The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Pan-cancer analysis of the extent and consequences of intratumor heterogeneity
Open accessAbstract
Intratumor heterogeneity (ITH) drives neoplastic progression and therapeutic resistance. We used the bioinformatics tools 'expanding ploidy and allele frequency on nested subpopulations' (EXPANDS) and PyClone to detect clones that are present at a ≥10% frequency in 1,165 exome sequences from tumors in The Cancer Genome Atlas. 86% of tumors across 12 cancer types had at least two clones. ITH in the morphology of nuclei was associated with genetic ITH (Spearman's correlation coefficient, ρ = 0.24–0.41; P < 0.001). Mutation of a driver gene that typically appears in smaller clones was a survival risk factor (hazard ratio (HR) = 2.15, 95% confidence interval (CI): 1.71–2.69). The risk of mortality also increased when >2 clones coexisted in the same tumor sample (HR = 1.49, 95% CI: 1.20–1.87). In two independent data sets, copy-number alterations affecting either <25% or >75% of a tumor's genome predicted reduced risk (HR = 0.15, 95% CI: 0.08–0.29). Mortality risk also declined when >4 clones coexisted in the sample, suggesting a trade-off between the costs and benefits of genomic instability. ITH and genomic instability thus have the potential to be useful measures that can universally be applied to all cancers.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108
Inferring tumour purity and stromal and immune cell admixture from expression data
Yoshihara, K., Shahmoradgoli, M., Martínez, E., Vegesna, R., Kim, H., Torres-Garcia, W., Treviño, V., Shen, H., Laird, P. W., Levine, D. A., et al. (2013) · Nature Communications · doi:10.1038/ncomms3612 · Cited by 9,778
Signatures of mutational processes in human cancer
Initiative, A. P. C. G., Alexandrov, L. B., ICGC Breast Cancer Consortium, ICGC MMML-Seq Consortium, PedBrain, I., Nik-Zainal, S., Wedge, D. C., Aparicio, S. A. J. R., Behjati, S., Biankin, A. V., et al. (2013) · Nature · doi:10.1038/nature12477 · Cited by 9,660
Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., & Kinzler, K. W. (2013) · Science · doi:10.1126/science.1235122 · Cited by 7,863
Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
Gerlinger, M., Rowan, A. J., Horswell, S., Larkin, J., Endesfelder, D., Gronroos, E., Martinez, P., Matthews, N., Stewart, A., Tarpey, P., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1113205 · Cited by 7,774
Nowell, P. C. (1976) · Science · doi:10.1126/science.959840 · Cited by 6,471
A general framework for estimating the relative pathogenicity of human genetic variants
Kircher, M., Witten, D. M., Jain, P., O'Roak, B. J., Cooper, G. M., & Shendure, J. (2014) · Nature Genetics · doi:10.1038/ng.2892 · Cited by 6,183
CellProfiler: image analysis software for identifying and quantifying cell phenotypes
Carpenter, A. E., Jones, T. R., Lamprecht, M. R., Clarke, C., Kang, I. H., Friman, O., Guertin, D. A., Chang, J. H., Lindquist, R. A., Moffat, J., et al. (2006) · Genome Biology · doi:10.1186/gb-2006-7-10-r100 · Cited by 5,157
Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples
Cibulskis, K., Lawrence, M. S., Carter, S. L., Sivachenko, A., Jaffe, D., Sougnez, C., Gabriel, S., Meyerson, M., Lander, E. S., & Getz, G. (2013) · Nature Biotechnology · doi:10.1038/nbt.2514 · Cited by 4,981
Mutational landscape and significance across 12 major cancer types
Kandoth, C., McLellan, M. D., Vandin, F., Ye, K., Niu, B., Lu, C., Xie, M., Zhang, Q., McMichael, J. F., Wyczalkowski, M. A., et al. (2013) · Nature · doi:10.1038/nature12634 · Cited by 4,419
Greaves, M., & Maley, C. C. (2012) · Nature · doi:10.1038/nature10762 · Cited by 3,162
Self-citationComprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas
The Cancer Genome Atlas Research Network (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1402121 · Cited by 3,148
Pan-cancer patterns of somatic copy number alteration
Zack, T. I., Schumacher, S. E., Carter, S. L., Cherniack, A. D., Saksena, G., Tabak, B., Lawrence, M. S., Zhang, C.-Z., Wala, J., Mermel, C. H., et al. (2013) · Nature Genetics · doi:10.1038/ng.2760 · Cited by 1,870
Mapping the Hallmarks of Lung Adenocarcinoma with Massively Parallel Sequencing
Imielinski, M., Berger, A. H., Hammerman, P. S., Hernandez, B., Pugh, T. J., Hodis, E., Cho, J., Suh, J., Capelletti, M., Sivachenko, A., et al. (2012) · Cell · doi:10.1016/j.cell.2012.08.029 · Cited by 1,789
Tumor heterogeneity: Causes and consequences
Marusyk, A., & Polyak, K. (2010) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2009.11.002 · Cited by 1,602
The Life History of 21 Breast Cancers
Nik-Zainal, S., Van Loo, P., Wedge, D. C., Alexandrov, L. B., Greenman, C. D., Lau, K. W., Raine, K., Jones, D., Marshall, J., Ramakrishna, M., et al. (2012) · Cell · doi:10.1016/j.cell.2012.04.023 · Cited by 1,443
Evolution and impact of subclonal mutations in chronic lymphocytic leukemia
Landau, D. A., Carter, S. L., Stojanov, P., McKenna, A., Stevenson, K., Lawrence, M. S., Sougnez, C., Stewart, C., Sivachenko, A., Wang, L., et al. (2013) · Cell · doi:10.1016/j.cell.2013.01.019 · Cited by 1,379
Emerging landscape of oncogenic signatures across human cancers
Ciriello, G., Miller, M. L., Aksoy, B. A., Senbabaoglu, Y., Schultz, N., & Sander, C. (2013) · Nature Genetics · doi:10.1038/ng.2762 · Cited by 1,378
The major evolutionary transitions
Szathmáry, E., & Smith, J. M. (1995) · Nature · doi:10.1038/374227a0 · Cited by 1,095
Clonal evolution in breast cancer revealed by single nucleus genome sequencing
Wang, Y., Waters, J., Leung, M. L., Unruh, A., Roh, W., Shi, X., Chen, K., Scheet, P., Vattathil, S., Liang, H., et al. (2014) · Nature · doi:10.1038/nature13600 · Cited by 1,029
PyClone: statistical inference of clonal population structure in cancer
Roth, A., Khattra, J., Yap, D., Wan, A., Laks, E., Biele, J., Ha, G., Aparicio, S., Bouchard-Côté, A., & Shah, S. P. (2014) · Nature Methods · doi:10.1038/nmeth.2883 · Cited by 999
Genetic clonal diversity predicts progression to esophageal adenocarcinoma
Maley, C. C., Galipeau, P. C., Finley, J. C., Wongsurawat, V. J., Li, X., Sanchez, C. A., Paulson, T. G., Blount, P. L., Risques, R.-A., Rabinovitch, P. S., et al. (2006) · Nature Genetics · doi:10.1038/ng1768 · Cited by 696
Self-citationClonal status of actionable driver events and the timing of mutational processes in cancer evolution
McGranahan, N., Favero, F., de Bruin, E. C., Birkbak, N. J., Szallasi, Z., & Swanton, C. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aaa1408 · Cited by 685
OpenSlide: A vendor-neutral software foundation for digital pathology
Goode, A., Gilbert, B., Harkes, J., Jukic, D., & Satyanarayanan, M. (2013) · Journal of Pathology Informatics · doi:10.4103/2153-3539.119005 · Cited by 546
DGIdb: mining the druggable genome
Griffith, M., Griffith, O. L., Coffman, A. C., Weible, J. V., McMichael, J. F., Spies, N. C., Koval, J., Das, I., Callaway, M. B., Eldred, J. M., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2689 · Cited by 533
Heterogeneity Maintenance in Glioblastoma: A Social Network
Bonavia, R., Inda, M.-D.-M., Cavenee, W. K., & Furnari, F. B. (2011) · Cancer Research · doi:10.1158/0008-5472.can-11-0153 · Cited by 439
Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV
Sathirapongsasuti, J. F., Lee, H., Horst, B. A. J., Brunner, G., Cochran, A. J., Binder, S., Quackenbush, J., & Nelson, S. F. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr462 · Cited by 378
Ha, G., Roth, A., Khattra, J., Ho, J., Yap, D., Prentice, L. M., Melnyk, N., McPherson, A., Bashashati, A., Laks, E., et al. (2014) · Genome Research · doi:10.1101/gr.180281.114 · Cited by 371
Paradoxical Relationship between Chromosomal Instability and Survival Outcome in Cancer
Birkbak, N. J., Eklund, A. C., Li, Q., McClelland, S. E., Endesfelder, D., Tan, P., Tan, I. B., Richardson, A. L., Szallasi, Z., & Swanton, C. (2011) · Cancer Research · doi:10.1158/0008-5472.can-10-3667 · Cited by 350
Mroz, E. A., Tward, A. M., Hammon, R. J., Ren, Y., & Rocco, J. W. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001786 · Cited by 290
Assessing the clinical utility of cancer genomic and proteomic data across tumor types
Yuan, Y., Van Allen, E. M., Omberg, L., Wagle, N., Amin-Mansour, A., Sokolov, A., Byers, L. A., Xu, Y., Hess, K. R., Diao, L., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2940 · Cited by 280
Almendro, V., Cheng, Y.-K., Randles, A., Itzkovitz, S., Marusyk, A., Ametller, E., Gonzalez-Farre, X., Muñoz, M., Russnes, H. G., Helland, Å., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2013.12.041 · Cited by 274
Biebricher, C. K., & Eigen, M. (2005) · Virus Research · doi:10.1016/j.virusres.2004.11.002 · Cited by 196
Roylance, R., Endesfelder, D., Gorman, P., Burrell, R. A., Sander, J., Tomlinson, I., Hanby, A. M., Speirs, V., Richardson, A. L., Birkbak, N. J., et al. (2011) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-11-0343 · Cited by 175
Roth, A., Ding, J., Morin, R., Crisan, A., Ha, G., Giuliany, R., Bashashati, A., Hirst, M., Turashvili, G., Oloumi, A., et al. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts053 · Cited by 171
Merlo, L. M. F., Shah, N. A., Li, X., Blount, P. L., Vaughan, T. L., Reid, B. J., & Maley, C. C. (2010) · Cancer Prevention Research · doi:10.1158/1940-6207.capr-10-0108 · Cited by 155
Self-citationEXPANDS: expanding ploidy and allele frequency on nested subpopulations
Andor, N., Harness, J. V., Müller, S., Mewes, H., & Petritsch, C. K. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt622 · Cited by 138
Self-citationCazier, J., Rao, S. R., McLean, C. M., Walker, A. K., Wright, B. J., Jaeger, E., Kartsonaki, C., Marsden, L., Yau, C., Camps, C., et al. (2014) · Nature Communications · doi:10.1038/ncomms4756 · Cited by 117
Quantifying tumor heterogeneity in whole-genome and whole-exome sequencing data
Oesper, L., Satas, G., & Raphael, B. J. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu651 · Cited by 115
Niche-based screening identifies small-molecule inhibitors of leukemia stem cells
Hartwell, K. A., Miller, P. G., Mukherjee, S., Kahn, A. R., Stewart, A. L., Logan, D. J., Negri, J. M., Duvet, M., Järås, M., Puram, R. V., et al. (2013) · Nature Chemical Biology · doi:10.1038/nchembio.1367 · Cited by 113
Cancer Evolution Is Associated with Pervasive Positive Selection on Globally Expressed Genes
Ostrow, S. L., Barshir, R., DeGregori, J. V., Yeger‐Lotem, E., & Hershberg, R. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004239 · Cited by 96
Wang, W., Ozolek, J. A., & Rohde, G. K. (2010) · Cytometry Part A · doi:10.1002/cyto.a.20853 · Cited by 92
Yadav, V. K., & De, S. (2014) · Briefings in Bioinformatics · doi:10.1093/bib/bbu002 · Cited by 81
A general framework for analyzing tumor subclonality using SNP array and DNA sequencing data
Li, B., & Li, J. Z. (2014) · Genome biology · doi:10.1186/s13059-014-0473-4 · Cited by 77
Bochtler, T., Stölzel, F., Heilig, C. E., Kunz, C., Mohr, B., Jauch, A. S., Janssen, J. W. G., Krämer, M., Benner, A., Bornhäuser, M., et al. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2013.50.7921 · Cited by 76
Tissue Heterogeneity of EGFR Mutation in Lung Adenocarcinoma
Sakurada, A., Lara-Guerra, H., Liu, G., Shepherd, F. A., & Tsao, M. (2008) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e318168be93 · Cited by 63
Dissecting cancer evolution at the macro-heterogeneity and micro-heterogeneity scale
Barber, L. J., Davies, M. N., & Gerlinger, M. (2014) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2014.12.001 · Cited by 57
Heim, D., Budczies, J., Stenzinger, A., Treue, D., Hufnagl, P., Denkert, C., Dietel, M., & Klauschen, F. (2014) · International Journal of Cancer · doi:10.1002/ijc.28882 · Cited by 53
Cancer Evolution Constrained by Mutation Order
Swanton, C. (2015) · New England Journal of Medicine · doi:10.1056/nejme1414288 · Cited by 24
Vitale, M. (2013) · Thyroid · doi:10.1089/thy.2012.0614 · Cited by 20
Cited by
Tumour heterogeneity and resistance to cancer therapies
Dagogo-Jack, I., & Shaw, A. T. (2018) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.166 · Cited by 3,846
Clonal heterogeneity and tumor evolution: past, present, and the future
McGranahan, N., & Swanton, C. (2017) · Cell · doi:10.1016/j.cell.2017.01.018 · Cited by 2,840
The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy
Havel, J. J., Chowell, D., & Chan, T. A. (2019) · Nature Reviews Cancer · doi:10.1038/s41568-019-0116-x · Cited by 2,286
Pan-cancer whole-genome analyses of metastatic solid tumours
Priestley, P., Baber, J., Lolkema, M. P., Steeghs, N., de Bruijn, E., Shale, C., Duyvesteyn, K., Haidari, S., van Hoeck, A., Onstenk, W., et al. (2019) · Nature · doi:10.1038/s41586-019-1689-y · Cited by 1,106
Intratumor Heterogeneity: The Rosetta Stone of Therapy Resistance
Marusyk, A., Janiszewska, M., & Polyak, K. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.03.007 · Cited by 1,009
Metadata
- Authors
- Andor, N., Graham, T. A., Jansen, M., Xia, L. C., Aktipis, C. A., Petritsch, C., Ji, H. P., & Maley, C. C.
- Venue
- Nature Medicine
- Published
- 2015-11-30
- Volume
- 22
- Issue
- 1
- Pages
- 105-113
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2182664595
- Cited by
- 768
- References
- 51
- FWCI
- 20.51
- Type
- journal article
- Language
- en
- Open access
- green
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.