前列腺癌预后标志的研究
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摘要
目的探索可以准确预测患者生存状态的基因标志物模型,提高前列腺癌的治疗成功率。方法利用前列腺癌患者的基因表达谱数据和样本临床数据,筛选出与患者生存时间显著相关的基因作为特征来构建预后模型,并对模型预测的准确性进行验证。结果构建了共包含ENSG00000101844,ENSG00000107077及ENSG00000117461 3个分子标记物为组合的预后标志物模型,该预后标志物模型表现出较好的预测性能,可有效提高前列腺癌预后评估的准确性。结论 mRNA预后标志物模型可有效预测患者的生存状态,且具有较高的预测准确性、实用性和稳定性,为分子预后标志物在实际临床中的应用提供了可能性,也为患者在选择合理的治疗方案上,提供更加准确的指导建议,同时为开发用于检测前列腺癌预后效果的医疗器械产品提供理论基础。
Objective To explore a genetic marker model that can accurately predict the patient's survival status and improve the success rate of prostate cancer treatment.Methods Using gene expression profiling data and clinical data of prostate cancer patients, the genes with significant correlation with patient survival time were selected as features to construct a prognostic model, and the accuracy of model prediction was verified.Results A prognostic marker model consisting of three molecular markers including ENSG00000101844, ENSG00000107077 and ENSG00000117461 was constructed. The prognostic marker model showed better predictive performance and could effectively improve the accuracy of prognosis evaluation of prostate cancer.Conclusion The mRNA prognostic marker model can effectively predict the survival status of patients, and has high prediction accuracy, practicability and stability. It provides possibility for the application of molecular prognosis markers in actual clinical practice, and also selects patients. Provide a more accurate guidance on reasonable treatment options, and provide a theoretical basis for the development of medical device products for detecting the prognosis of prostate cancer.
Objective To explore a genetic marker model that can accurately predict the patient's survival status and improve the success rate of prostate cancer treatment.Methods Using gene expression profiling data and clinical data of prostate cancer patients, the genes with significant correlation with patient survival time were selected as features to construct a prognostic model, and the accuracy of model prediction was verified.Results A prognostic marker model consisting of three molecular markers including ENSG00000101844, ENSG00000107077 and ENSG00000117461 was constructed. The prognostic marker model showed better predictive performance and could effectively improve the accuracy of prognosis evaluation of prostate cancer.Conclusion The mRNA prognostic marker model can effectively predict the survival status of patients, and has high prediction accuracy, practicability and stability. It provides possibility for the application of molecular prognosis markers in actual clinical practice, and also selects patients. Provide a more accurate guidance on reasonable treatment options, and provide a theoretical basis for the development of medical device products for detecting the prognosis of prostate cancer.
引文
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[17]Cao G,Dong W,Meng X,et al.Mir-511 inhibits growth and metastasis of human hepatocellular carcinoma cells by targeting pik3r3[J].Tumour Biol,2015,36(6):4453-4459.
[2]Rebecca L,Siegel MPH,Kimberly D,et al.Cancer statistics,2018[J].CA,2018,68(1):7-30.
[3]Bray F,Ferlay J,Soerjomataram I,et al.Global cancer statistics2018:Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J].CA,2018,68(1):394-424.
[4]Chen W.Cancer statistics:Updated cancer burden in china[J].Chin J Cancer Res,2015,27(1):1.
[5]Biddle A,Mackenzie IC.Cancer stem cells and emt in carcinoma[J].Cancer Metastasis Rev,2012.
[6]Fan YL,Zheng M,Tang YL,et al.A new perspective of vasculogenic mimicry:Emt and cancer stem cells(review)[J].Oncol Lett,2013,6(5):1174-1180.
[7]Brabletz T.Emt and met in metastasis:Where are the cancer stem cells?[J].Cancer Cell,2012,22(6):699-701.
[8]Yamamoto S,Tateishi K,Kudo Y,et al.Histone demethylase kdm4c regulates sphere formation by mediating the cross talk between wnt and notch pathways in colonic cancer cells[J].Carcinogenesis,2013,34(10):2380-2388.
[9]Zhang L,Huang J,Yang N,et al.Integrative genomic analysis of phosphatidylinositol 3'-kinase family identifies pik3r3 as a potential therapeutic target in epithelial ovarian cancer[J].Can JComp Med,2007,13(18):5314-5321.
[10]Soroceanu L,Kharbanda S,Chen R,et al.Identification of igf2signaling through phosphoinositide-3-kinase regulatory subunit3 as a growth-promoting axis in glioblastoma[J].Proc Natl Acad Sci USA,2007,104(9):3466-3471.
[11]Pradhan MP,Desai A,Palakal MJ.Systems biology approach to stage-wise characterization of epigenetic genes in lung adenocarcinoma[J].BMC Systems Biology,2013(7):141.
[12]Wang G,Deng Y,Cao X,et al.Blocking p55pik signaling inhibits proliferation and induces differentiation of leukemia cells[J].Cell Death and Differentiation,2012,19(11):1870-1879.
[13]Niemeyer BF,Parrish JK,Spoelstra NS,et al.Variable expression of pik3r3 and pten in ewing sarcoma impacts oncogenic phenotypes[J].PloS One,2015,10(1):e0116895.
[14]Klahan S,Wu MS,Hsi E,et al.Computational analysis of mrna expression profiles identifies the itg family and pik3r3 as crucial genes for regulating triple negative breast cancer cell migration[J].Bio Med Research International,2014(2014):536591.
[15]Yu T,Li J,Yan M,et al.Microrna-193a-3p and-5p suppress the metastasis of human non-small-cell lung cancer by downregulating the erbb4/pik3r3/mtor/s6k2 signaling pathway[J].Oncogene,2015,34(4):413-423.
[16]Wang G,Yang X,Li C,et al.Pik3r3 induces epithelial-tomesenchymal transition and promotes metastasis in colorectal cancer[J].Molecular Cancer the Rapeutics,2014,13(7):1837-1847.
[17]Cao G,Dong W,Meng X,et al.Mir-511 inhibits growth and metastasis of human hepatocellular carcinoma cells by targeting pik3r3[J].Tumour Biol,2015,36(6):4453-4459.