TCGAbiolinks retrieved molecular subtypes information from TCGA
samples. The functions PanCancerAtlas_subtypes
and
TCGAquery_subtype
can be used to get the information
tables.
While the PanCancerAtlas_subtypes
function gives access
to a curated table retrieved from synapse (probably with the most
updated molecular subtypes) the TCGAquery_subtype
function
has the complete table also with sample information retrieved from the
TCGA marker papers.
PanCancerAtlas_subtypes
: Curated molecular
subtypes.Data and description retrieved from synapse (https://www.synapse.org/#!Synapse:syn8402849)
Synapse has published a single file with all available molecular
subtypes that have been described by TCGA (all tumor types and all
molecular platforms), which can be accessed using the
PanCancerAtlas_subtypes
function as below:
<- PanCancerAtlas_subtypes()
subtypes ::datatable(subtypes,
DTfilter = 'top',
options = list(scrollX = TRUE, keys = TRUE, pageLength = 5),
rownames = FALSE)
The columns “Subtype_Selected” was selected as most prominent subtype classification (from the other columns)
All available molecular data based-subtype | Selected subtype | Number of samples | Link to file | Reference | link to paper | |
---|---|---|---|---|---|---|
ACC | mRNA, DNAmeth, protein, miRNA, CNA, COC, C1A.C1B | DNAmeth | 91 | Link | Cancer Cell 2016 | Link |
AML | mRNA and miRNA | mRNA | 187 | Link | NEJM 2013 | Link |
BLCA | mRNA subtypes | mRNA | 129 | Link | Nature 2014 | Link |
BRCA | PAM50 (mRNA) | PAM50 | 1218 | Link | Nature 2012 | Link |
GBM/LGG* | mRNA, DNAmeth, protein, Supervised_DNAmeth | Supervised_DNAmeth | 1122 | Link | Cell 2016 | Link |
Pan-GI (preliminary) ESCA/STAD/COAD/READ | Molecular_Subtype | Molecular_Subtype | 1011 | Link | Cancer Cell 2018 | Link |
HNSC | mRNA, DNAmeth, RPPA, miRNA, CNA, Paradigm | mRNA | 279 | Link (TabS7.2) | Nature 2015 | Link |
KICH | Eosinophilic | Eosinophilic | 66 | Link | Cancer Cell 2014 | Link |
KIRC | mRNA, miRNA | mRNA | 442 | Link | Nature 2013 | Link |
KIRP | mRNA, DNAmeth, protein, miRNA, CNA, COC | COC | 161 | Link | NEJM 2015 | Link |
LIHC (preliminary) | mRNA, DNAmeth, protein, miRNA, CNA, Paradigma, iCluster | iCluster | 196 | Link (Table S1A) | not published | |
LUAD | DNAmeth, iCluster | iCluster | 230 | Link (Table S7) | Nature 2014 | Link |
LUSC | mRNA | mRNA | 178 | Link (Data file S7.5) | Nature 2012 | Link |
OVCA | mRNA | mRNA | 489 | Link | Nature 2011 | Link |
PCPG | mRNA, DNAmeth, protein, miRNA, CNA | mRNA | 178 | tableS2 | Cancer Cell 2017 | Link |
PRAD | mRNA, DNAmeth, protein, miRNA, CNA, icluster, mutation/fusion | mutation/fusion | 333 | Link | Cell 2015 | Link |
SKCM | mRNA, DNAmeth, protein, miRNA, mutation | mutation | 331 | Link (Table S1D) | Cell 2015 | Link |
THCA | mRNA, DNAmeth, protein, miRNA, CNA, histology | mRNA | 496 | Link (Table S2 - Tab1) | Cell 2014 | Link |
UCEC | iCluster, MSI, CNA, mRNA | iCluster - updated according to Pan-Gyne/Pathways groups | 538 | Link (datafile S1.1) | Nature 2013 | Link |
Link | ||||||
UCS (preliminary) | mRNA | mRNA | 57 | Link | not published |
TCGAquery_subtype
: Working with molecular subtypes
data.The Cancer Genome Atlas (TCGA) Research Network has reported integrated genome-wide studies of various diseases. We have added some of the subtypes defined by these report in our package:
TCGA dataset | Link | Paper | Journal |
---|---|---|---|
ACC | doi:10.1016/j.ccell.2016.04.002 | Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma. | Cancer cell 2016 |
BRCA | https://www.cell.com/cancer-cell/fulltext/S1535-6108(18)30119-3 | A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers | Cancer cell 2018 |
BLCA | http://www.cell.com/cell/fulltext/S0092-8674(17)31056-5 | Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer Cell 2017 | |
CHOL | http://www.sciencedirect.com/science/article/pii/S2211124717302140?via%3Dihub | Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles | Cell Reports 2017 |
COAD | http://www.nature.com/nature/journal/v487/n7407/abs/nature11252.html | Comprehensive molecular characterization of human colon and rectal cancer | Nature 2012 |
ESCA | https://www.nature.com/articles/nature20805 | Integrated genomic characterization of oesophageal carcinoma | Nature 2017 |
GBM | http://dx.doi.org/10.1016/j.cell.2015.12.028 | Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma | Cell 2016 |
HNSC | http://www.nature.com/nature/journal/v517/n7536/abs/nature14129.html | Comprehensive genomic characterization of head and neck squamous cell carcinomas | Nature 2015 |
KICH | http://www.sciencedirect.com/science/article/pii/S1535610814003043 | The Somatic Genomic Landscape of Chromophobe Renal Cell Carcinoma | Cancer cell 2014 |
KIRC | http://www.nature.com/nature/journal/v499/n7456/abs/nature12222.html | Comprehensive molecular characterization of clear cell renal cell carcinoma | Nature 2013 |
KIRP | http://www.nejm.org/doi/full/10.1056/NEJMoa1505917 | Comprehensive Molecular Characterization of Papillary Renal-Cell Carcinoma | NEJM 2016 |
LIHC | http://linkinghub.elsevier.com/retrieve/pii/S0092-8674(17)30639-6 | Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma | Cell 2017 |
LGG | http://dx.doi.org/10.1016/j.cell.2015.12.028 | Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma | Cell 2016 |
LUAD | http://www.nature.com/nature/journal/v511/n7511/abs/nature13385.html | Comprehensive molecular profiling of lung adenocarcinoma | Nature 2014 |
LUSC | http://www.nature.com/nature/journal/v489/n7417/abs/nature11404.html | Comprehensive genomic characterization of squamous cell lung cancers | Nature 2012 |
PAAD | http://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30299-4 | Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma | Cancer Cell 2017 |
PCPG | http://dx.doi.org/10.1016/j.ccell.2017.01.001 | Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma | Cancer cell 2017 |
PRAD | http://www.sciencedirect.com/science/article/pii/S0092867415013392 | The Molecular Taxonomy of Primary Prostate Cancer | Cell 2015 |
READ | http://www.nature.com/nature/journal/v487/n7407/abs/nature11252.html | Comprehensive molecular characterization of human colon and rectal cancer | Nature 2012 |
SARC | http://www.cell.com/cell/fulltext/S0092-8674(17)31203-5 | Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas | Cell 2017 |
SKCM | http://www.sciencedirect.com/science/article/pii/S0092867415006340 | Genomic Classification of Cutaneous Melanoma | Cell 2015 |
STAD | http://www.nature.com/nature/journal/v511/n7511/abs/nature13385.html | Comprehensive molecular characterization of gastric adenocarcinoma | Nature 2013 |
THCA | http://www.sciencedirect.com/science/article/pii/S0092867414012380 | Integrated Genomic Characterization of Papillary Thyroid Carcinoma | Cell 2014 |
UCEC | http://www.nature.com/nature/journal/v497/n7447/abs/nature12113.html | Integrated genomic characterization of endometrial carcinoma | Nature 2013 |
UCS | http://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30053-3 | Integrated Molecular Characterization of Uterine Carcinosarcoma Cancer | Cell 2017 |
UVM | http://www.cell.com/cancer-cell/fulltext/S1535-6108(17)30295-7 | Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma | Cancer Cell 2017 |
These subtypes will be automatically added in the
summarizedExperiment object through GDCprepare. But you can also use the
TCGAquery_subtype
function to retrieve this
information.
<- TCGAquery_subtype(tumor = "lgg") lgg.gbm.subtype
A subset of the LGG subytpe is shown below:
sessionInfo()
## R version 4.2.1 Patched (2022-07-09 r82577)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur ... 10.16
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
##
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_GB/en_US.UTF-8
##
## attached base packages:
## [1] grid stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] maftools_2.14.0 jpeg_0.1-9
## [3] png_0.1-7 DT_0.26
## [5] dplyr_1.0.10 SummarizedExperiment_1.28.0
## [7] Biobase_2.58.0 GenomicRanges_1.50.0
## [9] GenomeInfoDb_1.34.0 IRanges_2.32.0
## [11] S4Vectors_0.36.0 BiocGenerics_0.44.0
## [13] MatrixGenerics_1.10.0 matrixStats_0.62.0
## [15] TCGAbiolinks_2.26.0 testthat_3.1.5
##
## loaded via a namespace (and not attached):
## [1] aroma.light_3.28.0 BiocFileCache_2.6.0
## [3] plyr_1.8.7 splines_4.2.1
## [5] BiocParallel_1.32.0 crosstalk_1.2.0
## [7] usethis_2.1.6 ggplot2_3.3.6
## [9] digest_0.6.30 htmltools_0.5.3
## [11] fansi_1.0.3 magrittr_2.0.3
## [13] memoise_2.0.1 tzdb_0.3.0
## [15] remotes_2.4.2 Biostrings_2.66.0
## [17] readr_2.1.3 R.utils_2.12.1
## [19] vroom_1.6.0 prettyunits_1.1.1
## [21] colorspace_2.0-3 blob_1.2.3
## [23] rvest_1.0.3 rappdirs_0.3.3
## [25] xfun_0.34 callr_3.7.2
## [27] crayon_1.5.2 RCurl_1.98-1.9
## [29] jsonlite_1.8.3 survival_3.4-0
## [31] glue_1.6.2 gtable_0.3.1
## [33] zlibbioc_1.44.0 XVector_0.38.0
## [35] DelayedArray_0.24.0 pkgbuild_1.3.1
## [37] scales_1.2.1 DBI_1.1.3
## [39] miniUI_0.1.1.1 Rcpp_1.0.9
## [41] xtable_1.8-4 progress_1.2.2
## [43] archive_1.1.5 bit_4.0.4
## [45] profvis_0.3.7 htmlwidgets_1.5.4
## [47] httr_1.4.4 RColorBrewer_1.1-3
## [49] ellipsis_0.3.2 urlchecker_1.0.1
## [51] pkgconfig_2.0.3 XML_3.99-0.12
## [53] R.methodsS3_1.8.2 deldir_1.0-6
## [55] sass_0.4.2 dbplyr_2.2.1
## [57] utf8_1.2.2 DNAcopy_1.72.0
## [59] tidyselect_1.2.0 rlang_1.0.6
## [61] later_1.3.0 AnnotationDbi_1.60.0
## [63] munsell_0.5.0 tools_4.2.1
## [65] cachem_1.0.6 downloader_0.4
## [67] cli_3.4.1 generics_0.1.3
## [69] RSQLite_2.2.18 devtools_2.4.5
## [71] evaluate_0.17 stringr_1.4.1
## [73] fastmap_1.1.0 yaml_2.3.6
## [75] processx_3.8.0 knitr_1.40
## [77] bit64_4.0.5 fs_1.5.2
## [79] purrr_0.3.5 KEGGREST_1.38.0
## [81] EDASeq_2.32.0 mime_0.12
## [83] R.oo_1.25.0 xml2_1.3.3
## [85] biomaRt_2.54.0 BiocStyle_2.26.0
## [87] brio_1.1.3 compiler_4.2.1
## [89] rstudioapi_0.14 filelock_1.0.2
## [91] curl_4.3.3 tibble_3.1.8
## [93] bslib_0.4.0 stringi_1.7.8
## [95] highr_0.9 ps_1.7.2
## [97] GenomicFeatures_1.50.0 TCGAbiolinksGUI.data_1.17.0
## [99] desc_1.4.2 lattice_0.20-45
## [101] Matrix_1.5-1 vctrs_0.5.0
## [103] pillar_1.8.1 lifecycle_1.0.3
## [105] BiocManager_1.30.19 jquerylib_0.1.4
## [107] data.table_1.14.4 bitops_1.0-7
## [109] rtracklayer_1.58.0 httpuv_1.6.6
## [111] latticeExtra_0.6-30 hwriter_1.3.2.1
## [113] BiocIO_1.8.0 R6_2.5.1
## [115] ShortRead_1.56.0 promises_1.2.0.1
## [117] sessioninfo_1.2.2 codetools_0.2-18
## [119] assertthat_0.2.1 pkgload_1.3.1
## [121] rjson_0.2.21 rprojroot_2.0.3
## [123] withr_2.5.0 GenomicAlignments_1.34.0
## [125] Rsamtools_2.14.0 GenomeInfoDbData_1.2.9
## [127] parallel_4.2.1 hms_1.1.2
## [129] tidyr_1.2.1 rmarkdown_2.17
## [131] shiny_1.7.3 interp_1.1-3
## [133] restfulr_0.0.15