The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
Open accessAbstract
Cancer at single-cell resolution: Single-cell sequencing can illuminate the genetic properties of brain cancers and reveal heterogeneity within a tumor. Patel et al. examined the genome sequence of single cells isolated from brain glioblastomas. The findings revealed shared chromosomal changes but also extensive transcription variation, including genes related to signaling, which represent potential therapeutic targets. The authors suggest that the variation in tumor cells reflects neural development and that such variation among cancer cells may prove to have clinical significance. Science , this issue p. 1396
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“First, in contexts such as development and physiology, some facets of cellular identity are transient in time and space. Temporal processes may, for example, progress along one or more trajectories (e.g., differentiation); oscillate continuously between cellular states (e.g., the cell cycle98,99 or circadian rhythm100); or be influenced by the physical position and neighborhood of the cell71,93.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [99]
Experimental — accuracy not yet measuredIn the citing paper
“Almost all previous work quantifying differences between single-cell datasets relies on discrete partitioning of the data before downstream analysis9–16.”
From Quantifying the effect of experimental perturbations at single-cell resolution (2021) · cites this paper as [9]
In the citing paper
“Recent studies have successfully applied similar approaches to single-cell data, for example, by Patel et al. [36] to identify gene signatures and TFs that correlate with the stemness gradient in glioblastoma”
From Mapping gene regulatory networks from single-cell omics data (2018) · cites this paper as [36]
In the citing paper
“Several studies inferred the cell cycle phase of individual cells from single-cell RNA-seq data30,35,97,99, relying on transcriptional signatures of discrete phases from earlier bulk profiling experiments146.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [99]
In the citing paper
“single-cell profiles provide a near-continuous sampling and show high conservation across cell types and species30,97,99”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [99]
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Citations
Cites
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
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
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
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
Identification of human brain tumour initiating cells
Singh, S. K., Hawkins, C. E., Clarke, I. D., Squire, J. A., Bayani, J., Hide, T., Henkelman, R. M., Cusimano, M. D., & Dirks, P. B. (2004) · Nature · doi:10.1038/nature03128 · Cited by 7,564
Glioma stem cells promote radioresistance by preferential activation of the DNA damage response
Bao, S., Wu, Q., McLendon, R. E., Hao, Y., Shi, Q., Hjelmeland, A. B., Dewhirst, M. W., Bigner, D. D., & Rich, J. N. (2006) · Nature · doi:10.1038/nature05236 · Cited by 6,517
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
The Somatic Genomic Landscape of Glioblastoma
Brennan, C. W., Verhaak, R. G. W., McKenna, A., Campos, B., Noushmehr, H., Salama, S. R., Zheng, S., Chakravarty, D., Sanborn, J. Z., Berman, S. H., et al. (2013) · Cell · doi:10.1016/j.cell.2013.09.034 · Cited by 5,016
Cahoy, J. D., Emery, B., Kaushal, A., Foo, L. C., Zamanian, J. L., Christopherson, K. S., Xing, Y., Lubischer, J. L., Krieg, P. A., Krupenko, S. A., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4178-07.2008 · Cited by 3,129
Cited by
Sorted by citations
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353
Scenic: single-cell regulatory network inference and clustering.
Aibar, S., González-Blas, C. B., Moerman, T., Huynh-Thu, V. A., Imrichova, H., Hulselmans, G., Rambow, F., Marine, J.-C., Geurts, P., Aerts, J., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4463 · Cited by 6,520
Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq
Tirosh, I., Izar, B., Prakadan, S. M., Wadsworth, M. H., Treacy, D., Trombetta, J. J., Rotem, A., Rodman, C., Lian, C., Murphy, G., et al. (2016) · Science · doi:10.1126/science.aad0501 · Cited by 4,944
Self-citationAn Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma
Neftel, C., Laffy, J., Filbin, M. G., Hara, T., Shore, M. E., Rahme, G. J., Richman, A. R., Silverbush, D., Shaw, M. L., Hebert, C. M., et al. (2019) · Cell · doi:10.1016/j.cell.2019.06.024 · Cited by 2,873
Self-citationZhang, Y., & Zhang, Z. (2020) · Cellular and Molecular Immunology · doi:10.1038/s41423-020-0488-6 · Cited by 2,906
Metadata
- Authors
- 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., Louis, D. N., Rozenblatt-Rosen, O., Suvà, M. L., Regev, A., & Bernstein, B. E.
- Affiliations
- Broad Institute (US)
- Harvard University (US)
- Broad Institute of Harvard and Massachusetts Institute of Techonology (MIT), Cambridge, MA 02142, USA.
- Corresponding author
- Patel, Anoop P.
- Tirosh, Itay
- Suvà, Mario L.
- Regev, Aviv
- Bernstein, Bradley E.
- ORCID
- Venue
- Science
- Published
- 2014-06-20
- Volume
- 344
- Issue
- 6190
- Pages
- 1396-1401
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC4123637
- OpenAlex
- W1792532087
- Cited by
- 5,063
- References
- 47
- Citations by year
- 2026: 437 · 2025: 505 · 2024: 545 · 2023: 514 · 2022: 501 · 2021: 538 · 2020: 521 · 2019: 376 · 2018: 352 · 2017: 306 · 2016: 251 · 2015: 167 · 2014: 43
- FWCI
- 104.76
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- PMC
- Funders
- Howard Hughes Medical Institute
- National Human Genome Research Institute (U54HG006991)
- National Cancer Institute (U24CA180922, P50CA165962)
- National Institute of Neurological Disorders and Stroke (R01NS032677, R25NS065743)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Oncology › Glioma Diagnosis and Treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- glioblastoma, intratumoral heterogeneity, tumor heterogeneity, cancer stemness, transcriptional programs, oncogenic signaling, hypoxia, immune response, glioblastoma subtypes, prognostic factors, single-cell transcriptomics
- MeSH terms
- Brain Neoplasms, Glioblastoma, Humans, Prognosis, RNA, Messenger, Genetic Variation, Sequence Analysis, RNA, Gene Expression Profiling, Single-Cell Analysis
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