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:
subtypes <- PanCancerAtlas_subtypes()
DT::datatable(subtypes,
filter = '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.
A subset of the LGG subytpe is shown below:
## R version 4.2.0 (2022-04-22)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.4 LTS
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## BLAS: /home/biocbuild/bbs-3.15-bioc/R/lib/libRblas.so
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## attached base packages:
## [1] grid stats4 stats graphics grDevices utils datasets
## [8] methods base
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## other attached packages:
## [1] maftools_2.12.0 jpeg_0.1-9
## [3] png_0.1-7 DT_0.23
## [5] dplyr_1.0.9 SummarizedExperiment_1.26.1
## [7] Biobase_2.56.0 GenomicRanges_1.48.0
## [9] GenomeInfoDb_1.32.2 IRanges_2.30.0
## [11] S4Vectors_0.34.0 BiocGenerics_0.42.0
## [13] MatrixGenerics_1.8.0 matrixStats_0.62.0
## [15] TCGAbiolinks_2.24.3 testthat_3.1.4
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## loaded via a namespace (and not attached):
## [1] colorspace_2.0-3 hwriter_1.3.2.1
## [3] rjson_0.2.21 ellipsis_0.3.2
## [5] rprojroot_2.0.3 DNAcopy_1.70.0
## [7] XVector_0.36.0 fs_1.5.2
## [9] rstudioapi_0.13 remotes_2.4.2
## [11] bit64_4.0.5 AnnotationDbi_1.58.0
## [13] fansi_1.0.3 xml2_1.3.3
## [15] splines_4.2.0 codetools_0.2-18
## [17] R.methodsS3_1.8.2 cachem_1.0.6
## [19] knitr_1.39 pkgload_1.2.4
## [21] jsonlite_1.8.0 Rsamtools_2.12.0
## [23] dbplyr_2.2.0 R.oo_1.25.0
## [25] BiocManager_1.30.18 readr_2.1.2
## [27] compiler_4.2.0 httr_1.4.3
## [29] assertthat_0.2.1 Matrix_1.4-1
## [31] fastmap_1.1.0 cli_3.3.0
## [33] htmltools_0.5.2 prettyunits_1.1.1
## [35] tools_4.2.0 gtable_0.3.0
## [37] glue_1.6.2 GenomeInfoDbData_1.2.8
## [39] rappdirs_0.3.3 ShortRead_1.54.0
## [41] Rcpp_1.0.8.3 jquerylib_0.1.4
## [43] vctrs_0.4.1 Biostrings_2.64.0
## [45] rtracklayer_1.56.0 crosstalk_1.2.0
## [47] xfun_0.31 stringr_1.4.0
## [49] ps_1.7.0 brio_1.1.3
## [51] rvest_1.0.2 lifecycle_1.0.1
## [53] restfulr_0.0.15 devtools_2.4.3
## [55] XML_3.99-0.10 zlibbioc_1.42.0
## [57] scales_1.2.0 aroma.light_3.26.0
## [59] BiocStyle_2.24.0 vroom_1.5.7
## [61] hms_1.1.1 parallel_4.2.0
## [63] RColorBrewer_1.1-3 yaml_2.3.5
## [65] curl_4.3.2 memoise_2.0.1
## [67] ggplot2_3.3.6 downloader_0.4
## [69] sass_0.4.1 biomaRt_2.52.0
## [71] latticeExtra_0.6-29 stringi_1.7.6
## [73] RSQLite_2.2.14 highr_0.9
## [75] BiocIO_1.6.0 desc_1.4.1
## [77] GenomicFeatures_1.48.3 filelock_1.0.2
## [79] BiocParallel_1.30.3 pkgbuild_1.3.1
## [81] rlang_1.0.2 pkgconfig_2.0.3
## [83] bitops_1.0-7 evaluate_0.15
## [85] TCGAbiolinksGUI.data_1.16.0 lattice_0.20-45
## [87] purrr_0.3.4 GenomicAlignments_1.32.0
## [89] htmlwidgets_1.5.4 bit_4.0.4
## [91] processx_3.6.0 tidyselect_1.1.2
## [93] plyr_1.8.7 magrittr_2.0.3
## [95] R6_2.5.1 generics_0.1.2
## [97] DelayedArray_0.22.0 DBI_1.1.2
## [99] pillar_1.7.0 withr_2.5.0
## [101] survival_3.3-1 KEGGREST_1.36.2
## [103] RCurl_1.98-1.7 EDASeq_2.30.0
## [105] tibble_3.1.7 crayon_1.5.1
## [107] utf8_1.2.2 BiocFileCache_2.4.0
## [109] tzdb_0.3.0 rmarkdown_2.14
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## [117] tidyr_1.2.0 R.utils_2.11.0
## [119] munsell_0.5.0 bslib_0.3.1
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