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Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
Open accessAbstract
BACKGROUND: Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples. METHODS: To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression. RESULTS: Phylogenetic reconstruction revealed branched evolutionary tumor growth, with 63 to 69% of all somatic mutations not detectable across every tumor region. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin (mTOR) kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro. Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors. CONCLUSIONS: Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection. (Funded by the Medical Research Council and others.).
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“A greater degree of divergence may be attributed to intra-tumor spatial heterogeneity and sampling bias: tumors can be spatially diverse, and organoids generated from a specific portion may lack the representativeness of distant regions130,131.”
From Organoids (2022) · cites this paper as [130]
Experimental — accuracy not yet measuredIn the citing paper
“a small needle biopsy of a single lesion may fail to reflect the true underlying intra- and inter-tumor genetic heterogeneity (15–17).”
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“It is now appreciated that most clinically relevant solid tumors are highly heterogeneous at the phenotypic, physiologic, and genomic levels (13–15) and that they continue to evolve over time.”
From Radiomics: Images Are More than Pictures, They Are Data (2016) · cites this paper as [14]
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“…us to map the landscape of cancer genetic diversity, to track cancer evolution over time and space, and to decipher the genetic drivers behind it (Gerlinger et al. 2012; de Bruin et al. 2014; Hobor et al. 2014; Misale et al. 2014; Arena et al. 2015; Siravegna et al. 2015; Yates et al. 2015;…”
The evolution of lung cancer and impact of subclonal selection in TRACERx
Frankell, A. M., Dietzen, M., Bakir, M. A., Lim, E. L., Karasaki, T., Ward, S., Veeriah, S., Colliver, E., Huebner, A., Bunkum, A., et al. (2023) · Nature · doi:10.1038/s41586-023-05783-5 · Cited by 329
“(2) The patient is unable to comply with protocol requirements.”
BackgroundMethodInfluentialAdvances in PET imaging of cancer
Schwenck, J., Sonanini, D., Cotton, J. M., Rammensee, H., la Fougère, C., Zender, L., & Pichler, B. J. (2023) · Nature reviews. Cancer · doi:10.1038/s41568-023-00576-4 · Cited by 343
Targeting the PI3K/Akt/mTOR pathway in castration-resistant prostate cancer
Bitting, R. L., & Armstrong, A. J. (2013) · Endocrine Related Cancer · doi:10.1530/erc-12-0394 · Cited by 316
Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts
Quinn, J. J., Jones, M. G., Okimoto, R. A., Nanjo, S., Chan, M. M., Yosef, N., Bivona, T. G., & Weissman, J. S. (2021) · Science · doi:10.1126/science.abc1944 · Cited by 319
Effector CD4 and CD8 T Cells and Their Role in the Tumor Microenvironment
Hadrup, S. R., Donia, M., & Straten, P. T. (2012) · Cancer Microenvironment · doi:10.1007/s12307-012-0127-6 · Cited by 318
Majumder, B., Ulaganathan, B., Thiyagarajan, S., Radhakrishnan, P., Narasimhan, H., Dhandapani, M., Brijwani, N., Pinto, D. D., Prasath, A., Shanthappa, B., et al. (2015) · Nature Communications · doi:10.1038/ncomms7169 · Cited by 317
Prevalence and Co-Occurrence of Actionable Genomic Alterations in High-Grade Bladder Cancer
Iyer, G., Al‐Ahmadie, H. A., Schultz, N. D., Hanrahan, A. J., Ostrovnaya, I., Balar, A. V., Kim, P. H., Lin, O., Weinhold, N., Sander, C., et al. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.46.5740 · Cited by 309
Holland, A. J., & Cleveland, D. W. (2012) · Nature Medicine · doi:10.1038/nm.2988 · Cited by 315
Molecular Genetics of Clear-Cell Renal Cell Carcinoma
Brugarolas, J. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2012.45.2003 · Cited by 318
Minimal functional driver gene heterogeneity among untreated metastases
Reiter, J. G., Makohon-Moore, A. P., Gerold, J. M., Heyde, A., Attiyeh, M. A., Kohutek, Z. A., Tokheim, C. J., Brown, A., DeBlasio, R. M., Niyazov, J., et al. (2018) · Science · doi:10.1126/science.aat7171 · Cited by 310
“(6) To calculate the mean ̄ N(t), we integrate the number of type 0 cells over time and multiply by the division rate b0, the driver mutation rate u, and the probability that a new lineage survives fl1, which we assume to be equal across all mutant lineages.”
BackgroundClinical trial design in the era of precision medicine
Fountzilas, E., Tsimberidou, A. M., Vo, H. H., & Kurzrock, R. (2022) · Genome Medicine · doi:10.1186/s13073-022-01102-1 · Cited by 332
“However, as omic technology has improved and become more widely used, a challenging reality has been demonstrated—individual tumors, especially when metastatic, are complex and differ from each other [7, 8].”
BackgroundMicroenvironmental Regulation of Epithelial–Mesenchymal Transitions in Cancer
Gao, D., Vahdat, L. T., Wong, S. T. C., Chang, J. C., & Mittal, V. (2012) · Cancer Research · doi:10.1158/0008-5472.can-12-1223 · Cited by 308
Krause, M., Dubrovska, A., Linge, A., & Baumann, M. A. (2016) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2016.02.002 · Cited by 310
“spatially separated samples within primary tumors and their metastases, was not present in all investigated tumor regions [117].”
BackgroundTreating cancer with microRNA replacement therapy: A literature review
Hosseinahli, N., Aghapour, M., Duijf, P. H. G., & Baradaran, B. (2018) · Journal of Cellular Physiology · doi:10.1002/jcp.26514 · Cited by 313
“It offers the opportunity to silence multiple mRNA targets with a single miRNA or to simultaneously target a single mRNA with several miRNA sequences (Gerlinger et al., 2012).”
BackgroundCopynumber: Efficient algorithms for single- and multi-track copy number segmentation
Nilsen, G., Liestøl, K., Loo, P. V., Vollan, H. K. M., Brodtkorb, M., Rueda, O. M., Chin, S., Russell, R., Baumbusch, L. O., Caldas, C., et al. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-591 · Cited by 302
ClearCode34: A Prognostic Risk Predictor for Localized Clear Cell Renal Cell Carcinoma
Brooks, S. A., Brannon, A. R., Parker, J. S., Fisher, J. C., Sen, O., Kattan, M. W., Hakimi, A. A., Hsieh, J. J.-D., Choueiri, T. K., Tamboli, P., et al. (2014) · European Urology · doi:10.1016/j.eururo.2014.02.035 · Cited by 307
Implementing personalized cancer genomics in clinical trials
Simon, R. M., & Roychowdhury, S. (2013) · Nature Reviews Drug Discovery · doi:10.1038/nrd3979 · Cited by 309
Wu, Y.-L. L. C., Lee, J. S., Thongprasert, S., Yu, C., Zhang, L., Ladrera, G., Srimuninnimit, V., Sriuranpong, V., Sandoval-Tan, J., Zhu, Y., et al. (2013) · The Lancet Oncology · doi:10.1016/s1470-2045(13)70254-7 · Cited by 302
Inhibiting WEE1 Selectively Kills Histone H3K36me3-Deficient Cancers by dNTP Starvation
Pfister, S. X., Markkanen, E., Jiang, Y., Sarkar, S., Woodcock, M., Orlando, G., Mavrommati, I., Pai, C., Zalmas, L., Drobnitzky, N., et al. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.09.015 · Cited by 323
“SETD2 mutations and KDM4A overexpression are together observed in more than 10% of cancers in kidney, large intestines, endometrium, and ovary (Berry and Janknecht, 2013; Dalgliesh et al., 2010; Gerlinger et al., 2012).”
BackgroundPan-cancer analysis of intratumor heterogeneity as a prognostic determinant of survival
Morris, L. G. T., Riaz, N., Desrichard, A., Şenbabaoğlu, Y., Hakimi, A. A., Makarov, V., Reis-Filho, J. S., & Chan, T. A.-T. (2016) · Oncotarget · doi:10.18632/oncotarget.7067 · Cited by 307
“These limitations would tend to attenuate the strength of associations in this study: the measures of ITH in this study are likely to be conservative, potentially underestimating the true extent of heterogeneity in tumors, as evidenced by studies that have sequenced multiple regions of tumors [3-5, 40, 41].”
BackgroundResultHeterogeneity of the tumor immune microenvironment and its clinical relevance
Jia, Q., Wang, A., Yuan, Y., Zhu, B., & Long, H. (2022) · Experimental Hematology and Oncology · doi:10.1186/s40164-022-00277-y · Cited by 332
Translational value of mouse models in oncology drug development
Gould, S. E., Junttila, M. R., & de Sauvage, F. J. (2015) · Nature Medicine · doi:10.1038/nm.3853 · Cited by 293
Pancreatic Cancer Metastases Harbor Evidence of Polyclonality
Maddipati, R., & Stanger, B. Z. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-15-0120 · Cited by 296
“In human cancers, subclones are defined genetically as distinct tumor populations that share a set of identical founder mutations (2, 11, 20).”
BackgroundIntratumor Heterogeneity in Hepatocellular Carcinoma
Friemel, J., Rechsteiner, M., Frick, L. D., Böhm, F., Struckmann, K., Egger, M., Moch, H., Heikenwälder, M. F., & Weber, A. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-0122 · Cited by 297
Choe, J., Lee, S. M., Do, K., Lee, G., Lee, J., Lee, S. M., & Seo, J. B. (2019) · Radiology · doi:10.1148/radiol.2019181960 · Cited by 300
Belfiore, L., Saunders, D. N., Ranson, M., Thurecht, K. J., Storm, G., & Vine, K. L. (2018) · Journal of Controlled Release · doi:10.1016/j.jconrel.2018.02.040 · Cited by 303
“The intratumoral heterogeneity of tumors provides a template for the clonal selection and expansion of target-negative tumor cells [13] and is a known mechanism of acquired resistance to targeted therapies [14, 15].”
Safety of combining radiotherapy with immune-checkpoint inhibition
Hwang, W. L., Pike, L., Royce, T. J., Mahal, B. A. V., & Loeffler, J. S. (2018) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-018-0046-7 · Cited by 299
Drug repurposing in oncology—patient and health systems opportunities
Bertolini, F., Sukhatme, V. P., & Bouche, G. (2015) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2015.169 · Cited by 298
Metabolism shapes the tumor microenvironment
Reina‐Campos, M., Moscat, J., & Díaz-Meco, M. T. (2017) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2017.05.006 · Cited by 292
“Because oncogenes can modulate tumor metabolism [8,9], it still remains to be fully determined if other oncogenic drivers, other tissues of origin, or a more complex oncogenic composition in the tumor bulk [10,11] can also regionally influence substrate utilization.”
Wettersten, H. I., Hakimi, A. A., Morin, D., Bianchi, C., Johnstone, M. E., Donohoe, D. R., Trott, J. F., Aboud, O. A., Stirdivant, S. M., Neri, B. P., et al. (2015) · Cancer Research · doi:10.1158/0008-5472.can-14-1703 · Cited by 295
“In addition, despite tumor heterogeneity observed in RCC (30), it would appear that in this era of personalized medicine, and based on the differences that we have observed, it may now be more appropriate to evaluate patient responses to drug therapies with knowledge of their initial tumor grade being part of the clin…”
BackgroundUnique Neoantigens Arise from Somatic Mutations in Patients with Gastrointestinal Cancers
Parkhurst, M. R., Robbins, P. F., Tran, E., Prickett, T. D., Gartner, J. J., Jia, L., Ivey, G. D., Li, Y. F., El‐Gamil, M., Lalani, A., et al. (2019) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-1494 · Cited by 292
“For therapeutic application, it may be beneficial to target multiple mutations to overcome inter tumoral and intratumoral heterogeneity (23, 24).”
BackgroundEGFR Variant Heterogeneity in Glioblastoma Resolved through Single-Nucleus Sequencing
Francis, J. M., Zhang, C.-Z., Maire, C. L., Jung, J., Manzo, V. E., Adalsteinsson, V. A., Homer, H., Haidar, S., Blumenstiel, B., Pedamallu, C. S., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0879 · Cited by 287
Genetic and non-genetic clonal diversity in cancer evolution
Black, J. R., & McGranahan, N. (2021) · Nature reviews. Cancer · doi:10.1038/s41568-021-00336-2 · Cited by 298
Van den Eynde, M., Mlecnik, B., Bindea, G., Fredriksen, T., Church, S. E., Lafontaine, L., Haicheur, N., Marliot, F., Angelova, M., Vasaturo, A., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.11.003 · Cited by 281
Metadata
- Authors
- Gerlinger, M., Rowan, A. J., Horswell, S., Larkin, J., Endesfelder, D., Gronroos, E., Martinez, P., Matthews, N., Stewart, A., Tarpey, P., Varela, I., Phillimore, B., Begum, S., McDonald, N. Q., Butler, A., Jones, D., Raine, K., Latimer, C., Santos, C. R., Nohadani, M., Eklund, A. C., Spencer-Dene, B., Clark, G., Pickering, L., Stamp, G., Gore, M., Szallasi, Z., Downward, J., Futreal, P. A., & Swanton, C.
- Affiliations
- Queen Mary University of London (GB)
- ORCID
- Gerlinger, Marco
- Rowan, Andrew J.
- Horswell, Stuart
- Larkin, James
- Endesfelder, David
- Gronroos, Eva
- Martinez, Pierre
- Tarpey, Patrick
- Varela, Ignacio
- Begum, Sharmin
- McDonald, Neil Q.
- Jones, David
- Raine, Keiran
- Latimer, Calli
- Eklund, Aron C.
- Pickering, Lisa
- Stamp, Gordon
- Downward, Julian
- Futreal, P. Andrew
- Swanton, Charles
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2012-03-08
- Volume
- 366
- Issue
- 10
- Pages
- 883-892
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- PMC
- PMC4878653
- OpenAlex
- W2150575159
- Semantic Scholar
- b97108a8e1dd8cf67ff9f374a8237fabf4c96ad4
- Cited by
- 7,774
- References
- 35
- Citations by year
- 2026: 304 · 2025: 297 · 2024: 306 · 2023: 349 · 2022: 499 · 2021: 571 · 2020: 550 · 2019: 540 · 2018: 632 · 2017: 671 · 2016: 722 · 2015: 691 · 2014: 679 · 2013: 621 · 2012: 326
- FWCI
- 246.14
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
- Funders
- Wellcome Trust (079643)
- Cancer Research UK (10747, 15680)
- National Institute for Health and Care Research
- Medical Research Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Keywords
- intratumoral heterogeneity, tumor evolution, renal carcinoma, metastatic renal cell carcinoma, phylogenetic inference, mTOR, SETD2, PTEN, KDM5C, tumor suppressor mutations, allelic imbalance, aneuploidy, gene expression signatures, biomarker development, personalized medicine
- MeSH terms
- Everolimus, Biopsy, Carcinoma, Renal Cell, Chromosome Aberrations, Humans, Immunosuppressive Agents, Kidney, Kidney Neoplasms, Mutation, Neoplasm Metastasis, Phenotype, Phylogeny, Ploidies, Biomarkers, Tumor, Sequence Analysis, DNA, Genetic Heterogeneity, Evolution, Molecular, Sirolimus, Polymorphism, Single Nucleotide, Exome
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