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Background G-protein-coupled receptor (GPCR) kinases (GRKs) interact with ligand-activated GPCR, causing intracellular phosphorylation and interfering with the intracellular signal transduction associated with the development of cancer. Colorectal cancer (CRC) is a fast-growing disease, and its molecular mechanism involves various regulatory proteins, including kinases. However, the GRK mechanism in CRC has not been explored. Methods We used an integrated computational approach to investigate the potential of GRK family members as targeted proteins in CRC. The GRK expression levels in tumor and normal tissues, colon adenocarcinoma samples, and metastatic colon adenocarcinoma were analyzed using ONCOMINE, GEPIA, and UALCAN, as well as TNM plots. Genetic changes in the GRK family genes were investigated using cBioportal. The prognostic value related to the gene expression of the GRK family was examined using GEPIA and UALCAN. Co-expression analysis of the GRK family was conducted using COXPRESdb. Association analysis of the Gene Ontology, KEGG pathway enrichment, and drug-gene analyses were performed using the over-representation analysis (ORA) in WebGestalt. Results GRK2, GRK3, and GRK5 mRNA levels increased significantly in patients with CRC and metastatic CRC. Genetic changes were detected in patients with CRC, including GRK7 (1.1%), GRK2 (1.7%), GRK4 (2.3%), GRK5 (2.5%), GRK6 (2.5%), GRK3 (2.9%), and GRK1 (4%). CRC patients with low mRNA of GRK7 levels had better disease-free and overall survival than those with high GRK7 levels. Hierarchical clustering analysis revealed significant positive correlations between GRK5 and GRK2 and between GRK2 and GRK6. KEGG pathway enrichment analysis showed that the gene network (GN) regulated several cellular pathways, such as the morphine addiction signaling and chemokine signaling pathways in cancer. The drug-gene association analysis indicated that the GN was associated with several drugs, including reboxetine, pindolol, beta-blocking agents, and protein kinase inhibitors. Conclusion No research has been conducted on the relation of GRK1 and GRK7 to cancer, particularly CRC. In this work, genes GRK2, GRK3, GRK5, and GRK6 were found to be oncogenes in CRC. Although inhibitors against GRK2, GRK5, and GRK6 have previously been developed, further research, particularly preclinical and clinical studies, is needed before these agents may be used to treat CRC.
Background G-protein-coupled receptor (GPCR) kinases (GRKs) interact with ligand-activated GPCR, causing intracellular phosphorylation and interfering with the intracellular signal transduction associated with the development of cancer. Colorectal cancer (CRC) is a fast-growing disease, and its molecular mechanism involves various regulatory proteins, including kinases. However, the GRK mechanism in CRC has not been explored. Methods We used an integrated computational approach to investigate the potential of GRK family members as targeted proteins in CRC. The GRK expression levels in tumor and normal tissues, colon adenocarcinoma samples, and metastatic colon adenocarcinoma were analyzed using ONCOMINE, GEPIA, and UALCAN, as well as TNM plots. Genetic changes in the GRK family genes were investigated using cBioportal. The prognostic value related to the gene expression of the GRK family was examined using GEPIA and UALCAN. Co-expression analysis of the GRK family was conducted using COXPRESdb. Association analysis of the Gene Ontology, KEGG pathway enrichment, and drug-gene analyses were performed using the over-representation analysis (ORA) in WebGestalt. Results GRK2, GRK3, and GRK5 mRNA levels increased significantly in patients with CRC and metastatic CRC. Genetic changes were detected in patients with CRC, including GRK7 (1.1%), GRK2 (1.7%), GRK4 (2.3%), GRK5 (2.5%), GRK6 (2.5%), GRK3 (2.9%), and GRK1 (4%). CRC patients with low mRNA of GRK7 levels had better disease-free and overall survival than those with high GRK7 levels. Hierarchical clustering analysis revealed significant positive correlations between GRK5 and GRK2 and between GRK2 and GRK6. KEGG pathway enrichment analysis showed that the gene network (GN) regulated several cellular pathways, such as the morphine addiction signaling and chemokine signaling pathways in cancer. The drug-gene association analysis indicated that the GN was associated with several drugs, including reboxetine, pindolol, beta-blocking agents, and protein kinase inhibitors. Conclusion No research has been conducted on the relation of GRK1 and GRK7 to cancer, particularly CRC. In this work, genes GRK2, GRK3, GRK5, and GRK6 were found to be oncogenes in CRC. Although inhibitors against GRK2, GRK5, and GRK6 have previously been developed, further research, particularly preclinical and clinical studies, is needed before these agents may be used to treat CRC.
The rapid development of personalized medicine places high demands on the control of drug dose and cellular drug response to provide patients with better curative effects and low side effects. To solve the problem of low detection accuracies of the cell-counting kit-8 (CCK8) method, a detection method based on surface-enhanced Raman spectroscopy (SERS) of cell-secreted proteins was adopted to evaluate the concentration of the anticancer drug cisplatin and the cellular drug response of nasopharyngeal carcinoma. CNE1 and NP69 cell lines were used to evaluate cisplatin response. The results showed that the combination of the SERS spectrum with principal component analysis–linear discriminant analysis could detect the difference in the response of cisplatin with a concentration difference of 1 μg/mL, which considerably exceeded that of CCK8. In addition, the SERS spectral peak intensity of the cell-secreted proteins strongly correlated with the cisplatin concentration. Furthermore, the mass spectrum of the secreted proteins of the nasopharyngeal carcinoma cells was analyzed to verify the results obtained using the SERS spectrum. The results demonstrated that SERS of secreted proteins has great potential for high-precision detection of chemotherapeutic drug response.
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