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.).
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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).”
In the citing paper
“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]
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
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
Flagged first, then by citations
Cited by
Sorted by citations
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
Radiomics: Images Are More than Pictures, They Are Data
Gillies, R. J., Kinahan, P. E., & Hricak, H. (2016) · Radiology · doi:10.1148/radiol.2015151169 · Cited by 8,421
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
Charoentong, P., Finotello, F., Angelova, M., Mayer, C., Efremova, M., Rieder, D., Hackl, H., & Trajanoski, Z. (2017) · Cell Reports · doi:10.1016/j.celrep.2016.12.019 · Cited by 5,041
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
Aerts, H. J. W. L., Velazquez, E. R., Leijenaar, R. T. H., Parmar, C., Grossmann, P., Carvalho, S., Bussink, J., Monshouwer, R., Haibe-Kains, B., Rietveld, D., et al. (2014) · Nature Communications · doi:10.1038/ncomms5006 · Cited by 5,132
“It is known that multiple subclonal populations coexist within tumours, reflecting extensive intratumoral ‘somatic evolution’ 15,16 .”
BackgroundSingle-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
Patel, A. P., Tirosh, I., Trombetta, J. J., Shalek, A. K., Gillespie, S. M., Wakimoto, H., Cahill, D. P., Nahed, B. V., Curry, W. T., Martuza, R. L., et al. (2014) · Science · doi:10.1126/science.1254257 · Cited by 5,063
Neoantigens in cancer immunotherapy
Schumacher, T. N., & Schreiber, R. D. (2015) · Science · doi:10.1126/science.aaa4971 · Cited by 4,783
Wolff, A. C., Hammond, M. E. H., Hicks, D. G., Dowsett, M., McShane, L. M., Allison, K. H., Allred, D. C., Bartlett, J. M. S., Bilous, M., Fitzgibbons, P. L., et al. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2013.50.9984 · Cited by 4,080
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
On the Dependency of Cellular Protein Levels on mRNA Abundance
Liu, Y., Beyer, A., & Aebersold, R. (2016) · Cell · doi:10.1016/j.cell.2016.03.014 · Cited by 3,221
Comprehensive molecular characterization of clear cell renal cell carcinoma
The Cancer Genome Atlas Research Network (2013) · Nature · doi:10.1038/nature12222 · Cited by 3,485
Moch, H., Cubilla, A. L., Humphrey, P. A., Reuter, V. E., & Ulbright, T. M. (2016) · European Urology · doi:10.1016/j.eururo.2016.02.029 · Cited by 3,157
“The use of such potential biomarkers must account for the considerable genetic intratumoural heterogeneity with the parallel evolution of multiple tumour clones [38,39].”
BackgroundEmerging Biological Principles of Metastasis
Lambert, A. W., Pattabiraman, D. R., & Weinberg, R. A. (2017) · Cell · doi:10.1016/j.cell.2016.11.037 · Cited by 3,191
“…such genetic divergence may, in real life, be very difficult to gauge, given the clonal diversity that may have arisen within a primary tumor (Gerlinger et al., 2012) and the fact that various genetically distinct clonal subpopulations may be represented within the primary tumor in…”
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
“Recurrent disruption of the SWI/SNF complex or activation of the PI3K pathway through distinct mutations in mTOR, TSC1, PTEN and PIK3CA are frequently observed in different subclones from the same renal cancer (Gerlinger et al., 2014a; Gerlinger et al., 2012; Voss et al., 2014).”
Self-citationHsieh, J. J., Purdue, M. P., Signoretti, S., Swanton, C., Albiges, L., Schmidinger, M., Heng, D. Y., Larkin, J., & Ficarra, V. (2017) · Nature Reviews Disease Primers · doi:10.1038/nrdp.2017.9 · Cited by 2,426
Self-citationMetabolic reprogramming and cancer progression
Faubert, B., Solmonson, A., & DeBerardinis, R. J. (2020) · Science · doi:10.1126/science.aaw5473 · Cited by 2,740
“In ccRCC, sequencing multiple regions of primary tumors revealed that most somatically acquired mutations are not present in all areas (57).”
BackgroundLiquid biopsies come of age: Towards implementation of circulating tumour DNA
Wan, J. C. M., Massie, C., Garcia-Corbacho, J., Mouliere, F., Brenton, J. D., Caldas, C., Pacey, S., Baird, R., & Rosenfeld, N. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2017.7 · Cited by 2,809
Yu, H. A., Arcila, M. E., Rekhtman, N., Sima, C. S., Zakowski, M. F., Pao, W., Kris, M. G., Miller, V. A., Ladanyi, M., & Riely, G. J. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-12-2246 · Cited by 2,454
Tumour heterogeneity and cancer cell plasticity
Meacham, C. E., & Morrison, S. J. (2013) · Nature · doi:10.1038/nature12624 · Cited by 2,526
The immune contexture in cancer prognosis and treatment
Fridman, W. H., Zitvogel, L., Sautès–Fridman, C., & Kroemer, G. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.101 · Cited by 2,263
The causes and consequences of genetic heterogeneity in cancer evolution
Burrell, R. A., McGranahan, N., Bartek, J., & Swanton, C. (2013) · Nature · doi:10.1038/nature12625 · Cited by 2,262
Self-citationLiquid Biopsies: Genotyping Circulating Tumor DNA
Diaz, L. A., & Bardelli, A. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2012.45.2011 · Cited by 2,210
Evolution of the Cancer Stem Cell Model
Kreso, A., & Dick, J. E. (2014) · Cell stem cell · doi:10.1016/j.stem.2014.02.006 · Cited by 2,304
Taube, J. M., Klein, A., Brahmer, J. R., Xu, H., Pan, X., Kim, J. H., Chen, L., Pardoll, D. M., Topalian, S. L., & Anders, R. A. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-3271 · Cited by 2,324
Absolute quantification of somatic DNA alterations in human cancer
Carter, S. L., Cibulskis, K., Helman, E., McKenna, A., Shen, H., Zack, T. I., Laird, P. W., Onofrio, R. C., Winckler, W., Weir, B. A., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2203 · Cited by 2,031
Intra-tumour heterogeneity: a looking glass for cancer?
Marusyk, A., Almendro, V., & Polyák, K. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3261 · Cited by 2,058
Clinical and biological implications of driver mutations in myelodysplastic syndromes
Papaemmanuil, E., Gerstung, M., Malcovati, L., Tauro, S., Gundem, G., Van Loo, P., Yoon, C. J., Ellis, P., Wedge, D. C., Pellagatti, A., et al. (2013) · Blood · doi:10.1182/blood-2013-08-518886 · Cited by 1,832
Self-citationLiquid biopsy: monitoring cancer-genetics in the blood
Crowley, E. H., Nicolantonio, F. D., Loupakis, F., & Bardelli, A. (2013) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2013.110 · Cited by 1,857
Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics
Sottoriva, A., Spiteri, I., Piccirillo, S. G. M., Touloumis, A., Collins, V. P., Marioni, J. C., Curtis, C., Watts, C., & Tavaré, S. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219747110 · Cited by 1,737
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
Wolff, A. C., Hammond, M. E. H., Hicks, D. G., Dowsett, M., McShane, L. M., Allison, K. H., Allred, D. C., Bartlett, J. M. S., Bilous, M., Fitzgibbons, P. L., et al. (2013) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2013-0953-sa · Cited by 1,782
Patient-Derived Xenograft Models: An Emerging Platform for Translational Cancer Research
Hidalgo, M. M., Amant, F. C., Biankin, A. V., Budínská, E., Byrne, A. T., Caldas, C., Clarke, R. B., de Jong, S., Jonkers, J., Mælandsmo, G. M., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-0001 · Cited by 1,797
New Technologies for Analysis of Extracellular Vesicles
Shao, H., Im, H., Castro, C. M., Breakefield, X. O., Weissleder, R., & Lee, H. (2018) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00534 · Cited by 1,697
Scher, H. I., Morris, M. J., Stadler, W. M., Higano, C. S., Basch, E., Fizazi, K. S., Antonarakis, E. S., Beer, T. M., Carducci, M. A., Chi, K. N., et al. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2015.64.2702 · Cited by 1,707
Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA
Murtaza, M., Dawson, S.-J., Tsui, D. W. Y., Gale, D., Forshew, T., Piskorz, A. M., Parkinson, C., Chin, S.-F., Kingsbury, Z., Wong, A. S. C., et al. (2013) · Nature · doi:10.1038/nature12065 · Cited by 1,624
Epithelial Mesenchymal Transition in Tumor Metastasis
Mittal, V. (2018) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-020117-043854 · Cited by 1,528
Whole–genome characterization of chemoresistant ovarian cancer
Patch, A., Christie, E. L., Etemadmoghadam, D., Garsed, D. W., George, J., Fereday, S., Nones, K., Cowin, P. A., Alsop, K., Bailey, P. J., et al. (2015) · Nature · doi:10.1038/nature14410 · Cited by 1,572
Matthay, K. K., Maris, J. M., Schleiermacher, G., Nakagawara, A., Mackall, C. L., Diller, L., & Weiss, W. A. (2016) · Nature Reviews Disease Primers · doi:10.1038/nrdp.2016.78 · Cited by 1,496
Single-cell genome sequencing: current state of the science
Gawad, C., Koh, W., & Quake, S. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.16 · Cited by 1,334
Matthews, H. K., Bertoli, C., & de Bruin, R. A. M. (2022) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-021-00404-3 · Cited by 1,506
Classifying Cancers Based on T-cell Infiltration and PD-L1
Teng, M. W. L., Ngiow, S. F., Ribas, A., & Smyth, M. J. (2015) · Cancer Research · doi:10.1158/0008-5472.can-15-0255 · Cited by 1,436
“In addition, given the 185 focal nature of PD-L1 expression withinmany tumors and emerg186 ing information about intratumoral genetic heterogeneity (31), if 187 very small needle biopsies or dispersed single-cell cytology speci188 mens are evaluated, a false-negative evaluation could potentially 189 result (23).”
Steeg, P. S. (2016) · Nature Reviews Cancer · doi:10.1038/nrc.2016.25 · Cited by 1,363
The Cancer Stem Cell Niche: How Essential Is the Niche in Regulating Stemness of Tumor Cells?
Plaks, V., Kong, N., & Werb, Z. (2015) · Cell Stem Cell · doi:10.1016/j.stem.2015.02.015 · Cited by 1,557
“…advanced genome sequencing has demonstrated that cancer within a single patient is a heterogeneous mixture of genetically distinct sub-clones that arise through branching evolution (Greaves and Maley, 2012; Burrell et al., 2013) and seed different parts of a single tumor (Gerlinger et al., 2012).”
The evolutionary history of lethal metastatic prostate cancer
ICGC Prostate UK Group, Gundem, G., Loo, P. V., Kremeyer, B., Alexandrov, L. B., Tubío, J. M. C., Papaemmanuil, E., Brewer, D. S., Kallio, H. M. L., Högnäs, G., et al. (2015) · Nature · doi:10.1038/nature14347 · Cited by 1,358
Self-citationEvolution 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
Wilm, A., Aw, P. P. K., Bertrand, D., Yeo, G. H. T., Ong, S. H., Wong, C. H., Khor, C. C., Petric, R., Hibberd, M. L., & Nagarajan, N. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks918 · Cited by 1,370
Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma
Johnson, B. E., Mazor, T., Hong, C., Barnes, M., Aihara, K., McLean, C. Y., Fouse, S. D., Yamamoto, S., Ueda, H., Tatsuno, K., et al. (2014) · Science · doi:10.1126/science.1239947 · Cited by 1,362
Lessons from the Cancer Genome
Garraway, L. A., & Lander, E. S. (2013) · Cell · doi:10.1016/j.cell.2013.03.002 · Cited by 1,377
Systemic Therapy for Metastatic Renal-Cell Carcinoma
Choueiri, T. K., & Motzer, R. J. (2017) · New England Journal of Medicine · doi:10.1056/nejmra1601333 · Cited by 1,307
Lindeman, N. I., Cagle, P. T., Beasley, M. B., Chitale, D. A., Dacic, S., Giaccone, G., Jenkins, R. B., Kwiatkowski, D. J., Saldivar, J.-S., Squire, J., et al. (2013) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e318290868f · Cited by 1,280
Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177
Mutant MHC class II epitopes drive therapeutic immune responses to cancer
Kreiter, S., Vormehr, M., van de Roemer, N., Diken, M., Löwer, M., Diekmann, J., Boegel, S., Schrörs, B., Vascotto, F., Castle, J. C., et al. (2015) · Nature · doi:10.1038/nature14426 · Cited by 1,243
Integrated molecular analysis of clear-cell renal cell carcinoma
Sato, Y., Yoshizato, T., Shiraishi, Y., Maekawa, S., Okuno, Y., Kamura, T., Shimamura, T., Sato‐Otsubo, A., Nagae, G., Suzuki, H., et al. (2013) · Nature Genetics · doi:10.1038/ng.2699 · Cited by 1,257
Tumour heterogeneity in the clinic
Bedard, P. L., Hansen, A. R., Ratain, M. J., & Siu, L. L. (2013) · Nature · doi:10.1038/nature12627 · Cited by 1,231
Applications and limitations of radiomics
Yip, S. S. F., & Aerts, H. J. W. L. (2016) · Physics in Medicine and Biology · doi:10.1088/0031-9155/61/13/r150 · Cited by 1,210
Gerlinger, M., Horswell, S. D., Larkin, J., Rowan, A., Salm, M., Varela, I., Fisher, R. A., McGranahan, N., Matthews, N., Santos, C. R., et al. (2014) · Nature Genetics · doi:10.1038/ng.2891 · Cited by 1,236
Self-citationRenal cell carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up
Escudier, B., Porta, C., Schmidinger, M., Rioux-Leclercq, N., Bex, A., Khoo, V., Grünwald, V., Gillessen, S., & Horwich, A. (2019) · Annals of Oncology · doi:10.1093/annonc/mdz056 · Cited by 1,151
Liver Cancer Cell of Origin, Molecular Class, and Effects on Patient Prognosis
Sia, D., Villanueva, A., Friedman, S. L., & Llovet, J. M. (2016) · Gastroenterology · doi:10.1053/j.gastro.2016.11.048 · Cited by 1,181
Le Tourneau, C., Delord, J.-P., Gonçalves, A., Gavoille, C., Dubot, C., Isambert, N., Campone, M., Trédan, O., Massiani, M.-A., Mauborgne, C., et al. (2015) · The Lancet Oncology · doi:10.1016/s1470-2045(15)00188-6 · Cited by 1,137
The evolutionary history of 2,658 cancers
Gerstung, M., Jolly, C., Leshchiner, I., Dentro, S. C., Gonzalez, S., Rosebrock, D., Mitchell, T. J., Rubanova, Y., Anur, P., Yu, K., et al. (2020) · Nature · doi:10.1038/s41586-019-1907-7 · Cited by 1,057
Biological and therapeutic impact of intratumor heterogeneity in cancer evolution
McGranahan, N., & Swanton, C. (2015) · Cancer Cell · doi:10.1016/j.ccell.2014.12.001 · Cited by 1,077
Self-citationGenomic Landscape of Non-Small Cell Lung Cancer in Smokers and Never-Smokers
Govindan, R., Ding, L., Griffith, M., Subramanian, J., Dees, N. D., Kanchi, K., Maher, C. A., Fulton, R. S., Fulton, L., Wallis, J. W., et al. (2012) · Cell · doi:10.1016/j.cell.2012.08.024 · Cited by 1,161
Combinatorial drug therapy for cancer in the post-genomic era
Al-Lazikani, B., Banerji, U., & Workman, P. (2012) · Nature Biotechnology · doi:10.1038/nbt.2284 · Cited by 1,070
Spatial and temporal diversity in genomic instability processes defines lung cancer evolution
de Bruin, E. C., McGranahan, N., Mitter, R., Salm, M., Wedge, D. C., Yates, L., Jamal-Hanjani, M., Shafi, S., Murugaesu, N., Rowan, A. J., et al. (2014) · Science · doi:10.1126/science.1253462 · Cited by 1,117
Self-citationDrug resistance and combating drug resistance in cancer
Wang, X., Zhang, H., & Chen, X. (2019) · Cancer Drug Resistance · doi:10.20517/cdr.2019.10 · Cited by 1,147
“Ample evidence has shown that subpopulations of cancer cells with various genetic makeups co-exist in primary tumors like ovarian cancer([100]), renal cell carcinoma([101]), breast cancer([102]), and chronic lymphocytic leukemia([103]).”
BackgroundClonal evolution and resistance to EGFR blockade in the blood of colorectal cancer patients
Siravegna, G., Mussolin, B., Buscarino, M., Corti, G., Cassingena, A., Crisafulli, G., Ponzetti, A., Cremolini, C., Amatu, A., Lauricella, C., et al. (2015) · Nature Medicine · doi:10.1038/nm.3870 · Cited by 1,088
Brastianos, P. K., Carter, S. L., Santagata, S., Cahill, D. P., Taylor-Weiner, A. N., Jones, R. T., Allen, E. M. V., Lawrence, M. S., Horowitz, P. M., Cibulskis, K., et al. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-15-0369 · Cited by 1,090
“Because cancers are genetically heterogeneous (3-9), sampling a cancer in two different locations is expected to reveal mutations exclusive to each sample.”
BackgroundInfluentialTowards personalized, tumour-specific, therapeutic vaccines for cancer
Hu, Z., Ott, P. A., & Wu, C. J. (2018) · Nature Reviews Immunology · doi:10.1038/nri.2017.131 · Cited by 1,067
Braun, D. A., Hou, Y., Bakouny, Z., Ficial, M., Sant’ Angelo, M., Forman, J., Ross-Macdonald, P., Berger, A. C., Jegede, O. A., Elagina, L., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0839-y · Cited by 992
Targeting neoantigens to augment antitumour immunity
Yarchoan, M., Johnson, B. A., Lutz, E. R., Laheru, D. A., & Jaffee, E. M. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2016.154 · Cited by 997
Mu, P., Zhang, Z., Benelli, M., Karthaus, W. R., Hoover, E., Chen, C.-C., Wongvipat, J., Ku, S., Gao, D., Cao, Z., et al. (2017) · Science · doi:10.1126/science.aah4307 · Cited by 1,089
The Next-Generation Sequencing Revolution and Its Impact on Genomics
Koboldt, D. C., Steinberg, K. M., Larson, D. E., Wilson, R. K., & Mardis, E. R. (2013) · Cell · doi:10.1016/j.cell.2013.09.006 · Cited by 1,098
Whole-genome landscape of pancreatic neuroendocrine tumours
Initiative, A. P. C. G., Scarpa, A., Chang, D. K., Nones, K., Corbo, V., Patch, A.-M., Bailey, P., Lawlor, R. T., Johns, A. L., Miller, D. K., et al. (2017) · Nature · doi:10.1038/nature21063 · Cited by 999
Widespread Genetic Heterogeneity in Multiple Myeloma: Implications for Targeted Therapy
Lohr, J. G., Stojanov, P., Carter, S. L., Cruz-Gordillo, P., Lawrence, M. S., Auclair, D., Sougnez, C., Knoechel, B., Gould, J., Saksena, G., et al. (2014) · Cancer Cell · doi:10.1016/j.ccr.2013.12.015 · Cited by 988
Self-citationA Big Bang model of human colorectal tumor growth
Sottoriva, A., Kang, H., Ma, Z., Graham, T. A., Salomon, M. P., Zhao, J., Marjoram, P., Siegmund, K. D., Press, M. F., Shibata, D. K., et al. (2015) · Nature Genetics · doi:10.1038/ng.3214 · Cited by 1,037
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
“Multiregional sequencing of renal carcinoma, glioblastoma and lung cancer have all showed significant divergence between distinct areas of the same tumor (Gerlinger et al., 2012; Thrane et al., 2018; Yates et al., 2015; Zhang et al., 2014).”
BackgroundZhao, Z., Chen, X., Dowbaj, A. M., Sljukic, A., Bratlie, K., Lin, L., Fong, E. L. S., Balachander, G. M., Chen, Z., Soragni, A., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00174-y · Cited by 1,082
PyClone: statistical inference of clonal population structure in cancer
Roth, A. J. L., Khattra, J. S., Yap, D., Wan, A. N. C., Laks, E., Biele, J., Ha, G., Aparicio, S. A. J. R., Bouchard‐Côté, A., & Shah, S. P. (2014) · Nature Methods · doi:10.1038/nmeth.2883 · Cited by 1,002
Signal Transduction in CancerPreprint
Sever, R., & Brugge, J. S. (2015) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a006098 · Cited by 1,028
“Recent evidence emerging from sequencing of single cells and multiple regions of tumors from individual patients has revealed this is far greater than previously imagined (Navin et al. 2011; Ruiz et al. 2011; Ding et al. 2012; Gerlinger et al. 2012; Xu et al. 2012b; Bashashati et al. 2013) In one study of kidney tumor…”
Acquired Resistance and Clonal Evolution in Melanoma during BRAF Inhibitor Therapy
Shi, H., Hugo, W., Kong, X., Hong, A., Koya, R. C., Moriceau, G., Chodon, T., Guo, R., Johnson, D. B., Dahlman, K. B., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0642 · Cited by 982
5-fluorouracil and other fluoropyrimidines in colorectal cancer: Past, present and future
Vodenkova, S., Buchler, T., Cervena, K., Veskrnova, V., Vodicka, P., & Vymetalkova, V. (2020) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2019.107447 · Cited by 956
Cancer heterogeneity: implications for targeted therapeutics
Fisher, R. A., Pusztai, L., & Swanton, C. (2013) · British Journal of Cancer · doi:10.1038/bjc.2012.581 · Cited by 972
Self-citationIntratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing
Zhang, J., Fujimoto, J., Zhang, J., Wedge, D. C., Song, X., Zhang, J., Seth, S., Chow, C.-W., Cao, Y., Gumbs, C., et al. (2014) · Science · doi:10.1126/science.1256930 · Cited by 965
Self-citationLiquid Biopsy: From Discovery to Clinical Application
Alix‐Panabières, C., & Pantel, K. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-1311 · Cited by 1,006
“Even if one metastatic lesion can be biopsied, substantial genetic heterogeneity of metastatic lesions located at different sites in the same patient has been demonstrated (111).”
BackgroundBAP1 loss defines a new class of renal cell carcinoma
Peña‐Llopis, S., Vega-Rubín-de-Celis, S., Liao, A., Leng, N., Pavía-Jiménez, A., Wang, S., Yamasaki, T., Zhrebker, L., Sivanand, S., Spence, P., et al. (2012) · Nature Genetics · doi:10.1038/ng.2323 · Cited by 990
Intratumor Heterogeneity: Evolution through Space and Time
Swanton, C. (2012) · Cancer Research · doi:10.1158/0008-5472.can-12-2217 · Cited by 931
Self-citationApplication of Cell-free DNA Analysis to Cancer Treatment
Corcoran, R. B., & Chabner, B. A. (2018) · New England Journal of Medicine · doi:10.1056/nejmra1706174 · Cited by 980
Cancer Epigenetics: Tumor Heterogeneity, Plasticity of Stem-like States, and Drug Resistance
Easwaran, H., Tsai, H.-C., & Baylin, S. B. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.05.015 · Cited by 915
Cancer Cell Metabolism: One Hallmark, Many Faces
Cantor, J. R., & Sabatini, D. M. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0345 · Cited by 989
Liquid biopsy: current technology and clinical applications
Nikanjam, M., Kato, S., & Kurzrock, R. (2022) · Journal of Hematology & Oncology · doi:10.1186/s13045-022-01351-y · Cited by 963
“Single tumor-biopsy samples can lead to an underestimation of the tumor genomic landscape given intratumor heterogeneity [51].”
BackgroundDeep learning in cancer diagnosis, prognosis and treatment selection
Tran, K. A., Kondrashova, O., Bradley, A., Williams, E. D., Pearson, J. V., & Waddell, N. (2021) · Genome Medicine · doi:10.1186/s13073-021-00968-x · Cited by 932
“An exciting new approach for studying the TME is spatial transcriptomics which allows quantification of gene expression in individual cells or regions while maintaining their positional representation, thus capturing spatial heterogeneity of gene expression at high resolution [149, 150].”
BackgroundHow cancer metabolism is tuned for proliferation and vulnerable to disruption
Schulze, A., & Harris, A. L. (2012) · Nature · doi:10.1038/nature11706 · Cited by 945
Current Challenges in Cancer Treatment
Zugazagoitia, J., Guedes, C., Ponce, S., Ferrer, I., Molina‐Pinelo, S., & Paz-Ares, L. G. (2016) · Clinical Therapeutics · doi:10.1016/j.clinthera.2016.03.026 · Cited by 961
“In addition, 25% to 50% of the detected mutations were private (tumor regions not detected in order).(51) This high level of intratumor heterogeneity has also been confirmed in other tumor types, including lung cancer.”
BackgroundMolecular profiling for precision cancer therapies
Malone, E. R., Oliva, M., Sabatini, P. J. B., Stockley, T. L., & Siu, L. L. (2020) · Genome Medicine · doi:10.1186/s13073-019-0703-1 · Cited by 982
“Topics that remain to be addressed include the high variability of CTC and plasma ctDNA levels between individual patients that result from inconsistent shedding and the impact of disease burden and/or cancer type on circulating nucleic acids [47].”
BackgroundInterplay between the Cancer Genome and Epigenome
Shen, H., & Laird, P. W. (2013) · Cell · doi:10.1016/j.cell.2013.03.008 · Cited by 949
Replication stress links structural and numerical cancer chromosomal instability
Burrell, R. A., McClelland, S. E., Endesfelder, D., Groth, P., Weller, M.-C., Shaikh, N., Domingo, E., Kanu, N., Dewhurst, S. M., Gronroos, E. C., et al. (2013) · Nature · doi:10.1038/nature11935 · Cited by 868
Self-citationHeterogeneity of genomic evolution and mutational profiles in multiple myeloma
Bolli, N., Avet-Loiseau, H., Wedge, D. C., Van Loo, P., Alexandrov, L. B., Martincorena, I., Dawson, K. J., Iorio, F., Nik-Zainal, S., Bignell, G. R., et al. (2014) · Nature Communications · doi:10.1038/ncomms3997 · Cited by 875
Self-citationEpigenetic modulators, modifiers and mediators in cancer aetiology and progression
Feinberg, A. P., Koldobskiy, M. A., & Göndör, A. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.13 · Cited by 841
Exosome-based liquid biopsies in cancer: opportunities and challenges
Wang, Y., Hurley, J. D., Roberts, D., Chakrabortty, S. K., Enderle, D., Noerholm, M., Breakefield, X. O., & Skog, J. (2021) · Annals of Oncology · doi:10.1016/j.annonc.2021.01.074 · Cited by 882
Cancer Stem Cells: Basic Concepts and Therapeutic Implications
Nassar, D., & Blanpain, C. (2016) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathol-012615-044438 · Cited by 904
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
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