翻译 - TCGAbiolinks 6 - Compilation of TCGA molecular subtypes

TCGAbiolinks:分子亚型

在运行程序前,我们需要导入必要的包:

library(TCGAbiolinks)

library(SummarizedExperiment)

TCGAbiolinks从TCGA样本中检索分子亚型信息。函数PanCancerAtlas_subtypesTCGAquery_subtype可用于获取分子亚型的信息表。

分子亚型实际上指的是测序的数据亚型,比如mRNA、miRNA、DNA甲基化等

虽然PanCancerAtlas_subtypes函数可以从synapse中获得精准的分子亚型表(可能具有最新的分子亚型),但TCGAquery_subtype函数能从TCGA标记的文章中获得完整的分子亚型信息,并带有样本信息。

1. PanCancerAtlas_subtypes:精准的分子亚型。

从synapse中检索数据及其相应的描述可以参考:https://www.synapse.org/#!Synapse:syn8402849

Synapse目前发布了一个文件,其中包含TCGA中所有可用分子亚型,包括所有肿瘤类型和所有分子平台(即测序平台))。我们可以使用PanCancerAtlas_subtypes函数获取信息:

subtypes <- PanCancerAtlas_subtypes()
DT::datatable(subtypes,
             filter = 'top',
             options = list(scrollX = TRUE, keys = TRUE, pageLength = 5),
             rownames = FALSE)
pan.samplesIDcancer.typeSubtype_mRNASubtype_DNAmethSubtype_proteinSubtype_miRNASubtype_CNASubtype_IntegrativeSubtype_otherSubtype_Selected
TCGA-OR-A5J1ACCsteroid-phenotype-high+proliferationCIMP-highmiRNA_1QuietCOC3C1AACC.CIMP-high
TCGA-OR-A5J2ACCsteroid-phenotype-high+proliferationCIMP-low1miRNA_1NoisyCOC3C1AACC.CIMP-low
TCGA-OR-A5J3ACCsteroid-phenotype-highCIMP-intermediate3miRNA_6ChromosomalCOC2C1AACC.CIMP-intermediate
TCGA-OR-A5J4ACCCIMP-highmiRNA_6ChromosomalACC.CIMP-high
TCGA-OR-A5J5ACCsteroid-phenotype-highCIMP-intermediatemiRNA_2ChromosomalCOC2C1AACC.CIMP-intermediate

只显示了一部分数据

选择“Subtype_Selected”列作为最突出的亚型分类(来自其他列)

All available molecular data based-subtypeSelected subtypeNumber of samplesLink to fileReferencelink to paper
ACCmRNA, DNAmeth, protein, miRNA, CNA, COC, C1A.C1BDNAmeth91LinkCancer Cell 2016Link
AMLmRNA and miRNAmRNA187LinkNEJM 2013Link
BLCAmRNA subtypesmRNA129LinkNature 2014Link
BRCAPAM50 (mRNA)PAM501218LinkNature 2012Link
GBM/LGG*mRNA, DNAmeth, protein, Supervised_DNAmethSupervised_DNAmeth1122LinkCell 2016Link
Pan-GI (preliminary) ESCA/STAD/COAD/READMolecular_SubtypeMolecular_Subtype1011LinkCancer Cell 2018Link
HNSCmRNA, DNAmeth, RPPA, miRNA, CNA, ParadigmmRNA279Link (TabS7.2)Nature 2015Link
KICHEosinophilicEosinophilic66LinkCancer Cell 2014Link
KIRCmRNA, miRNAmRNA442LinkNature 2013Link
KIRPmRNA, DNAmeth, protein, miRNA, CNA, COCCOC161LinkNEJM 2015Link
LIHC (preliminary)mRNA, DNAmeth, protein, miRNA, CNA, Paradigma, iClusteriCluster196[Link](https://wiki.nci.nih.gov/download/attachments/139067884/Supplementary Tables-1-2016.xlsx?version=1&modificationDate=1452270515000&api=v2) (Table S1A)not published
LUADDNAmeth, iClusteriCluster230Link (Table S7)Nature 2014Link
LUSCmRNAmRNA178Link (Data file S7.5)Nature 2012Link
OVCAmRNAmRNA489LinkNature 2011Link
PCPGmRNA, DNAmeth, protein, miRNA, CNAmRNA178tableS2Cancer Cell 2017Link
PRADmRNA, DNAmeth, protein, miRNA, CNA, icluster, mutation/fusionmutation/fusion333LinkCell 2015Link
SKCMmRNA, DNAmeth, protein, miRNA, mutationmutation331Link (Table S1D)Cell 2015Link
THCAmRNA, DNAmeth, protein, miRNA, CNA, histologymRNA496Link (Table S2 - Tab1)Cell 2014Link
UCECiCluster, MSI, CNA, mRNAiCluster - updated according to Pan-Gyne/Pathways groups538Link (datafile S1.1)Nature 2013Link
Link
UCS (preliminary)mRNAmRNA57Linknot published

2. TCGAquery_subtype:使用分子亚型数据。

癌症基因组图谱(TCGA)研究网络报告了各种疾病的综合全基因组研究。我们在包中添加了这些报告定义的一些分子亚型:

TCGA datasetLinkPaperJournal
ACCdoi:10.1016/j.ccell.2016.04.002Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma.Cancer cell 2016
BRCAhttps://www.cell.com/cancer-cell/fulltext/S1535-6108(18)30119-3A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast CancersCancer cell 2018
BLCAhttp://www.cell.com/cell/fulltext/S0092-8674(17)31056-5Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer Cell 2017
CHOLhttp://www.sciencedirect.com/science/article/pii/S2211124717302140?via%3DihubIntegrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular ProfilesCell Reports 2017
COADhttp://www.nature.com/nature/journal/v487/n7407/abs/nature11252.htmlComprehensive molecular characterization of human colon and rectal cancerNature 2012
ESCAhttps://www.nature.com/articles/nature20805Integrated genomic characterization of oesophageal carcinomaNature 2017
GBMhttp://dx.doi.org/10.1016/j.cell.2015.12.028Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse GliomaCell 2016
HNSChttp://www.nature.com/nature/journal/v517/n7536/abs/nature14129.htmlComprehensive genomic characterization of head and neck squamous cell carcinomasNature 2015
KICHhttp://www.sciencedirect.com/science/article/pii/S1535610814003043The Somatic Genomic Landscape of Chromophobe Renal Cell CarcinomaCancer cell 2014
KIRChttp://www.nature.com/nature/journal/v499/n7456/abs/nature12222.htmlComprehensive molecular characterization of clear cell renal cell carcinomaNature 2013
KIRPhttp://www.nejm.org/doi/full/10.1056/NEJMoa1505917Comprehensive Molecular Characterization of Papillary Renal-Cell CarcinomaNEJM 2016
LIHChttp://linkinghub.elsevier.com/retrieve/pii/S0092-8674(17)30639-6Comprehensive and Integrative Genomic Characterization of Hepatocellular CarcinomaCell 2017
LGGhttp://dx.doi.org/10.1016/j.cell.2015.12.028Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse GliomaCell 2016
LUADhttp://www.nature.com/nature/journal/v511/n7511/abs/nature13385.htmlComprehensive molecular profiling of lung adenocarcinomaNature 2014
LUSChttp://www.nature.com/nature/journal/v489/n7417/abs/nature11404.htmlComprehensive genomic characterization of squamous cell lung cancersNature 2012
PAADhttp://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30299-4Integrated Genomic Characterization of Pancreatic Ductal AdenocarcinomaCancer Cell 2017
PCPGhttp://dx.doi.org/10.1016/j.ccell.2017.01.001Comprehensive Molecular Characterization of Pheochromocytoma and ParagangliomaCancer cell 2017
PRADhttp://www.sciencedirect.com/science/article/pii/S0092867415013392The Molecular Taxonomy of Primary Prostate CancerCell 2015
READhttp://www.nature.com/nature/journal/v487/n7407/abs/nature11252.htmlComprehensive molecular characterization of human colon and rectal cancerNature 2012
SARChttp://www.cell.com/cell/fulltext/S0092-8674(17)31203-5Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue SarcomasCell 2017
SKCMhttp://www.sciencedirect.com/science/article/pii/S0092867415006340Genomic Classification of Cutaneous MelanomaCell 2015
STADhttp://www.nature.com/nature/journal/v511/n7511/abs/nature13385.htmlComprehensive molecular characterization of gastric adenocarcinomaNature 2013
THCAhttp://www.sciencedirect.com/science/article/pii/S0092867414012380Integrated Genomic Characterization of Papillary Thyroid CarcinomaCell 2014
UCEChttp://www.nature.com/nature/journal/v497/n7447/abs/nature12113.htmlIntegrated genomic characterization of endometrial carcinomaNature 2013
UCShttp://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30053-3Integrated Molecular Characterization of Uterine Carcinosarcoma CancerCell 2017
UVMhttp://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30295-7Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal MelanomaCancer Cell 2017

这些分子亚型将通过GDCprepare自动添加到summaExperiment对象中。但您也可以TCGAquery_subtype函数来检索此信息。

lgg.gbm.subtype <- TCGAquery_subtype(tumor = "lgg")

LGG亚型的子集如下所示:

patientTissue.source.siteStudyBCRWhole.exomeWhole.genomeRNAseqSNP6U133aHM450HM27RPPAHistologyGradeAge..years.at.diagnosis.GenderSurvival..months.Vital.status..1.dead.Karnofsky.Performance.ScoreMutation.CountPercent.aneuploidyIDH.statusX1p.19q.codeletionIDH.codel.subtypeMGMT.promoter.statusChr.7.gain.Chr.10.lossChr.19.20.co.gainTERT.promoter.statusTERT.expression..log2.TERT.expression.statusATRX.statusDAXX.statusTelomere.MaintenanceBRAF.V600E.statusBRAF.KIAA1549.fusionABSOLUTE.purityABSOLUTE.ploidyESTIMATE.stromal.scoreESTIMATE.immune.scoreESTIMATE.combined.scoreOriginal.SubtypeTranscriptome.SubtypePan.Glioma.RNA.Expression.ClusterIDH.specific.RNA.Expression.ClusterPan.Glioma.DNA.Methylation.ClusterIDH.specific.DNA.Methylation.ClusterSupervised.DNA.Methylation.ClusterRandom.Forest.Sturm.ClusterRPPA.clusterTelomere.length.estimate.in.blood.normal..Kb.Telomere.length.estimate.in.tumor..Kb.
TCGA-CS-4938Thomas Jefferson UniversityBrain Lower Grade GliomaIGCYesYesYesYesNoYesNoYesastrocytomaG231female4.6982507090150.069411737Mutantnon-codelIDHmut-non-codelUnmethylatedNo combined CNANo chr 19/20 gainWT0Not expressedMutantWTATRXWTWT0.792422.0321804.96141226.9936IDHmut-non-codelLGr3IDHmut-R3LGm2IDHmut-K2G-CIMP-highIDHK28.11195.1859
TCGA-CS-4941Thomas Jefferson UniversityBrain Lower Grade GliomaIGCYesYesYesYesNoYesNoNoastrocytomaG367male7.6880466190500.224149226WTnon-codelIDHwtMethylatedGain chr 7 & loss chr 10No chr 19/20 gainMutant3.8073549220576ExpressedWTWTTERTWTWT0.612.05706.87122283.23362990.1048IDHwtCLLGr4IDHwt-R2LGm5IDHwt-K2Mesenchymal-likeMesenchymal1.41911.6129
TCGA-CS-4942Thomas Jefferson UniversityBrain Lower Grade GliomaIGCYesNoYesYesNoYesNoYesastrocytomaG344female43.8612915190240.093693446Mutantnon-codelIDHmut-non-codelUnmethylatedNo combined CNANo chr 19/20 gainWT0Not expressedMutantWTATRXWTWT0.762.05563.47632076.29172639.768IDHmut-non-codelPNLGr3IDHmut-R3LGm2IDHmut-K2G-CIMP-highIDHK2
TCGA-CS-4943Thomas Jefferson UniversityBrain Lower Grade GliomaIGCYesNoYesYesNoYesNoYesastrocytomaG337male18.1359048050300.172371054Mutantnon-codelIDHmut-non-codelMethylatedNo combined CNANo chr 19/20 gainWT0Not expressedMutantWTATRXWTWT0.833.92460.2841819.13471279.4188IDHmut-non-codelPNLGr3IDHmut-R3LGm2IDHmut-K2G-CIMP-highIDHK2
TCGA-CS-4944Thomas Jefferson UniversityBrain Lower Grade GliomaIGCYesYesYesYesNoYesNoYesastrocytomaG250male10.6121327090200.060307007Mutantnon-codelIDHmut-non-codelMethylatedNo combined CNANo chr 19/20 gainMutant2.58496250072116ExpressedWTWTTERTWTWT0.741.94701.13451281.9921983.1265IDHmut-non-codelLGr3IDHmut-R3LGm2IDHmut-K2G-CIMP-highIDHK23.26451.4981

3. 版本信息


sessionInfo()
## R version 3.5.3 (2019-03-11)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.6 LTS
## 
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.8-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.8-bioc/R/lib/libRlapack.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
##  [1] grid      parallel  stats4    stats     graphics  grDevices utils    
##  [8] datasets  methods   base     
## 
## other attached packages:
##  [1] TCGAbiolinks_2.10.5         maftools_1.8.0             
##  [3] bigmemory_4.5.33            png_0.1-7                  
##  [5] DT_0.5                      dplyr_0.8.0.1              
##  [7] SummarizedExperiment_1.12.0 DelayedArray_0.8.0         
##  [9] BiocParallel_1.16.6         matrixStats_0.54.0         
## [11] Biobase_2.42.0              GenomicRanges_1.34.0       
## [13] GenomeInfoDb_1.18.2         IRanges_2.16.0             
## [15] S4Vectors_0.20.1            BiocGenerics_0.28.0        
## [17] testthat_2.0.1             
## 
## loaded via a namespace (and not attached):
##   [1] R.utils_2.8.0                 tidyselect_0.2.5             
##   [3] RSQLite_2.1.1                 AnnotationDbi_1.44.0         
##   [5] htmlwidgets_1.3               devtools_2.0.1               
##   [7] DESeq_1.34.1                  munsell_0.5.0                
##   [9] codetools_0.2-16              preprocessCore_1.44.0        
##  [11] withr_2.1.2                   colorspace_1.4-1             
##  [13] highr_0.7                     knitr_1.22                   
##  [15] rstudioapi_0.10               NMF_0.21.0                   
##  [17] labeling_0.3                  GenomeInfoDbData_1.2.0       
##  [19] hwriter_1.3.2                 KMsurv_0.1-5                 
##  [21] bit64_0.9-7                   rprojroot_1.3-2              
##  [23] downloader_0.4                generics_0.0.2               
##  [25] xfun_0.5                      ggthemes_4.1.0               
##  [27] randomForest_4.6-14           EDASeq_2.16.3                
##  [29] R6_2.4.0                      doParallel_1.0.14            
##  [31] locfit_1.5-9.1                bitops_1.0-6                 
##  [33] assertthat_0.2.0              promises_1.0.1               
##  [35] scales_1.0.0                  gtable_0.2.0                 
##  [37] sva_3.30.1                    processx_3.3.0               
##  [39] wheatmap_0.1.0                sesameData_1.0.0             
##  [41] rlang_0.3.1                   genefilter_1.64.0            
##  [43] cmprsk_2.2-7                  GlobalOptions_0.1.0          
##  [45] splines_3.5.3                 rtracklayer_1.42.2           
##  [47] lazyeval_0.2.2                wordcloud_2.6                
##  [49] selectr_0.4-1                 broom_0.5.1                  
##  [51] reshape2_1.4.3                BiocManager_1.30.4           
##  [53] yaml_2.2.0                    GenomicFeatures_1.34.6       
##  [55] crosstalk_1.0.0               backports_1.1.3              
##  [57] httpuv_1.5.0                  tools_3.5.3                  
##  [59] usethis_1.4.0                 gridBase_0.4-7               
##  [61] ggplot2_3.1.0                 RColorBrewer_1.1-2           
##  [63] DNAcopy_1.56.0                sessioninfo_1.1.1            
##  [65] Rcpp_1.0.1                    plyr_1.8.4                   
##  [67] progress_1.2.0                zlibbioc_1.28.0              
##  [69] purrr_0.3.2                   RCurl_1.95-4.12              
##  [71] ps_1.3.0                      prettyunits_1.0.2            
##  [73] ggpubr_0.2                    GetoptLong_0.1.7             
##  [75] cowplot_0.9.4                 zoo_1.8-4                    
##  [77] ggrepel_0.8.0                 cluster_2.0.7-1              
##  [79] fs_1.2.7                      magrittr_1.5                 
##  [81] data.table_1.12.0             circlize_0.4.5               
##  [83] survminer_0.4.3               pkgload_1.0.2                
##  [85] aroma.light_3.12.0            hms_0.4.2                    
##  [87] mime_0.6                      evaluate_0.13                
##  [89] xtable_1.8-3                  XML_3.98-1.19                
##  [91] mclust_5.4.3                  gridExtra_2.3                
##  [93] shape_1.4.4                   compiler_3.5.3               
##  [95] biomaRt_2.38.0                tibble_2.1.1                 
##  [97] crayon_1.3.4                  R.oo_1.22.0                  
##  [99] htmltools_0.3.6               mgcv_1.8-27                  
## [101] later_0.8.0                   tidyr_0.8.3                  
## [103] geneplotter_1.60.0            DBI_1.0.0                    
## [105] ExperimentHub_1.8.0           matlab_1.0.2                 
## [107] ComplexHeatmap_1.20.0         BiocStyle_2.10.0             
## [109] ShortRead_1.40.0              Matrix_1.2-16                
## [111] readr_1.3.1                   cli_1.1.0                    
## [113] R.methodsS3_1.7.1             bigmemory.sri_0.1.3          
## [115] pkgconfig_2.0.2               km.ci_0.5-2                  
## [117] sesame_1.0.0                  registry_0.5-1               
## [119] GenomicAlignments_1.18.1      xml2_1.2.0                   
## [121] foreach_1.4.4                 annotate_1.60.1              
## [123] rngtools_1.3.1                pkgmaker_0.27                
## [125] XVector_0.22.0                bibtex_0.4.2                 
## [127] rvest_0.3.2                   stringr_1.4.0                
## [129] callr_3.2.0                   digest_0.6.18                
## [131] ConsensusClusterPlus_1.46.0   Biostrings_2.50.2            
## [133] rmarkdown_1.12                survMisc_0.5.5               
## [135] edgeR_3.24.3                  curl_3.3                     
## [137] shiny_1.2.0                   Rsamtools_1.34.1             
## [139] rjson_0.2.20                  nlme_3.1-137                 
## [141] jsonlite_1.6                  BSgenome_1.50.0              
## [143] desc_1.2.0                    limma_3.38.3                 
## [145] pillar_1.3.1                  lattice_0.20-38              
## [147] httr_1.4.0                    pkgbuild_1.0.2               
## [149] survival_2.43-3               interactiveDisplayBase_1.20.0
## [151] glue_1.3.1                    remotes_2.0.2                
## [153] iterators_1.0.10              bit_1.1-14                   
## [155] stringi_1.4.3                 blob_1.1.1                   
## [157] AnnotationHub_2.14.5          latticeExtra_0.6-28          
## [159] memoise_1.1.0
更新时间:2019-05-25 17:37:45

本文由 AlphaJP 创作,如果您觉得本文不错,请随意赞赏
采用 知识共享署名4.0 国际许可协议进行许可
本站文章除注明转载/出处外,均为本站原创或翻译,转载前请务必署名
原文链接:https://blog.computsystmed.com/archives/translation-tcgabiolinks-compilation-of-tcga-molecular-subtypes
最后更新:2019-05-25 17:37:45

评论

Your browser is out of date!

Update your browser to view this website correctly. Update my browser now

×