常用肿瘤基因分析方法及基于TCGA数据库的分析应用
|
摘要
随着二代测序技术的快速发展,数据量不断累积,肿瘤学家的目光逐渐由多物种测序转移至高通量测序数据的分析和比对。基因数据分析方法层出不穷,高通量的组学分析手段不断优化和创新,基因数据的挖掘和分析工作正处于飞速发展的时期。以肿瘤病人样本为核心的数据库The Cancer Genome Atlas (TCGA)由此应运而生,该数据库全方位记录了从临床肿瘤病人样本得到的基因数据如DNA序列、转录本信息、表观遗传学修饰等。本文主要从数据分析方法、TCGA数据库及其应用实例等3个方面详细介绍了肿瘤相关基因数据的深入挖掘和生物信息学分析方法的最新研究进展,以期为研究人员利用大数据发现肿瘤防治相关的新靶点提供借鉴和参考。
The development of second-generation sequencing(NGS) technology is providing numerous data which shifts the focus of cancer research from the sequencing of multi-species to the analysis and comparison of select data via high-throughput sequencing. The NGS also facilitates the diversity of available genetic data analysis methods, the constant optimization and innovation of analytical approaches for high-throughput genomics as well as the rapid development of genetic data mining and analysis models. The Cancer Genome Atlas(TCGA) database is a direct result of this work. The TCGA database provides a comprehensive record of genetic data collected from a tumor patient's sample, including its DNA sequence, transcriptional information, epigenetic modification and related. This review elaborates the latest progress in both the mining algorithm and analysis methods for tumor genomics. Specially, we introduce and review the TCGA database and data analysis approaches while demonstrating its applicability using representative cases. This review may shed light on new tumor-related targets discovery for researchers by means of bid data.
The development of second-generation sequencing(NGS) technology is providing numerous data which shifts the focus of cancer research from the sequencing of multi-species to the analysis and comparison of select data via high-throughput sequencing. The NGS also facilitates the diversity of available genetic data analysis methods, the constant optimization and innovation of analytical approaches for high-throughput genomics as well as the rapid development of genetic data mining and analysis models. The Cancer Genome Atlas(TCGA) database is a direct result of this work. The TCGA database provides a comprehensive record of genetic data collected from a tumor patient's sample, including its DNA sequence, transcriptional information, epigenetic modification and related. This review elaborates the latest progress in both the mining algorithm and analysis methods for tumor genomics. Specially, we introduce and review the TCGA database and data analysis approaches while demonstrating its applicability using representative cases. This review may shed light on new tumor-related targets discovery for researchers by means of bid data.
引文
[1]George B,Seals S,Aban I.Survival analysis and regression models.J Nucl Cardiol,2014,21:686-694.
[2]Rasmussen L,Pratt N,Hansen MR,Hallas J,Pottegard A.Using the"proportion of patients covered"and the KaplanMeier survival analysis to describe treatment persistence.Pharmacoepidemiol Drug Saf,2018,27:867-871.
[3]Hsu CH,Yu M.Cox regression analysis with missing covariates via nonparametric multiple imputation.Stat Methods Med Res,2018,962280218772592.
[4]Ritchie ME,Phipson B,Wu D,Hu Y,Law CW,Shi W,Smyth GK.limma powers differential expression analyses for RNA-sequencing and microarray studies.Nucleic Acids Res,2015,43:e47.
[5]Heyer LJ,Kruglyak S,Yooseph S.Exploring expression data:identification and analysis of coexpressed genes.Genome Res,1999,9:1106-1115.
[6]Bunger R,Mallet RT.Metabolomics and receiver operating characteristic analysis:a promising approach for sepsis diagnosis.Crit Care Med,2016,44:1784-1785.
[7]Grau J,Grosse I,Keilwagen J.PRROC:computing and visualizing precision-recall and receiver operating characteristic curves in R.Bioinformatics,2015,31:2595-2597.
[8]Cichonska A,Rousu J,Marttinen P,Kangas AJ,Soininen P,Lehtimaki T,Raitakari OT,Jarvelin MR,Salomaa V,Ala-Korpela M,Ripatti S,Pirinen M.metaCCA:summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.Bioinformatics,2016,32:1981-1989.
[9]Dimou NL,Tsirigos KD,Elofsson A,Bagos PG.GWAR:robust analysis and meta-analysis of genome-wide association studies.Bioinformatics,2017,33:1521-1527.
[10]Chin L,Andersen JN,Futreal PA.Cancer genomics:from discovery science to personalized medicine.Nature Medicine,2011,17:297-303.
[11]Tomczak K,Czerwinska P,Wiznerowicz M.The Cancer Genome Atlas(TCGA):an immeasurable source of knowledge.Contemp Oncol(Pozn),2015,19:A68-77.
[12]Hanahan D,Weinberg RA.The hallmarks of cancer.Cell,2000,100:57-70.
[13]Sirintrapun SJ,Zehir A,Syed A,Gao J,Schultz N,Cheng DT.Translational bioinformatics and clinical research(biomedical)informatics.Clin Lab Med,2016,36:153-181.
[14]Li QK,Pavlovich CP,Zhang H,Kinsinger CR,Chan DW.Challenges and opportunities in the proteomic characterization of clear cell renal cell carcinoma(ccRCC):a critical step towards the personalized care of renal cancers.Semin Cancer Biol,2018,DOI:10.1016/j.semcancer.2018.06.004.
[15]Smith CC,Beckermann KE,Bortone DS,de Cubas AA,Bixby LM,Lee SJ,Panda A,Ganesan S,Bhanot G,Wallen EM,Milowsky MI,Kim WY,Rathmell WK,Swanstrom R,Parker JS,Serody JS,Selitsky SR,Vincent BG.Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma.J Clin Invest,2018,128(11):4804-4820.
[16]Byron SA,Van Keuren-Jensen KR,Engelthaler DM,Carpten JD,Craig DW.Translating RNA sequencing into clinical diagnostics:opportunities and challenges.Nat Rev Genet,2016,17:257-271.
[17]Chen H,Li C,Peng X,Zhou Z,Weinstein JN,Cancer Genome Atlas Research N,Liang H.A pan-cancer analysis of enhancer expression in nearly 9000 patient samples.Cell,2018,173:386-399 e312.
[18]Gebert LFR,MacRae IJ.Regulation of microRNAfunction in animals.Nat Rev Mol Cell Biol,2018,20(1):21-37.
[19]Rupaimoole R,Slack FJ.MicroRNA therapeutics:towards a new era for the management of cancer and other diseases.Nat Rev Drug Discov,2017,16:203-222.
[20]Bartel DP.MicroRNAs:target recognition and regulatory functions.Cell,2009,136:215-233.
[21]Cortez MA,Ivan C,Valdecanas D,Wang X,Peltier HJ,Ye Y,Araujo L,Carbone DP,Shilo K,Giri DK,Kelnar K,Martin D,Komaki R,Gomez DR,Krishnan S,Calin GA,Bader AG,Welsh JW.PDL1 Regulation by p53 via miR-34.J Natl Cancer Inst,2016,108.
[22]Boyd SD.Diagnostic applications of high-throughput DNA sequencing.Annu Rev Pathol,2013,8:381-410.
[23]Lasken RS,McLean JS.Recent advances in genomic DNAsequencing of microbial species from single cells.Nat Rev Genet,2014,15:577-584.
[24]McCarroll SA,Kuruvilla FG,Korn JM,Cawley S,Nemesh J,Wysoker A,Shapero MH,de Bakker PI,Maller JB,Kirby A,Elliott AL,Parkin M,Hubbell E,Webster T,Mei R,Veitch J,Collins PJ,Handsaker R,Lincoln S,Nizzari M,Blume J,Jones KW,Rava R,Daly MJ,Gabriel SB,Altshuler D.Integrated detection and populationgenetic analysis of SNPs and copy number variation.Nat Genet,2008,40:1166-1174.
[25]Flavahan WA,Gaskell E,Bernstein BE.Epigenetic plasticity and the hallmarks of cancer.Science,2017,357(6348):pii:eaal2380.
[26]Okugawa Y,Grady WM,Goel A.Epigenetic Alterations in Colorectal Cancer:Emerging Biomarkers.Gastroenterology,2015,149:1204-1225 e1212.
[27]Dor Y,Cedar H.Principles of DNA methylation and their implications for biology and medicine.Lancet,2018,392(10149):777-786.
[28]Lu Y,Ling S,Hegde AM,Byers LA,Coombes K,Mills GB,Akbani R.Using reverse-phase protein arrays as pharmacodynamic assays for functional proteomics,biomarker discovery,and drug development in cancer.Semin Oncol,2016,43:476-483.
[29]Jiang T,Shi W,Wali VB,Pongor LS,Li C,Lau R,Gyorffy B,Lifton RP,Symmans WF,Pusztai L,Hatzis C.Predictors of chemosensitivity in triple negative breast cancer:an integrated genomic analysis.PLoS Med,2016,13:e1002193.
[30]Salem O,Erdem N,Jung J,Munstermann E,Worner A,Wilhelm H,Wiemann S,Korner C.The highly expressed5'isomiR of hsa-miR-140-3p contributes to the tumorsuppressive effects of miR-140 by reducing breast cancer proliferation and migration.BMC Genomics,2016,17:566.
[31]Gibori H,Eliyahu S,Krivitsky A,Ben-Shushan D,Epshtein Y,Tiram G,Blau R,Ofek P,Lee JS,Ruppin E,Landsman L,Barshack I,Golan T,Merquiol E,Blum G,Satchi-Fainaro R.Amphiphilic nanocarrier-induced modulation of PLK1 and miR-34a leads to improved therapeutic response in pancreatic cancer.Nat Commun,2018,9:16.
[32]Thorsson V,Gibbs DL,Brown SD,Wolf D,Bortone DS,Ou Yang TH,Porta-Pardo E,Gao GF,Plaisier CL,Eddy JA,Ziv E,Culhane AC,Paull EO,Sivakumar IKA,Gentles AJ,Malhotra R,Farshidfar F,Colaprico A,Parker JS,Mose LE,Vo NS,Liu J,Liu Y,Rader J,Dhankani V,Reynolds SM,Bowlby R,Califano A,Cherniack AD,Anastassiou D,Bedognetti D,Rao A,Chen K,Krasnitz A,Hu H,Malta TM,Noushmehr H,Pedamallu CS,Bullman S,Ojesina AI,Lamb A,Zhou W,Shen H,Choueiri TK,Weinstein JN,Guinney J,Saltz J,Holt RA,Rabkin CE,Cancer Genome Atlas Research N,Lazar AJ,Serody JS,Demicco EG,Disis ML,Vincent BG,Shmulevich L.The immune landscape of cancer.Immunity,2018,48:812-830e814.
[33]Berger AC,Korkut A,Kanchi RS,Hegde AM,Lenoir W,Liu W,Liu Y,Fan H,Shen H,Ravikumar V,Rao A,Schultz A,Li X,Sumazin P,Williams C,Mestdagh P,Gunaratne PH,Yau C,Bowlby R,Robertson AG,Tiezzi DG,Wang C,Cherniack AD,Godwin AK,Kuderer NM,Rader JS,Zuna RE,Sood AK,Lazar AJ,Ojesina AI,Adebamowo C,Adebamowo SN,Baggerly KA,Chen TW,Chiu HS,Lefever S,Liu L,MacKenzie K,Orsulic S,Roszik J,Shelley CS,Song Q,Vellano CP,Wentzensen N,Cancer Genome Atlas Research N,Weinstein JN,Mills GB,Levine DA,Akbani R.A comprehensive pan-cancer molecular study of gynecologic and breast cancers.Cancer Cell,2018,33:690-705 e699.
[34]Yu KH,Fitzpatrick MR,Pappas L,Chan W,Kung J,Snyder M.Omics analysis system for precision oncology(OASISPRO):a web-based omics analysis tool for clinical phenotype prediction.Bioinformatics,2018,34(2):319-320.
[35]Fisch KM,Meissner T,Gioia L,Ducom JC,Carland TM,Loguercio S,Su AI.Omics Pipe:a community-based framework for reproducible multi-omics data analysis.Bioinformatics,2015,31:1724-1728.
[36]Zhang YS,Xia L,Sang J,Li M,Liu L,Li MG,Niu GY,Cao JB,Teng XF,Zhou Q,Zhang Z.The BIG Data Center’s database resources.Hereditas(Beijing),2018,40(11):1039-1043.张源笙,夏琳,桑健,李漫,刘琳,李萌伟,牛广艺,曹佳宝,滕徐菲,周晴,章张.生命与健康大数据中心资源.遗传,2018,40(11):1039-1043.
[2]Rasmussen L,Pratt N,Hansen MR,Hallas J,Pottegard A.Using the"proportion of patients covered"and the KaplanMeier survival analysis to describe treatment persistence.Pharmacoepidemiol Drug Saf,2018,27:867-871.
[3]Hsu CH,Yu M.Cox regression analysis with missing covariates via nonparametric multiple imputation.Stat Methods Med Res,2018,962280218772592.
[4]Ritchie ME,Phipson B,Wu D,Hu Y,Law CW,Shi W,Smyth GK.limma powers differential expression analyses for RNA-sequencing and microarray studies.Nucleic Acids Res,2015,43:e47.
[5]Heyer LJ,Kruglyak S,Yooseph S.Exploring expression data:identification and analysis of coexpressed genes.Genome Res,1999,9:1106-1115.
[6]Bunger R,Mallet RT.Metabolomics and receiver operating characteristic analysis:a promising approach for sepsis diagnosis.Crit Care Med,2016,44:1784-1785.
[7]Grau J,Grosse I,Keilwagen J.PRROC:computing and visualizing precision-recall and receiver operating characteristic curves in R.Bioinformatics,2015,31:2595-2597.
[8]Cichonska A,Rousu J,Marttinen P,Kangas AJ,Soininen P,Lehtimaki T,Raitakari OT,Jarvelin MR,Salomaa V,Ala-Korpela M,Ripatti S,Pirinen M.metaCCA:summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.Bioinformatics,2016,32:1981-1989.
[9]Dimou NL,Tsirigos KD,Elofsson A,Bagos PG.GWAR:robust analysis and meta-analysis of genome-wide association studies.Bioinformatics,2017,33:1521-1527.
[10]Chin L,Andersen JN,Futreal PA.Cancer genomics:from discovery science to personalized medicine.Nature Medicine,2011,17:297-303.
[11]Tomczak K,Czerwinska P,Wiznerowicz M.The Cancer Genome Atlas(TCGA):an immeasurable source of knowledge.Contemp Oncol(Pozn),2015,19:A68-77.
[12]Hanahan D,Weinberg RA.The hallmarks of cancer.Cell,2000,100:57-70.
[13]Sirintrapun SJ,Zehir A,Syed A,Gao J,Schultz N,Cheng DT.Translational bioinformatics and clinical research(biomedical)informatics.Clin Lab Med,2016,36:153-181.
[14]Li QK,Pavlovich CP,Zhang H,Kinsinger CR,Chan DW.Challenges and opportunities in the proteomic characterization of clear cell renal cell carcinoma(ccRCC):a critical step towards the personalized care of renal cancers.Semin Cancer Biol,2018,DOI:10.1016/j.semcancer.2018.06.004.
[15]Smith CC,Beckermann KE,Bortone DS,de Cubas AA,Bixby LM,Lee SJ,Panda A,Ganesan S,Bhanot G,Wallen EM,Milowsky MI,Kim WY,Rathmell WK,Swanstrom R,Parker JS,Serody JS,Selitsky SR,Vincent BG.Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma.J Clin Invest,2018,128(11):4804-4820.
[16]Byron SA,Van Keuren-Jensen KR,Engelthaler DM,Carpten JD,Craig DW.Translating RNA sequencing into clinical diagnostics:opportunities and challenges.Nat Rev Genet,2016,17:257-271.
[17]Chen H,Li C,Peng X,Zhou Z,Weinstein JN,Cancer Genome Atlas Research N,Liang H.A pan-cancer analysis of enhancer expression in nearly 9000 patient samples.Cell,2018,173:386-399 e312.
[18]Gebert LFR,MacRae IJ.Regulation of microRNAfunction in animals.Nat Rev Mol Cell Biol,2018,20(1):21-37.
[19]Rupaimoole R,Slack FJ.MicroRNA therapeutics:towards a new era for the management of cancer and other diseases.Nat Rev Drug Discov,2017,16:203-222.
[20]Bartel DP.MicroRNAs:target recognition and regulatory functions.Cell,2009,136:215-233.
[21]Cortez MA,Ivan C,Valdecanas D,Wang X,Peltier HJ,Ye Y,Araujo L,Carbone DP,Shilo K,Giri DK,Kelnar K,Martin D,Komaki R,Gomez DR,Krishnan S,Calin GA,Bader AG,Welsh JW.PDL1 Regulation by p53 via miR-34.J Natl Cancer Inst,2016,108.
[22]Boyd SD.Diagnostic applications of high-throughput DNA sequencing.Annu Rev Pathol,2013,8:381-410.
[23]Lasken RS,McLean JS.Recent advances in genomic DNAsequencing of microbial species from single cells.Nat Rev Genet,2014,15:577-584.
[24]McCarroll SA,Kuruvilla FG,Korn JM,Cawley S,Nemesh J,Wysoker A,Shapero MH,de Bakker PI,Maller JB,Kirby A,Elliott AL,Parkin M,Hubbell E,Webster T,Mei R,Veitch J,Collins PJ,Handsaker R,Lincoln S,Nizzari M,Blume J,Jones KW,Rava R,Daly MJ,Gabriel SB,Altshuler D.Integrated detection and populationgenetic analysis of SNPs and copy number variation.Nat Genet,2008,40:1166-1174.
[25]Flavahan WA,Gaskell E,Bernstein BE.Epigenetic plasticity and the hallmarks of cancer.Science,2017,357(6348):pii:eaal2380.
[26]Okugawa Y,Grady WM,Goel A.Epigenetic Alterations in Colorectal Cancer:Emerging Biomarkers.Gastroenterology,2015,149:1204-1225 e1212.
[27]Dor Y,Cedar H.Principles of DNA methylation and their implications for biology and medicine.Lancet,2018,392(10149):777-786.
[28]Lu Y,Ling S,Hegde AM,Byers LA,Coombes K,Mills GB,Akbani R.Using reverse-phase protein arrays as pharmacodynamic assays for functional proteomics,biomarker discovery,and drug development in cancer.Semin Oncol,2016,43:476-483.
[29]Jiang T,Shi W,Wali VB,Pongor LS,Li C,Lau R,Gyorffy B,Lifton RP,Symmans WF,Pusztai L,Hatzis C.Predictors of chemosensitivity in triple negative breast cancer:an integrated genomic analysis.PLoS Med,2016,13:e1002193.
[30]Salem O,Erdem N,Jung J,Munstermann E,Worner A,Wilhelm H,Wiemann S,Korner C.The highly expressed5'isomiR of hsa-miR-140-3p contributes to the tumorsuppressive effects of miR-140 by reducing breast cancer proliferation and migration.BMC Genomics,2016,17:566.
[31]Gibori H,Eliyahu S,Krivitsky A,Ben-Shushan D,Epshtein Y,Tiram G,Blau R,Ofek P,Lee JS,Ruppin E,Landsman L,Barshack I,Golan T,Merquiol E,Blum G,Satchi-Fainaro R.Amphiphilic nanocarrier-induced modulation of PLK1 and miR-34a leads to improved therapeutic response in pancreatic cancer.Nat Commun,2018,9:16.
[32]Thorsson V,Gibbs DL,Brown SD,Wolf D,Bortone DS,Ou Yang TH,Porta-Pardo E,Gao GF,Plaisier CL,Eddy JA,Ziv E,Culhane AC,Paull EO,Sivakumar IKA,Gentles AJ,Malhotra R,Farshidfar F,Colaprico A,Parker JS,Mose LE,Vo NS,Liu J,Liu Y,Rader J,Dhankani V,Reynolds SM,Bowlby R,Califano A,Cherniack AD,Anastassiou D,Bedognetti D,Rao A,Chen K,Krasnitz A,Hu H,Malta TM,Noushmehr H,Pedamallu CS,Bullman S,Ojesina AI,Lamb A,Zhou W,Shen H,Choueiri TK,Weinstein JN,Guinney J,Saltz J,Holt RA,Rabkin CE,Cancer Genome Atlas Research N,Lazar AJ,Serody JS,Demicco EG,Disis ML,Vincent BG,Shmulevich L.The immune landscape of cancer.Immunity,2018,48:812-830e814.
[33]Berger AC,Korkut A,Kanchi RS,Hegde AM,Lenoir W,Liu W,Liu Y,Fan H,Shen H,Ravikumar V,Rao A,Schultz A,Li X,Sumazin P,Williams C,Mestdagh P,Gunaratne PH,Yau C,Bowlby R,Robertson AG,Tiezzi DG,Wang C,Cherniack AD,Godwin AK,Kuderer NM,Rader JS,Zuna RE,Sood AK,Lazar AJ,Ojesina AI,Adebamowo C,Adebamowo SN,Baggerly KA,Chen TW,Chiu HS,Lefever S,Liu L,MacKenzie K,Orsulic S,Roszik J,Shelley CS,Song Q,Vellano CP,Wentzensen N,Cancer Genome Atlas Research N,Weinstein JN,Mills GB,Levine DA,Akbani R.A comprehensive pan-cancer molecular study of gynecologic and breast cancers.Cancer Cell,2018,33:690-705 e699.
[34]Yu KH,Fitzpatrick MR,Pappas L,Chan W,Kung J,Snyder M.Omics analysis system for precision oncology(OASISPRO):a web-based omics analysis tool for clinical phenotype prediction.Bioinformatics,2018,34(2):319-320.
[35]Fisch KM,Meissner T,Gioia L,Ducom JC,Carland TM,Loguercio S,Su AI.Omics Pipe:a community-based framework for reproducible multi-omics data analysis.Bioinformatics,2015,31:1724-1728.
[36]Zhang YS,Xia L,Sang J,Li M,Liu L,Li MG,Niu GY,Cao JB,Teng XF,Zhou Q,Zhang Z.The BIG Data Center’s database resources.Hereditas(Beijing),2018,40(11):1039-1043.张源笙,夏琳,桑健,李漫,刘琳,李萌伟,牛广艺,曹佳宝,滕徐菲,周晴,章张.生命与健康大数据中心资源.遗传,2018,40(11):1039-1043.