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Plasma Proteomics of Colorectal Cancer Based on Data-Independent Acquisition.

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Journal of proteome research 📖 저널 OA 35.6% 2026 Vol.25(1) p. 317-328
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Zhang Q, Zhu W, Wei L, Shen J, Li M, Ji J, Wang Q

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Colorectal cancer (CRC) is an aggressive malignant tumor of the digestive system that poses a serious threat to human health.

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APA Zhang Q, Zhu W, et al. (2026). Plasma Proteomics of Colorectal Cancer Based on Data-Independent Acquisition.. Journal of proteome research, 25(1), 317-328. https://doi.org/10.1021/acs.jproteome.5c00651
MLA Zhang Q, et al.. "Plasma Proteomics of Colorectal Cancer Based on Data-Independent Acquisition.." Journal of proteome research, vol. 25, no. 1, 2026, pp. 317-328.
PMID 41329965

Abstract

Colorectal cancer (CRC) is an aggressive malignant tumor of the digestive system that poses a serious threat to human health. Therefore, there is an urgent need to discover early diagnostic markers and effective therapeutic targets for CRC. In this study, data independent acquisition (DIA) mass spectrometry quantitative technology combined with bioinformatics analysis was used to carry out personalized quantitative proteomics research on abundant protein depletion plasma samples from 48 CRC patients at different TNM stages and healthy individuals. A total of 1089 Protein Groups were identified. By comparing the plasma protein expression profiles between CRC patients and healthy individuals, differentially expressed proteins (DEPs) CRP, FABP1, FABP4 and OSTP with significant changes were screened out, and GO functional, KEGG pathway, and GSEA enrichment analysis were performed. Mfuzz clustering analysis categorized the DEPs in CRC plasma into six expression patterns. Among them, the OSTP protein level in proteomics data and the mRNA level of the gene in TCGA database both showed an upward trend with the progression of the disease, suggesting that it may serve as a diagnostic and prognostic marker in plasma to reflect the disease progression of CRC patients. ROC analysis showed robust predictive performance, and PRM validation cohort correlated well with DIA results, providing potential insights for CRC research.

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