Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics
Open accessAbstract
Glioblastoma (GB) is the most common and aggressive primary brain malignancy, with poor prognosis and a lack of effective therapeutic options. Accumulating evidence suggests that intratumor heterogeneity likely is the key to understanding treatment failure. However, the extent of intratumor heterogeneity as a result of tumor evolution is still poorly understood. To address this, we developed a unique surgical multisampling scheme to collect spatially distinct tumor fragments from 11 GB patients. We present an integrated genomic analysis that uncovers extensive intratumor heterogeneity, with most patients displaying different GB subtypes within the same tumor. Moreover, we reconstructed the phylogeny of the fragments for each patient, identifying copy number alterations in EGFR and CDKN2A/B/p14ARF as early events, and aberrations in PDGFRA and PTEN as later events during cancer progression. We also characterized the clonal organization of each tumor fragment at the single-molecule level, detecting multiple coexisting cell lineages. Our results reveal the genome-wide architecture of intratumor variability in GB across multiple spatial scales and patient-specific patterns of cancer evolution, with consequences for treatment design.
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
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?
Glioblastoma is the most common malignant primary brain tumor, but it is classified as a rare disease because its incidence rate of 3 per 100,000 people is below the rare disease definition rate of less than 10 per 100,000 people.
“While glioblastoma is the most common malignant primary brain tumor26–28, it is still classified as a “rare” disease, as its incidence rate (i.e., 3/100,000 people) is substantially lower than the rare disease definition rate (i.e., <10/100,000 people)24.”
From Federated learning enables big data for rare cancer boundary detection (2022) · cites this paper as [28]
GBM is challenged by molecular heterogeneity and genetic instability, even within the same patient.
“A significant challenge in the development of efficacious treatments for GBM is the molecular heterogeneity and genetic instability of these tumors, even within the same patient.38”
From Combination therapy in a xenograft model of glioblastoma: Enhancement of the antitumor activity of temozolomide by an MDM2 antagonist (2017) · cites this paper as [38]
Most clinically relevant solid tumors are highly heterogeneous at the phenotypic, physiologic, and genomic levels and continue to evolve over time.
“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 [15]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Radiotherapy Plus Concomitant and Adjuvant Temozolomide for Glioblastoma
Stupp, R., Mason, W. P., van den Bent, M. J., Weller, M., Fisher, B., Taphoorn, M. J. B., Belanger, K., Brandes, A. A., Marosi, C., Bogdahn, U., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa043330 · Cited by 21,807 · see citing works
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 · see citing works
Comprehensive genomic characterization defines human glioblastoma genes and core pathways
The Cancer Genome Atlas Research Network (2008) · Nature · doi:10.1038/nature07385 · Cited by 7,735 · see citing works
Verhaak, R. G. W., Hoadley, K. A., Purdom, E., Wang, V., Qi, Y., Wilkerson, M. D., Miller, C. R., Ding, L., Golub, T., Mesirov, J. P., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2009.12.020 · Cited by 7,575 · see citing works
Stummer, W., Pichlmeier, U., Meinel, T., Wiestler, O. D., Zanella, F., & Reulen, H.-J. (2006) · The Lancet Oncology · doi:10.1016/s1470-2045(06)70665-9 · Cited by 3,423 · see citing works
Greaves, M., & Maley, C. C. (2012) · Nature · doi:10.1038/nature10762 · Cited by 3,162 · see citing works
PHILLIPS, H. S., Kharbanda, S., Chen, R., Forrest, W. F., Soriano, R. H., Wu, T. D., Misra, A., Nigro, J. M., Colman, H., Soroceanu, L., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.02.019 · Cited by 3,106 · see citing works
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 · see citing works
Intra-tumour heterogeneity: a looking glass for cancer?
Marusyk, A., Almendro, V., & Polyák, K. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3261 · Cited by 2,003 · see citing works
Walker, M. D., Green, S. B., Byar, D., Alexander, E., Batzdorf, U., Brooks, W. H., Hunt, W., Maccarty, C. S., Mahaley, M., Mealey, J., et al. (1980) · New England Journal of Medicine · doi:10.1056/nejm198012043032303 · Cited by 1,727 · see citing works
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 1,690 · see citing works
Tumor heterogeneity: Causes and consequences
Marusyk, A., & Polyák, K. (2009) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2009.11.002 · Cited by 1,596 · see citing works
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 · see citing works
The Control of the Metabolic Switch in Cancers by Oncogenes and Tumor Suppressor Genes
Levine, A. J., & Puzio-Kuter, A. M. (2010) · Science · doi:10.1126/science.1193494 · Cited by 1,243 · see citing works
Allele-specific copy number analysis of tumors
Loo, P. V., Nord, S., Lingjærde, O. C., Russnes, H. G., Rye, I. H., Sun, W., Weigman, V., Marynen, P., Zetterberg, A., Naume, B., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1009843107 · Cited by 1,231 · see citing works
Beroukhim, R., Getz, G. A., Nghiemphu, L., Barretina, J., Hsueh, T., Linhart, D., Vivanco, I., Lee, J. C., Huang, J. H. Y., Alexander, S., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0710052104 · Cited by 1,055 · see citing works
荒木, 則. (2006) · Mebio oncology · Cited by 771 · see citing works
Mosaic Amplification of Multiple Receptor Tyrosine Kinase Genes in Glioblastoma
Snuderl, M., Fazlollahi, L., Le, L. P., Nitta, M., Zhelyazkova, B. H., Davidson, C. J., Akhavanfard, S., Cahill, D. P., Aldape, K., Betensky, R. A., et al. (2011) · Cancer Cell · doi:10.1016/j.ccr.2011.11.005 · Cited by 708 · see citing works
Evolutionary dynamics of carcinogenesis and why targeted therapy does not work
Gillies, R. J., Verduzco, D., & Gatenby, R. A. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3298 · Cited by 677 · see citing works
Evolution of the cancer genome
Yates, L. R., & Campbell, P. J. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3317 · Cited by 645 · see citing works
Szerlip, N. J., Pedraza, A. M., Chakravarty, D., Azim, M., McGuire, J., Fang, Y., Ozawa, T., Holland, E. C., Huse, J. T., Jhanwar, S. C., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1114033109 · Cited by 538 · see citing works
Inferring tumor progression from genomic heterogeneityPreprint
Navin, N. E., Krasnitz, A., Rodgers, L., Cook, K., Meth, J. L., Kendall, J., Riggs, M. G., Eberling, Y., Troge, J. E., Grubor, V. D., et al. (2009) · Genome Research · doi:10.1101/gr.099622.109 · Cited by 515 · see citing works
Intratumor Heterogeneity: Seeing the Wood for the Trees
Yap, T. A., Gerlinger, M., Futreal, P. A., Pusztai, L., & Swanton, C. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003854 · Cited by 487 · see citing works
Nogales‐Cadenas, R., Carmona‐Sáez, P., Vázquez, M., Vicente, C., Yang, X., Tirado, F., Carazo, J. M., & Pascual-Montano, A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp416 · Cited by 438 · see citing works
Burnet, N. G., Jefferies, S. J., Benson, R. J., et al. (2005) · British Journal of Cancer · doi:10.1038/sj.bjc.6602321 · Cited by 379 · see citing works
Investigating stem cells in human colon by using methylation patterns
Yatabe, Y., Tavaré, S., & Shibata, D. K. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.191225998 · Cited by 368 · see citing works
Self-citationIchimura, K., Schmidt, E., Goike, H., et al. (1996) · PubMed · Cited by 266 · see citing works
Cancer Stem Cell Tumor Model Reveals Invasive Morphology and Increased Phenotypical Heterogeneity
Sottoriva, A., Verhoeff, J. J. C., Borovski, T., McWeeney, S. K., Александрович, Н. Л., Medema, J. P., Sloot, P. M. A., & Vermeulen, L. (2010) · Cancer Research · doi:10.1158/0008-5472.can-09-3663 · Cited by 193 · see citing works
Self-citationSiegmund, K. D., Marjoram, P., Woo, Y., Tavaré, S., & Shibata, D. K. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0810276106 · Cited by 155 · see citing works
Self-citationChristopher, S. A., Diegelman, P., Porter, C. W., & Kruger, W. D. (2002) · PubMed · Cited by 147 · see citing works
Uncovering MicroRNA and Transcription Factor Mediated Regulatory Networks in Glioblastoma
Sun, J., Gong, X. Q., Purow, B. W., & Zhao, Z. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002488 · Cited by 142 · see citing works
López‐Ginés, C., Gil‐Benso, R., Ferrer-Luna, R., et al. (2010) · Modern Pathology · doi:10.1038/modpathol.2010.62 · Cited by 117 · see citing works
Piccirillo, S. G. M., Dietz, S., Madhu, B., Griffiths, J. R., Price, S. J., Collins, V. P., & Watts, C. (2012) · British Journal of Cancer · doi:10.1038/bjc.2012.271 · Cited by 111 · see citing works
Self-citationLetouzé, É., Allory, Y., Bollet, M. A., Radvanyi, F., & Guyon, F. (2010) · Genome biology · doi:10.1186/gb-2010-11-7-r76 · Cited by 101 · see citing works
The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns
Nicolas, P., Kim, K., Shibata, D. K., et al. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030028 · Cited by 100 · see citing works
NLK positively regulates Wnt/β‐catenin signalling by phosphorylating LEF1 in neural progenitor cells
Ota, S., Ishitani, S., Shimizu, N., Matsumoto, K., Itoh, M., & Ishitani, T. (2012) · The EMBO Journal · doi:10.1038/emboj.2012.46 · Cited by 82 · see citing works
Sottoriva, A., Spiteri, I., Shibata, D. K., Curtis, C. N., & Tavaré, S. (2012) · Cancer Research · doi:10.1158/0008-5472.can-12-2273 · Cited by 71 · see citing works
Self-citationModeling Evolutionary Dynamics of Epigenetic Mutations in Hierarchically Organized Tumors
Sottoriva, A., Vermeulen, L., & Tavaré, S. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001132 · Cited by 63 · see citing works
Self-citationHuang, T., Xie, Z., Wang, J., Li, M., Jing, N., & Li, L. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.251165 · Cited by 51 · see citing works
Integrating Approximate Bayesian Computation with Complex Agent-Based Models for Cancer Research
Sottoriva, A., & Tavaré, S. (2010) · Physica-Verlag eBooks · doi:10.1007/978-3-7908-2604-3_5 · Cited by 32 · see citing works
Self-citationThe Use of Global Profiling in Biomarker Development for Gliomas
Sulman, E. P., & Aldape, K. D. (2010) · Brain Pathology · doi:10.1111/j.1750-3639.2010.00456.x · Cited by 28 · see citing works
Neurogenesis in the Adult Brain I
Seki, T., Álvarez-Buylla, A., Parent, J. M., et al. (2011) · Springer eBooks · doi:10.1007/978-4-431-53933-9 · Cited by 19 · see citing works
Loss of chromosome 10 in glioblastoma: Relation to proliferation and angiogenesis
Horiguchi, H., Hirose, T., Sano, T., et al. (1999) · Pathology International · doi:10.1046/j.1440-1827.1999.00934.x · Cited by 14 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
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 · see citing works
Single-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 · see citing works
Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology
Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V., & Madabhushi, A. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0252-y · Cited by 1,698 · see citing works
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 · see citing works
Treating cancer with selective CDK4/6 inhibitors
O'Leary, B., Finn, R. S., & Turner, N. C. (2016) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.26 · Cited by 1,137 · see citing works
Wen, P. Y., Weller, M., Lee, E. Q., Alexander, B. M., Barnholtz-Sloan, J. S., Barthel, F. P., Batchelor, T. T., Bindra, R. S., Chang, S. M., Chiocca, E. A., et al. (2020) · Neuro-Oncology · doi:10.1093/neuonc/noaa106 · Cited by 1,168 · see citing works
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 · see citing works
Intratumor 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 · see citing works
Hollon, T. C., Pandian, B., Adapa, A. R., Urias, E., Save, A. V., Khalsa, S. S. S., Eichberg, D. G., D’Amico, R. S., Farooq, Z. U., Lewis, S., et al. (2020) · Nature Medicine · doi:10.1038/s41591-019-0715-9 · Cited by 790 · see citing works
Immunogenicity of somatic mutations in human gastrointestinal cancers
Tran, E., Ahmadzadeh, M., Lu, Y.-C., Gros, A., Turcotte, S., Robbins, P. F., Gartner, J. J., Zheng, Z., Li, Y. F., Ray, S., et al. (2015) · Science · doi:10.1126/science.aad1253 · Cited by 729 · see citing works
Paediatric and adult glioblastoma: multiform (epi)genomic culprits emerge
Sturm, D., Bender, S., Jones, D. T. W., Lichter, P., Grill, J., Becher, O., Hawkins, C., Majewski, J., Jones, C., Costello, J. F., et al. (2014) · Nature Reviews Cancer · doi:10.1038/nrc3655 · Cited by 555 · see citing works
Glioblastoma: defining tumor niches
Hambardzumyan, D., & Bergers, G. (2015) · Trends in Cancer · doi:10.1016/j.trecan.2015.10.009 · Cited by 522 · see citing works
Phenotypic screening in cancer drug discovery — past, present and future
Moffat, J. G., Rudolph, J., & Bailey, D. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4366 · Cited by 507 · see citing works
Single-cell analysis tools for drug discovery and development
Heath, J. R., Ribas, A., & Mischel, P. S. (2016) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2015.16 · Cited by 473 · see citing works
Kim, H., Zheng, S., Amini, S. S., Virk, S. M., Mikkelsen, T., Brat, D. J., Grimsby, J., Sougnez, C., Muller, F., Hu, J., et al. (2015) · Genome Research · doi:10.1101/gr.180612.114 · Cited by 411 · see citing works
Federated learning enables big data for rare cancer boundary detection
Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33407-5 · Cited by 394 · see citing works
Defining the biological basis of radiomic phenotypes in lung cancer
Grossmann, P., Stringfield, O., El-Hachem, N., Bui, M. M., Rios Velazquez, E., Parmar, C., Leijenaar, R. T., Haibe-Kains, B., Lambin, P., Gillies, R. J., et al. (2017) · eLife · doi:10.7554/elife.23421 · Cited by 365 · see citing works
<i>EGFR</i> 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 · see citing works
Spatial and temporal homogeneity of driver mutations in diffuse intrinsic pontine glioma
Nikbakht, H., Panditharatna, E., Mikael, L. G., Li, R., Gayden, T., Osmond, M., Ho, C.-Y., Kambhampati, M., Hwang, E. I., Faury, D., et al. (2016) · Nature Communications · doi:10.1038/ncomms11185 · Cited by 252 · see citing works
Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells
Darmanis, S., Gallant, C. J., Marinescu, V. D., Niklasson, M., Segerman, A., Flamourakis, G., Fredriksson, S., Assarsson, E., Lundberg, M., Nelander, S., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2015.12.021 · Cited by 219 · see citing works
The Many Facets of Therapy Resistance and Tumor Recurrence in Glioblastoma
Goenka, A., Tiek, D., Song, X., Huang, T., Hu, B., & Cheng, S.-Y. (2021) · Cells · doi:10.3390/cells10030484 · Cited by 169 · see citing works
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 · see citing works
Habashy, K. J., Mansour, R., Moussalem, C., Sawaya, R., & Massaad, M. J. (2022) · British Journal of Cancer · doi:10.1038/s41416-022-01864-w · Cited by 95 · see citing works
Akgül, S., Patch, A.-M., D’Souza, R. C. J., Mukhopadhyay, P., Nones, K., Kempe, S., Kazakoff, S. H., Jeffree, R. L., Stringer, B. W., Pearson, J. V., et al. (2019) · Cancers · doi:10.3390/cancers11020190 · Cited by 57 · see citing works
Wang, H., Cai, S., Bailey, B. J., Reza Saadatzadeh, M., Ding, J., Tonsing-Carter, E., Georgiadis, T. M., Zachary Gunter, T., Long, E. C., Minto, R. E., et al. (2017) · Journal of Neurosurgery · doi:10.3171/2016.1.jns152513 · Cited by 49 · see citing works
Bakas, S., Vollmuth, P., Galldiks, N., Booth, T. C., Aerts, H. J. W. L., Bi, W. L., Wiestler, B., Tiwari, P., Pati, S., Baid, U., et al. (2024) · The Lancet Oncology · doi:10.1016/s1470-2045(24)00315-2 · Cited by 36 · see citing works
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 · see citing works
Immunotherapy in Glioblastoma: A Clinical Perspective
Desbaillets, N., & Hottinger, A. F. (2021) · Cancers · doi:10.3390/cancers13153721 · Cited by 31 · see citing works
- Authors
- Sottoriva, A., Spiteri, I., Piccirillo, S. G. M., Touloumis, A., Collins, V. P., Marioni, J. C., Curtis, C., Watts, C., & Tavaré, S.
- Affiliations
- University of Southern California (US)
- Cancer Research UK (GB)
- University of Cambridge (GB)
- European Bioinformatics Institute (GB)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-02-14
- Volume
- 110
- Issue
- 10
- Pages
- 4009-4014
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3593922
- OpenAlex
- W2040458067
- Cited by
- 1,737
- References
- 43
- Citations by year
- 2026: 68 · 2025: 82 · 2024: 107 · 2023: 140 · 2022: 134 · 2021: 171 · 2020: 170 · 2019: 154 · 2018: 153 · 2017: 153 · 2016: 137 · 2015: 126 · 2014: 107 · 2013: 32 · 2012: 1
- FWCI
- 47.09
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- University of Brighton Repository (University of Brighton) (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Funders
- Cancer Research UK (19556, C14303/A10825)
- Brain Tumour Charity (10/136)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Genetics › Glioma Diagnosis and Treatment
- Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
- Keywords
- glioblastoma, intratumoral heterogeneity, tumor evolution, phylogenetic inference, copy number alterations, EGFR, PDGFRA, PTEN, clonal architecture, single-molecule sequencing, tumor subtypes, tumor progression
- MeSH terms
- Base Sequence, Brain Neoplasms, Chromosome Aberrations, DNA, Neoplasm, Glioblastoma, Humans, Phylogeny, Disease Progression, Genes, erbB-1, Evolution, Molecular, Genes, p16, DNA Copy Number Variations, Transcriptome
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
