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Variable Clonal Repopulation Dynamics Influence Chemotherapy Response in Colorectal Cancer
Open accessAbstract
Dissecting Diversity: Solid tumors are composed of functionally diverse tumor cells. The prevailing view is that this "intratumoral heterogeneity" arises from the accumulation of mutations during tumor growth, resulting in multiple genetically defined subclones of cells that respond in different ways to selective pressures such as chemotherapy. Kreso et al. (p. 543 , published online 13 December; see the Perspective by Marusyk and Polyak ) simultaneously monitored the genetic profiles and growth behavior of human colorectal cancer cells that were serially passaged in mice. Individual tumor cells within a uniform genetic lineage displayed extensive variation in survival, growth dynamics, and response to a chemotherapeutic drug. Thus, additional diversity-generating mechanisms such as epigenetic regulation or microenvironmental variability appear to operate within a genetic clone, endowing a subset of tumor cells with robust survival potential, especially during stress.
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Cites
Comprehensive molecular characterization of human colon and rectal cancer
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11252 · Cited by 8,499
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
Greaves, M., & Maley, C. C. (2012) · Nature · doi:10.1038/nature10762 · Cited by 3,162
Clinical Resistance to STI-571 Cancer Therapy Caused by BCR-ABL Gene Mutation or Amplification
Gorre, M. E., Mohammed, M., Ellwood, K., Hsu, N., Paquette, R., Rao, P. N., & Sawyers, C. L. (2001) · Science · doi:10.1126/science.1062538 · Cited by 3,104
Persister cells, dormancy and infectious disease
Lewis, K. (2007) · Nature Reviews Microbiology · doi:10.1038/nrmicro1557 · Cited by 2,052
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
Control of Stochasticity in Eukaryotic Gene Expression
Raser, J. M., & O'Shea, E. K. (2004) · Science · doi:10.1126/science.1098641 · Cited by 1,425
Functional and phylogenetic diversity as predictors of biodiversity–ecosystem-function relationships
Flynn, D. F. B., Mirotchnick, N., Jain, M., Palmer, M. I., & Naeem, S. (2011) · Ecology · doi:10.1890/10-1245.1 · Cited by 890
Microdroplet-based PCR enrichment for large-scale targeted sequencing
Tewhey, R., Warner, J. B., Nakano, M., Libby, B., Medkova, M., David, P. H., Kotsopoulos, S. K., Samuels, M. L., Hutchison, J. B., Larson, J. W., et al. (2009) · Nature Biotechnology · doi:10.1038/nbt.1583 · Cited by 454
Cited by
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
Batlle, E., & Clevers, H. (2017) · Nature Medicine · doi:10.1038/nm.4409 · Cited by 2,769
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
Assarsson, E., Lundberg, M., Holmquist, G., Björkesten, J., Bucht Thorsen, S., Ekman, D., Eriksson, A., Rennel Dickens, E., Ohlsson, S., Edfeldt, G., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095192 · Cited by 1,874
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
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
Hou, Y., Guo, H., Cao, C., Li, X., Hu, B., Zhu, P., Wu, X., Wen, L., Tang, F., Huang, Y., et al. (2016) · Cell Research · doi:10.1038/cr.2016.23 · Cited by 647
Emran, T. B., Shahriar, A., Mahmud, A. R., Rahman, T., Abir, M. H., Siddiquee, M. F. R., Ahmed, H., Rahman, N., Nainu, F., Wahyudin, E., et al. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.891652 · Cited by 606
Mechanisms Governing Metastatic Dormancy and Reactivation
Giancotti, F. G. (2013) · Cell · doi:10.1016/j.cell.2013.10.029 · Cited by 586
Targeting Cancer Stemness in the Clinic: From Hype to Hope
Saygin, C., Matei, D., Majeti, R., Reizes, O., & Lathia, J. D. (2019) · Cell Stem Cell · doi:10.1016/j.stem.2018.11.017 · Cited by 517
Resistance to anti-EGFR therapy in colorectal cancer: From heterogeneity to convergent evolution
Misale, S., Di Nicolantonio, F., Sartore-Bianchi, A., Siena, S., & Bardelli, A. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-0462 · Cited by 513
Self-renewal as a therapeutic target in human colorectal cancer
Kreso, A., van Galen, P., Pedley, N. M., Lima-Fernandes, E., Frelin, C., Davis, T., Cao, L., Baiazitov, R., Du, W., Sydorenko, N., et al. (2014) · Nature Medicine · doi:10.1038/nm.3418 · Cited by 500
Self-citationTargeting Cancer Cell Dormancy
Recasens, A., & Munoz, L. (2019) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2018.12.004 · Cited by 356
Cell-to-cell variation in p53 dynamics leads to fractional killing.
Paek, A. L., Liu, J. C., Loewer, A., Forrester, W. C., & Lahav, G. (2016) · Cell · doi:10.1016/j.cell.2016.03.025 · Cited by 292
Heterogeneity in Colorectal Cancer: A Challenge for Personalized Medicine?
Molinari, C., Marisi, G., Passardi, A., Matteucci, L., De Maio, G., & Ulivi, P. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19123733 · Cited by 262
Gump, J. M., Staskiewicz, L., Morgan, M. J., Bamberg, A., Riches, D. W. H., & Thorburn, A. (2014) · Nature Cell Biology · doi:10.1038/ncb2886 · Cited by 230
Cancer drug-tolerant persister cells: from biological questions to clinical opportunities
Russo, M., Chen, M., Mariella, E., Peng, H., Rehman, S. K., Sancho, E., Sogari, A., Toh, T. S., Balaban, N. Q., Batlle, E., et al. (2024) · Nature Reviews Cancer · doi:10.1038/s41568-024-00737-z · Cited by 210
Self-citationLeukemia Propagating Cells Rebuild an Evolving Niche in Response to Therapy
Duan, C.-W., Shi, J., Chen, J., Wang, B., Yu, Y.-H., Qin, X., Zhou, X.-C., Cai, Y.-J., Li, Z.-Q., Zhang, F., et al. (2014) · Cancer Cell · doi:10.1016/j.ccr.2014.04.015 · Cited by 198
Kim, K.-T., Lee, H. W., Lee, H.-O., Song, H. J., Jeong, D. E., Shin, S., Kim, H., Shin, Y., Nam, D.-H., Jeong, B. C., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-0945-9 · Cited by 198
MEK inhibitors activate Wnt signalling and induce stem cell plasticity in colorectal cancer
Zhan, T., Ambrosi, G., Wandmacher, A. M., Rauscher, B., Betge, J., Rindtorff, N., Häussler, R. S., Hinsenkamp, I., Bamberg, L., Hessling, B., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09898-0 · Cited by 189
Surviving apoptosis: life–death signaling in single cells
Flusberg, D. A., & Sorger, P. K. (2015) · Trends in Cell Biology · doi:10.1016/j.tcb.2015.03.003 · Cited by 149
Merino, D., Weber, T. S., Serrano, A., Vaillant, F., Liu, K., Pal, B., Di Stefano, L., Schreuder, J., Lin, D., Chen, Y., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08595-2 · Cited by 145
3D Bioprinting of Tumor Models for Cancer Research
Kang, Y., Datta, P., Shanmughapriya, S., & Ozbolat, I. T. (2020) · ACS Applied Bio Materials · doi:10.1021/acsabm.0c00791 · Cited by 112
Manic, G., Signore, M., Sistigu, A., Russo, G., Corradi, F., Siteni, S., Musella, M., Vitale, S., De Angelis, M. L., Pallocca, M., et al. (2018) · Gut · doi:10.1136/gutjnl-2016-312623 · Cited by 98
Cellular barcoding to decipher clonal dynamics in disease
Sankaran, V. G., Weissman, J. S., & Zon, L. I. (2022) · Science · doi:10.1126/science.abm5874 · Cited by 93
Modeling of Patient-Derived Xenografts in Colorectal Cancer
(2017) · doi:10.1158/1535-7163.mct-16-0721 · Cited by 64
Patient-derived tumor models: a more suitable tool for pre-clinical studies in colorectal cancer
Rizzo, G., Bertotti, A., Leto, S. M., & Vetrano, S. (2021) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-021-01970-2 · Cited by 51
Genetic Alterations of Metastatic Colorectal Cancer
Testa, U., Castelli, G., & Pelosi, E. (2020) · Biomedicines · doi:10.3390/biomedicines8100414 · Cited by 44
Haynes, J., McKee, T. D., Haller, A., Wang, Y., Leung, C., Gendoo, D. M. A., Lima-Fernandes, E., Kreso, A., Wolman, R., Szentgyorgyi, E., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-1715 · Cited by 22
Self-citation
Metadata
- Authors
- Kreso, A., O'Brien, C. A., van Galen, P., Gan, O. I., Notta, F., Brown, A. M. K., Ng, K., Ma, J., Wienholds, E., Dunant, C., Pollett, A., Gallinger, S., McPherson, J., Mullighan, C. G., Shibata, D., & Dick, J. E.
- Venue
- Science
- Published
- 2013-02
- Volume
- 339
- Issue
- 6119
- Pages
- 543-548
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2135523574
- Cited by
- 744
- References
- 9
- FWCI
- 20.55
- Type
- journal article
- Language
- en
- Open access
- green
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