Predicting metachronous liver metastasis from colorectal cancer using serum proteomic fingerprinting

Abstract

Background: There are currently no accurate predictive markers of metachronous liver metastasis (MLM) from colorectal cancer.

Methods: Magnetic bead-based fractionation coupled with mass spectrometry analysis was used to compare serum samples from 64 patients with MLM and 64 without recurrence or metastasis for at least 3 y after radical colorectal surgery (NM). A total of 40 MLM and 40 NM serum samples were randomly selected to build a decision tree, and the remainder were tested as blinded samples. Selected peptides were identified.

Results: The patients in the two groups were matched for gender, age, tumor location, TNM staging, and histologic differentiation grade. Preoperative serum carcinoembryonic antigen retained no independent power to predict MLM. The decision tree model with eight proteomic features (m/z 3315, 6637, 1207, 1466, 4167, 4210, 2660, and 4186) correctly classified 33 of 40 NM sera (82.5%) and 32 of 40 MLM sera (80%) in the training set and 19 of 24 NM sera (79.2%) and 17 of 24 MLM sera (70.8%) in the test set. The peptides were identified as fragments of alpha-fetoprotein, complement C4-A, fibrinogen alpha, eukaryotic peptide chain release factor GTP-binding subunit ERF3B, and angiotensinogen.

Conclusions: In patients matched for gender, age, tumor location, TNM staging, and histologic differentiation grade, preoperative carcinoembryonic antigen retained no independent power to predict MLM. The decision tree model of eight proteomic features demonstrated promising value for predicting MLM in patients who underwent radical resection of colorectal cancer.

Keywords: Metachronous liver metastasis; Proteomics; Serum proteomic fingerprinting.