer early. The purpose of this study is to develop and validate a blood-based assay for the early detection of colorectal cancer. The study will collect blood and stool samples from healthy patients undergoing routine screening colonoscopy and from patients recently diagnosed with colorectal cancer or advanced adenomas. A blood-based test for colorectal cancer and pre-cancerous lesions could offer an accurate, convenient, and patient-friendly screening option for current and future generations, and, in doing so, could save and improve lives by increasing adherence and early detection.~Freenome is looking for three types of patients in this study:~Cohort A:~People ages 50-84 who have been recently diagnosed with (or strong clinical suspicion for) colorectal cancer or advanced adenoma. Blood samples must be collected before any cancer treatment has been initiated.~Cohort B:~People ages 50-84 undergoing routine screening colonoscopies for colorectal cancer as part of their regular medical check-ups. Blood samples must be collected before bowel preparation for the colonoscopy.~Cohort C:~People 18 years or older who have been recently diagnosed with (or strong clinical suspicion for) colorectal cancer or advanced adenoma. Blood samples must be collected before any cancer treatment has been initiated.
Freenome is using a type of artificial intelligence, called machine learning, to identify patterns of cell-free biomarkers in blood to detect cancer early. The purpose of this study is to develop and validate a blood-based assay to detect colorectal cancer by collecting blood and stool samples from healthy patients undergoing routine screening colonoscopy and from patients recently diagnosed with colorectal cancer or advanced adenomas.