The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer
Open accessAbstract
Summary We evaluated ancestry effects on mutation rates, DNA methylation, and mRNA and miRNA expression among 10,678 patients across 33 cancer types from The Cancer Genome Atlas. We demonstrated that cancer subtypes and ancestry-related technical artifacts are important confounders that have been insufficiently accounted for. Once accounted for, ancestry-associated differences spanned all molecular features and hundreds of genes. Biologically significant differences were usually tissue-specific but not specific to cancer. However, admixture and pathway analyses suggested some of these differences are causally related to cancer. Specific findings included an increased FBXW7 mutations in patients of African origin, decreased VHL and PBRM1 mutations in renal cancer patients of African origin, and decreased immune activity in bladder cancer patients of East Asian origin.
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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F.-A., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E.-M., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,845
Nishimura, R., Osako, T., Nishiyama, Y., Tashima, R., Nakano, M., Fujisue, M., Toyozumi, Y., & Arima, N. (2013) · Oncology · doi:10.1159/000353099 · Cited by 13,166
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248
Fast model-based estimation of ancestry in unrelated individuals
Alexander, D. H., Novembre, J., & Lange, K. (2009) · Genome Research · doi:10.1101/gr.094052.109 · Cited by 9,898
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
Self-citationUMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101
The 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
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The impact of site-specific digital histology signatures on deep learning model accuracy and bias
Howard, F. M., Dolezal, J., Kochanny, S., Schulte, J., Chen, H., Heij, L., Huo, D., Nanda, R., Olopade, O. I., Kather, J. N., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24698-1 · Cited by 330
Nassar, A. H., Adib, E., Abou Alaiwi, S., El Zarif, T., Groha, S., Akl, E. W., Nuzzo, P. V., Mouhieddine, T. H., Perea-Chamblee, T., Taraszka, K., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.08.022 · Cited by 121
Self-citationConcurrent loss of the Y chromosome in cancer and T cells impacts outcome
Chen, X., Shen, Y., Choi, S., Abdel-Hafiz, H. A., Basu, M., Hoelzen, L., Tufano, M., Kailasam Mani, S. K., Ranjpour, M., Zhu, J., et al. (2025) · Nature · doi:10.1038/s41586-025-09071-2 · Cited by 50
Metadata
- Authors
- Carrot-Zhang, J., Chambwe, N., Damrauer, J. S., Knijnenburg, T. A., Robertson, A. G., Yau, C., Zhou, W., Berger, A. C., Huang, K.-L., Newberg, J. Y., Mashl, R. J., Romanel, A., Sayaman, R. W., Demichelis, F., Felau, I., Frampton, G. M., Han, S., Hoadley, K. A., Kemal, A., Laird, P. W., Lazar, A. J., Le, X., Oak, N., Shen, H., Wong, C. K., Zenklusen, J. C., Ziv, E., Aguet, F., Ding, L., Demchok, J. A., Mensah, M. K. A., Caesar-Johnson, S., Tarnuzzer, R., Wang, Z., Yang, L., Alfoldi, J., Karczewski, K. J., MacArthur, D. G., Meyerson, M., Benz, C., Stuart, J. M., Cherniack, A. D., & Beroukhim, R.
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 37
- Issue
- 5
- Pages
- 639-654.e6
- ISSN
- 1535-6108 (ISSN-L)
- OpenAlex
- W3022369650
- Cited by
- 331
- References
- 64
- FWCI
- 12.66
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Carrot-Zhang, J., Chambwe, N., Damrauer, J. S., Knijnenburg, T. A., Robertson, A. G., Yau, C., Zhou, W., Berger, A. C., Huang, K.-L., Newberg, J. Y., Mashl, R. J., Romanel, A., Sayaman, R. W., Demichelis, F., Felau, I., Frampton, G. M., Han, S., Hoadley, K. A., Kemal, A., . . . Beroukhim, R. (2020). Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer. Cancer Cell. https://doi.org/10.1016/j.ccell.2020.04.012
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
