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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Nearly all prior work comparing single-cell datasets first partitions the data discretely before downstream analysis.
“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]
Recent studies have successfully applied co-expression-like approaches to single-cell data to identify gene signatures and transcription factors that correlate with the stemness gradient in glioblastoma.
“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]
Some facets of cellular identity are transient in time and space, and temporal processes may progress along trajectories, oscillate, or be influenced by spatial position.
“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]
Several studies inferred individual cells' cell cycle phase from scRNA-seq using transcriptional signatures of discrete phases from earlier bulk profiling.
“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]
Single-cell profiles provide near-continuous sampling and show high conservation across cell types and species.
“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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- 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 · 2013: 2 · 2012: 1
- 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 › Genetics › 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
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 ›
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