Prediction of docetaxel-sensitive prostate cancer based on metabolic subtypes and biomarkers
10.3760/cma.j.cn121382-20240807-00612
- VernacularTitle:基于代谢亚型和生物标志物预测多西他赛敏感性前列腺癌
- Author:
Zheng ZHANG
1
;
Guixin WANG
;
Baoshuai ZHANG
;
Shimiao ZHU
Author Information
1. 天津医科大学第二医院泌尿外科，天津 300211
- Keywords:
Prostate cancer;
Tumor metabolism;
Docetaxel;
Prognostic model;
Biomarkers
- From:
International Journal of Biomedical Engineering
2024;47(6):600-608
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To predict the docetaxel-sensitive prostate cancer based on metabolic subtypes and biomarkers.Methods:Gene expression profiles and clinical data of prostate cancer patients were downloaded from the cancer genome atlas (TCGA) and GEO databases. Single-factor Cox regression analysis was used to screen for metabolic-related genes in prostate cancer, and a prognostic model was constructed using the glmnet package. Metabolic subtypes were classified using the ConsensusClusterPlus package. Weighted gene co-expression network was used to analyze the biomarkers of docetaxel-sensitive prostate cancer. Ribonucleotide reductase M2 ( RRM2) gene was silenced by transfection of blank vector and short hairpin RNA (shRNA) of RRM2 to inhibit its expression. The relative expression level of RRM2 protein in docetaxel-resistant PC-3-DR cells was detected by Western blotting. The effects of RRM2 on the number of colonies and the number of cells migrating to the lower chamber of PC-3-DR cells were determined by colony formation assay and cell migration assay. Results:A total of 8 genes were screened, including synaptojanin 1 ( SYNJ1), RRM2, macrophage migration inhibitory factor ( MIF), fucose-1-phosphate guanyltransferase ( FPGT), arginase 1 ( ARG1), adenosylmethionine decarboxylase 1 ( AMD1), aldo-keto reductase family 1, member B10 ( AKR1B10), and acyl-CoA synthetase short chain family member 2 ( ACSS2). A model for predicting the prognosis of prostate cancer patients was constructed, and the area under the curve for predicting 3-year disease-free survival of prostate cancer was 0.70. Three different metabolic subtypes were identified. The disease-free survival of C3 subtype was shorter ( P=0.018), and the half maximal inhibitory concentration (IC 50) of docetaxel in the C3 subtype was lower than that in the C1 and C2 subtypes (all P<0.01). The genes and biomarkers associated with docetaxel resistance were acyl-CoA oxidase 1 ( ACOX1), isocitrate dehydrogenase 1 ( IDH1), glutathione S-transferase kappa 1 ( GSTK1), sterol carrier protein 2 ( SCP2), and solute carrier family 27 member 2 ( SLC27A2). In PC-3-DR cells, the relative expression levels of RRM2 and Ki67 proteins in the transfection group (1.77±0.15, 0.52±0.08) were lower than those in the control group (3.10±0.26, 1.18±0.13), and the differences were statistically significant (all P<0.05). The number of colonies and the number of cells migrating to the lower chamber in the transfection group [(56.00±3.61, 81.67±15.82) unit] were lower than those in the control group [(151.70±7.37, 320.00±35.37) unit], and the differences were statistically significant (all P<0.05). Conclusions:The multi-gene-based prognostic model can successfully predict disease-free survival of prostate cancer patients. Advanced prostate cancer patients with C3 subtype based on metabolic genes are suitable for docetaxel-based chemotherapy.
