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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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“The mutations of the concerned genes in all breast cancers of the Cancer Genome Atlas (TCGA) (n = 1084) (1).”
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InfluentialSelf-citationThree-dimensional genome landscape of primary human cancers
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Self-citationFibroblast as a critical stromal cell type determining prognosis in prostate cancer
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Self-citationTransition to naïve human pluripotency mirrors pan-cancer DNA hypermethylation
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MethodOncogenic potential of human pluripotent stem cell‐derived lung organoids with HER2 overexpression
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“Furthermore, these data highlight the need to consider the oncogenic cell-of-origin when designing new treatment regimens (54).”
BackgroundSelf-citationMCM4 is a novel prognostic biomarker and promotes cancer cell growth in glioma
Yang, S., Yuan, Y., Ren, W., Wang, H., Zhao, Z., Zhao, H., Zhao, Q., Chen, X., Jiang, X., & Zhang, L. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.1004324 · Cited by 29
Self-citationSanjaya, P., Maljanen, K., Katainen, R., Waszak, S. M., Ambrose, J. C., Arumugam, P., Bevers, R. P. J., Bleda, M., Boardman-Pretty, F., Boustred, C. R., et al. (2023) · Genome Medicine · doi:10.1186/s13073-023-01204-4 · Cited by 31
“In top-5 prediction of WGS data, both methods performed similarly (PCAWG MuAt 97.6%, DNN 97.2%), whereas in WES data, DNN was more accurate (TCGA MuAt 90.6%, DNN 91.8%).”
MethodInfluentialUnraveling cancer lineage drivers in squamous cell carcinomas
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“Not surprisingly, HPV+ HNSCCs strongly cluster with other HPV+ tumors (mainly CxSCC, see below) based on pan-SCCs integrative comparisons, known as “iCluster 27” (Campbell et al., 2018; Hoadley et al., 2018) (Figure 1).”
BackgroundInfluentialMacrophage Migration and Phagocytosis Are Controlled by Kindlin-3's Link to the Cytoskeleton
Liu, H., Zhu, L., Dudiki, T., Gabanic, B., Good, L., Podrez, E. A., Cherepanova, O. A., Qin, J., & Byzova, T. V. (2020) · The Journal of Immunology · doi:10.4049/jimmunol.1901134 · Cited by 29
Comparative analysis of the molecular subtype landscape in canine and human mammary gland tumors
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Targeting chromosomal instability and aneuploidy in cancer
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Self-citationSmall-Molecule Inhibitors (SMIs) as an Effective Therapeutic Strategy for Endometrial Cancer
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“Recently, molecular similarities have been revealed between gynecological and breast cancer in a comprehensive integrative molecular analysis of the complete 33 types of tumors in TCGA [48].”
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Self-citationLipid droplets control mitogenic lipid mediator production in human cancer cells
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“%) cancers (TCGA, PanCancer Atlas [18]).”
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“Recent observations indicate that cancer epigenomes, particularly DNA-methylation marks, result from both, transformation-specific changes and epigenetic patterns already present in the cell of origin that was transformed into a neoplastic cell [18, 42].”
BackgroundComparison of sampling methods for next generation sequencing for patients with lung cancer
Kunimasa, K., Matsumoto, S., Nishino, K., Honma, K., Maeda, N., Kuhara, H., Tamiya, M., Inoue, T., Kawamura, T., Kimura, T., et al. (2022) · Cancer Medicine · doi:10.1002/cam4.4632 · Cited by 29
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EphB4 and ephrinB2 act in opposition in the head and neck tumor microenvironment
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“For the estimation of kinase activities, we evaluated different lists of kinase substrates from repositories (e.g. PhosphositePlus (Hornbeck et al. 2015)), computational text mining (Bachman, Gyori, and Sorger 2019), kinase inhibitor experiments (Hijazi et al. 2020) or phosphorylation of cell…”
MethodAhmad, A., Paffrath, V., Clima, R., Busch, J. F., Rabien, A., Kilic, E., Villegas, S. L., Timmermann, B., Attimonelli, M., Jung, K., et al. (2019) · Cancers · doi:10.3390/cancers11091298 · Cited by 28
“Compared with the current model where the organ of origin determines the tumor type, a system was proposed based solely on molecular features which could be considered more relevant for tumor classification [12].”
BackgroundPan-Cancer Classification Based on Self-Normalizing Neural Networks and Feature Selection
Li, J., Xu, Q., Wu, M., Huang, T., & Wang, Y. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00766 · Cited by 28
“Some different cancers even have similar CNV patterns and mechanisms (Hoadley et al., 2018).”
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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. 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- 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
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- Hibshoosh, Hanina
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- Mariani, Odette
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- Force, Seth
- Khuri, Fadlo
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- Carroll, Peter R.
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- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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