Compilation of TCGA molecular subtypes
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:
Session Information
## R version 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.5 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.16-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB 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 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_0.25
## [5] dplyr_1.0.10 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_0.5.3
## [11] fansi_1.0.3 magrittr_2.0.3
## [13] memoise_2.0.1 tzdb_0.3.0
## [15] remotes_2.4.2 Biostrings_2.65.6
## [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_1.0.3 rappdirs_0.3.3
## [25] xfun_0.33 callr_3.7.2
## [27] crayon_1.5.1 RCurl_1.98-1.8
## [29] jsonlite_1.8.0 survival_3.4-0
## [31] glue_1.6.2 gtable_0.3.1
## [33] zlibbioc_1.43.0 XVector_0.37.1
## [35] DelayedArray_0.23.2 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] bit_4.0.4 profvis_0.3.7
## [45] htmlwidgets_1.5.4 httr_1.4.4
## [47] RColorBrewer_1.1-3 ellipsis_0.3.2
## [49] urlchecker_1.0.1 pkgconfig_2.0.3
## [51] XML_3.99-0.10 R.methodsS3_1.8.2
## [53] deldir_1.0-6 sass_0.4.2
## [55] dbplyr_2.2.1 utf8_1.2.2
## [57] DNAcopy_1.71.0 tidyselect_1.1.2
## [59] rlang_1.0.5 later_1.3.0
## [61] AnnotationDbi_1.59.1 munsell_0.5.0
## [63] tools_4.2.1 cachem_1.0.6
## [65] downloader_0.4 cli_3.4.0
## [67] generics_0.1.3 RSQLite_2.2.17
## [69] devtools_2.4.4 evaluate_0.16
## [71] stringr_1.4.1 fastmap_1.1.0
## [73] yaml_2.3.5 processx_3.7.0
## [75] knitr_1.40 bit64_4.0.5
## [77] fs_1.5.2 purrr_0.3.4
## [79] KEGGREST_1.37.3 EDASeq_2.31.0
## [81] mime_0.12 R.oo_1.25.0
## [83] xml2_1.3.3 biomaRt_2.53.2
## [85] BiocStyle_2.25.0 brio_1.1.3
## [87] compiler_4.2.1 rstudioapi_0.14
## [89] filelock_1.0.2 curl_4.3.2
## [91] tibble_3.1.8 bslib_0.4.0
## [93] stringi_1.7.8 highr_0.9
## [95] ps_1.7.1 GenomicFeatures_1.49.7
## [97] TCGAbiolinksGUI.data_1.17.0 desc_1.4.2
## [99] lattice_0.20-45 Matrix_1.5-1
## [101] vctrs_0.4.1 pillar_1.8.1
## [103] lifecycle_1.0.2 BiocManager_1.30.18
## [105] jquerylib_0.1.4 data.table_1.14.2
## [107] bitops_1.0-7 rtracklayer_1.57.0
## [109] httpuv_1.6.6 latticeExtra_0.6-30
## [111] hwriter_1.3.2.1 BiocIO_1.7.1
## [113] R6_2.5.1 ShortRead_1.55.0
## [115] promises_1.2.0.1 sessioninfo_1.2.2
## [117] codetools_0.2-18 assertthat_0.2.1
## [119] pkgload_1.3.0 rjson_0.2.21
## [121] rprojroot_2.0.3 withr_2.5.0
## [123] GenomicAlignments_1.33.1 Rsamtools_2.13.4
## [125] GenomeInfoDbData_1.2.8 parallel_4.2.1
## [127] hms_1.1.2 tidyr_1.2.1
## [129] rmarkdown_2.16 shiny_1.7.2
## [131] interp_1.1-3 restfulr_0.0.15