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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Greater genomic divergence between tumor organoids and the parent tumor may be due to intra-tumor spatial heterogeneity and sampling bias, because organoids from one portion may not represent distant regions.
“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]
The Discussion reports that a single tumor biopsy can miss genetic aberrations elsewhere in a heterogeneous tumor and explicitly identifies sampling bias. That supports the proposed mechanism, but this paper studies spatially separated tumor samples, not organoids or genomic divergence between organoids and their parent tumors. (LLM, conf=0.84)
Experimental — accuracy not yet measuredA small needle biopsy of a single lesion may fail to reflect intra- and inter-tumor genetic heterogeneity.
“a small needle biopsy of a single lesion may fail to reflect the true underlying intra- and inter-tumor genetic heterogeneity (15–17).”
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 [14]
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- 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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