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 (2022-06-23)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Monterey 12.5
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
##
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] grid stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] maftools_2.13.0 jpeg_0.1-9
## [3] png_0.1-7 DT_0.23
## [5] dplyr_1.0.9 SummarizedExperiment_1.27.3
## [7] Biobase_2.57.1 GenomicRanges_1.49.1
## [9] GenomeInfoDb_1.33.7 IRanges_2.31.2
## [11] S4Vectors_0.35.4 BiocGenerics_0.43.4
## [13] MatrixGenerics_1.9.1 matrixStats_0.62.0
## [15] TCGAbiolinks_2.25.3 testthat_3.1.4
##
## loaded via a namespace (and not attached):
## [1] aroma.light_3.27.0 BiocFileCache_2.5.0
## [3] plyr_1.8.7 splines_4.2.1
## [5] BiocParallel_1.31.12 crosstalk_1.2.0
## [7] usethis_2.1.6 ggplot2_3.3.6
## [9] digest_0.6.29 htmltools_0.5.2
## [11] fansi_1.0.3 magrittr_2.0.3
## [13] memoise_2.0.1 tzdb_0.3.0
## [15] remotes_2.4.2 Biostrings_2.65.6
## [17] readr_2.1.2 R.utils_2.12.0
## [19] vroom_1.5.7 prettyunits_1.1.1
## [21] colorspace_2.0-3 blob_1.2.3
## [23] rvest_1.0.2 rappdirs_0.3.3
## [25] xfun_0.31 callr_3.7.1
## [27] crayon_1.5.1 RCurl_1.98-1.7
## [29] jsonlite_1.8.0 survival_3.3-1
## [31] glue_1.6.2 gtable_0.3.0
## [33] zlibbioc_1.43.0 XVector_0.37.1
## [35] DelayedArray_0.23.2 pkgbuild_1.3.1
## [37] scales_1.2.0 DBI_1.1.3
## [39] Rcpp_1.0.9 progress_1.2.2
## [41] bit_4.0.4 htmlwidgets_1.5.4
## [43] httr_1.4.3 RColorBrewer_1.1-3
## [45] ellipsis_0.3.2 pkgconfig_2.0.3
## [47] XML_3.99-0.10 R.methodsS3_1.8.2
## [49] sass_0.4.1 dbplyr_2.2.1
## [51] deldir_1.0-6 utf8_1.2.2
## [53] DNAcopy_1.71.0 tidyselect_1.1.2
## [55] rlang_1.0.4 AnnotationDbi_1.59.1
## [57] munsell_0.5.0 tools_4.2.1
## [59] cachem_1.0.6 downloader_0.4
## [61] cli_3.3.0 generics_0.1.3
## [63] RSQLite_2.2.14 devtools_2.4.3
## [65] evaluate_0.15 stringr_1.4.0
## [67] fastmap_1.1.0 yaml_2.3.5
## [69] processx_3.7.0 knitr_1.39
## [71] bit64_4.0.5 fs_1.5.2
## [73] purrr_0.3.4 KEGGREST_1.37.3
## [75] EDASeq_2.31.0 R.oo_1.25.0
## [77] xml2_1.3.3 biomaRt_2.53.2
## [79] BiocStyle_2.25.0 brio_1.1.3
## [81] compiler_4.2.1 rstudioapi_0.13
## [83] filelock_1.0.2 curl_4.3.2
## [85] tibble_3.1.7 bslib_0.3.1
## [87] stringi_1.7.8 highr_0.9
## [89] ps_1.7.1 TCGAbiolinksGUI.data_1.17.0
## [91] GenomicFeatures_1.49.7 desc_1.4.1
## [93] lattice_0.20-45 Matrix_1.4-1
## [95] vctrs_0.4.1 pillar_1.7.0
## [97] lifecycle_1.0.1 BiocManager_1.30.18
## [99] jquerylib_0.1.4 data.table_1.14.2
## [101] bitops_1.0-7 rtracklayer_1.57.0
## [103] R6_2.5.1 BiocIO_1.7.1
## [105] latticeExtra_0.6-30 hwriter_1.3.2.1
## [107] ShortRead_1.55.0 sessioninfo_1.2.2
## [109] codetools_0.2-18 assertthat_0.2.1
## [111] pkgload_1.3.0 rprojroot_2.0.3
## [113] rjson_0.2.21 withr_2.5.0
## [115] GenomicAlignments_1.33.1 Rsamtools_2.13.4
## [117] GenomeInfoDbData_1.2.8 parallel_4.2.1
## [119] hms_1.1.1 tidyr_1.2.0
## [121] rmarkdown_2.14 interp_1.1-3
## [123] restfulr_0.0.15