IDDF2024-ABS-0336 Identification of plasma protein biomarkers for colorectal cancer diagnosis and prognosis

<h3>Background</h3> The incidence and mortality of colorectal cancer (CRC) have been steadily rising in many countries. There is an urgent need to identify convenient, reliable biomarkers for CRC early diagnosis and precise prognostic prediction. <h3>Methods</h3> Untargeted plasma proteomics profiling by liquid chromatography coupled to tandem mass spectrometry was performed among a cohort of 321 participants as a discovery set (i.e., 107 CRC cases, 107 advanced adenomas (AA) cases, and 107 healthy controls (HC)), as well as a cohort of 353 participants as a validation set (i.e., 136 CRC, 81 AA, and 136 HC) (IDDF2024-ABS-0336 Figure 1). Random forest algorithm and the least absolute shrinkage and selection operator regression were adopted for the selection of protein biomarkers and the construction of diagnostic and prognostic models. <h3>Results</h3> We identified 133 significantly altered proteins in CRC vs. HC, 15 in AA vs. HC, and 32 in CRC vs. AA. A model of 8 plasma proteins (COMP, C1QTNF3, H4C1, LRG1, PGM1, PKP1, PTPRJ, and TEK) showed great performance in discriminating CRC from HC, with an AUC of 0.932 (95% confidence interval [CI]: 0.857-0.989) in the validation set. A model of 6 proteins (CNTN4, COMP, IGFBP5, LDHA, PGAM1, and SPP1) showed the optimal ability to discriminate AA from HC, with an AUC of 0.816 (95% CI: 0.689-0.932) (IDDF2024-ABS-0336 Figure 2). Moreover, we established a prognostic model of 8 proteins (ANKRD26, APOA4, C9, FCGRT, LGALS1, PDGFRB, PGD, and PON1), showing an AUC of 0.705 for 3-year and 0.690 for 5-year disease-free survival in the validation set of CRC patients (IDDF2024-ABS-0336 Figure 3). <h3>Conclusions</h3> The identified profile of protein biomarkers may contribute to the development of powerful blood-based tests for CRC early detection and prognostic monitoring, ultimately enabling precision interventions and improved patient outcomes.