# 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.

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

A subset of the LGG subytpe is shown below:

# Session Information

    sessionInfo()

    ## R version 4.2.0 (2022-04-22 ucrt)
    ## Platform: x86_64-w64-mingw32/x64 (64-bit)
    ## Running under: Windows Server x64 (build 20348)
    ##
    ## Matrix products: default
    ##
    ## locale:
    ## [1] LC_COLLATE=C
    ## [2] LC_CTYPE=English_United States.utf8
    ## [3] LC_MONETARY=English_United States.utf8
    ## [4] LC_NUMERIC=C
    ## [5] LC_TIME=English_United States.utf8
    ##
    ## attached base packages:
    ## [1] grid      stats4    stats     graphics  grDevices utils     datasets
    ## [8] methods   base
    ##
    ## 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
    ##
    ## 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
    ## [111] progress_1.2.2              usethis_2.1.6
    ## [113] data.table_1.14.2           blob_1.2.3
    ## [115] callr_3.7.0                 digest_0.6.29
    ## [117] tidyr_1.2.0                 R.utils_2.11.0
    ## [119] munsell_0.5.0               bslib_0.3.1
    ## [121] sessioninfo_1.2.2