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Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer
Open accessAbstract
We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development.
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“The nature of these mutations differs for each cancer [90] and in each individual [90,91,92].”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [92]
Experimental — accuracy not yet measuredIn the citing paper
“First, although tumors are readily recognized through gene expression signatures, they retain transcriptomic features of the parental tissue so that tumors arising in the same organ are more similar to each other than tumors arising in different organs.”
From Metabolic reprogramming and cancer progression (2020) · cites this paper as [3]
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“A study that classified thousands of human tumors found that tissue of origin was a major factor defining DNA methylation and gene expression patterns (3).”
From Metabolic reprogramming and cancer progression (2020) · cites this paper as [3]
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Cites
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Nishimura, R., Osako, T., Nishiyama, Y., Tashima, R., Nakano, M., Fujisue, M., Toyozumi, Y., & Arima, N. (2013) · Oncology · doi:10.1159/000353099 · Cited by 13,239
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
Integrated genomic analyses of ovarian carcinoma
Perou, C. M. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/hvp3-wg08 · Cited by 7,927
Self-citationThe Immune Landscape of Cancer
Thorsson, V., Gibbs, D. L., Brown, S. D., Wolf, D., Bortone, D. S., Ou Yang, T.-H., Porta-Pardo, E., Gao, G. F., Plaisier, C. L., Eddy, J. A., et al. (2018) · Immunity · doi:10.1016/j.immuni.2018.03.023 · Cited by 5,870 · cited 4×
“Immune-signaling subtypes identified in Thorsson et al. (2018) also co-localized on the TumorMap, indicating relationships between the iClusters, histopathology, and the types of immune infiltration (Figure 5B).”
BackgroundInfluentialSelf-citationIntegrated genomic characterization of endometrial carcinoma
The Cancer Genome Atlas Research Network, & Levine, D. A. (2013) · Nature · doi:10.1038/nature12113 · Cited by 5,784
Self-citationComprehensive molecular profiling of lung adenocarcinoma
The Cancer Genome Atlas Research Network (2014) · Nature · doi:10.1038/nature13385 · Cited by 5,732 · cited 2×
“…of stemness, attesting to their underlying molecular heterogeneity, as previously reported (Cancer Genome Atlas Network, 2015; Cancer Genome Atlas Research Network, 2011, 2012, 2014a, 2014b, 2015a, 2015b, 2017; Cancer Genome Atlas Research Network et al., 2013a, 2013b; Robertson et al., 2017).”
BackgroundConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking
Wilkerson, M. D., & Hayes, D. N. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq170 · Cited by 5,645 · cited 1×
“Unsupervised consensus clustering using Consensus Cluster Plus (Wilkerson and Hayes, 2010) was performed on 10,165 tumors with 15,363 genes.”
MethodSelf-citationMutational heterogeneity in cancer and the search for new cancer-associated genes
Lawrence, M. S., Stojanov, P., Polak, P., Kryukov, G. V., Cibulskis, K., Sivachenko, A., Carter, S. L., Stewart, C., Mermel, C. H., Roberts, S. A., et al. (2013) · Nature · doi:10.1038/nature12213 · Cited by 5,461 · cited 6×
“Eight iClusters were dominated by a single tumor type (C24:LAML, C11:LGG [IDH1 mut], C6:OV, C8:UCEC, C12:THCA, C16:PRAD, C26:LIHC, C14:LUAD).”
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- Malta, 2018, Comprehensive analysis of cancer stemness, Cell, 173
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Items 101–200 of 1,002
Arruabarrena-Aristorena, A., Maag, J. L. V., Kittane, S., Cai, Y., Karthaus, W. R., Ladewig, E., Park, J., Kannan, S., Ferrando, L., Cocco, E., et al. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.08.003 · Cited by 130
“Analysis from The Cancer Genome Atlas (TCGA, PanCancer Atlas [Hoadley et al., 2018]), a cohort almost exclusively comprised of primary breast cancer samples, revealed a lower frequency of FOXA1 mutations, with a higher proportion of lesions occurring at the H1 helix (Figures S1C–S1E).”
MethodSelf-citationBarriga, F. M., Tsanov, K. M., Ho, Y.-J., Sohail, N., Zhang, A., Baslan, T., Wuest, A. N., Del Priore, I., Meškauskaitė, B., Livshits, G., et al. (2022) · Nature Cancer · doi:10.1038/s43018-022-00443-5 · Cited by 125
Mammary stem cells and progenitors: targeting the roots of breast cancer for prevention
Tharmapalan, P., Mahendralingam, M. J., Berman, H. K., & Khokha, R. (2019) · The EMBO Journal · doi:10.15252/embj.2018100852 · Cited by 126
Cytotoxic lymphocytes target characteristic biophysical vulnerabilities in cancer
Tello‐Lafoz, M., Srpan, K., Sanchez, E. E., Hu, J. Y., Remšík, J., Romin, Y., Calò, A., Hoen, D. R., Bhanot, U. K., Morris, L. G. T., et al. (2021) · Immunity · doi:10.1016/j.immuni.2021.02.020 · Cited by 129
Self-citationMolecular Pathology of Primary Non-small Cell Lung Cancer
Suster, D. I., & Mino-Kenudson, M. A. (2020) · Archives of Medical Research · doi:10.1016/j.arcmed.2020.08.004 · Cited by 130
Integrative clinical and molecular characterization of translocation renal cell carcinoma
Bakouny, Z., Sadagopan, A., Ravi, P. K., Metaferia, N. Y., Li, J., AbuHammad, S., Tang, S., Denize, T., Garner, E. R., Gao, X. Y., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2021.110190 · Cited by 123
Self-citationEpigenetic dysregulation from chromosomal transit in micronuclei
Agustinus, A. S., Al-Rawi, D. H., Dameracharla, B., Raviram, R., Jones, B. S. C. L., Stransky, S., Scipioni, L., Luebeck, J., Bona, M. D., Norkūnaitė, D., et al. (2023) · Nature · doi:10.1038/s41586-023-06084-7 · Cited by 130
“Epigenetic reprogramming is a key driver of tumorigenesis and recent studies have identified numerous alterations in epigenetic modifying enzymes as a source for abnormalities seen in cancer [3, 31-36].”
BackgroundCHASMplus Reveals the Scope of Somatic Missense Mutations Driving Human Cancers
Tokheim, C. J., & Karchin, R. (2019) · Cell Systems · doi:10.1016/j.cels.2019.05.005 · Cited by 134
Carcinogenicity assessment: Addressing the challenges of cancer and chemicals in the environment
Madia, F., Worth, A. P., Whelan, M., & Corvi, R. (2019) · Environment International · doi:10.1016/j.envint.2019.04.067 · Cited by 124
Deep transfer learning for reducing health care disparities arising from biomedical data inequality
Gao, Y., & Cui, Y. (2020) · Nature Communications · doi:10.1038/s41467-020-18918-3 · Cited by 138
Development and validation of a prognostic and predictive 32-gene signature for gastric cancer
Cheong, J., Wang, S. C., Park, S., Porembka, M. R., Christie, A. L., Kim, H., Kim, H. S., Zhu, H., Hyung, W. J., Noh, S. H., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28437-y · Cited by 120
Self-citationAn approach for normalization and quality control for NanoString RNA expression data
Bhattacharya, A., Hamilton, A. M., Furberg, H., Pietzak, E., Purdue, M. P., Troester, M. A., Hoadley, K. A., & Love, M. I. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa163 · Cited by 122
Self-citationUse of ctDNA in early breast cancer: analytical validity and clinical potential
Panet, F., Papakonstantinou, A., Borrell, M., Vivancos, J., Vivancos, A. P., & Oliveira, M. (2024) · npj Breast Cancer · doi:10.1038/s41523-024-00653-3 · Cited by 126
“DNAmethylation,whichoccursprimarilyonacytosineringwithincytosine-guanine(CpG)dinucleotides,isimportanttocontrolgeneexpression,andits patternsareknowntobethebestcell-of-originbiomarker 32,33 .”
DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse
Zhou, W., Hinoue, T., Barnes, B., Mitchell, O. D., Iqbal, W., Lee, S. M., Foy, K. K., Lee, K., Moyer, E. J., VanderArk, A., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100144 · Cited by 116
“Large-scale projects, including The Cancer Genome Atlas (TCGA) (Hoadley et al., 2018), cover additional tens of thousands of samples, not deposited at GEO.”
BackgroundSelf-citationUniversal cancer screening: revolutionary, rational, and realizable
Ahlquist, D. A. (2018) · npj Precision Oncology · doi:10.1038/s41698-018-0066-x · Cited by 135
Development of synthetic lethality in cancer: molecular and cellular classification
Li, S., Topatana, W., Juengpanich, S., Cao, J., Hu, J., Zhang, B., Ma, D., Cai, X., & Chen, M. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-00358-6 · Cited by 123
Self-citationQu, H. Y., Zhou, M., Yan, Z., Wang, H., Rustgi, V. K., Zhang, S., Gevaert, O., & Metaxas, D. (2021) · npj Precision Oncology · doi:10.1038/s41698-021-00225-9 · Cited by 119
“We did not fi ne-tune models for all possible gene pro fi les from TCGA, because the point mutation and CNA percentage of some genes are extremely low in lung or liver cancers.”
MethodInfluentialA Human Adult Stem Cell Signature Marks Aggressive Variants across Epithelial Cancers
Smith, B. A., Balanis, N. G., Nanjundiah, A., Sheu, K. M., Tsai, B. L., Zhang, Q., Park, J. W., Thompson, M. J., Huang, J., Witte, O. N., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.08.062 · Cited by 116
Self-citationBhat‐Nakshatri, P., Gao, H., Liu, S., McGuire, P. C., Xuei, X., Wan, J., Liu, Y., Althouse, S. K., Colter, A. B., Sandusky, G. E., et al. (2020) · Cell Reports Medicine · doi:10.1016/j.xcrm.2021.100219 · Cited by 115
“Although it is not possible to definitively link cancer to its cell of origin,(12) a recent pan-cancer analysis revealed cell-of-origin gene signatures are dominant in tumors.(11) To determine whether such a relationship exists between signatures of normal breast epithelial cell clusters and breast tumors, we compared…”
BackgroundResultSelf-citationTipifarnib as a Precision Therapy for HRAS -Mutant Head and Neck Squamous Cell Carcinomas
Gilardi, M., Wang, Z., Proietto, M., Chillà, A., Calleja-Valera, J. L., Goto, Y., Vanoni, M., Janes, M. R., Mikulski, Z., Gualberto, A., et al. (2020) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-19-0958 · Cited by 115
Self-citationMolecular analysis of TCGA breast cancer histologic types
Thennavan, A., de Beça, F. F., Xia, Y., García‐Recio, S., Allison, K. H., Collins, L. C., Tse, G. M.-K., Chen, Y., Schnitt, S. J., Hoadley, K. A., et al. (2021) · Cell Genomics · doi:10.1016/j.xgen.2021.100067 · Cited by 114
Self-citationDreßler, L., Bortolomeazzi, M., Keddar, M. R., Mišetić, H., Sartini, G., Acha‐Sagredo, A., Montorsi, L., Wijewardhane, N., Repana, D., Nulsen, J., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02607-z · Cited by 119
“Cancer types and non-cancer tissues were mapped to organ systems using previous classification [72].”
MethodMETTL1 promotes tumorigenesis through tRNA-derived fragment biogenesis in prostate cancer
García-Vílchez, R., Añazco-Guenkova, A. M., Dietmann, S., López, J., Morón-Calvente, V., D’Ambrosi, S., Nombela, P., Zamacola, K., Mendizabal, I., Garcia‐Longarte, S., et al. (2023) · Molecular Cancer · doi:10.1186/s12943-023-01809-8 · Cited by 118
“0 [89] were used to assess cellular abundance and cell type-specific gene expression patterns from bulk tissue transcriptome data obtained from The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) collection [152] using cBioPortal [153, 154] and Taylor datasets [6].”
MethodIntegrative Analysis Defines Distinct Prognostic Subgroups of Intrahepatic Cholangiocarcinoma
Goeppert, B. F., Tóth, R., Singer, S., Albrecht, T., Lipka, D. B., Lutsik, P., Brocks, D., Baehr, M., Muecke, O., Assenov, Y., et al. (2019) · Hepatology · doi:10.1002/hep.30493 · Cited by 112
Self-citationLee, B. Y., Hogg, E. K. J., Below, C., Kononov, A., Blanco‐Gómez, A., Heider, F., Xu, J., Hutton, C., Zhang, X. M., Scheidt, T., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27607-8 · Cited by 115
Beyond sequencing: machine learning algorithms extract biology hidden in Nanopore signal data
Wan, Y. K., Hendra, C., Pratanwanich, P. N., & Göke, J. (2021) · Trends in Genetics · doi:10.1016/j.tig.2021.09.001 · Cited by 111
Self-citationÉlez, E., Ros, J., Navarro, J. F., Villacampa, G. J., Moreno-Cárdenas, A. B., Arenillas, C., Bernatowicz, K., Comas, R., Li, S., Kodack, D. P., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01976-z · Cited by 111
Methylation biomarkers for early cancer detection and diagnosis: Current and future perspectives
Ibrahim, J., Peeters, M., Camp, G. V., & de Beeck, K. O. (2022) · European Journal of Cancer · doi:10.1016/j.ejca.2022.10.015 · Cited by 116
ERBB3 mutations in cancer: biological aspects, prevalence and therapeutics
Kiavué, N., Cabel, L., Melaabi, S., Bataillon, G., Callens, C., Lerebours, F., Pierga, J., & Bidard, F. (2019) · Oncogene · doi:10.1038/s41388-019-1001-5 · Cited by 109
“3 Position of hotspot or characterized missense mutations on the HER3 protein sequence, with the absolute number of cases found in the Memorial Sloan Kettering (MSK) IMPACT [80] cohort and in the TCGA PanCancer Atlas [81] displayed for each mutation (figure modified from cBioPortal).”
BackgroundThe Cancer Microbiome: Recent Highlights and Knowledge Gaps
Knippel, R. J., Drewes, J. L., & Sears, C. L. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0324 · Cited by 112
FGFR4 regulates tumor subtype differentiation in luminal breast cancer and metastatic disease
García‐Recio, S., Thennavan, A., East, M. P., Parker, J. S., Cejalvo, J. M., Garay, J. P., Hollern, D. P., He, X., Mott, K. R., Galván, P., et al. (2020) · Journal of Clinical Investigation · doi:10.1172/jci130323 · Cited by 109
Self-citationMekonnen, N., Yang, H., & Shin, Y. K. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.880643 · Cited by 117
Self-citationAccelerating the understanding of cancer biology through the lens of genomics
Wang, D., Liu, B., & Zhang, Z. (2023) · Cell · doi:10.1016/j.cell.2023.02.015 · Cited by 116
Chromatin-remodeling links metabolic signaling to gene expression
Morrison, A. J. (2020) · Molecular Metabolism · doi:10.1016/j.molmet.2020.100973 · Cited by 112
“Importantly, increased glycogen storage and decreased expression of genes in the oxidative phosphorylation pathway are dependent on loss of PBRM1 and VHL.”
BackgroundInfluentialSun, H., Cao, S., Mashl, R. J., Mo, C.-K., Zaccaria, S., Wendl, M. C., Davies, S. R., Bailey, M. H., Primeau, T. M., Hoog, J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25177-3 · Cited by 104
Self-citationCheteh, E. H., Sarne, V., Ceder, S., Bianchi, J., Augsten, M., Rundqvist, H., Egevad, L., Östman, A., & Wiman, K. G. (2020) · Cell Death Discovery · doi:10.1038/s41420-020-0272-5 · Cited by 105
Patient-derived tumor-like cell clusters for drug testing in cancer therapy
Yin, S., Xi, R., Wu, A., Wang, S., Li, Y., Wang, C., Tang, L., Xia, Y., Yang, D., Li, J., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aaz1723 · Cited by 104
Self-citationMoving pan-cancer studies from basic research toward the clinic
Chen, F., Wendl, M. C., Wyczalkowski, M. A., Bailey, M. H., Li, Y., & Ding, L. (2021) · Nature Cancer · doi:10.1038/s43018-021-00250-4 · Cited by 108
Self-citationGenome-wide analysis of somatic noncoding mutation patterns in cancer
Dietlein, F., Wang, A. B., Fagre, C. R., Tang, A., Besselink, N. J. M., Cuppen, E. P. J. G., Li, C., Sunyaev, S. R., Neal, J. T., & Allen, E. M. V. (2022) · Science · doi:10.1126/science.abg5601 · Cited by 103
Liang, W.-W., Lu, R. J.-H., Jayasinghe, R. G., Foltz, S. M., Porta-Pardo, E., Geffen, Y., Wendl, M. C., Lazcano, R., Kolodziejczak, I., Song, Y., et al. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.07.013 · Cited by 105
Self-citationPowell, S., Vu, L., Spanos, W., & Pyeon, D. (2021) · Cancers · doi:10.3390/cancers13205206 · Cited by 98
Emerging epigenomic landscapes of pancreatic cancer in the era of precision medicine
Lomberk, G. A., Dusetti, N., Iovanna, J., & Urrutia, R. A. (2019) · Nature Communications · doi:10.1038/s41467-019-11812-7 · Cited by 101
Zhu, T., Liu, J., Beck, S., Pan, S., Capper, D., Lechner, M., Thirlwell, C., Breeze, C. E., & Teschendorff, A. E. (2022) · Nature Methods · doi:10.1038/s41592-022-01412-7 · Cited by 103
Self-citationGlutathione Metabolism in Renal Cell Carcinoma Progression and Implications for Therapies
Xiao, Y., & Meierhofer, D. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20153672 · Cited by 104
“Instead, the cancer classification should be based on the similarity of molecular features across different tissue types, which was considered to be more relevant for targeting the same mutations and oncogenic signaling pathways [21].”
BackgroundTargeting DNA repair in cancer: current state and novel approaches
Klinakis, A., Karagiannis, D., & Rampias, T. N. (2019) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-019-03299-8 · Cited by 108
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InfluentialSidders, B. S., Zhang, P., Goodwin, K., O’Connor, G., Russell, D. L., Borodovsky, A., Armenia, J., McEwen, R. K., Linghu, B., Bendell, J. C., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-2183 · Cited by 104
“(28), and associated clinical data were taken from ref.”
BackgroundSelf-citationXu, J., Shao, T., Song, M., Xie, Y., Zhou, J., Yin, J., Ding, N., Zou, H., Li, Y., & Zhang, J. (2020) · Molecular Cancer · doi:10.1186/s12943-020-01174-w · Cited by 103
Self-citationEmergence of ERBB2 Mutation as a Biomarker and an Actionable Target in Solid Cancers
Subramanian, J., Katta, A., Masood, A., Vudem, D. R., & Kancha, R. K. (2019) · The Oncologist · doi:10.1634/theoncologist.2018-0845 · Cited by 105
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Roelands, J. P., Hendrickx, W., Zoppoli, G. M., Mall, R., Saad, M., Halliwill, K. D., Curigliano, G., Rinchai, D., Decock, J. V., Delogu, L. G., et al. (2020) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2020-000617 · Cited by 100
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Shi, X., Li, Y., Yuan, Q., Tang, S., Guo, S., Zhang, Y., He, J., Zhang, X., Han, M., Liu, Z., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29857-6 · Cited by 103
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Weiss, J. M., Hunter, M. V., Cruz, N. M., Baggiolini, A., Tagore, M. M., Ma, Y., Misale, S., Marasco, M., Simon-Vermot, T., Campbell, N. R., et al. (2022) · Nature · doi:10.1038/s41586-022-04584-6 · Cited by 102
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Colaprico, A., Olsen, C., Bailey, M. H., Odom, G., Terkelsen, T., Silva, T. C., Olsen, A. V., Cantini, L., Zinovyev, A. Y., Barillot, E., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-13803-0 · Cited by 101
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Duran‐Ferrer, M., Clot, G., Nadeu, F., Beekman, R., Baumann, T., Nordlund, J., Marincevic-Zuniga, Y., Lönnerholm, G., Rivas‐Delgado, A., Martín, S., et al. (2020) · Nature Cancer · doi:10.1038/s43018-020-00131-2 · Cited by 102
Self-citationLobular Breast Cancer: Histomorphology and Different Concepts of a Special Spectrum of Tumors
Christgen, M., Cserni, G., Floris, G., Marchiò, C., Djerroudi, L., Kreipe, H. H., Derksen, P. W. B., & Vincent‐Salomon, A. (2021) · Cancers · doi:10.3390/cancers13153695 · Cited by 108
Dunbar, A. J., Bolton, K. L., Devlin, S. M., Sánchez-Vega, F., Gao, J., Mones, J. V., Wills, J., Kelly, D., Farina, M., Cordner, K. B., et al. (2020) · Blood · doi:10.1182/blood.2020007488 · Cited by 105
Self-citationTsujita, K., Satow, R., Asada, S., Nakamura, Y., Arnes, L., Sako, K., Fujita, Y., Fukami, K., & Itoh, T. (2021) · Nature Communications · doi:10.1038/s41467-021-26156-4 · Cited by 101
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Pan, Y., Han, H., Hu, H., Wang, H., Song, Y., Yuan, H., Tong, X., Patel, A. S., Misirlioğlu, S., Tang, S., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.11.015 · Cited by 97
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Wang, T., Ruan, S., Zhao, X., Shi, X., Teng, H., Zhong, J., You, M., Xia, K., Sun, Z. S., & Mao, F. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1033 · Cited by 93
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Wu, J., Li, C., Gensheimer, M. F., Padda, S. K., Kato, F., Shirato, H., Wei, Y., Schönlieb, C., Price, S. J., Jaffray, D. A., et al. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00377-0 · Cited by 98
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Montagud, A., Béal, J., Tobalina, L., Traynard, P., Subramanian, V., Szalai, B., Alföldi, R., Puskás, L. G., Valencia, A., Barillot, E., et al. (2022) · eLife · doi:10.7554/elife.72626 · Cited by 98
Tagliazucchi, G. M., Wiecek, A. J., Withnell, E., & Secrier, M. (2023) · Nature Communications · doi:10.1038/s41467-023-36439-7 · Cited by 98
Association between PD1 mRNA and response to anti-PD1 monotherapy across multiple cancer types
Paré, L., Pascual, T., Seguí, E., Teixidó, C., González‐Cao, M., Galván, P., Rodríguez, A., González‐Farré, B., Cuatrecasas, M., Pineda, E., et al. (2018) · Annals of Oncology · doi:10.1093/annonc/mdy335 · Cited by 98
MAPK activity dynamics regulate non-cell autonomous effects of oncogene expression
Aikin, T. J., Peterson, A. F., Pokrass, M. J., Clark, H. R., & Regot, S. (2020) · eLife · doi:10.7554/elife.60541 · Cited by 94
Pan-cancer analysis of genomic scar patterns caused by homologous repair deficiency (HRD)
Rempel, E., Kluck, K., Beck, S., Ourailidis, I., Kazdal, D. N., Neumann, O., Volckmar, A., Kirchner, M., Goldschmid, H., Pfarr, N., et al. (2022) · npj Precision Oncology · doi:10.1038/s41698-022-00276-6 · Cited by 98
Conway, A., Mitchell, C. L., Kilgour, E., Brady, G., Dive, C., & Cook, N. (2018) · British Journal of Cancer · doi:10.1038/s41416-018-0332-2 · Cited by 95
Genetic variation associated with condensate dysregulation in disease
Banani, S. F., Afeyan, L. K., Hawken, S. W., Henninger, J. E., Dall’Agnese, A., Clark, V. E., Platt, J. M., Oksuz, O., Hannett, N. M., Sagi, I., et al. (2022) · Developmental Cell · doi:10.1016/j.devcel.2022.06.010 · Cited by 93
Longitudinal single-cell profiling of chemotherapy response in acute myeloid leukemia
Naldini, M. M., Casirati, G., Barcella, M., Rancoita, P. M. V., Cosentino, A., Caserta, C., Pavesi, F., Zonari, E., Desantis, G., Gilioli, D., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36969-0 · Cited by 97
Cancer aneuploidies are shaped primarily by effects on tumour fitness
Shih, J., Sarmashghi, S., Zhakula-Kostadinova, N., Zhang, S., Georgis, Y., Hoyt, S. H., Cuoco, M. S., Gao, G. F., Spurr, L. F., Berger, A. C., et al. (2023) · Nature · doi:10.1038/s41586-023-06266-3 · Cited by 108
Self-citationProtein codes promote selective subcellular compartmentalization
Kilgore, H. R., Chinn, I., Mikhael, P. G., Mitnikov, I., Van Dongen, C., Zylberberg, G., Afeyan, L., Banani, S. F., Wilson-Hawken, S., Lee, T. I., et al. (2025) · Science · doi:10.1126/science.adq2634 · Cited by 99
Ashley, C. W., Paula, A. D. C., Kumar, R., Mandelker, D. L., Pei, X., Riaz, N., Reis-Filho, J. S., & Weigelt, B. (2018) · Gynecologic Oncology · doi:10.1016/j.ygyno.2018.10.032 · Cited by 94
Molecular profile of bladder cancer progression to clinically aggressive subtypes
Guo, C. C., Lee, S., Lee, J. G., Chen, H., Zaleski, M. P., Choi, W., McConkey, D. J., Wei, P., & Czerniak, B. A. (2024) · Nature Reviews Urology · doi:10.1038/s41585-023-00847-7 · Cited by 99
“Sarcomatoid carcinomas have high mutational loads similar to those in conventional urothelial carcinoma, melanoma and non-small-cell lung cancers 58 .”
Self-citationRahmanto, Y. S., Shen, W., Shi, X., Chen, X. X., Yu, Y., Yu, Z.-C., Miyamoto, T., Lee, M.-H., Singh, V., Asaka, R., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16416-0 · Cited by 91
Self-citationZaritsky, A., Jamieson, A. R., Welf, E. S., Nevarez, A. J., Cillay, J., Eskiocak, U., Cantarel, B. L., & Danuser, G. M. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.003 · Cited by 91
Spurr, L. F., Martinez, C. A., Kang, W., Chen, M., Zha, Y., Hseu, R. D., Gutiontov, S. I., Turchan, W. T., Lynch, C. M., Pointer, K. B., et al. (2022) · Nature Cancer · doi:10.1038/s43018-022-00467-x · Cited by 96
Genome-wide mapping of somatic mutation rates uncovers drivers of cancer
Sherman, M. A., Yaari, A. U., Priebe, O., Dietlein, F., Loh, P.-R., & Berger, B. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01353-8 · Cited by 80
Self-citationLee, M. S., & Sanoff, H. K. (2020) · BMJ · doi:10.1136/bmj.m4050 · Cited by 87
Colonic Adenocarcinomas Harboring NTRK Fusion Genes
Lasota, J. P., Chłopek, M., Lamoureux, J., Christiansen, J., Kowalik, A., Wasąg, B., Felisiak-Gołąbek, A., Agaimy, A., Biernat, W., Canzonieri, V., et al. (2019) · The American Journal of Surgical Pathology · doi:10.1097/pas.0000000000001377 · Cited by 91
Self-citationAssociation ofMUC16Mutation With Response to Immune Checkpoint Inhibitors in Solid Tumors
Zhang, L., Han, X., & Shi, Y. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.13201 · Cited by 89
Self-citationTargeting Pim kinases in hematological cancers: molecular and clinical review
Bellon, M., & Nicot, C. (2023) · Molecular Cancer · doi:10.1186/s12943-023-01721-1 · Cited by 89
“BCGSC-13 [95], DLBCL from Broad-12 [96], DLBCL from DFCI-18 [94], and DLBCL from TCGA [98].”
BackgroundZeng, C., Stroup, E. K., Zhang, Z., Chiu, B. C. ‐., & Zhang, W. (2019) · 癌症:英文版 · doi:10.1186/s40880-019-0356-x · Cited by 90
Self-citationRemoving unwanted variation from large-scale RNA sequencing data with PRPS
Molania, R., Foroutan, M., Gagnon-Bartsch, J. A., Gandolfo, L. C., Jain, A., Sinha, A., Olshansky, G., Dobrovic, A., Papenfuss, A. T., & Speed, T. P. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01440-w · Cited by 92
“The idea of pseudo-replicates has also been used to remove batch effects in TCGA RNA-seq data with the unpublished algorithm EB ++ 56 .”
MethodDayton, T. L., Alcala, N., Moonen, L., den Hartigh, L., Geurts, V., Mangiante, L., Lap, L. M. V., Dost, A. F. M., Beumer, J., Levy, S., et al. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.11.007 · Cited by 89
“Whereas mLCNEC23 PDTOs were resistant to both single-agent treatments and their combination, BRAF -mutant LNET10 PDTOs were sensitive to all treatments (area under the fitted dose response curve—AUC—for combination, 186 and 96, respectively).”
Sorrentino, C., D’Antonio, L., Fieni, C., Ciummo, S. L., & Carlo, E. D. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.778329 · Cited by 92
Mo, S. P., Coulson, J. M., & Prior, I. A. (2018) · Biochemical Society Transactions · doi:10.1042/bst20180173 · Cited by 85
Daugan, M. V., Revel, M., Russick, J., Dragon‐Durey, M., Gaboriaud, C., Robe-Rybkine, T., Poillerat, V., Grünenwald, A., Lacroix, G., Bougoüin, A., et al. (2021) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-20-0532 · Cited by 87
“C1S gene expression in patients with ccRCC from TCGA was associated with a poor prognosis (Fig.”
BackgroundInfluentialCo-occurrence and mutual exclusivity: what cross-cancer mutation patterns can tell us
Tekle, G. E., Bernasocchi, T., Unni, A. M., Bertoni, F., Rossi, D., Rubin, M. A., & Theurillat, J.-P. P. (2021) · Trends in cancer · doi:10.1016/j.trecan.2021.04.009 · Cited by 89
Self-citationMa, X., Riaz, N., Samstein, R. M., Lee, M., Makarov, V., Valero, C., Chowell, D., Kuo, F., Hoen, D. R., Fitzgerald, C. W. R., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01108-w · Cited by 87
Self-citationLeveraging big data of immune checkpoint blockade response identifies novel potential targets
Barèche, Y., Kelly, D., Aghababazadeh, F. A., Nakano, M., Esfahani, P. N., Tkachuk, D., Mohammad, H., Samstein, R. M., Lee, C., Morris, L. G. T., et al. (2022) · Annals of Oncology · doi:10.1016/j.annonc.2022.08.084 · Cited by 85
Nadendla, E. K., Tweedell, R. E., Kasof, G. M., & Kanneganti, T. (2025) · Cell Discovery · doi:10.1038/s41421-025-00791-3 · Cited by 95
TCPA v3.0: An Integrative Platform to Explore the Pan-Cancer Analysis of Functional Proteomic Data
Chen, M.-J. M., Li, J., Wang, Y., Akbani, R., Lu, Y., Mills, G. B., & Liang, H. (2019) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra118.001260 · Cited by 84
Self-citationLi, Y., Umbach, D. M., Krahn, J. M., Shats, I., Li, X., & Li, L. (2021) · BMC Genomics · doi:10.1186/s12864-021-07581-7 · Cited by 88
“While pan-cancer classification and prediction using transcriptomic data have been successfully applied for identification of biomarkers and of cancer subtypes as well as for prediction of disease progression [66 – 68], clinical cancer treatment options are often in part guided by oncomutations.”
BackgroundPredicting master transcription factors from pan-cancer expression data
Reddy, J., Fonseca, M. A., Corona, R. I., Nameki, R. A., Dezem, F. S., Klein, I. A., Chang, H. S. Y., Chaves‐Moreira, D., Afeyan, L. K., Malta, T. M., et al. (2021) · Science Advances · doi:10.1126/sciadv.abf6123 · Cited by 82
Self-citationThe Project Baseline Health Study: a step towards a broader mission to map human health
Arges, K., Assimes, T., Bajaj, V., Balu, S., Bashir, M. R., Beskow, L., Blanco, R., Califf, R., Campbell, P., Carin, L., et al. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0290-y · Cited by 82
Self-citationWeeden, C. E., Gayevskiy, V., Marceaux, C., Batey, D., Tan, T., Yokote, K., Ribera, N. T., Clatch, A., Christo, S. N., Teh, C. E., et al. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.03.019 · Cited by 83
A multimodal graph neural network framework for cancer molecular subtype classification
Li, B., & Nabavi, S. (2024) · BMC Bioinformatics · doi:10.1186/s12859-023-05622-4 · Cited by 96
“The first is cancer molecular subtype classification on the TCGA Pan-cancer dataset and the second is breast cancer subtype classification on the TCGA breast invasive carcinoma (BRCA) dataset [15, 30].”
BackgroundMethodA census of pathway maps in cancer systems biology
Kuenzi, B. M., & Ideker, T. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-0240-7 · Cited by 82
Parsons, L. P., Challa, S., Gibson, B. A., Nandu, T. S., Stokes, M. S., Huang, D., Lea, J. S., & Kraus, W. L. (2021) · eLife · doi:10.7554/elife.60481 · Cited by 83
Vedanayagam, J., Chatila, W. K., Aksoy, B. A., Majumdar, S., Skanderup, A. J., Demir, E., Schultz, N. D., Sander, C., & Lai, E. C. (2019) · Nature Communications · doi:10.1038/s41467-019-11610-1 · Cited by 79
Self-citationDetection and relevance of epigenetic markers on ctDNA: recent advances and future outlook
Lianidou, E. S. (2021) · Molecular Oncology · doi:10.1002/1878-0261.12978 · Cited by 80
Cell-type heterogeneity: Why we should adjust for it in epigenome and biomarker studies
Qi, L., & Teschendorff, A. E. (2022) · Clinical Epigenetics · doi:10.1186/s13148-022-01253-3 · Cited by 78
Metadata
- Authors
- Hoadley, K. A., Yau, C., Hinoue, T., Wolf, D. M., Lazar, A. J., Drill, E., Shen, R., Taylor, A. M., Cherniack, A. D., Thorsson, V., Akbani, R., Bowlby, R., Wong, C. K., Wiznerowicz, M., Sanchez-Vega, F., Robertson, A. G., Schneider, B. G., Lawrence, M. S., Noushmehr, H., Malta, T. M., Caesar-Johnson, S. J., Demchok, J. A., Felau, I., Kasapi, M., Ferguson, M. L., Hutter, C. M., Sofia, H. J., Tarnuzzer, R., Wang, Z., Yang, L., Zenklusen, J. C., Zhang, J. (., Chudamani, S., Liu, J., Lolla, L., Naresh, R., Pihl, T., Sun, Q., Wan, Y., Wu, Y., Cho, J., DeFreitas, T., Frazer, S., Gehlenborg, N., Getz, G., Heiman, D. I., Kim, J., Lawrence, M. S., Lin, P., Meier, S., Noble, M. S., Saksena, G., Voet, D., Zhang, H., Bernard, B., Chambwe, N., Dhankani, V., Knijnenburg, T., Kramer, R., Leinonen, K., Liu, Y., Miller, M., Reynolds, S., Shmulevich, I., Thorsson, V., Zhang, W., Akbani, R., Broom, B. M., Hegde, A. M., Ju, Z., Kanchi, R. S., Korkut, A., Li, J., Liang, H., Ling, S., Liu, W., Lu, Y., Mills, G. B., Ng, K.-S., Rao, A., Ryan, M., Wang, J., Weinstein, J. N., Zhang, J., Abeshouse, A., Armenia, J., Chakravarty, D., Chatila, W. K., de Bruijn, I., Gao, J., Gross, B. E., Heins, Z. J., Kundra, R., La, K., Ladanyi, M., Luna, A., Nissan, M. G., Ochoa, A., Phillips, S. M., Reznik, E., Sanchez-Vega, F., Sander, C., Schultz, N., Sheridan, R., Sumer, S. O., Sun, Y., Taylor, B. S., Wang, J., Zhang, H., Anur, P., Peto, M., Spellman, P., Benz, C., Stuart, J. M., Wong, C. K., Yau, C., Hayes, D. N., Parker, J. S., Wilkerson, M. D., Ally, A., Balasundaram, M., Bowlby, R., Brooks, D., Carlsen, R., Chuah, E., Dhalla, N., Holt, R., Jones, S. J. M., Kasaian, K., Lee, D., Ma, Y., Marra, M. A., Mayo, M., Moore, R. A., Mungall, A. J., Mungall, K., Robertson, A. G., Sadeghi, S., Schein, J. E., Sipahimalani, P., Tam, A., Thiessen, N., Tse, K., Wong, T., Berger, A. C., Beroukhim, R., Cherniack, A. D., Cibulskis, C., Gabriel, S. B., Gao, G. F., Ha, G., Meyerson, M., Schumacher, S. E., Shih, J., Kucherlapati, M. H., Kucherlapati, R. S., Baylin, S., Cope, L., Danilova, L., Bootwalla, M. S., Lai, P. H., Maglinte, D. T., Van Den Berg, D. J., Weisenberger, D. J., Auman, J. T., Balu, S., Bodenheimer, T., Fan, C., Hoadley, K. A., Hoyle, A. P., Jefferys, S. R., Jones, C. D., Meng, S., Mieczkowski, P. A., Mose, L. E., Perou, A. H., Perou, C. M., Roach, J., Shi, Y., Simons, J. V., Skelly, T., Soloway, M. G., Tan, D., Veluvolu, U., Fan, H., Hinoue, T., Laird, P. W., Shen, H., Zhou, W., Bellair, M., Chang, K., Covington, K., Creighton, C. J., Dinh, H., Doddapaneni, H., Donehower, L. A., Drummond, J., Gibbs, R. A., Glenn, R., Hale, W., Han, Y., Hu, J., Korchina, V., Lee, S., Lewis, L., Li, W., Liu, X., Morgan, M., Morton, D., Muzny, D., Santibanez, J., Sheth, M., Shinbrot, E., Wang, L., Wang, M., Wheeler, D. A., Xi, L., Zhao, F., Hess, J., Appelbaum, E. L., Bailey, M., Cordes, M. G., Ding, L., Fronick, C. C., Fulton, L. A., Fulton, R. S., Kandoth, C., Mardis, E. R., McLellan, M. D., Miller, C. A., Schmidt, H. K., Wilson, R. K., Crain, D., Curley, E., Gardner, J., Lau, K., Mallery, D., Morris, S., Paulauskis, J., Penny, R., Shelton, C., Shelton, T., Sherman, M., Thompson, E., Yena, P., Bowen, J., Gastier-Foster, J. M., Gerken, M., Leraas, K. M., Lichtenberg, T. M., Ramirez, N. C., Wise, L., Zmuda, E., Corcoran, N., Costello, T., Hovens, C., Carvalho, A. L., de Carvalho, A. C., Fregnani, J. H., Longatto-Filho, A., Reis, R. M., Scapulatempo-Neto, C., Silveira, H. C. S., Vidal, D. O., Burnette, A., Eschbacher, J., Hermes, B., Noss, A., Singh, R., Anderson, M. L., Castro, P. D., Ittmann, M., Huntsman, D., Kohl, B., Le, X., Thorp, R., Andry, C., Duffy, E. R., Lyadov, V., Paklina, O., Setdikova, G., Shabunin, A., Tavobilov, M., McPherson, C., Warnick, R., Berkowitz, R., Cramer, D., Feltmate, C., Horowitz, N., Kibel, A., Muto, M., Raut, C. P., Malykh, A., Barnholtz-Sloan, J. S., Barrett, W., Devine, K., Fulop, J., Ostrom, Q. T., Shimmel, K., Wolinsky, Y., Sloan, A. E., De Rose, A., Giuliante, F., Goodman, M., Karlan, B. Y., Hagedorn, C. H., Eckman, J., Harr, J., Myers, J., Tucker, K., Zach, L. A., Deyarmin, B., Hu, H., Kvecher, L., Larson, C., Mural, R. J., Somiari, S., Vicha, A., Zelinka, T., Bennett, J., Iacocca, M., Rabeno, B., Swanson, P., Latour, M., Lacombe, L., Têtu, B., Bergeron, A., McGraw, M., Staugaitis, S. M., Chabot, J., Hibshoosh, H., Sepulveda, A., Su, T., Wang, T., Potapova, O., Voronina, O., Desjardins, L., Mariani, O., Roman-Roman, S., Sastre, X., Stern, M.-H., Cheng, F., Signoretti, S., Berchuck, A., Bigner, D., Lipp, E., Marks, J., McCall, S., McLendon, R., Secord, A., Sharp, A., Behera, M., Brat, D. J., Chen, A., Delman, K., Force, S., Khuri, F., Magliocca, K., Maithel, S., Olson, J. J., Owonikoko, T., Pickens, A., Ramalingam, S., Shin, D. M., Sica, G., Van Meir, E. G., Zhang, H., Eijckenboom, W., Gillis, A., Korpershoek, E., Looijenga, L., Oosterhuis, W., Stoop, H., van Kessel, K. E., Zwarthoff, E. C., Calatozzolo, C., Cuppini, L., Cuzzubbo, S., DiMeco, F., Finocchiaro, G., Mattei, L., Perin, A., Pollo, B., Chen, C., Houck, J., Lohavanichbutr, P., Hartmann, A., Stoehr, C., Stoehr, R., Taubert, H., Wach, S., Wullich, B., Kycler, W., Murawa, D., Wiznerowicz, M., Chung, K., Edenfield, W. J., Martin, J., Baudin, E., Bubley, G., Bueno, R., De Rienzo, A., Richards, W. G., Kalkanis, S., Mikkelsen, T., Noushmehr, H., Scarpace, L., Girard, N., Aymerich, M., Campo, E., Giné, E., Guillermo, A. L., Van Bang, N., Hanh, P. T., Phu, B. D., Tang, Y., Colman, H., Evason, K., Dottino, P. R., Martignetti, J. A., Gabra, H., Juhl, H., Akeredolu, T., Stepa, S., Hoon, D., Ahn, K., Kang, K. J., Beuschlein, F., Breggia, A., Birrer, M., Bell, D., Borad, M., Bryce, A. H., Castle, E., Chandan, V., Cheville, J., Copland, J. A., Farnell, M., Flotte, T., Giama, N., Ho, T., Kendrick, M., Kocher, J.-P., Kopp, K., Moser, C., Nagorney, D., O’Brien, D., O’Neill, B. P., Patel, T., Petersen, G., Que, F., Rivera, M., Roberts, L., Smallridge, R., Smyrk, T., Stanton, M., Thompson, R. H., Torbenson, M., Yang, J. D., Zhang, L., Brimo, F., Ajani, J. A., Gonzalez, A. M. A., Behrens, C., Bondaruk, O., Broaddus, R., Czerniak, B., Esmaeli, B., Fujimoto, J., Gershenwald, J., Guo, C., Lazar, A. J., Logothetis, C., Meric-Bernstam, F., Moran, C., Ramondetta, L., Rice, D., Sood, A., Tamboli, P., Thompson, T., Troncoso, P., Tsao, A., Wistuba, I., Carter, C., Haydu, L., Hersey, P., Jakrot, V., Kakavand, H., Kefford, R., Lee, K., Long, G., Mann, G., Quinn, M., Saw, R., Scolyer, R., Shannon, K., Spillane, A., Stretch, J., Synott, M., Thompson, J., Wilmott, J., Al-Ahmadie, H., Chan, T. A., Ghossein, R., Gopalan, A., Levine, D. A., Reuter, V., Singer, S., Singh, B., Tien, N. V., Broudy, T., Mirsaidi, C., Nair, P., Drwiega, P., Miller, J., Smith, J., Zaren, H., Park, J.-W., Hung, N. P., Kebebew, E., Linehan, W. M., Metwalli, A. R., Pacak, K., Pinto, P. A., Schiffman, M., Schmidt, L. S., Vocke, C. D., Wentzensen, N., Worrell, R., Yang, H., Moncrieff, M., Goparaju, C., Melamed, J., Pass, H., Botnariuc, N., Caraman, I., Cernat, M., Chemencedji, I., Clipca, A., Doruc, S., Gorincioi, G., Mura, S., Pirtac, M., Stancul, I., Tcaciuc, D., Albert, M., Alexopoulou, I., Arnaout, A., Bartlett, J., Engel, J., Gilbert, S., Parfitt, J., Sekhon, H., Thomas, G., Rassl, D. M., Rintoul, R. C., Bifulco, C., Tamakawa, R., Urba, W., Hayward, N., Timmers, H., Antenucci, A., Facciolo, F., Grazi, G., Marino, M., Merola, R., de Krijger, R., Gimenez-Roqueplo, A.-P., Piché, A., Chevalier, S., McKercher, G., Birsoy, K., Barnett, G., Brewer, C., Farver, C., Naska, T., Pennell, N. A., Raymond, D., Schilero, C., Smolenski, K., Williams, F., Morrison, C., Borgia, J. A., Liptay, M. J., Pool, M., Seder, C. W., Junker, K., Omberg, L., Dinkin, M., Manikhas, G., Alvaro, D., Bragazzi, M. C., Cardinale, V., Carpino, G., Gaudio, E., Chesla, D., Cottingham, S., Dubina, M., Moiseenko, F., Dhanasekaran, R., Becker, K.-F., Janssen, K.-P., Slotta-Huspenina, J., Abdel-Rahman, M. H., Aziz, D., Bell, S., Cebulla, C. M., Davis, A., Duell, R., Elder, J. B., Hilty, J., Kumar, B., Lang, J., Lehman, N. L., Mandt, R., Nguyen, P., Pilarski, R., Rai, K., Schoenfield, L., Senecal, K., Wakely, P., Hansen, P., Lechan, R., Powers, J., Tischler, A., Grizzle, W. E., Sexton, K. C., Kastl, A., Henderson, J., Porten, S., Waldmann, J., Fassnacht, M., Asa, S. L., Schadendorf, D., Couce, M., Graefen, M., Huland, H., Sauter, G., Schlomm, T., Simon, R., Tennstedt, P., Olabode, O., Nelson, M., Bathe, O., Carroll, P. R., Chan, J. M., Disaia, P., Glenn, P., Kelley, R. K., Landen, C. N., Phillips, J., Prados, M., Simko, J., Smith-McCune, K., VandenBerg, S., Roggin, K., Fehrenbach, A., Kendler, A., Sifri, S., Steele, R., Jimeno, A., Carey, F., Forgie, I., Mannelli, M., Carney, M., Hernandez, B., Campos, B., Herold-Mende, C., Jungk, C., Unterberg, A., von Deimling, A., Bossler, A., Galbraith, J., Jacobus, L., Knudson, M., Knutson, T., Ma, D., Milhem, M., Sigmund, R., Godwin, A. K., Madan, R., Rosenthal, H. G., Adebamowo, C., Adebamowo, S. N., Boussioutas, A., Beer, D., Giordano, T., Mes-Masson, A.-M., Saad, F., Bocklage, T., Landrum, L., Mannel, R., Moore, K., Moxley, K., Postier, R., Walker, J., Zuna, R., Feldman, M., Valdivieso, F., Dhir, R., Luketich, J., Pinero, E. M. M., Quintero-Aguilo, M., Carlotti, C. G., Dos Santos, J. S., Kemp, R., Sankarankuty, A., Tirapelli, D., Catto, J., Agnew, K., Swisher, E., Creaney, J., Robinson, B., Shelley, C. S., Godwin, E. M., Kendall, S., Shipman, C., Bradford, C., Carey, T., Haddad, A., Moyer, J., Peterson, L., Prince, M., Rozek, L., Wolf, G., Bowman, R., Fong, K. M., Yang, I., Korst, R., Rathmell, W. K., Fantacone-Campbell, J. L., Hooke, J. A., Kovatich, A. J., Shriver, C. D., DiPersio, J., Drake, B., Govindan, R., Heath, S., Ley, T., Van Tine, B., Westervelt, P., Rubin, M. A., Lee, J. I., Aredes, N. D., Mariamidze, A., Stuart, J. M., Benz, C. C., & Laird, P. W.
- Affiliations
- University of California, San Francisco (US)
- Memorial Sloan Kettering Cancer Center (US)
- Broad Institute (US)
- Vanderbilt University Medical Center (US)
- Henry Ford Health (US)
- Buck Institute for Research on Aging (US)
- Van Andel Institute (US)
- BC Cancer Agency (CA)
- Institute for Systems Biology (US)
- The University of Texas MD Anderson Cancer Center (US)
- University of California, Santa Cruz (US)
- University of North Carolina at Chapel Hill (US)
- Poznan University of Medical Sciences (PL)
- Corresponding author
- Felau, Ina
- Nissan, Moriah G.
- Weisenberger, Daniel J.
- Jones, Corbin D.
- Bellair, Michelle
- Mallery, David
- Oosterhuis, Wolter
- Kefford, Richard
- Vocke, Cathy D.
- Zuna, Rosemary
- Rubin, Mark A.
- Aredes, Natália D.
- ORCID
- Wolf, Denise M.
- Drill, Esther
- Shen, Ronglai
- Taylor, Alison M.
- Schneider, Barbara G.
- Malta, Tathiane M.
- Felau, Ina
- Kasapi, Melpomeni
- Ferguson, Martin L.
- Sofia, Heidi J.
- Tarnuzzer, Roy
- Yang, Liming
- Zenklusen, Jean C.
- Zhang, Jiashan (Julia)
- Liu, Jia
- Pihl, Todd
- Sun, Qiang
- Wu, Ye
- Gehlenborg, Nils
- Getz, Gad
- Heiman, David I.
- Kim, Jaegil
- Lin, Pei
- Noble, Michael S.
- Saksena, Gordon
- Zhang, Hailei
- Bernard, Brady
- Chambwe, Nyasha
- Knijnenburg, Theo
- Liu, Yuexin
- Miller, Michael
- Shmulevich, Ilya
- Zhang, Wei
- Broom, Bradley M.
- Hegde, Apurva M.
- Ju, Zhenlin
- Korkut, Anil
- Li, Jun
- Liang, Han
- Lu, Yiling
- Mills, Gordon B.
- Wang, Jing
- Weinstein, John N.
- Zhang, Jiexin
- Armenia, Joshua
- Chakravarty, Debyani
- Chatila, Walid K.
- Gross, Benjamin E.
- Heins, Zachary J.
- Kundra, Ritika
- Ladanyi, Marc
- Luna, Augustin
- Ochoa, Angelica
- Phillips, Sarah M.
- Reznik, Ed
- Sander, Chris
- Schultz, Nikolaus
- Sun, Yichao
- Taylor, Barry S.
- Zhang, Hongxin
- Spellman, Paul
- Hayes, D. Neil
- Parker, Joel S.
- Wilkerson, Matthew D.
- Holt, Robert
- Jones, Steven J.M.
- Marra, Marco A.
- Moore, Richard A.
- Mungall, Andrew J.
- Sadeghi, Sara
- Tam, Angela
- Wong, Tina
- Berger, Ashton C.
- Beroukhim, Rameen
- Cibulskis, Carrie
- Gabriel, Stacey B.
- Ha, Gavin
- Meyerson, Matthew
- Schumacher, Steven E.
- Shih, Juliann
- Kucherlapati, Melanie H.
- Kucherlapati, Raju S.
- Baylin, Stephen
- Cope, Leslie
- Danilova, Ludmila
- Maglinte, Dennis T.
- Weisenberger, Daniel J.
- Auman, J. Todd
- Hoyle, Alan P.
- Jones, Corbin D.
- Mieczkowski, Piotr A.
- Perou, Charles M.
- Roach, Jeffrey
- Shi, Yan
- Fan, Huihui
- Shen, Hui
- Zhou, Wanding
- Chang, Kyle
- Covington, Kyle
- Creighton, Chad J.
- Dinh, Huyen
- Doddapaneni, HarshaVardhan
- Gibbs, Richard A.
- Han, Yi
- Korchina, Viktoriya
- Liu, Xiuping
- Morgan, Margaret
- Muzny, Donna
- Sheth, Margi
- Shinbrot, Eve
- Wang, Linghua
- Wang, Min
- Wheeler, David A.
- Zhao, Fengmei
- Hess, Julian
- Bailey, Matthew
- Ding, Li
- Fronick, Catrina C.
- Fulton, Robert S.
- Kandoth, Cyriac
- Mardis, Elaine R.
- McLellan, Michael D.
- Miller, Christopher A.
- Wilson, Richard K.
- Sherman, Mark
- Bowen, Jay
- Leraas, Kristen M.
- Lichtenberg, Tara M.
- Ramirez, Nilsa C.
- Zmuda, Erik
- Corcoran, Niall
- Hovens, Christopher
- Fregnani, José H.
- Reis, Rui M.
- Silveira, Henrique C.S.
- Vidal, Daniel O.
- Anderson, Matthew L.
- Ittmann, Michael
- Huntsman, David
- Kohl, Bernard
- Andry, Chris
- Duffy, Elizabeth R.
- Lyadov, Vladimir
- Paklina, Oxana
- Setdikova, Galiya
- Tavobilov, Mikhail
- Warnick, Ronald
- Berkowitz, Ross
- Feltmate, Colleen
- Horowitz, Neil
- Kibel, Adam
- Raut, Chandrajit P.
- Ostrom, Quinn T.
- Sloan, Andrew E.
- Giuliante, Felice
- Goodman, Marc
- Karlan, Beth Y.
- Somiari, Stella
- Bennett, Joseph
- Iacocca, Mary
- Lacombe, Louis
- Têtu, Bernard
- Bergeron, Alain
- McGraw, Mary
- Hibshoosh, Hanina
- Sepulveda, Antonia
- Wang, Timothy
- Potapova, Olga
- Voronina, Olga
- Desjardins, Laurence
- Mariani, Odette
- Stern, Marc-Henri
- Cheng, Feixiong
- Signoretti, Sabina
- Berchuck, Andrew
- Bigner, Darell
- Lipp, Eric
- McCall, Shannon
- McLendon, Roger
- Secord, Angeles
- Behera, Madhusmita
- Brat, Daniel J.
- Chen, Amy
- Delman, Keith
- Force, Seth
- Khuri, Fadlo
- Magliocca, Kelly
- Maithel, Shishir
- Olson, Jeffrey J.
- Owonikoko, Taofeek
- Ramalingam, Suresh
- Shin, Dong M.
- Sica, Gabriel
- Zhang, Hongzheng
- Looijenga, Leendert
- Oosterhuis, Wolter
- Zwarthoff, Ellen C.
- Calatozzolo, Chiara
- Cuzzubbo, Stefania
- DiMeco, Francesco
- Finocchiaro, Gaetano
- Mattei, Luca
- Perin, Alessandro
- Pollo, Bianca
- Taubert, Helge
- Wach, Sven
- Wullich, Bernd
- Kycler, Witold
- Murawa, Dawid
- Martin, Julie
- Bubley, Glenn
- Bueno, Raphael
- Richards, William G.
- Kalkanis, Steven
- Mikkelsen, Tom
- Scarpace, Lisa
- Girard, Nicolas
- Aymerich, Marta
- Giné, Eva
- Tang, Yufang
- Colman, Howard
- Evason, Kimberley
- Gabra, Hani
- Juhl, Hartmut
- Hoon, Dave
- Kang, Koo Jeong
- Beuschlein, Felix
- Breggia, Anne
- Birrer, Michael
- Borad, Mitesh
- Bryce, Alan H.
- Chandan, Vishal
- Cheville, John
- Copland, John A.
- Flotte, Thomas
- Ho, Thai
- Kendrick, Michael
- Kocher, Jean-Pierre
- Nagorney, David
- O’Brien, Daniel
- O’Neill, Brian Patrick
- Patel, Tushar
- Rivera, Michael
- Roberts, Lewis
- Smyrk, Thomas
- Torbenson, Michael
- Yang, Ju Dong
- Zhang, Lizhi
- Brimo, Fadi
- Ajani, Jaffer A.
- Behrens, Carmen
- Broaddus, Russell
- Czerniak, Bogdan
- Esmaeli, Bita
- Fujimoto, Junya
- Guo, Charles
- Logothetis, Christopher
- Ramondetta, Lois
- Sood, Anil
- Troncoso, Patricia
- Tsao, Anne
- Wistuba, Ignacio
- Carter, Candace
- Haydu, Lauren
- Jakrot, Valerie
- Kakavand, Hojabr
- Kefford, Richard
- Lee, Kenneth
- Long, Georgina
- Mann, Graham
- Quinn, Michael
- Saw, Robyn
- Scolyer, Richard
- Shannon, Kerwin
- Spillane, Andrew
- Stretch, Jonathan
- Thompson, John
- Wilmott, James
- Chan, Timothy A.
- Ghossein, Ronald
- Gopalan, Anuradha
- Levine, Douglas A.
- Singer, Samuel
- Singh, Bhuvanesh
- Broudy, Thomas
- Nair, Praveen
- Zaren, Howard
- Park, Joong-Won
- Kebebew, Electron
- Linehan, W. Marston
- Metwalli, Adam R.
- Pinto, Peter A.
- Schiffman, Mark
- Schmidt, Laura S.
- Vocke, Cathy D.
- Wentzensen, Nicolas
- Yang, Hannah
- Moncrieff, Marc
- Goparaju, Chandra
- Melamed, Jonathan
- Pass, Harvey
- Cernat, Mircea
- Arnaout, Angel
- Bartlett, John
- Thomas, George
- Rassl, Doris M.
- Rintoul, Robert C.
- Bifulco, Carlo
- Urba, Walter
- Hayward, Nicholas
- Timmers, Henri
- Facciolo, Francesco
- Marino, Mirella
- Piché, Alain
- Chevalier, Simone
- McKercher, Ginette
- Barnett, Gene
- Farver, Carol
- Pennell, Nathan A.
- Borgia, Jeffrey A.
- Seder, Christopher W.
- Junker, Kerstin
- Omberg, Larsson
- Manikhas, George
- Alvaro, Domenico
- Bragazzi, Maria Consiglia
- Cardinale, Vincenzo
- Carpino, Guido
- Gaudio, Eugenio
- Dubina, Michael
- Moiseenko, Fedor
- Dhanasekaran, Renumathy
- Becker, Karl-Friedrich
- Janssen, Klaus-Peter
- Cebulla, Colleen M.
- Elder, J. Bradley
- Lehman, Norman L.
- Nguyen, Phuong
- Pilarski, Robert
- Rai, Karan
- Schoenfield, Lynn
- Wakely, Paul
- Lechan, Ronald
- Tischler, Arthur
- Grizzle, William E.
- Henderson, Joel
- Porten, Sima
- Fassnacht, Martin
- Asa, Sylvia L.
- Schadendorf, Dirk
- Couce, Marta
- Graefen, Markus
- Huland, Hartwig
- Sauter, Guido
- Schlomm, Thorsten
- Simon, Ronald
- Tennstedt, Pierre
- Nelson, Mark
- Bathe, Oliver
- Carroll, Peter R.
- Chan, June M.
- Kelley, Robin K.
- Landen, Charles N.
- Prados, Michael
- VandenBerg, Scott
- Roggin, Kevin
- Kendler, Ady
- Steele, Ruth
- Jimeno, Antonio
- Forgie, Ian
- Mannelli, Massimo
- Carney, Michael
- Campos, Benito
- Unterberg, Andreas
- Bossler, Aaron
- Ma, Deqin
- Milhem, Mohammed
- Godwin, Andrew K.
- Madan, Rashna
- Adebamowo, Clement
- Adebamowo, Sally N.
- Boussioutas, Alex
- Beer, David
- Giordano, Thomas
- Bocklage, Therese
- Landrum, Lisa
- Moore, Kathleen
- Moxley, Katherine
- Zuna, Rosemary
- Feldman, Michael
- Luketich, James
- Carlotti, Carlos Gilberto
- Kemp, Rafael
- Tirapelli, Daniela
- Catto, James
- Swisher, Elizabeth
- Creaney, Jenette
- Robinson, Bruce
- Shelley, Carl Simon
- Bradford, Carol
- Carey, Thomas
- Prince, Mark
- Rozek, Laura
- Wolf, Gregory
- Fong, Kwun M.
- Yang, Ian
- Rathmell, W. Kimryn
- Kovatich, Albert J.
- Shriver, Craig D.
- DiPersio, John
- Drake, Bettina
- Govindan, Ramaswamy
- Heath, Sharon
- Ley, Timothy
- Rubin, Mark A.
- Lee, Jung Il
- Aredes, Natália D.
- Mariamidze, Armaz
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 173
- Issue
- 2
- Pages
- 291-304.e6
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC5957518
- OpenAlex
- W2796153844
- Cited by
- 2,546
- References
- 58
- Citations by year
- 2026: 284 · 2025: 294 · 2024: 296 · 2023: 355 · 2022: 375 · 2021: 374 · 2020: 330 · 2019: 178 · 2018: 56
- FWCI
- 71.94
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (acceptedVersion, cc-by-nc-nd)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by-nc-nd)
- UWA Profiles and Research Repository (UWA) (submittedVersion, cc-by)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- Bern Open Repository and Information System (University of Bern) (submittedVersion, cc-by-nc-nd)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- eScholarship (California Digital Library) (submittedVersion)
- Florence Research (University of Florence) (submittedVersion)
- IRIS Research product catalog (Sapienza University of Rome) (submittedVersion, cc-by-nc-nd)
- mediaTUM (Technical University of Munich) (submittedVersion, other-oa)
- Institutional Research Information System University of Ferrara (University of Ferrara) (submittedVersion, cc-by-nc-nd)
- Spiral (Imperial College London) (submittedVersion, cc-by-nc-nd)
- Funders
- National Human Genome Research Institute
- National Cancer Institute
- National Institutes of Health (U24 CA143866, U24 CA143843, P30 CA016672, U24 CA143867, U24 CA143840, U24 CA143882, U24 CA143858, U24 CA143835, U54 HG003273, U24 CA143883, U24 CA143848, U24 CA144025, U24 CA143845, U54 HG003079, U24 CA143799, U54 HG003067)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- cell of origin, molecular classification of cancer, pan-cancer analysis, TCGA, aneuploidy, DNA methylation, mRNA expression, microRNA expression, reverse phase protein array, histological subtypes, tissue type, stemness, molecular clustering
- MeSH terms
- Aneuploidy, Chromosomes, Humans, Mutation, Neoplasm Proteins, Neoplasms, RNA, Messenger, Cluster Analysis, Databases, Factual, CpG Islands, DNA Methylation, MicroRNAs
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