Phenotypic plasticity and genetic control in colorectal cancer evolution.
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
11 2022
11 2022
Historique:
received:
09
08
2021
accepted:
01
09
2022
pubmed:
27
10
2022
medline:
26
11
2022
entrez:
26
10
2022
Statut:
ppublish
Résumé
Genetic and epigenetic variation, together with transcriptional plasticity, contribute to intratumour heterogeneity
Identifiants
pubmed: 36289336
doi: 10.1038/s41586-022-05311-x
pii: 10.1038/s41586-022-05311-x
pmc: PMC9684078
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
744-753Subventions
Organisme : Cancer Research UK
ID : A26815
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 209409/Z/17/Z
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A22909
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : U54 CA217376
Pays : United States
Organisme : Wellcome Trust
ID : 202778/B/16/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 105104/Z/14/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/P000789/1
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 202778/Z/16/Z
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A19771
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : P01 CA196569
Pays : United States
Informations de copyright
© 2022. The Author(s).
Références
Black, J. R. M. & McGranahan, N. Genetic and non-genetic clonal diversity in cancer evolution. Nat. Rev. Cancer 21, 379–392 (2021).
Turajlic, S., Sottoriva, A., Graham, T. & Swanton, C. Resolving genetic heterogeneity in cancer. Nat. Rev. Genet. 20, 404–416 (2019).
pubmed: 30918367
Williams, M. J., Sottoriva, A. & Graham, T. A. Measuring clonal evolution in cancer with genomics. Annu. Rev. Genomics Hum. Genet. 20, 309–329 (2019).
pubmed: 31059289
Sun, R. et al. Between-region genetic divergence reflects the mode and tempo of tumor evolution. Nat. Genet. 49, 1015–1024 (2017).
pubmed: 28581503
pmcid: 5643198
Williams, M. J. et al. Quantification of subclonal selection in cancer from bulk sequencing data. Nat. Genet. 50, 895–903 (2018).
pubmed: 29808029
pmcid: 6475346
Lakatos, E. et al. Evolutionary dynamics of neoantigens in growing tumors. Nat. Genet. 52, 1057–1066 (2020).
pubmed: 32929288
pmcid: 7610467
Rosenthal, R. et al. Neoantigen-directed immune escape in lung cancer evolution. Nature 567, 479–485 (2019).
pubmed: 30894752
pmcid: 6954100
Robertson-Tessi, M., Gillies, R. J., Gatenby, R. A. & Anderson, A. R. A. Impact of metabolic heterogeneity on tumor growth, invasion, and treatment outcomes. Cancer Res. 75, 1567–1579 (2015).
pubmed: 25878146
pmcid: 4421891
Anderson, A. R. A., Weaver, A. M., Cummings, P. T. & Quaranta, V. Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment. Cell 127, 905–915 (2006).
pubmed: 17129778
Enderling, H. et al. Paradoxical dependencies of tumor dormancy and progression on basic cell kinetics. Cancer Res. 69, 8814–8821 (2009).
pubmed: 19887613
Waclaw, B. et al. A spatial model predicts that dispersal and cell turnover limit intratumour heterogeneity. Nature 525, 261–264 (2015).
pubmed: 26308893
pmcid: 4782800
Gallaher, J. A., Enriquez-Navas, P. M., Luddy, K. A., Gatenby, R. A. & Anderson, A. R. A. Spatial heterogeneity and evolutionary dynamics modulate time to recurrence in continuous and adaptive cancer therapies. Cancer Res. 78, 2127–2139 (2018).
pubmed: 29382708
pmcid: 5899666
Massey, S. C. et al. Simulating PDGF-driven glioma growth and invasion in an anatomically accurate brain domain. Bull. Math. Biol. 80, 1292–1309 (2018).
pubmed: 28842831
Noble, R. et al. Spatial structure governs the mode of tumour evolution. Nat. Ecol. Evol. 6, 207–217 (2022).
pubmed: 34949822
Stark, R., Grzelak, M. & Hadfield, J. RNA sequencing: the teenage years. Nat. Rev. Genet. 20, 631–656 (2019).
pubmed: 31341269
Guinney, J. et al. The consensus molecular subtypes of colorectal cancer. Nat. Med. 21, 1350–1356 (2015).
pubmed: 26457759
pmcid: 4636487
Isella, C. et al. Selective analysis of cancer-cell intrinsic transcriptional traits defines novel clinically relevant subtypes of colorectal cancer. Nat. Commun. 8, 15107 (2017).
pubmed: 28561063
pmcid: 5499209
Ryser, M. D. et al. Minimal barriers to invasion during human colorectal tumor growth. Nat. Commun. 11, 1280 (2020).
pubmed: 32152322
pmcid: 7062901
Casasent, A. K. et al. Multiclonal invasion in breast tumors identified by topographic single cell sequencing. Cell 172, 205–217 (2018).
pubmed: 29307488
pmcid: 5766405
Shaffer, S. M. et al. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature 546, 431–435 (2017).
pubmed: 28607484
pmcid: 5542814
Kreso, A. et al. Variable clonal repopulation dynamics influence chemotherapy response in colorectal cancer. Science 339, 543–548 (2013).
pubmed: 23239622
Reiter, J. G. et al. Minimal functional driver gene heterogeneity among untreated metastases. Science 361, 1033–1037 (2018).
pubmed: 30190408
pmcid: 6329287
Heide, T. et al. The co-evolution of the genome and epigenome in colorectal cancer. Nature https://doi.org/10.1038/s41586-022-05202-1 (2022).
Liberzon, A. et al. The Molecular Signatures Database Hallmark Gene Set Collection. Cell Syst. 1, 417–425 (2015).
pubmed: 26771021
pmcid: 4707969
Jiménez-Sánchez, A. et al. Unraveling tumor–immune heterogeneity in advanced ovarian cancer uncovers immunogenic effect of chemotherapy. Nat. Genet. 52, 582–593 (2020).
pubmed: 32483290
pmcid: 8353209
Dunne, P. D. et al. Challenging the cancer molecular stratification dogma: intratumoral heterogeneity undermines consensus molecular subtypes and potential diagnostic value in colorectal cancer. Clin. Cancer Res. 22, 4095–4104 (2016).
pubmed: 27151745
Sirinukunwattana, K. et al. Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning. Gut https://doi.org/10.1136/gutjnl-2019-319866 (2020).
Dunne, P. D. et al. Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification. Nat. Commun. 8, 15657 (2017).
pubmed: 28561046
pmcid: 5460026
Pagel, M. Inferring the historical patterns of biological evolution. Nature 401, 877–884 (1999).
pubmed: 10553904
Freckleton, R. P., Harvey, P. H. & Pagel, M. Phylogenetic analysis and comparative data: a test and review of evidence. Am. Nat. 160, 712–726 (2002).
pubmed: 18707460
Michalik, L., Desvergne, B. & Wahli, W. Peroxisome-proliferator-activated receptors and cancers: complex stories. Nat. Rev. Cancer 4, 61–70 (2004).
pubmed: 14708026
Fuchs, S. Y., Ougolkov, A. V., Spiegelman, V. S. & Minamoto, T. Oncogenic beta-catenin signaling networks in colorectal cancer. Cell Cycle 4, 1522–1539 (2005).
pubmed: 16258275
Currie, E., Schulze, A., Zechner, R., Walther, T. C. & Farese, R. V. Cellular fatty acid metabolism and cancer. Cell Metab. 18, 153–161 (2013).
pubmed: 23791484
pmcid: 3742569
Steen, C. B., Liu, C. L., Alizadeh, A. A. & Newman, A. M. Profiling cell type abundance and expression in bulk tissues with CIBERSORTx. Methods Mol. Biol. 2117, 135–157 (2020).
pubmed: 31960376
pmcid: 7695353
Lenos, K. J. et al. Stem cell functionality is microenvironmentally defined during tumour expansion and therapy response in colon cancer. Nat. Cell Biol. 20, 1193–1202 (2018).
pubmed: 30177776
pmcid: 6163039
van der Heijden, M. et al. Spatiotemporal regulation of clonogenicity in colorectal cancer xenografts. Proc. Natl Acad. Sci. USA 116, 6140–6145 (2019).
pubmed: 30850544
pmcid: 6442578
Nica, A. C. & Dermitzakis, E. T. Expression quantitative trait loci: present and future. Philos. Trans. R. Soc. Lond. B Biol. Sci. 368, 20120362 (2013).
pubmed: 23650636
pmcid: 3682727
Sheltzer, J. M. et al. Single-chromosome gains commonly function as tumor suppressors. Cancer Cell 31, 240–255 (2017).
pubmed: 28089890
pmcid: 5713901
Priestley, P. et al. Pan-cancer whole-genome analyses of metastatic solid tumours. Nature 575, 210–216 (2019).
pubmed: 31645765
pmcid: 6872491
Stratton, M. R., Campbell, P. J. & Futreal, P. A. The cancer genome. Nature 458, 719–724 (2009).
pubmed: 19360079
pmcid: 2821689
Martínez-Jiménez, F. et al. A compendium of mutational cancer driver genes. Nat. Rev. Cancer 20, 555–572 (2020).
pubmed: 32778778
Cross, W. et al. The evolutionary landscape of colorectal tumorigenesis. Nat. Ecol. Evol. 2, 1661–1672 (2018).
pubmed: 30177804
pmcid: 6152905
Dentro, S. C. et al. Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes. Cell 184, 2239–2254 (2021).
pubmed: 33831375
pmcid: 8054914
Caravagna, G. et al. Subclonal reconstruction of tumors by using machine learning and population genetics. Nat. Genet. 52, 898–907 (2020).
pubmed: 32879509
pmcid: 7610388
Martincorena, I. et al. Universal patterns of selection in cancer and somatic tissues. Cell 171, 1029–1041 (2017).
pubmed: 29056346
pmcid: 5720395
Giannakis, M. et al. Genomic correlates of immune-cell infiltrates in colorectal carcinoma. Cell Rep. 15, 857–865 (2016).
pubmed: 27149842
pmcid: 4850357
Vasaikar, S. et al. Proteogenomic analysis of human colon cancer reveals new therapeutic opportunities. Cell 177, 1035–1049 (2019).
pubmed: 31031003
pmcid: 6768830
Tsherniak, A. et al. Defining a cancer dependency map. Cell 170, 564–576 (2017).
pubmed: 28753430
pmcid: 5667678
Sottoriva, A. et al. A big bang model of human colorectal tumor growth. Nat. Genet. 47, 209–216 (2015).
pubmed: 25665006
pmcid: 4575589
Williams, M. J., Werner, B., Barnes, C. P., Graham, T. A. & Sottoriva, A. Identification of neutral tumor evolution across cancer types. Nat. Genet. 48, 238–244 (2016).
pubmed: 26780609
pmcid: 4934603
Chkhaidze, K. et al. Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data. PLoS Comput. Biol. 15, e1007243 (2019).
pubmed: 31356595
pmcid: 6687187
Baker, A.-M. et al. Robust RNA-based in situ mutation detection delineates colorectal cancer subclonal evolution. Nat. Commun. 8, 1998 (2017).
pubmed: 29222441
pmcid: 5722928
Adzhubei, I., Jordan, D. M. & Sunyaev, S. R. Predicting functional effect of human missense mutations using PolyPhen-2. Curr. Protoc. Hum. Genet. Chapter 7, Unit7.20 (2013).
pubmed: 23315928
Del Moral, P., Doucet, A. & Jasra, A. An adaptive sequential Monte Carlo method for approximate Bayesian computation. Stat. Comput. 22, 1009–1020 (2012).
Burnham, K. P. & Anderson, D. R. Multimodel inference: understanding AIC and BIC in model selection. Sociol. Methods Res. 33, 261–304 (2004).
Werner, B. et al. Measuring single cell divisions in human tissues from multi-region sequencing data. Nat. Commun. 11, 1035 (2020).
pubmed: 32098957
pmcid: 7042311
Eyre-Walker, A. & Keightley, P. D. The distribution of fitness effects of new mutations. Nat. Rev. Genet. 8, 610–618 (2007).
pubmed: 17637733
Nam A. S. et al. Single-cell multi-omics of human clonal hematopoiesis reveals that DNMT3A R882 mutations perturb early progenitor states through selective hypomethylation. Nat. Genet. 54, 1514–1526 (2022).
pubmed: 36138229
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
pubmed: 25516281
pmcid: 4302049
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Biswas, D. et al. A clonal expression biomarker associates with lung cancer mortality. Nat. Med. 25, 1540–1548 (2019).
pubmed: 31591602
pmcid: 6984959
Simpson, G. L. Analogue methods in palaeoecology: using the analogue package. J. Stat. Softw. 22, 1–29 (2007).
Galili, T. dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics 31, 3718–3720 (2015).
pubmed: 26209431
pmcid: 4817050
Smedley, D. et al. BioMart—biological queries made easy. BMC Genomics 10, 22 (2009).
pubmed: 19144180
pmcid: 2649164
Yu, G., Wang, L. G., Han, Y. & He, Q. Y. ClusterProfiler: an R package for comparing biological themes among gene clusters. OMICS J. Integr. Biol. 16, 284–287 (2012).
Elmentaite, R. et al. Cells of the human intestinal tract mapped across space and time. Nature 597, 250–255 (2021).
pubmed: 34497389
pmcid: 8426186
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 (2021).
pubmed: 34062119
pmcid: 8238499
Merlos-Suárez, A. et al. The intestinal stem cell signature identifies colorectal cancer stem cells and predicts disease relapse. Cell Stem Cell 8, 511–524 (2011).
pubmed: 21419747
Hänzelmann, S., Castelo, R. & Guinney, J. GSVA: gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics 14, 7 (2013).
pubmed: 23323831
pmcid: 3618321
Eide, P. W., Bruun, J., Lothe, R. A. & Sveen, A. CMScaller: an R package for consensus molecular subtyping of colorectal cancer pre-clinical models. Sci. Rep. 7, 16618 (2017).
pubmed: 29192179
pmcid: 5709354
Nixon, K. C. The Parsimony Ratchet, a new method for rapid parsimony analysis. Cladistics 15, 407–414 (1999).
pubmed: 34902938
Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).
pubmed: 21169378
Fitch, W. M. Toward defining the course of evolution: minimum change for a specific tree topology. Syst. Biol. 20, 406–416 (1971).
Farris, J. S. Methods for computing Wagner trees. Syst. Zool. 19, 83–92 (1970).
Swofford, D. L. & Maddison, W. P. Reconstructing ancestral character states under Wagner parsimony. Math. Biosci. 87, 199–229 (1987).
Paradis, E. & Schliep, K. Ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).
pubmed: 30016406
Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).
Szklarczyk, D. et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 49, D605–D612 (2021).
pubmed: 33237311
Newman, A. M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015).
pubmed: 25822800
pmcid: 4739640
Fishilevich, S. et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database 2017, bax028 (2017).
pubmed: 28605766
pmcid: 5467550
Storey, J. D., Bass, A. J., Dabney, A. & Robinson, D. qvalue: Q-value estimation for false discovery rate control. http://github.com/jdstorey/qvalue (2021).
Lawrence, M., Gentleman, R. & Carey, V. rtracklayer: an R package for interfacing with genome browsers. Bioinformatics 25, 1841–1842 (2009).
pubmed: 19468054
pmcid: 2705236
Champely, S. pwr: Basic functions for power analysis. https://CRAN.R-project.org/package=pwr (2020).
Vu, V. Q. ggbiplot: A ggplot2 based biplot. https://github.com/vqv/ggbiplot (2011).
Gonzalez-Perez, A. et al. IntOGen-mutations identifies cancer drivers across tumor types. Nat. Methods 10, 1081–1082 (2013).
pubmed: 24037244
pmcid: 5758042
Meyers, R. M. et al. Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells. Nat. Genet. 49, 1779–1784 (2017).
pubmed: 29083409
pmcid: 5709193
van der Meer, D. et al. Cell Model Passports—a hub for clinical, genetic and functional datasets of preclinical cancer models. Nucleic Acids Res. 47, D923–D929 (2019).
pubmed: 30260411
Blighe, K. EnhancedVolcano. Bioconductor https://doi.org/10.18129/B9.BIOC.ENHANCEDVOLCANO (2022).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
pubmed: 16199517
pmcid: 1239896