69 Background: Colorectal cancer (CRC) remains a leading cancer despite current screening modalities. Precancerous lesions, or Advanced Adenomas (AA), commonly precede invasive cancer development by years. Newer technologies use circulating tumor DNA and/or proteins for CRC detection but have not been able to effectively detect AA. Aberrant protein glycosylation is associated with (pre-)malignant lesions. To detect glycoproteome profiles associated with the occurrence of AA, we studied serum glycoproteins in AA/CRC. Methods: A novel platform combining liquid-chromatography/mass-spectrometry (LC-MS) and artificial-intelligence (AI)-powered data processing allowing high resolution, high throughput glycoproteomic profiling was used to identify glycoprotein biomarkers in peripheral blood. Samples were sourced from biorepositories and included patients diagnosed with CRC, AA, ulcerative colitis (UC) and controls. The samples were split into a training (50%) and a hold-out testing set (50%) for the development of a machine learning (ML)-based multivariable predictive model. Statistical analysis was performed on normalized data to identify biomarkers differentiating AAs and different stages of CRC from controls. Results: We studied 563 patient samples: 196 controls (mean age 51.7; 52% female); 32 AA (mean age 68.6; 53% female); 247 CRC (mean age 65.6; 50% female) and 88 UC (mean age 44.1; 47% female). There were 250 differentially abundant (FDR < 0.05) glycopeptides/peptides when comparing CRC and AA samples with healthy and UC controls. A subset was assessed, generating a six (6) biomarker ML classification model. This model was applied to the hold-out test and achieved an overall sensitivity of 91.4% and specificity of 91.8% for predicting AA/CRC versus healthy/UC with an area under the receiver operating characteristic of 0.962. AA and CRC separately were predicted with a sensitivity of 84.4% and 92.8%, respectively, relative to healthy/UC with sensitivities for CRC stage 1/2 and stage 3/4 being 91.2% and 93.2%, respectively). Conclusions: Glycoproteomic serum profiles accurately detect precancerous AA in addition to CRC and offer a new approach to effective CRC screening. We will have completed an interim analysis of a large prospective observational study at the time of the meeting. Clinical trial information: NCT05445570 . [Table: see text]

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e15529 Background: Excluding skin cancers, colorectal cancer is the third most common cancer diagnosed in both men and women in the United States. Colorectal cancer (CRC) affects men and women of all racial and ethnic groups and is most often found in people who are 50 years old or older. To aid diagnosis and improve screening for CRC, this study focuses on identifying glycoprotein biomarkers using blood serum. Methods: Novel methods including liquid-chromatography/mass-spectrometry (LC-MS) with in-house peak integration software PB-Net were used to identify glycoprotein biomarkers by analyzing blood serum. Samples were sourced from different biorepositories including 245 CRC, 38 adenoma and 196 healthy controls. The data were split into 75% training and 25% hold-out test set for multivariable predictions. Statistical analysis was performed on normalized data to identify potential biomarkers differentiating adenoma and different stages of CRC samples from the healthy controls. Results: There were 419 significantly differentially expressed glycopeptides/peptides from comparisons between CRC and adenoma samples against the healthy control samples with an FDR < 0.05. A subset of these biomarkers were assessed, generating a 21-biomarker multivariable classifier model. We observed a test set AUC of 0.926, and the sensitivity for all stages of CRC was 90% (87% early stage, 92% late stage). Notably, sensitivity for adenomas was 79%, a large improvement upon the state of the art in adenoma diagnosis. Conclusions: Identification of these key glycopeptides/peptides in blood serum could prove to be a promising non-invasive diagnostic tool that can help improve screening and aid in early detection of advanced adenomas and CRC.