The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
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]
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“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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Citations
Cites
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
An Integrated Genomic Analysis of Human Glioblastoma Multiforme
Parsons, D. W., Jones, S., Zhang, X., Lin, J. C.-H., Leary, R. J., Angenendt, P., Mankoo, P., Carter, H., Siu, I.-M., Gallia, G. L., et al. (2008) · Science · doi:10.1126/science.1164382 · Cited by 5,857
Core Signaling Pathways in Human Pancreatic Cancers Revealed by Global Genomic Analyses
Jones, S., Zhang, X., Parsons, D. W., Lin, J. C.-H., Leary, R. J., Angenendt, P., Mankoo, P., Carter, H., Kamiyama, H., Jimeno, A., et al. (2008) · Science · doi:10.1126/science.1164368 · Cited by 3,969
The Consensus Coding Sequences of Human Breast and Colorectal Cancers
Sjöblom, T., Jones, S., Wood, L. D., Parsons, D. W., Lin, J., Barber, T. D., Mandelker, D. L., Leary, R. J., Ptak, J., Silliman, N., et al. (2006) · Science · doi:10.1126/science.1133427 · Cited by 3,161
Tumour evolution inferred by single-cell sequencing
Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., Cook, K., Stepansky, A., Levy, D., Esposito, D., et al. (2011) · Nature · doi:10.1038/nature09807 · Cited by 2,598
Distant metastasis occurs late during the genetic evolution of pancreatic cancer
Yachida, S., Jones, S., Bozic, I., Antal, T., Leary, R., Fu, B., Kamiyama, M., Hruban, R. H., Eshleman, J. R., Nowak, M. A., et al. (2010) · Nature · doi:10.1038/nature09515 · Cited by 2,502
Recurring mutations found by sequencing an acute myeloid leukemia genome
Mardis, E. R., Ding, L., Dooling, D. J., Larson, D. E., McLellan, M. D., Chen, K., Koboldt, D. C., Fulton, R. S., Delehaunty, K. D., McGrath, S. D., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0903840 · Cited by 2,219
Cancer as an evolutionary and ecological process
Merlo, L. M. F., Pepper, J. W., Reid, B. J., & Maley, C. C. (2006) · Nature reviews. Cancer · doi:10.1038/nrc2013 · Cited by 1,743
Flanigan, R. C., Salmon, S. E., Blumenstein, B. A., Bearman, S. I., Roy, V., McGrath, P. C., Caton, J. R., Munshi, N. C., & Crawford, E. D. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa003013 · Cited by 1,710
Detection of Mutations in EGFR in Circulating Lung-Cancer Cells
Maheswaran, S., Sequist, L. V., Nagrath, S., Ulkus, L., Brannigan, B., Collura, C. V., Inserra, E., Diederichs, S., Iafrate, A. J., Bell, D. W., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0800668 · Cited by 1,617
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Single-cell mutational profiling and clonal phylogeny in cancer
Potter, N. E., Ermini, L., Papaemmanuil, E., Cazzaniga, G., Vijayaraghavan, G., Titley, I., Ford, A., Campbell, P., Kearney, L., & Greaves, M. (2013) · Genome Research · doi:10.1101/gr.159913.113 · Cited by 107
Chae, Y. K., Davis, A. A., Carneiro, B. A., Chandra, S., Mohindra, N., Kalyan, A., Kaplan, J., Matsangou, M., Pai, S., Costa, R., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.11692 · Cited by 110
Coy, H., Hsieh, K., Wu, W., Nagarajan, M. B., Young, J. R., Douek, M. L., Brown, M. S., Scalzo, F., & Raman, S. S. (2019) · Abdominal Radiology · doi:10.1007/s00261-019-01929-0 · Cited by 110
Droplet-based single cell RNAseq tools: a practical guide
Salomon, R., Kaczorowski, D., Valdes-Mora, F., Nordon, R. E., Neild, A., Farbehi, N., Bartonicek, N., & Gallego-Ortega, D. (2019) · Lab on a Chip · doi:10.1039/c8lc01239c · Cited by 109
Mitochondrial complex II, a novel target for anti-cancer agents
Kluckova, K., Bezawork-Geleta, A., Rohlena, J., Dong, L., & Neuzil, J. (2013) · Biochimica et Biophysica Acta (BBA) - Bioenergetics · doi:10.1016/j.bbabio.2012.10.015 · Cited by 104
A 3D human renal cell carcinoma-on-a-chip for the study of tumor angiogenesis
Miller, C. P., Tsuchida, C., Zheng, Y., Himmelfarb, J., & Akilesh, S. (2018) · Neoplasia · doi:10.1016/j.neo.2018.02.011 · Cited by 105
“Our system will also permit study of intratumoral heterogeneity [48] by generating primary tumor cultures from different anatomic regions of the tumor and frommetastatic sites.”
BackgroundLigero, M., Garcia-Ruiz, A., Viaplana, C., Villacampa, G., Raciti, M. V., Landa, J., Matos, I., Martin-Liberal, J., Ochoa-de-Olza, M., Hierro, C., et al. (2021) · Radiology · doi:10.1148/radiol.2021200928 · Cited by 107
A role for cytosolic fumarate hydratase in urea cycle metabolism and renal neoplasia
Adam, J., Yang, M., Bauerschmidt, C., Kitagawa, M., O’Flaherty, L., Maheswaran, P., Özkan, G., Sahgal, N., Baban, D., Kato, K., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.04.006 · Cited by 97
Zhou, M., Hall, L., Goldgof, D., Russo, R., Balagurunathan, Y., Gillies, R., & Gatenby, R. (2014) · Translational Oncology · doi:10.1593/tlo.13730 · Cited by 97
Engineering chimeric antigen receptor-T cells for cancer treatment
Ye, B., Stary, C. M., Li, X., Gao, Q., Kang, C., & Xiong, X. (2018) · Molecular Cancer · doi:10.1186/s12943-018-0814-0 · Cited by 95
Peters, S. M. B., Privé, B. M., de Bakker, M., de Lange, F., Jentzen, W., Eek, A., Muselaers, C. H. J., Mehra, N., Witjes, J. A., Gotthardt, M., et al. (2022) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05471-4 · Cited by 88
Leto, S. M., & Trusolino, L. (2014) · Journal of Molecular Medicine · doi:10.1007/s00109-014-1161-2 · Cited by 87
Role of imaging in the era of precision medicine
Giardino, A., Gupta, S., Olson, E., Sepulveda, K., Lenchik, L., Ivanidze, J., Rakow-Penner, R., Patel, M. J., Subramaniam, R. M., & Ganeshan, D. (2017) · Academic Radiology · doi:10.1016/j.acra.2016.11.021 · Cited by 87
Tumor heterogeneity in VHL drives metastasis in clear cell renal cell carcinoma
Hu, J., Tan, P., Ishihara, M., Bayley, N. A., Schokrpur, S., Reynoso, J. G., Zhang, Y., Lim, R. J., Dumitras, C., Yang, L., et al. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01362-2 · Cited by 85
Using single‐cell multiple omics approaches to resolve tumor heterogeneity
Ortega, M. A., Poirion, O., Zhu, X., Huang, S., Wolfgruber, T. K., Sebra, R., & Garmire, L. X. (2017) · Clinical and Translational Medicine · doi:10.1186/s40169-017-0177-y · Cited by 81
Biopsy-free circulating tumor DNA assay identifies actionable mutations in lung cancer
Villaflor, V., Won, B., Nagy, R., Banks, K., Lanman, R. B., Talasaz, A., & Salgia, R. (2016) · Oncotarget · doi:10.18632/oncotarget.11801 · Cited by 75
Neutralization of terminal differentiation in gliomagenesis
Hu, J., Ho, A. L., Yuan, L., Hu, B., Hua, S., Hwang, S. S., Zhang, J., Hu, T., Zheng, H., Gan, B., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1308610110 · Cited by 76
Genome Sequencing during a Patient’s Journey through Cancer
Nangalia, J., & Campbell, P. J. (2019) · New England Journal of Medicine · doi:10.1056/nejmra1910138 · Cited by 66
Ahronian, L. G., & Corcoran, R. B. (2017) · Genome Medicine · doi:10.1186/s13073-017-0431-3 · Cited by 67
“ations present in a given tumor [10], may represent only”
BackgroundIntratumor CMS heterogeneity impacts patient prognosis in localized colon cancer
Marisa, L., Blum, Y., Taieb, J., Ayadi, M., Pilati, C., Le Malicot, K., Lepage, C., Salazar, R., Aust, D., Duval, A., et al. (2021) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-21-0529 · Cited by 68
“ITH ismostly studied at the genetic level, referring then to subclonality, and was in particular documented through multi-regions intratumor DNA sequencing (11, 28).”
BackgroundClonal dynamics following p53 loss of heterozygosity in Kras-driven cancers
Muzumdar, M. D., Dorans, K. J., Chung, K. M., Robbins, R., Tammela, T., Gocheva, V., Li, C. M.-C., & Jacks, T. (2016) · Nature Communications · doi:10.1038/ncomms12685 · Cited by 72
Gupta, R., Othman, T., Chen, C., Sandhu, J., Ouyang, C., & Fakih, M. (2020) · The Oncologist · doi:10.1634/theoncologist.2019-0441 · Cited by 70
“Furthermore, certain cases, such as metastatic disease, often have actionable molecular alterations across multiple sites that would be difficult to access through a single tissue biopsy [2, 4, 5].”
BackgroundOxidative stress as an iceberg in carcinogenesis and cancer biology
Toyokuni, S. (2016) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2015.11.025 · Cited by 66
Xiang, X., Liu, Z., Zhang, C., Li, Z., Gao, J., Zhang, C., Cao, Q., Cheng, J., Liu, H., Chen, D., et al. (2021) · Advanced Science · doi:10.1002/advs.202101230 · Cited by 71
Jansen, R. W., van Amstel, P., Martens, R. M., Kooi, I. E., Wesseling, P., de Langen, A. J., Menke-Van der Houven van Oordt, C. W., Jansen, B. H. E., Moll, A. C., Dorsman, J. C., et al. (2018) · Oncotarget · doi:10.18632/oncotarget.24893 · Cited by 63
Detection of circulating tumor DNA in patients with osteosarcoma
Barris, D. M., Weiner, S. B., Dubin, R. A., Fremed, M., Zhang, X., Piperdi, S., Zhang, W., Maqbool, S., Gill, J., Roth, M., et al. (2018) · Oncotarget · doi:10.18632/oncotarget.24268 · Cited by 63
“By selecting mutations in primary tumor as our search terms for ctDNA, we likely excluded mutations representative of clonal expansion and full tumor heterogeneity [24].”
BackgroundApplication of liquid biopsy in bone and soft tissue sarcomas: Present and future
Li, X., Seebacher, N. A., Hornicek, F. J., Xiao, T., & Duan, Z. (2018) · Cancer Letters · doi:10.1016/j.canlet.2018.09.012 · Cited by 53
Shukla, N. N., Patel, J. A., Magnan, H., Zehir, A., You, D., Tang, J., Meng, F., Samoila, A., Slotkin, E. K., Ambati, S. R., et al. (2017) · JCO Precision Oncology · doi:10.1200/po.16.00028 · Cited by 52
Kato, S., Schwaederlé, M. C., Fanta, P. T., Okamura, R., Leichman, L., Lippman, S. M., Lanman, R. B., Raymond, V. M., Talasaz, A., & Kurzrock, R. (2019) · JCO Precision Oncology · doi:10.1200/po.18.00158 · Cited by 52
Recent advances in microfluidic methods in cancer liquid biopsy
Iliescu, F. S., Poenar, D. P., Yu, F., Ni, M., Chan, K. H., Cima, I., Taylor, H. K., Cima, I., & Iliescu, C. (2019) · Biomicrofluidics · doi:10.1063/1.5087690 · Cited by 51
[¹²³I]Iodometomidate imaging in adrenocortical carcinoma
Kreissl, M. C., Schirbel, A., Fassnacht, M., Haenscheid, H., Verburg, F. A., Bock, S., Saeger, W., Knoedler, P., Reiners, C., Buck, A. K., et al. (2013) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2012-3261 · Cited by 50
The role of protein acetylation in carcinogenesis and targeted drug discovery
Yang, J., Song, C., & Zhan, X. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.972312 · Cited by 42
Leveraging microenvironmental synthetic lethalities to treat cancer
Metcalf, K. J., Alazzeh, A., Werb, Z., & Weaver, V. M. (2021) · Journal of Clinical Investigation · doi:10.1172/jci143765 · Cited by 42
“Overview of the tumor microenvironment and drug resistance Tumors are composed of a population of cancer cells that are genetically, phenotypically, and spatially heterogeneous, and this heterogeneity correlates with drug resistance (11, 12).”
BackgroundInduction of targeted necrosis with HER2-targeted platinum( iv ) anticancer prodrugs
Wong, D. Y. Q., Lim, J. H., & Ang, W. H. (2015) · Chemical Science · doi:10.1039/c5sc00015g · Cited by 40
Karyotypic Aberrations in Oncogenesis and Cancer Therapy
Vitale, I., Manic, G., Senovilla, L., Kroemer, G., & Galluzzi, L. (2015) · Trends in Cancer · doi:10.1016/j.trecan.2015.08.001 · Cited by 34
“Moreover, advanced-stage (but not early-stage) neoplasms are often characterized by elevated intratumoral heterogeneity in chromosomal content and a very complex karyotype [12,13].”
BackgroundJammihal, T., Saliby, R. M., Labaki, C., Soulati, H., Gallegos, J., Peris, A., McCurry, D., Yu, C., Shah, V., Poduval, D., et al. (2025) · Nature Cancer · doi:10.1038/s43018-024-00896-w · Cited by 38
Engineering cell heterogeneity into organs-on-a-chip
Mertz, D. R., Ahmed, T., & Takayama, S. (2018) · Lab on a Chip · doi:10.1039/c8lc00413g · Cited by 33
Mitra, A., Andrews, M. C., Roh, W., De Macedo, M. P., Hudgens, C. W., Carapeto, F., Singh, S., Reuben, A., Wang, F., Mao, X., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15538-9 · Cited by 27
Models of renal cell carcinoma used to investigate molecular mechanisms and develop new therapeutics
Shapiro, D. D., Virumbrales-Muñoz, M., Beebe, D. J., & Abel, E. J. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.871252 · Cited by 28
“In general, primary RCC tumors can demonstrate profound intratumoral genomic heterogeneity (15), and multi-region sequencing of primary tumors have demonstrated that up to seven biopsies are required to detect at least 75% of the many subclonal driver events (16).”
BackgroundInfluentialJi, T., Zhang, L., Deng, M., Huang, S., Wang, Y., Pham, T. T., Smith, A. A., Sridhar, V., Cabernard, C., Wang, J., et al. (2019) · Disease Models & Mechanisms · doi:10.1242/dmm.040147 · Cited by 25
“For example, individual tumor cells can acquire different types of mutations and grow into distinct subclones within the same tumor (de Bruin et al., 2014; Gerlinger et al., 2012).”
Troiani, T., Napolitano, S., Martini, G., Martinelli, E., Cardone, C., Normanno, N., Vitagliano, D., Morgillo, F., Fenizia, F., Lambiase, M., et al. (2015) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-0211 · Cited by 18
Jia, J., Morse, M. A., Nagy, R. J., Lanman, R. B., & Strickler, J. H. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00305 · Cited by 17
“One explanation for the discrepancy between tissue and blood profiling results is that MET amplification represented a subclonal alteration that was not consistently present throughout the same lesion (intratumoral heterogeneity) or between different lesions throughout the body (intertumoral heterogeneity), as describ…”
BackgroundLiang, L., Ding, Y., Yu, Y., Liu, K., Rao, S., Ge, Y., & Zeng, M. (2021) · BMC Medical Imaging · doi:10.1186/s12880-021-00605-4 · Cited by 13
“From the results of our study, NGTDM_Strength from T1WI was independently related to the therapy response of PDAC, supporting that radiomics features could potentially reflect the biological information of tumours, including the intratumoural heterogeneity associated with the response to treatment and survival [14, 34…”
ResultBlood Vessel-Targeted Therapy in Colorectal Cancer: Current Strategies and Future Perspectives
Jacobsen, A., Siebler, J., Grützmann, R., Stürzl, M., & Naschberger, E. (2024) · Cancers · doi:10.3390/cancers16050890 · Cited by 11
Mangum, R., Reuther, J., Sen Baksi, K., Gandhi, I., Zabriskie, R. C., Recinos, A., Raesz-Martinez, R., Lin, F. Y., Potter, S. L., Sher, A. C., et al. (2023) · Pediatric Hematology and Oncology · doi:10.1080/08880018.2023.2228837 · Cited by 8
“3 As such, molecular profiles obtained from diagnostic tissue samples can fail to capture the full breadth of genetic changes represented throughout the bulk of the tumor.”
Kidney cancer models for pre-clinical drug discovery: challenges and opportunities
Pohl, L., Friedhoff, J., Jurcic, C., Teroerde, M., Schindler, I., Strepi, K., Schneider, F., Kaczorowski, A., Hohenfellner, M., Duensing, A., et al. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.889686 · Cited by 5
“Besides a remarkable inter- and intratumoral genomic and functional heterogeneity (23, 35), ccRCC shows a number of immunological features that distinguish it from other tumor entities and that may impose challenges for modeling RCC in vitro and in vivo.”
BackgroundPopescu, I., Croitoru, V. M., Croitoru-Cazacu, I. M., Dudau, A.-M., Herlea, V., Dima, S. O., & Croitoru, A. E. (2024) · Journal of Personalized Medicine · doi:10.3390/jpm14070750 · Cited by 4
Immunosuppression and phenotypic plasticity in an atlas of human hepatocholangiocarcinoma
Li, Y., Xun, Z., Long, J., Sun, H., Yang, X., Wang, Y., Wang, Y., Xue, J., Zhang, N., Zhang, J., et al. (2024) · Hepatobiliary Surgery and Nutrition · doi:10.21037/hbsn-23-400 · Cited by 2
Reply to J. Perlmutter et al and D. Yee et al
Schott, A. F., & Hayes, D. F. (2012) · Journal of Clinical Oncology · doi:10.1200/jco.2012.45.3589
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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