Multi-omic cross-sectional cohort study of pre-malignant Barrett's esophagus reveals early structural variation and retrotransposon activity.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
17 03 2022
17 03 2022
Historique:
received:
15
07
2021
accepted:
14
01
2022
entrez:
18
3
2022
pubmed:
19
3
2022
medline:
6
4
2022
Statut:
epublish
Résumé
Barrett's esophagus is a pre-malignant lesion that can progress to esophageal adenocarcinoma. We perform a multi-omic analysis of pre-cancer samples from 146 patients with a range of outcomes, comprising 642 person years of follow-up. Whole genome sequencing reveals complex structural variants and LINE-1 retrotransposons, as well as known copy number changes, occurring even prior to dysplasia. The structural variant burden captures the most variance across the cohort and genomic profiles do not always match consensus clinical pathology dysplasia grades. Increasing structural variant burden is associated with: high levels of chromothripsis and breakage-fusion-bridge events; increased expression of genes related to cell cycle checkpoint, DNA repair and chromosomal instability; and epigenetic silencing of Wnt signalling and cell cycle genes. Timing analysis reveals molecular events triggering genomic instability with more clonal expansion in dysplastic samples. Overall genomic complexity occurs early in the Barrett's natural history and may inform the potential for cancer beyond the clinically discernible phenotype.
Identifiants
pubmed: 35301290
doi: 10.1038/s41467-022-28237-4
pii: 10.1038/s41467-022-28237-4
pmc: PMC8931005
doi:
Substances chimiques
Retroelements
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1407Subventions
Organisme : Department of Health
ID : BRC-1215-20014
Pays : United Kingdom
Organisme : Medical Research Council
ID : RG84269
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203141/Z/16/Z
Pays : United Kingdom
Organisme : Cancer Research UK
ID : RG81771/84119
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W014122/1
Pays : United Kingdom
Informations de copyright
© 2022. The Author(s).
Références
Srivastava, S., Reid, B. J., Ghosh, S. & Kramer, B. S. Research needs for understanding the biology of overdiagnosis in cancer screening. J. Cell. Physiol. 231, 1870–1875 (2016).
pubmed: 26505642
pmcid: 5811189
doi: 10.1002/jcp.25227
Pashayan, N. & Pharoah, P. D. P. The challenge of early detection in cancer. Science 368, 589–590 (2020).
pubmed: 32381710
doi: 10.1126/science.aaz2078
Zagari, R. M. et al. Gastro-oesophageal reflux symptoms, oesophagitis and barrett’s oesophagus in the general population: the Loiano-Monghidoro study. Gut 57, 1354–1359 (2008).
pubmed: 18424568
doi: 10.1136/gut.2007.145177
Ronkainen, J. et al. Prevalence of Barrett’s esophagus in the general population: an endoscopic study. Gastroenterology 129, 1825–1831 (2005).
pubmed: 16344051
doi: 10.1053/j.gastro.2005.08.053
Anderson, L. et al. Risk factors for Barrett’s oesophagus and oesophageal adenocarcinoma: results from the FINBAR study. World J. Gastroenterol. 13, 1585–1594 (2007).
Cook, M. B. et al. Gastroesophageal reflux in relation to adenocarcinomas of the esophagus: a pooled analysis from the Barrett’s and Esophageal Adenocarcinoma Consortium (BEACON). PLoS ONE 9, e103508 (2014).
Kadri, S. R. et al. Acceptability and accuracy of a non-endoscopic screening test for Barrett’s oesophagus in primary care: cohort study. BMJ 341, c4372 (2010).
pubmed: 20833740
pmcid: 2938899
doi: 10.1136/bmj.c4372
Bhat, S. et al. Risk of malignant progression in Barrett’s esophagus patients: results from a large population-based study. J. Natl Cancer Inst. 103, 1049–1057 (2011).
pubmed: 21680910
pmcid: 3632011
doi: 10.1093/jnci/djr203
Desai, T. K. et al. The incidence of oesophageal adenocarcinoma in non-dysplastic Barrett’s oesophagus: a meta-analysis. Gut 61, 970–976 (2012).
pubmed: 21997553
doi: 10.1136/gutjnl-2011-300730
Smyth, E. C. et al. Oesophageal cancer. Nat. Rev. Dis. Prim. 3, 17048 (2017).
pubmed: 28748917
doi: 10.1038/nrdp.2017.48
Duits, L. C. et al. Barrett’s oesophagus patients with low-grade dysplasia can be accurately risk-stratified after histological review by an expert pathology panel. Gut 64, 700–706 (2015).
pubmed: 25034523
doi: 10.1136/gutjnl-2014-307278
Van Der Wel, M. J., Coleman, H. G., Bergman, J. J. G. H. M., Jansen, M. & Meijer, S. L. Histopathologist features predictive of diagnostic concordance at expert level among a large international sample of pathologists diagnosing Barrett’s dysplasia using digital pathology. Gut 69, 811–822 (2020).
pubmed: 31852770
doi: 10.1136/gutjnl-2019-318985
Frankell, A. M. et al. The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic. Nat. Genet. 51, 506–516 (2019).
pubmed: 30718927
pmcid: 6420087
doi: 10.1038/s41588-018-0331-5
TCGA. Integrated genomic characterization of oesophageal carcinoma. Nature 541, 169–175 (2017).
doi: 10.1038/nature20805
Secrier, M. et al. Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance. Nat. Genet. 48, 1131–1141 (2016).
pubmed: 27595477
pmcid: 5957269
doi: 10.1038/ng.3659
Dulak, A. M. et al. Exome and whole-genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity. Nat. Genet. 45, 478–486 (2013).
pubmed: 23525077
pmcid: 3678719
doi: 10.1038/ng.2591
Nones, K. et al. Genomic catastrophes frequently arise in esophageal adenocarcinoma and drive tumorigenesis. Nat. Commun. 5, 5224 (2014).
pubmed: 25351503
doi: 10.1038/ncomms6224
Rodriguez-Martin, B. et al. Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition. Nat. Genet. 52, 306–319 (2020).
pubmed: 32024998
pmcid: 7058536
doi: 10.1038/s41588-019-0562-0
Cortés-Ciriano, I. et al. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. Nat. Genet. 52, 331–341 (2020).
pubmed: 32025003
pmcid: 7058534
doi: 10.1038/s41588-019-0576-7
Akagi, T. et al. Chromosomal abnormalities and novel disease-related regions in progression from Barrett’s esophagus to esophageal adenocarcinoma. Int. J. Cancer 125, 2349–2359 (2009).
pubmed: 19670330
pmcid: 2766567
doi: 10.1002/ijc.24620
Stachler, M. D. et al. Paired exome analysis of Barrett’s esophagus and adenocarcinoma. Nat. Genet. 47, 1047–1055 (2015).
pubmed: 26192918
pmcid: 4552571
doi: 10.1038/ng.3343
Ross-Innes, C. S. et al. Whole-genome sequencing provides new insights into the clonal architecture of Barrett’s esophagus and esophageal adenocarcinoma. Nat. Genet. 47, 1038–1046 (2015).
pubmed: 26192915
pmcid: 4556068
doi: 10.1038/ng.3357
Agrawal, N. et al. Comparative genomic analysis of esophageal adenocarcinoma and squamous cell carcinoma. Cancer Discov. 2, 899–905 (2012).
pubmed: 22877736
pmcid: 3473124
doi: 10.1158/2159-8290.CD-12-0189
Terheggen, G. & Neuhaus, H. Radiofrequency ablation in the treatment of Barrett’s esophagus. Endosk. Heute 26, 241–247 (2013).
Wu, W. et al. Hypomethylation of noncoding DNA regions and overexpression of the long noncoding RNA, AFAP1-AS1, in Barrett’s esophagus and esophageal adenocarcinoma. Gastroenterology 144, 956–966 (2013). e4.
pubmed: 23333711
doi: 10.1053/j.gastro.2013.01.019
Krause, L. et al. Identification of the CIMP-like subtype and aberrant methylation of members of the chromosomal segregation and spindle assembly pathways in esophageal adenocarcinoma. Carcinogenesis 37, 356–365 (2015).
doi: 10.1093/carcin/bgw018
Maag, J. L. V. et al. Novel aberrations uncovered in Barrett’s esophagus and esophageal adenocarcinoma using whole transcriptome sequencing. Mol. Cancer Res. 15, 1558–1569 (2017).
pubmed: 28751461
doi: 10.1158/1541-7786.MCR-17-0332
Alvarez, H. et al. Widespread hypomethylation occurs early and synergizes with gene amplification during esophageal carcinogenesis. PLoS Genet. 7, e1001356 (2011).
pubmed: 21483804
pmcid: 3069107
doi: 10.1371/journal.pgen.1001356
Newell, F. et al. Complex structural rearrangements are present in high-grade dysplastic Barrett’s oesophagus samples. BMC Med. Genomics 12, 31 (2019).
pubmed: 30717762
pmcid: 6360790
doi: 10.1186/s12920-019-0476-9
Blount, P. L. et al. Clonal ordering of 17p and 5q allelic losses in Barrett dysplasia and adenocarcinoma. Proc. Natl Acad. Sci. USA 90, 3221–3225 (1993).
pubmed: 8475062
pmcid: 46271
doi: 10.1073/pnas.90.8.3221
Neshat, K. et al. p53 Mutations in Barrett’s adenocarcinoma and high-grade dysplasia. Gastroenterology 106, 1589–1595 (1994).
pubmed: 8194706
doi: 10.1016/0016-5085(94)90415-4
Gu, J. et al. Genome-wide catalogue of chromosomal aberrations in barrett’s esophagus and esophageal adenocarcinoma: a high-density single nucleotide polymorphism array analysis. Cancer Prev. Res. 3, 1176–1186 (2010).
doi: 10.1158/1940-6207.CAPR-09-0265
Stachler, M. D. et al. Detection of mutations in Barrett’s esophagus before progression to high-grade dysplasia or adenocarcinoma. Gastroenterology 155, 156–167 (2018).
pubmed: 29608884
doi: 10.1053/j.gastro.2018.03.047
Li, X. et al. Temporal and spatial evolution of somatic chromosomal alterations: a case-cohort study of Barrett’s esophagus. Cancer Prev. Res. 7, 114–127 (2014).
doi: 10.1158/1940-6207.CAPR-13-0289
Schneider, P. M. et al. Mutations of p53 in Barrett’s esophagus and Barrett’s cancer: a prospective study of ninety-eight cases. J. Thorac. Cardiovasc. Surg. 111, 323 (1996).
pubmed: 8583805
doi: 10.1016/S0022-5223(96)70441-5
Weaver, J. M. J. et al. Ordering of mutations in preinvasive disease stages of esophageal carcinogenesis. Nat. Genet. 46, 837–843 (2014).
pubmed: 24952744
pmcid: 4116294
doi: 10.1038/ng.3013
Killcoyne, S. et al. Genomic copy number predicts esophageal cancer years before transformation. Nat. Med. 26, 1726–1732 (2020).
pubmed: 32895572
pmcid: 7116403
doi: 10.1038/s41591-020-1033-y
COSMIC. Mutational signatures (v3). https://cancer.sanger.ac.uk/cosmic/signatures/SBS (2019).
Tamborero, D. et al. A pan-cancer landscape of interactions between solid tumors and infiltrating immune cell populations. Clin. Cancer Res. 24, 3717–3728 (2018).
pubmed: 29666300
doi: 10.1158/1078-0432.CCR-17-3509
Carter, S. L., Eklund, A. C., Kohane, I. S., Harris, L. N. & Szallasi, Z. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat. Genet. 38, 1043–1048 (2006).
pubmed: 16921376
doi: 10.1038/ng1861
Naini, B. V., Souza, R. F. & Odze, R. D. Barrett’s esophagus: a comprehensive and contemporary review for pathologists. Am. J. Surg. Pathol. 40, e45–e66 (2016).
pubmed: 26813745
pmcid: 4833583
doi: 10.1097/PAS.0000000000000598
Odze, R. D. Diagnosis and grading of dysplasia in Barrett’s oesophagus. J. Clin. Pathol. 59, 1029–1038 (2006).
pubmed: 17021130
pmcid: 1861756
doi: 10.1136/jcp.2005.035337
Zouridis, H. et al. Methylation subtypes and large-scale epigenetic alterations in gastric cancer. Sci. Transl. Med. 4, 156ra140 (2012).
pubmed: 23076357
doi: 10.1126/scitranslmed.3004504
Weisenberger, D. J. et al. CpG island methylator phenotype underlies sporadic microsatellite instability and is tightly associated with BRAF mutation in colorectal cancer. Nat. Genet. 38, 787–793 (2006).
pubmed: 16804544
doi: 10.1038/ng1834
Hinoue, T. et al. Genome-scale analysis of aberrant DNA methylation in colorectal cancer. Genome Res. 22, 271–282 (2012).
pubmed: 21659424
pmcid: 3266034
doi: 10.1101/gr.117523.110
Koltsova, A. S. et al. On the complexity of mechanisms and consequences of chromothripsis: an update. Front. Genet. 10, 393 (2019).
pubmed: 31114609
pmcid: 6503150
doi: 10.3389/fgene.2019.00393
Nik-Zainal, S. et al. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature 534, 47–54 (2016).
pubmed: 27135926
pmcid: 4910866
doi: 10.1038/nature17676
Shinde, J. et al. Palimpsest: an R package for studying mutational and structural variant signatures along clonal evolution in cancer. Bioinformatics 34, 3380–3381 (2018).
pubmed: 29771315
Ferrari, A. et al. A whole-genome sequence and transcriptome perspective on HER2-positive breast cancers. Nat. Commun. 7, 12222 (2016).
Marotta, M. et al. A common copy-number breakpoint of ERBB2 amplification in breast cancer colocalizes with a complex block of segmental duplications. Breast Cancer Res. 14, R150 (2012).
Marotta, M. et al. Palindromic amplification of the ERBB2 oncogene in primary HER2-positive breast tumors. Sci. Rep. 7, 41921 (2017).
Hadi, K. et al. Distinct classes of complex structural variation uncovered across thousands of cancer genome graphs. Cell 183, 197–210 (2020).
pubmed: 33007263
pmcid: 7912537
doi: 10.1016/j.cell.2020.08.006
Cajuso, T. et al. Retrotransposon insertions can initiate colorectal cancer and are associated with poor survival. Nat. Commun. 10, 4022 (2019).
pubmed: 31492840
pmcid: 6731219
doi: 10.1038/s41467-019-11770-0
Doucet-O’Hare, T. T. et al. LINE-1 expression and retrotransposition in Barrett’s esophagus and esophageal carcinoma. Proc. Natl Acad. Sci. USA 112, E4894–E4900 (2015).
pubmed: 26283398
pmcid: 4568228
Shademan, M. et al. Promoter methylation, transcription, and retrotransposition of LINE-1 in colorectal adenomas and adenocarcinomas. Cancer Cell Int. 20, 426 (2020).
pubmed: 32905102
pmcid: 7466817
doi: 10.1186/s12935-020-01511-5
Ewing, A. D. et al. Widespread somatic L1 retrotransposition occurs early during gastrointestinal cancer evolution. Genome Res. 25, 1536–1545 (2015).
pubmed: 26260970
pmcid: 4579339
doi: 10.1101/gr.196238.115
Liu, Y. et al. Bisulfite-free direct detection of 5-methylcytosine and 5-hydroxymethylcytosine at base resolution. Nat. Biotechnol. 37, 424–429 (2019).
pubmed: 30804537
doi: 10.1038/s41587-019-0041-2
Prevo, L. J., Sanchez, C. A., Galipeau, P. C. & Reid, B. J. p53-mutant clones and field effects in Barrett’s esophagus. Cancer Res. 59, 4784–4787 (1999).
pubmed: 10519384
Zeki, S. S., McDonald, S. A. & Graham, T. A. Field cancerization in Barrett’s esophagus. Discov. Med. 12, 371–379 (2011).
pubmed: 22127108
Lochhead, P. et al. Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression. Mod. Pathol. 28, 14–29 (2015).
pubmed: 24925058
doi: 10.1038/modpathol.2014.81
Paulson, T. et al. Somatic whole genome dynamics of precancer in Barrett’s esophagus. Res. Sq. 0, 0–0 (2021).
Stachler, M. D. et al. Origins of cancer genome complexity revealed by haplotype-resolved genomic analysis of evolution of Barrett’s esophagus to esophageal adenocarcinoma. Preprint at bioRxiv https://doi.org/10.1101/2021.03.26.437288 (2021).
Fitzgerald, R. C. et al. British Society of Gastroenterology guidelines on the diagnosis and management of Barrett’s oesophagus. Gut 63, 7–42 (2014).
pubmed: 24165758
doi: 10.1136/gutjnl-2013-305372
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
pubmed: 19451168
pmcid: 2705234
doi: 10.1093/bioinformatics/btp324
Niu, B. et al. MSIsensor: microsatellite instability detection using paired tumor-normal sequence data. Bioinformatics 30, 1015–1016 (2014).
pubmed: 24371154
doi: 10.1093/bioinformatics/btt755
Saunders, C. T. et al. Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics 28, 1811–1817 (2012).
pubmed: 22581179
doi: 10.1093/bioinformatics/bts271
Jammula, S. G. et al. Identification of subtypes of Barrett’s esophagus and esophageal adenocarcinoma based on DNA methylation profiles and integration of transcriptome and genome data. Gastroenterology 158, 1682–1697 (2020).
pubmed: 32032585
doi: 10.1053/j.gastro.2020.01.044
Chen, X. et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics 32, 1220–1222 (2016).
pubmed: 26647377
doi: 10.1093/bioinformatics/btv710
Alioto, T. S. et al. A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing. Nat. Commun. 6, 10001 (2015).
pubmed: 26647970
doi: 10.1038/ncomms10001
McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
pubmed: 20644199
pmcid: 2928508
doi: 10.1101/gr.107524.110
Nik-Zainal, S. et al. The life history of 21 breast cancers. Cell 149, 994–1007 (2012).
pubmed: 22608083
pmcid: 3428864
doi: 10.1016/j.cell.2012.04.023
Alexandrov, L. B. et al. Signatures of mutational processes in human cancer. Nature 500, 415–421 (2013).
pubmed: 23945592
pmcid: 3776390
doi: 10.1038/nature12477
Letouzé, E. et al. Mutational signatures reveal the dynamic interplay of risk factors and cellular processes during liver tumorigenesis. Nat. Commun. 8, 1315 (2017).
pubmed: 29101368
pmcid: 5670220
doi: 10.1038/s41467-017-01358-x
Cortés-Ciriano, I. et al. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. Nat. Genet. 52, 331–341 (2020).
pubmed: 32025003
pmcid: 7058534
doi: 10.1038/s41588-019-0576-7
Hadi, K. et al. Distinct classes of complex structural variation uncovered across thousands of cancer genome graphs. Cell. 183, 197–210.e32 (2020).
pubmed: 33007263
pmcid: 7912537
doi: 10.1016/j.cell.2020.08.006
Tubio, J. M. C. et al. Extensive transduction of nonrepetitive DNA mediated by L1 retrotransposition in cancer genomes. Science 345, 1251343 (2014).
Dobin, A. et al. STAR: Ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
pubmed: 23104886
doi: 10.1093/bioinformatics/bts635
Johnson, W. E., Li, C. & Rabinovic, A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127 (2007).
pubmed: 16632515
doi: 10.1093/biostatistics/kxj037
McCarthy, D. J., Chen, Y. & Smyth, G. K. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 40, 4288–4297 (2012).
pubmed: 22287627
pmcid: 3378882
doi: 10.1093/nar/gks042
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2009).
pubmed: 19910308
pmcid: 2796818
doi: 10.1093/bioinformatics/btp616
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
doi: 10.1186/1471-2105-14-7
Mermel, C. H. et al. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 12, R41 (2011).
pubmed: 21527027
pmcid: 3218867
doi: 10.1186/gb-2011-12-4-r41
Plackett, R. L. ANALYSIS OF PERMUTATIONS. J. Appl. Stat. 24, 193–202 (1975).
doi: 10.2307/2346567
Luce, R. D. Individual Choice Behavior: A Theoretical Analysis (Wiley, New York, 1959).
Mollica, C. & Tardella, L. PLMIX: an R package for modelling and clustering partially ranked data. J. Stat. Comput. Simul. 90, 925–959 (2020).
doi: 10.1080/00949655.2020.1711909
Fortin, J. P., Triche, T. J. & Hansen, K. D. Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi. Bioinformatics 33, 558–560 (2017).
pubmed: 28035024
Teschendorff, A. E. et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics 29, 189–196 (2013).
pubmed: 23175756
doi: 10.1093/bioinformatics/bts680
Tian, Y. et al. ChAMP: updated methylation analysis pipeline for Illumina BeadChips. Bioinformatics 33, 3982–3984 (2017).
pubmed: 28961746
pmcid: 5860089
doi: 10.1093/bioinformatics/btx513
Ritchie, M. E. et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
pubmed: 25605792
pmcid: 4402510
doi: 10.1093/nar/gkv007
Kim, J. et al. Integrated genomic characterization of oesophageal carcinoma. Nature 541, 169–174 (2017).
doi: 10.1038/nature20805
Zheng, S. et al. Comprehensive pan-genomic characterization of adrenocortical carcinoma. Cancer Cell 29, 723–736 (2016).
pubmed: 27165744
pmcid: 4864952
doi: 10.1016/j.ccell.2016.04.002