精准医疗与伴随诊断专刊 |
|
|
|
|
二代基因测序数据管理和大数据平台在精准医学中的应用 |
武奥申,刘小娜,刘昀赫,刘刚,刘雷() |
复旦大学生物医学研究院 上海 200032 |
|
Application of Second Generation Gene Sequencing Data Management and Big Data Platform in Precision Medicine |
Ao-shen WU,Xiao-na LIU,Yun-he LIU,Gang LIU,Lei LIU() |
Institute of Biological Sciences, Fudan University, Beijing 200032,China |
引用本文:
武奥申,刘小娜,刘昀赫,刘刚,刘雷. 二代基因测序数据管理和大数据平台在精准医学中的应用[J]. 中国生物工程杂志, 2019, 39(2): 101-111.
Ao-shen WU,Xiao-na LIU,Yun-he LIU,Gang LIU,Lei LIU. Application of Second Generation Gene Sequencing Data Management and Big Data Platform in Precision Medicine. China Biotechnology, 2019, 39(2): 101-111.
链接本文:
https://manu60.magtech.com.cn/biotech/CN/10.13523/j.cb.20190212
或
https://manu60.magtech.com.cn/biotech/CN/Y2019/V39/I2/101
|
[1] |
National Research Council ( US). Toward precision medicine: building a knowledge network for biomedical research and a new taxonomy of disease. Washington (DC): National Academies Press. 2011.
|
[2] |
Collins F S, Varmus H . A new initiative on precision medicine. The New England Journal of Medicine, 2015,372(9):793-795.
doi: 10.1056/NEJMp1500523
pmid: 25635347
|
[3] |
杨湘玲, 朱健生, 刘贤云 , 等. 新型无创DNA产前检测在诊断胎儿染色体非整倍体疾病中的应用. 中国产前诊断杂志(电子版), 2013,5(2):15-17.
|
|
Yang X L, Zhu J S, LIU X Y , et al. Impication of noninvasive DNA prenatal diagnosis of chromasomal aneuploidy. Chinese Journal of Prenatal Diagnosis (electronic version), 2013,5(2):15-17.
|
[4] |
Fonda A F, Stoll K, Bernhardt B A . Pre-and post-test genetic counseling for chromosomal and Mendelian disorders. Seminars in Perinatology, 2016,40(1):44-55.
doi: 10.1053/j.semperi.2015.11.007
pmid: 26718445
|
[5] |
Willig L K, Petrikin J E, Smith L D , et al, Whole-genome sequencing for identification of Mendelian disorders in critically ill infants: a retrospective analysis of diagnostic and clinical findings. The Lancet, 2015,3(5):377-387.
doi: 10.1016/S2213-2600(15)00139-3
pmid: 25937001
|
[6] |
Yang Y P, Muzny D M, Reid J G , et al. Clinical whole-exome sequencing for the diagnosis of mendelian disorders. N Engl J Med, 2013,369(16):1502-1511.
doi: 10.1056/NEJMoa1306555
|
[7] |
吴一龙 . 精准癌医学: 走向未来的路. 循证医学, 2015,15(1):1-2.
doi: 10.3969/j.issn.1671-5144.2015.01.001
|
|
Wu Y L . Precision cancer medicine: A way to the future. Journal of Evidence-Based Medicine, 2015,15(1):1-2.
doi: 10.3969/j.issn.1671-5144.2015.01.001
|
[8] |
Tang L D, Xu W R . Challenges and opportunities for pharmaceutical industry in the era of precision medicion. Drugs&Clinic, 2015,4:351-354
|
[9] |
Roychowdhury S, Matthew K, Robinson D R , et al, Personalized oncology through integrative high-throughput sequencing: a pilot study. Science Translational Medicine, 2011, 3(111): 111ra121-111ra121.
|
[10] |
李艳明, 杨亚东, 张昭军 , 等. 精准医学大数据的分析与共享. 中国医学前沿杂志(电子版), 2015,7(6):4-10.
doi: 10.3969/j.issn.1674-7372.2015.06.002
|
|
Li Y M, Yang Y D, Zhang Z J , et al. The share and analyses of big data for precision medicine. Chinese Journal of the Frontiers of Medical Science, 2015,7(6):4-10.
doi: 10.3969/j.issn.1674-7372.2015.06.002
|
[11] |
徐武夷, 杨文 . 乳腺癌治疗进展. 转化医学杂志, 2011,24(1):29-33.
|
|
Xu W Y, Yang W . Progression of breast cancer therapy. Journal of Naval General Hospital, 2011,24(1):29-33.
|
[12] |
Alizadeh A A, Eisen M B, Davis R E , et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature, 2000,403(6769):503-511.
doi: 10.1038/35000501
|
[13] |
Begley C G, Ellis L M . Drug development: Raise standards for preclinical cancer research. Nature, 2012,483(7391):531-533.
doi: 10.1038/483531a
|
[14] |
Shen S, Qu Y C, Zhang J . The application of next generation sequencing on epigenetic study. Hereditas, 2014,36(3):256-275.
doi: 10.3724/SP.J.1005.2014.0256
pmid: 24846966
|
[15] |
Zhang Y, Ng H H, Erdjument-Bromage H , et al. Analysis of the NuRD subunits reveals a histone deacetylase core complex and a connection with DNA methylation. Genes & Development, 1999,13(15):1924-1935.
doi: 10.1101/gad.13.15.1924
pmid: 10444591
|
[16] |
Widschwendter M, Fiegl Heidi, Egle D , et al. Epigenetic stem cell signature in cancer. Nature Genetics, 2007,39(2):157-158.
doi: 10.1038/ng1941
pmid: 17200673
|
[17] |
许力凡, 张记, 田志强 , 等. 表观遗传学与肿瘤干细胞. 遗传, 2013,35(9):1049-1057.
doi: 10.3724/SP.J.1005.2013.01049
|
|
Xu L F, Zhang J, Tian Z Q , et al. Epigenetics in cancer stem cell. Hereditas, 2013,35(9):1049-1057.
doi: 10.3724/SP.J.1005.2013.01049
|
[18] |
Luo J, Jin F . Recent advances in understanding the impact of intestinal microbiota on host behavior. Chinese Science Bulletin, 2014,59(22):2169-2190.
doi: 10.1360/N972014-00120
|
[19] |
盛华芳, 周宏伟 . 微生物组学大数据分析方法、挑战与机遇. 南方医科大学学报, 2015,35(7):931-934.
doi: 10.3969/j.issn.1673-4254.2015.07.01
|
|
Sheng H F, Zhou H W . Methods, challenge and opportunities for big data analyses of microbiome. Journal Southern Medical University, 2015,35(7):931-934.
doi: 10.3969/j.issn.1673-4254.2015.07.01
|
[20] |
支沛轩 , 浅述肿瘤精准医疗的研究进展. 中国实用医药, 2016,11(4):287-288.
doi: 10.14163/j.cnki.11-5547/r.2016.04.216
|
|
Zhi P X . Brief review of progression of cancer precision medicine. China Practical Medicine, 2016,11(4):287-288.
doi: 10.14163/j.cnki.11-5547/r.2016.04.216
|
[21] |
郑广勇, 杨桢, 曹瑞芳 , 等. 宏基因组大数据分析的质量控制流程规范. 大数据, 2018,4(3):3-12.
|
|
Zheng G Y, Yang Z, Cao R F , et al. Quality control of big data analysis for metagenomics. Big Data Research, 2018,4(3):3-12.
|
[22] |
焦怡琳, 王吉春, 张群 , 等. 中国在精准医学领域面临的机遇与挑战. 中国公共卫生管理, 2015,31(5):601-603.
|
|
Jiao Y L, Wang J C, Zhang Q , et al. Opportunities and challenges of China precision medicine. Chinese Journal of Public Health Management, 2015,31(5):601-603.
|
[23] |
郑洁, 李维 . 精准医学的再思考. 医学信息学杂志, 2016,37(1):8-12.
doi: 10.3969/j.issn.1673-6036.2016.01.002
|
|
Zheng J, Li W . Rethinking of precision medicine. Journal of Medical Informatics, 2016,37(1):8-12.
doi: 10.3969/j.issn.1673-6036.2016.01.002
|
[24] |
吴家睿 . 建立在系统生物学基础上的精准医学. 生命科学, 2015,27(5):558-563.
|
|
Wu J R . Precision medicine on system biology. Chinese Bulletin of Life Sciences, 2015,27(5):558-563.
|
[25] |
肖飞 . 从循证医学到精准医学的思考. 中华肾病研究电子杂志, 2014,3(3):123-128.
doi: 10.3877/cma.j.issn.2095-3216.2014.03.002
|
|
Xiao F . A paradigm shift from evidence-based medicine to precision medicine. Chinese Journal of Kidney Disease Invesigation, 2014,3(3):123-128.
doi: 10.3877/cma.j.issn.2095-3216.2014.03.002
|
[26] |
Dong X, Berti-Equille L, Srivastava D . Truth discovery and copying detection in a dynamic world. Proceedings of the VLDB Endowment, 2009,2(1):562-573.
doi: 10.14778/1687627.1687691
|
[27] |
Luxton D D . Recommendations for the ethical use and design of artificial intelligent care providers. Artif Intell Med, 2014,62(1):1-10.
doi: 10.1016/j.artmed.2014.06.004
pmid: 25059820
|
[28] |
Bartgis J, Albright G . Online role-play simulations with emotionally responsive avatars for the early detection of Native youth psychological distress, including depression and suicidal ideation. Am Indian Alsk Native Ment Health Res, 2016,23(2):1-27.
doi: 10.5820/aian.2302.2016.1
pmid: 27115130
|
[29] |
Pouke M, Hakkila J . Elderly healthcare monitoring using an avatar-based 3D virtual environment. Int J Environ Res Public Health, 2013,10(12):7283-7298.
doi: 10.3390/ijerph10127283
pmid: 3881167
|
[30] |
Esteva A, Kuprel Brett, Novoa R A , et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature, 2017,542(7639):115-118.
doi: 10.1038/nature21056
pmid: 28117445
|
[31] |
Gulshan V, Peng L, Coram M , et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA, 2016,316(22):2402-2410.
doi: 10.1001/jama.2016.17216
pmid: 27898976
|
[32] |
Edge S B, Compton C C . The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol, 2010,17(6):1471-1474.
doi: 10.1245/s10434-010-0985-4
|
[33] |
Fanshawe T R, Lynch A G, Ellis I O , et al. Assessing agreement between multiple raters with missing rating information, applied to breast cancer tumour grading. PLoS One, 2008,3(8):e2925.
doi: 10.1371/journal.pone.0002925
pmid: 18698346
|
[34] |
Ertosun M G, Rubin D L . Automated grading of gliomas using deep learning in digital pathology images: a modular approach with ensemble of convolutional neural networks. AMIA Annu Symp Proc, 2015: 1899-1908.
pmid: 26958289
|
[35] |
Cornet G. Robot companions and ethics a pragmatic approach of ethical design. J Int Bioethique, 2013, 24(4): 49- 58, 179-180.
|
[36] |
Larson J A, Johnson M H, Bhayani S B . Application of surgical safety standards to robotic surgery: five principles of ethics for nonmaleficence. J Am Coll Surg, 2014,218(2):290-293.
doi: 10.1016/j.jamcollsurg.2013.11.006
pmid: 24315652
|
[37] |
Somashekhar S P, Sepúlveda M J, Puglielli S , et al. Watson for oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board. Ann Oncol, 2018,29(2):418-423.
doi: 10.1093/annonc/mdx781
pmid: 29324970
|
[38] |
Alanazi H O, Abdullah A H, Qureshi K N . A critical review for developing accurate and dynamic predictive models using machine learning methods in medicine and health care. Journal of Medical Systems, 2017,41(4):1-10.
doi: 10.1007/s10916-016-0650-y
|
[39] |
Crosby J, Peloso G M, Auer P L , et al. Loss-of-function mutations in APOC3, triglycerides, and coronary disease. N Engl J Med, 2014,371(1):22-31.
doi: 10.1056/NEJMoa1307095
pmid: 4180269
|
[40] |
Dewey F E, Gusarova V , O’Dushlaine C,et al. Inactivating variants in angptl4 and risk of coronary artery disease. N Engl J Med, 2016,374(12):1123-1133.
doi: 10.1056/NEJMoa1510926
|
[41] |
Cohen J, Pertsemlidis A , et al.Kotowski I K. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat Genet, 2005,37(2):161-165.
doi: 10.1038/ng1509
pmid: 15654334
|
[42] |
Abifadel M, Varret M, Rabès J P , et al. Mutations in PCSK9 cause autosomal dominant hypercholesterolemia. Nat Genet, 2003,34(2):154-156.
doi: 10.1038/ng1161
pmid: 12730697
|
[43] |
Seidah N G . The PCSK9 revolution and the potential of PCSK9-based therapies to reduce LDL-cholesterol. Glob Cardiol Sci Pract, 2017,1:e201702.
doi: 10.21542/gcsp.2017.2
pmid: 5621713
|
[44] |
Nioi P, Sigurdsson A, Thorleifsson G , et al., Variant ASGR1 associated with a reduced risk of coronary artery disease. N Engl J Med, 2016,374(22):2131-2141.
doi: 10.1056/NEJMoa1508419
pmid: 27192541
|
[45] |
Tybjaerg-Hansen A . The sialylation pathway and coronary artery disease. N Engl J Med, 2016,374(22):2169-2171.
doi: 10.1056/NEJMe1604773
pmid: 27192165
|
[46] |
Lamb J, Crawford E D, Peck D , et al. The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Science, 2006,313(5795):1929-1935.
doi: 10.1126/science.1132939
pmid: 17008526
|
[47] |
Kuchenbaecker K B, Hopper J L, Barnes D R , et al. Risks of breast, ovarian, and contralateral breast cancer for brca1 and brca2 mutation carriers. JAMA, 2017,317(23):2402-2416.
doi: 10.1001/jama.2017.7112
pmid: 28632866
|
[48] |
Paz-Ares L, Tan E H , O’Byrne K,et al. Afatinib versus gefitinib in patients with EGFR mutation-positive advanced non-small-cell lung cancer: overall survival data from the phase IIb LUX-Lung 7 trial. Ann Oncol, 2017,28(2):270-277.
doi: 10.1093/annonc/mdw611
pmid: 5391700
|
[49] |
Tsao M S, Aviel-Ronen S, Ding K , et al. Prognostic and predictive importance of p53 and RAS for adjuvant chemotherapy in non small-cell lung cancer. J Clin Oncol, 2007,25(33):5240-5247.
doi: 10.1200/JCO.2007.12.6953
|
[50] |
Solomon B J, Mok T, Kim D W , et al. First-line crizotinib versus chemotherapy in ALK-positive lung cancer. N Engl J Med, 2014,371(23):2167-2177.
doi: 10.1056/NEJMoa1408440
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|