国际肿瘤学杂志››2020,Vol. 47››Issue (5): 293-296.doi:10.3760/cma.j.cn371439-20200123-00021
收稿日期:
2020-01-23修回日期:
2020-03-23出版日期:
2020-05-08发布日期:
2020-07-02通讯作者:
于韬 E-mail:yutao@cancerhosp-ln-cmu.comReceived:
2020-01-23Revised:
2020-03-23Online:
2020-05-08Published:
2020-07-02Contact:
Yu Tao E-mail:yutao@cancerhosp-ln-cmu.com摘要:
胶质瘤是中枢神经系统最常见的原发性肿瘤,尽管临床选择多模式治疗,但大多数患者的总体预后很差,特别是胶质母细胞瘤,这与胶质瘤的生物学特性有关。而基因的改变已被证实与胶质母细胞瘤的发生密切相关。不同的基因表达对胶质瘤的治疗和预后具有指导作用,深入了解胶质瘤背后的基因与疾病的关系,将有助于探索潜在的个体化靶向治疗方法。
赵聪选, 于韬. 胶质瘤相关基因的挖掘及预测[J]. 国际肿瘤学杂志, 2020, 47(5): 293-296.
Zhao Congxuan, Yu Tao. Mining and prediction of glioma-related genes[J]. Journal of International Oncology, 2020, 47(5): 293-296.
[1] | Ferlay J, Parkin DM, Steliarova-Foucher E. Estimates of cancer incidence and mortality in Europe in 2008[J]. Eur J Cancer, 2010,46(4):765-781. DOI: 10.1016/j.ejca.2009.12.014. doi:10.1016/j.ejca.2009.12.014 |
[2] | Porter KR, Mccarthy BJ, Freels S, et al. Prevalence estimates for primary brain tumors in the United States by age, gender, behavior, and histology[J]. Neuro Oncol, 2010,12(6):520-527. DOI: 10.1093/neuonc/nop066. doi:10.1093/neuonc/nop066pmid:20511189 |
[3] | Prados MD, Byron SA, Tran NL, et al. Toward precision medicine in glioblastoma: the promise and the challenges[J]. Neuro Oncol, 2015,17(8):1051-1063. DOI: 10.1093/neuonc/nov031. doi:10.1093/neuonc/nov031pmid:25934816 |
[4] | Mu N, Gu J, Liu N, et al. PRL-3 is a potential glioblastoma prognostic marker and promotes glioblastoma progression by enhancing MMP7 through the ERK and JNK pathways[J]. Theranostics, 2018,8(6):1527-1539. DOI: 10.7150/thno.22699. doi:10.7150/thno.22699pmid:29556339 |
[5] | Koshkin PA, Chistiakov DA, Nikitin AG, et al. Analysis of expression of microRNAs and genes involved in the control of key signaling mechanisms that support or inhibit development of brain tumors of different grades[J]. Clin Chim Acta, 2014,20(430):55-62. DOI: 10.1016/j.cca.2014.01.001. |
[6] | 季玉陈, 李妍, 胡京霞, 等. 胶质瘤组织中microRNA-200a的表达及其与患者预后的关系[J]. 郑州大学学报(医学版), 2016,51(1):105-108. |
[7] | Tini P, Pastina P, Nardone V, et al. The combined EGFR protein expression analysis refines the prognostic value of the MGMT promoter methylation status in glioblastoma[J]. Clin Neurol Neurosurg, 2016,11(149):15-21. DOI: 10.1016/j.clineuro.2016.07.023. |
[8] | Naoum GE, Zhu ZB, Buchsbaum DJ, et al. Survivin a radiogenetic promoter for glioblastoma viral gene therapy independently from CArG mojpgs[J]. Clin Transl Med, 2017,6(1):11. DOI: 10.1186/s40169-017-0140-y. doi:10.1186/s40169-017-0140-ypmid:28251571 |
[9] | Bainbridge MN, Armstrong GN, Gramatges MM, et al. Germline mutations in shelterin complex genes are associated with familial glioma[J]. J Natl Cancer Inst, 2015,107(1):384. DOI: 10.1093/jnci/dju384. doi:10.1093/jnci/dju384pmid:25482530 |
[10] | Bruzek AK, Zureick AH, McKeever PE, et al. Molecular characte-rization reveals NF1 deletions and FGFR1-activating mutations in a pediatric spinal oligodendroglioma[J]. Pediatr Blood Cancer, 2017,64(6): 10.1002/pbc.26346. DOI: 10.1002/pbc.26346. doi:10.1002/pbc.26374pmid:27905689 |
[11] | Stathias V, Pastori C, Griffin TZ, et al. Idenjpgying glioblastoma gene networks based on hypergeometric test analysis[J]. PLoS One, 2014,9(12):e115842. DOI: 10.1371/journal.pone.0115842. doi:10.1371/journal.pone.0115842pmid:25551752 |
[12] | Rosenberg S, Verreault M, Schmitt C, et al. Multi-omics analysis of primary glioblastoma cell lines shows recapitulation of pivotal mole-cular features of parental tumors[J]. Neuro Oncol, 2017,19(2):219-228. DOI: 10.1093/neuonc/now160. doi:10.1093/neuonc/now160pmid:27571888 |
[13] | Li Y, Xu J, Chen H, et al. Comprehensive analysis of the functional microRNA-mRNA regulatory network idenjpgies miRNA signatures associated with glioma malignant progression[J]. Nucleic Acids Res, 2013,41(22):e203. DOI: 10.1093/nar/gkt1054. doi:10.1093/nar/gkt1054pmid:24194606 |
[14] | 孙红梅, 常志强, 张淑娟, 等. 融合基因关系网和功能预测恶性胶质瘤基因方法研究[J]. 现代生物医学进展, 2014,14(13):2549-2553. DOI: 10.13241/j.cnki.pmb.2014.13.041. |
[15] | Bolouri H, Zhao LP, Holland EC. Big data visualization idenjpgies the multidimensional molecular landscape of human gliomas[J]. Proc Natl Acad Sci U S A, 2016,113(19):5394-5399. DOI: 10.1073/pnas.1601591113. doi:10.1073/pnas.1601591113pmid:27118839 |
[16] | Durmaz A, Henderson TAD, Brubaker D, et al. Frequent subgraph mining of personalized signaling pathway networks groups patients with frequently dysregulated disease pathways and predicts prognosis[J]. Pac Symp Biocomput, 2017,22:402-413. DOI: 10.1142/9789813207813_0038. doi:10.1142/9789813207813_0038pmid:27896993 |
[17] | ̆Zitnik M, Zupan B. Gene network inference by fusing data from diverse distributions[J]. Bioinformatics, 2015,31(12):i230-i239. DOI: 10.1093/bioinformatics/btv258. doi:10.1093/bioinformatics/btv258pmid:26072487 |
[18] | Ceccarelli M, Barthel FP, Malta TM, et al. Molecular profiling reveals biologically discrete subsets and pathways of progression in diffuse glioma[J]. Cell, 2016,164(3):550-563. DOI: 10.1016/j.cell.2015.12.028. doi:10.1016/j.cell.2015.12.028pmid:26824661 |
[19] | 韦博. 基于芯片数据和文本挖掘的胶质瘤生物信息学分析[D]. 吉林: 吉林大学, 2015. |
[20] | 陈玉升, 郭杨, 申汉威, 等. 胶质瘤差异表达基因筛选、功能富集和相关信号通路生物信息学分析[J]. 中华医学杂志, 2019,99(29):2311-2314. DOI: 10.3760/cma.j.issn.0376-2491.2019.29.013. |
[21] | Diehn M, Nardini C, Wang DS, et al. Idenjpgication of noninvasive imaging surrogates for brain tumor gene-expression modules[J]. Proc Natl Acad Sci U S A, 2008,105(13):5213-5218. DOI: 10.1073/pnas.0801279105. doi:10.1073/pnas.0801279105pmid:18362333 |
[22] | Jamshidi N, Diehn M, Bredel M, et al. Illuminating radiogenomic characteristics of glioblastoma muljpgorme through integration of MR imaging, messenger RNA expression, and DNA copy number variation[J]. Radiology, 2014,270(1):1-2. DOI: 10.1148/radiol.13130078. doi:10.1148/radiol.13132294pmid:24056404 |
[23] | Kong DS, Kim J, Lee IH, et al. Integrative radiogenomic analysis for multicentric radiophenotype in glioblastoma[J]. Oncotarget, 2016,7(10):11526-11538. DOI: 10.18632/oncotarget.7115. doi:10.18632/oncotarget.7115pmid:26863628 |
[24] | Gevaert O, Mitchell LA, Achrol AS, et al. Glioblastoma muljpgorme: exploratory radiogenomic analysis by using quantitative image features[J]. Radiology, 2014,273(1):168-174. DOI: 10.1148/radiol.14131731. doi:10.1148/radiol.14131731 |
[25] | Pinker K, Shitano F, Sala E, et al. Background, current role, and potential applications of radiogenomics[J]. J Magn Reson Imaging, 2018,47(3):604-620. DOI: 10.1002/jmri.25870. doi:10.1002/jmri.25870pmid:29095543 |
[26] | Chai R, Zhang K, Wang K, et al. A novel gene signature based on five glioblastoma stem-like cell relevant genes predicts the survival of primary glioblastoma[J]. J Cancer Res Clin Oncol, 2018,144(3):439-447. DOI: 10.1007/s00432-017-2572-6. doi:10.1007/s00432-017-2572-6pmid:29299749 |
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