CILP2 is a potential biomarker for the prediction and therapeutic target of peritoneal metastases in colorectal cancer
Peritoneal metastases (PM) in colorectal cancer (CRC) is associated with a dismal prognosis. Identifying and exploiting new biomarkers, signatures, and molecular targets for personalised interventions in the treatment of PM in CRC is imperative. We conducted transcriptomic profiling using RNA-seq da...
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Veröffentlicht in: | Scientific reports 2024-05, Vol.14 (1), p.12487-10, Article 12487 |
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Zusammenfassung: | Peritoneal metastases (PM) in colorectal cancer (CRC) is associated with a dismal prognosis. Identifying and exploiting new biomarkers, signatures, and molecular targets for personalised interventions in the treatment of PM in CRC is imperative. We conducted transcriptomic profiling using RNA-seq data generated from the primary tissues of 19 CRC patients with PM. Using our dataset established in a previous study, we identified 1422 differentially expressed genes compared to non-metastatic CRC. The profiling demonstrated no differential expression in liver and lung metastatic CRC. We selected 12 genes based on stringent criteria and evaluated their expression patterns in a validation cohort of 32 PM patients and 84 without PM using real-time reverse transcription-polymerase chain reaction. We selected cartilage intermediate layer protein 2 (CILP2) because of high mRNA expression in PM patients in our validation cohort and its association with a poor prognosis in The Cancer Genome Atlas. Kaplan–Meier survival analysis in our validation cohort demonstrated that CRC patients with high CILP2 expression had significantly poor survival outcomes. Knockdown of CILP2 significantly reduced the proliferation, colony-forming ability, invasiveness, and migratory capacity and downregulated the expression of molecules related to epithelial-mesenchymal transition in HCT116 cells. In an in vivo peritoneal dissemination mouse knockdown of CILP2 also inhibited CRC growth. Therefore, CILP2 is a promising biomarker for the prediction and treatment of PM in CRC. |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-024-63366-4 |