PREVECOL, a predictive model for early detection of colorectal cancer and precancerous lesions in liquid biopsy.

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3629 Background: Colorectal cancer (CRC) is the second cause of cancer-related deaths worldwide. Most of these deaths could have been prevented by increasing the effectiveness of CRC screening programs, which exhibit a low participation rate, partly due to the limited available screening options, alongside discomfort associated with the screening procedure (faecal test). Liquid biopsy-based technology offers new alternatives to improve CRC early detection. CRC and advanced adenoma (AA) patients show molecular alterations at different biological levels that can be detected in peripheral blood and used for diagnostic purposes. AMADIX has developed PreveCol, an innovative blood test based on molecular biomarkers and clinical features for early detection of CRC and AA, before the onset of the first symptoms. We present the validation of PreveCol predictive model through a European prospective clinical study involving average-risk population actively engaged in a real CRC screening program. PreveCol has been granted with the Breakthrough Device Designation by the FDA in December 2023. Methods: Samples from two prospective clinical studies were used for training and validation. A case-control study (n= 538 individuals: 173 CRC, 181 AA, 184 Controls; 13 Spanish sites) and a clinical study based on a real CRC screening program (n= 3163 individuals: 78 CRC, 156 AA, 146 HRPL, and 2783 Controls; 9 European sites). PreveCol molecular signature (11 proteins and 10 miRNAs), was determined in plasma samples using RT-qPCR and ELISA/CLIA. Machine learning techniques were used to develop an ensemble algorithm. K-fold cross validation techniques were used in the training to set the hyperparameters for each model. Hyperparameter optimalization was performed to find the best parameters of the grid. Once the algorithm was locked and the clinical cut-off was established in the training set, the signature was validated in the European prospective study sub-cohort. Results: For CRC detection, PreveCol demonstrates an Area Under the ROC curve (AUC) of 92%, with a sensitivity (SS) of 81.8% and specificity (SP) of 86%. Moreover, the model exhibits high sensitivity (above 90%) in identifying CRC in early stages (stages 1 and 2), as well as lesions located in the proximal colon. In addition, the AUC of PreveCol for Advanced Adenomas detection is 86.88%, (SS of 70.8% and SP of 86%), showing that PreveCol presents higher sensitivity compared to other identified tests for detecting precancerous lesions. Conclusions: These findings highlight PreveCol's potential to significantly impact on patient prognosis and survival by facilitating the early detection of CRC and premalignant lesions as well as lesions in critical areas of the colon, thereby contributing to improved screening efficacy and patient outcomes.