Plasma proteomic characterization of colorectal cancer patients with FOLFOX chemotherapy by integrated proteomics technology

Wang，Xi1,2,3; Zhang，Keren3; He，Wan1,2; Zhang，Luobin3; Gao，Biwei1; Tian，Ruijun3; Xu，Ruilian1,2

2024-12-01

10.1186/s12014-024-09454-z

Clinical Proteomics   影响因子和分区

1542-6416

1559-0275

Background: Colorectal Cancer (CRC) is a prevalent form of cancer, and the effectiveness of the main postoperative chemotherapy treatment, FOLFOX, varies among patients. In this study, we aimed to identify potential biomarkers for predicting the prognosis of CRC patients treated with FOLFOX through plasma proteomic characterization. Methods: Using a fully integrated sample preparation technology SISPROT-based proteomics workflow, we achieved deep proteome coverage and trained a machine learning model from a discovery cohort of 90 CRC patients to differentiate FOLFOX-sensitive and FOLFOX-resistant patients. The model was then validated by targeted proteomics on an independent test cohort of 26 patients. Results: We achieved deep proteome coverage of 831 protein groups in total and 536 protein groups in average for non-depleted plasma from CRC patients by using a Orbitrap Exploris 240 with moderate sensitivity. Our results revealed distinct molecular changes in FOLFOX-sensitive and FOLFOX-resistant patients. We confidently identified known prognostic biomarkers for colorectal cancer, such as S100A4, LGALS1, and FABP5. The classifier based on the biomarker panel demonstrated a promised AUC value of 0.908 with 93% accuracy. Additionally, we established a protein panel to predict FOLFOX effectiveness, and several proteins within the panel were validated using targeted proteomic methods. Conclusions: Our study sheds light on the pathways affected in CRC patients treated with FOLFOX chemotherapy and identifies potential biomarkers that could be valuable for prognosis prediction. Our findings showed the potential of mass spectrometry-based proteomics and machine learning as an unbiased and systematic approach for discovering biomarkers in CRC.

Colorectal cancer Machine learning MS-based proteomics Plasma proteome PRM validation

SCI

英语

第一 ; 通讯

2-s2.0-85189884702

Scopus

1.The Second Clinical Medical College of Jinan University,the First Affiliated Hospital of Southern University of Science and Technology,Shenzhen People’s Hospital,Shenzhen,518020,China
2.The First Affiliated Hospital,Jinan University,Guangzhou,510632,China
3.Department of Chemistry and Research Center for Chemical Biology and Omics Analysis,School of Science,Southern University of Science and Technology,Shenzhen,518055,China

Wang，Xi,Zhang，Keren,He，Wan,et al. Plasma proteomic characterization of colorectal cancer patients with FOLFOX chemotherapy by integrated proteomics technology[J]. Clinical Proteomics,2024,21(1).

Wang，Xi.,Zhang，Keren.,He，Wan.,Zhang，Luobin.,Gao，Biwei.,...&Xu，Ruilian.(2024).Plasma proteomic characterization of colorectal cancer patients with FOLFOX chemotherapy by integrated proteomics technology.Clinical Proteomics,21(1).

Wang，Xi,et al."Plasma proteomic characterization of colorectal cancer patients with FOLFOX chemotherapy by integrated proteomics technology".Clinical Proteomics 21.1(2024).