Abstract
Transmissible cancers are malignant cell lineages that spread clonally between individuals. Several such cancers, termed bivalve transmissible neoplasia (BTN), induce leukemia-like disease in marine bivalves. This is the case of BTN lineages affecting the common cockle, Cerastoderma edule, which inhabits the Atlantic coasts of Europe and northwest Africa. To investigate the evolution of cockle BTN, we collected 6,854 cockles, diagnosed 390 BTN tumors, generated a reference genome and assessed genomic variation across 61 tumors. Our analyses confirmed the existence of two BTN lineages with hemocytic origins. Mitochondrial variation revealed mitochondrial capture and host co-infection events. Mutational analyses identified lineage-specific signatures, one of which likely reflects DNA alkylation. Cytogenetic and copy number analyses uncovered pervasive genomic instability, with whole-genome duplication, oncogene amplification and alkylation-repair suppression as likely drivers. Satellite DNA distributions suggested ancient clonal origins. Our study illuminates long-term cancer evolution under the sea and reveals tolerance of extreme instability in neoplastic genomes.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
The reference genome sequence for Cerastoderma edule and sequencing data supporting the findings of this study have been deposited in the European Nucleotide Archive (www.ebi.ac.uk/ena) under overarching accession code PRJEB58149. Human mutational signatures were retrieved from the COSMIC v.3.2 database (cancer.sanger.ac.uk). Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding authors on reasonable request.
Code availability
Computer code used for data analyses is available on GitLab (gitlab.com/mobilegenomesgroup/scuba_cancers).
References
Murchison, E. P. Clonally transmissible cancers in dogs and Tasmanian devils. Oncogene 27, S19–S30 (2009).
Metzger, M. J. & Goff, S. P. A sixth modality of infectious disease: contagious cancer from devils to clams and beyond. PLoS Pathog. 12, e1005904 (2016).
Cohen, D. The canine transmissible venereal tumor: a unique result of tumor progression. Adv. Cancer Res. 43, 75–112 (1985).
Murgia, C., Pritchard, J. K., Kim, S. Y., Fassati, A. & Weiss, R. A. Clonal origin and evolution of a transmissible cancer. Cell 126, 477–487 (2006).
Murchison, E. P. et al. Transmissible dog cancer genome reveals the origin and history of an ancient cell lineage. Science 343, 437–440 (2014).
Pearse, A.-M. & Swift, K. Transmission of devil facial-tumour disease. Nature 439, 549–549 (2006).
Murchison, E. P. et al. Genome sequencing and analysis of the Tasmanian devil and its transmissible cancer. Cell 148, 780–791 (2012).
Stammnitz, M. R. et al. The evolution of two transmissible cancers in Tasmanian devils. Science 380, 283–293 (2023).
Metzger, M. J., Reinisch, C., Sherry, J. & Goff, S. P. Horizontal transmission of clonal cancer cells causes leukemia in soft-shell clams. Cell 161, 255–263 (2015).
Metzger, M. J. et al. Widespread transmission of independent cancer lineages within multiple bivalve species. Nature 534, 705–709 (2016).
Yonemitsu, M. A. et al. A single clonal lineage of transmissible cancer identified in two marine mussel species in South America and Europe. eLife 8, e47788 (2019).
Skazina, M. et al. First description of a widespread Mytilus trossulus-derived bivalve transmissible cancer lineage in M. trossulus itself. Sci. Rep. 11, 5809 (2021).
Garcia-Souto, D. et al. Mitochondrial genome sequencing of marine leukaemias reveals cancer contagion between clam species in the Seas of Southern Europe. eLife 11, e66946 (2022).
Michnowska, A., Hart, S. F. M., Smolarz, K., Hallmann, A. & Metzger, M. J. Horizontal transmission of disseminated neoplasia in the widespread clam Macoma balthica from the Southern Baltic Sea. Mol. Ecol. 31, 3128–3136 (2022).
Carballal, M. J., Barber, B. J., Iglesias, D. & Villalba, A. Neoplastic diseases of marine bivalves. J. Invertebr. Pathol. 131, 83–106 (2015).
Elston, R. A., Kent, M. & Drum, A. Progression, lethality and remission of hemic neoplasia in the bay mussel Mytilus edulis. Dis. Aquat. Organ. 4, 135–142 (1988).
Burioli, E. A. V. et al. Implementation of various approaches to study the prevalence, incidence and progression of disseminated neoplasia in mussel stocks. J. Invertebr. Pathol. 168, 107271 (2019).
Hayward, P. J. & Ryland, J. S. Handbook of the Marine Fauna of North-West Europe (Oxford Univ. Press, 2017).
Twomey, E. & Mulcahy, M. F. A proliferative disorder of possible hemic origin in the common cockle, Cerastoderma edule. J. Invertebr. Pathol. 44, 109–111 (1984).
Villalba, A., Carballal, M. J. & López, C. Disseminated neoplasia and large foci indicating heavy haemocytic infiltration in cockles Cerastoderma edule from Galicia (NW Spain). Dis. Aquat. Organ. 46, 213–216 (2001).
Carballal, M. J., Iglesias, D., Santamarina, J., Ferro-Soto, B. & Villalba, A. Parasites and pathologic conditions of the cockle Cerastoderma edule populations of the coast of Galicia (NW Spain). J. Invertebr. Pathol. 78, 87–97 (2001).
Díaz, S., Iglesias, D., Villalba, A. & Carballal, M. J. Long-term epidemiological study of disseminated neoplasia of cockles in Galicia (NW Spain): temporal patterns at individual and population levels, influence of environmental and cockle-based factors and lethality. J. Fish Dis. 39, 1027–1042 (2016).
Hammel, M. et al. Prevalence and polymorphism of a mussel transmissible cancer in Europe. Mol. Ecol. 31, 736–751 (2022).
Miyata, T. & Yasunaga, T. Molecular evolution of mRNA: a method for estimating evolutionary rates of synonymous and amino acid substitutions from homologous nucleotide sequences and its application. J. Mol. Evol. 16, 23–36 (1980).
Martincorena, I. et al. Universal patterns of selection in cancer and somatic tissues. Cell 171, 1029–1041.e21 (2017).
Baez-Ortega, A. et al. Somatic evolution and global expansion of an ancient transmissible cancer lineage. Science 365, eaau9923 (2019).
Martínez, L., Freire, R., Arias-Pérez, A., Méndez, J. & Insua, A. Patterns of genetic variation across the distribution range of the cockle Cerastoderma edule inferred from microsatellites and mitochondrial DNA. Mar. Biol. 162, 1393–1406 (2015).
Hart, S. F. M. et al. Centuries of genome instability and evolution in soft-shell clam, Mya arenaria, bivalve transmissible neoplasia. Nat. Cancer https://doi.org/10.1038/s43018-023-00643-7 (2023).
Rebbeck, C. A., Leroi, A. M. & Burt, A. Mitochondrial capture by a transmissible cancer. Science 331, 303–303 (2011).
Strakova, A. et al. Recurrent horizontal transfer identifies mitochondrial positive selection in a transmissible cancer. Nat. Commun. 11, 3059 (2020).
Spees, J. L., Olson, S. D., Whitney, M. J. & Prockop, D. J. Mitochondrial transfer between cells can rescue aerobic respiration. Proc. Natl Acad. Sci. USA 103, 1283–1288 (2006).
Tan, A. S. et al. Mitochondrial genome acquisition restores respiratory function and tumorigenic potential of cancer cells without mitochondrial DNA. Cell Metab. 21, 81–94 (2015).
Saha, T. et al. Intercellular nanotubes mediate mitochondrial trafficking between cancer and immune cells. Nat. Nanotechnol. 17, 98–106 (2022).
Cross, M. E. et al. Genetic evidence supports recolonisation by Mya arenaria of western Europe from North America. Mar. Ecol. Prog. Ser. 549, 99–112 (2016).
Alexandrov, L. B. et al. The repertoire of mutational signatures in human cancer. Nature 578, 94–101 (2020).
Yuan, Y. et al. Comprehensive molecular characterization of mitochondrial genomes in human cancers. Nat. Genet. 52, 342–352 (2020).
Alexandrov, L. B. et al. Signatures of mutational processes in human cancer. Nature 500, 415–421 (2013).
Gori, K. & Baez-Ortega, A. sigfit: flexible Bayesian inference of mutational signatures. Preprint at bioRxiv https://doi.org/10.1101/372896 (2020).
Lindahl, T. & Nyberg, B. Heat-induced deamination of cytosine residues in deoxyribonucleic acid. Biochemistry 13, 3405–3410 (1974).
Zou, X. et al. A systematic CRISPR screen defines mutational mechanisms underpinning signatures caused by replication errors and endogenous DNA damage. Nat. Cancer 2, 643–657 (2021).
Nik-Zainal, S. et al. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature 534, 47–54 (2016).
Singh, V. K., Rastogi, A., Hu, X., Wang, Y. & De, S. Mutational signature SBS8 predominantly arises due to late replication errors in cancer. Commun. Biol. 3, 1–10 (2020).
Le Grand, F. et al. Prevalence, intensity, and aneuploidy patterns of disseminated neoplasia in cockles (Cerastoderma edule) from Arcachon Bay: seasonal variation and position in sediment. J. Invertebr. Pathol. 104, 110–118 (2010).
Díaz, S. et al. Disseminated neoplasia causes changes in ploidy and apoptosis frequency in cockles Cerastoderma edule. J. Invertebr. Pathol. 113, 214–219 (2013).
Matias, A. M. et al. Karyotype variation in neoplastic cells associated to severity of disseminated neoplasia in the cockle Cerastoderma edule. Aquaculture 428–429, 223–225 (2014).
Oliner, J. D., Saiki, A. Y. & Caenepeel, S. The role of MDM2 amplification and overexpression in tumorigenesis. Cold Spring Harb. Perspect. Med. 6, a026336 (2016).
Kato, S. et al. Analysis of MDM2 amplification: next-generation sequencing of patients with diverse malignancies. JCO Precis. Oncol. https://doi.org/10.1200/PO.17.00235 (2018).
Büschges, R. et al. Amplification and expression of cyclin D genes (CCND1 CCND2 and CCND3) in human malignant gliomas. Brain Pathol. 9, 435–442 (1999).
Kasugai, Y. et al. Identification of CCND3 and BYSL as candidate targets for the 6p21 amplification in diffuse large B-cell lymphoma. Clin. Cancer Res. 11, 8265–8272 (2005).
Pegg, A. E., Dolan, M. E. & Moschel, R. C. in Progress in Nucleic Acid Research and Molecular Biology, Vol. 51 (eds Cohn, W. E. & Moldave, K.) 167–223 (Academic Press, 1995).
Shiraishi, A., Sakumi, K. & Sekiguchi, M. Increased susceptibility to chemotherapeutic alkylating agents of mice deficient in DNA repair methyltransferase. Carcinogenesis 21, 1879–1883 (2000).
Lower, S. S., McGurk, M. P., Clark, A. G. & Barbash, D. A. Satellite DNA evolution: old ideas, new approaches. Curr. Opin. Genet. Dev. 49, 70–78 (2018).
Davoli, T. & de Lange, T. The causes and consequences of polyploidy in normal development and cancer. Annu. Rev. Cell Dev. Biol. 27, 585–610 (2011).
Gemble, S. et al. Genetic instability from a single S phase after whole-genome duplication. Nature 604, 146–151 (2022).
Santaguida, S. & Amon, A. Short- and long-term effects of chromosome mis-segregation and aneuploidy. Nat. Rev. Mol. Cell Biol. 16, 473–485 (2015).
Ly, P. et al. Chromosome segregation errors generate a diverse spectrum of simple and complex genomic rearrangements. Nat. Genet. 51, 705–715 (2019).
Crockford, A. et al. Cyclin D mediates tolerance of genome-doubling in cancers with functional p53. Ann. Oncol. 28, 149–p156 (2017).
Matsuo, H. et al. Recurrent CCND3 mutations in MLL-rearranged acute myeloid leukemia. Blood Adv. 2, 2879–2889 (2018).
Walker, C., Böttger, S. & Low, B. Mortalin-based cytoplasmic sequestration of p53 in a nonmammalian cancer model. Am. J. Pathol. 168, 1526–1530 (2006).
Pye, R. J. et al. A second transmissible cancer in Tasmanian devils. Proc. Natl Acad. Sci. USA 113, 374–379 (2016).
García-Souto, D. et al. Methylation profile of a satellite DNA constituting the intercalary G + C-rich heterochromatin of the cut trough shell Spisula subtruncata (Bivalvia, Mactridae). Sci. Rep. 7, 6930 (2017).
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303.3997 [q-bio] (2013).
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Parrish, N., Hormozdiari, F. & Eskin, E. Assembly of non-unique insertion content using next-generation sequencing. BMC Bioinformatics 12, S3 (2011).
Hurtado, N. S. & Pasantes, J. J. Surface spreading of synaptonemal complexes in the clam Dosinia exoleta (Mollusca, Bivalvia). Chromosome Res. 13, 575–580 (2005).
Lu, H., Giordano, F. & Ning, Z. Oxford Nanopore MinION sequencing and genome assembly. Genomics Proteomics Bioinformatics 14, 265–279 (2016).
Zimin, A. V. et al. Hybrid assembly of the large and highly repetitive genome of Aegilops tauschii, a progenitor of bread wheat, with the MaSuRCA mega-reads algorithm. Genome Res. 27, 787–792 (2017).
Poplin, R. et al. Scaling accurate genetic variant discovery to tens of thousands of samples. Preprint at bioRxiv https://doi.org/10.1101/201178 (2017).
Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).
Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213–219 (2013).
Darriba, D. et al. ModelTest-NG: a new and scalable tool for the selection of DNA and protein evolutionary models. Mol. Biol. Evol. 37, 291–294 (2020).
Jin, Y. & Brown, R. P. Partition number, rate priors and unreliable divergence times in Bayesian phylogenetic dating. Cladistics 34, 568–573 (2018).
Rimmer, A. et al. Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nat. Genet. 46, 912–918 (2014).
Rausch, T. et al. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 28, i333–i339 (2012).
Layer, R. M., Chiang, C., Quinlan, A. R. & Hall, I. M. LUMPY: a probabilistic framework for structural variant discovery. Genome Biol. 15, R84 (2014).
Chen, X. et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics 32, 1220–1222 (2016).
Nixon, K. C. The Parsimony Ratchet, a new method for rapid parsimony analysis. Cladistics 15, 407–414 (1999).
García-Souto, D., Pérez-García, C., Morán, P. & Pasantes, J. J. Divergent evolutionary behavior of H3 histone gene and rDNA clusters in venerid clams. Mol. Cytogenet. 8, 40 (2015).
Insua, A., Freire, R. & Méndez, J. The 5S rDNA of the bivalve Cerastoderma edule: nucleotide sequence of the repeat unit and chromosomal location relative to 18S–28S rDNA. Genet. Sel. Evol. 31, 509 (1999).
Acknowledgements
This research was funded by the European Research Council (ERC) Starting Grant no. 716290 (‘SCUBA CANCERS’), awarded to J.M.C.T. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Sampling research was carried out mainly at the Universidade de Vigo’s Centro de Investigación Mariña, supported by the ‘Excellence in Research (INUGA)’ Program from the Regional Council of Culture, Education and Universities, and co-funded by the European Union through the ERDF Operational Program Galicia 2014–2020 ‘A way to make Europe’. Molecular biology and bioinformatics research was carried out mainly at the Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), supported by the European Regional Development Fund ‘A way to make Europe’ and the Research Centre of the Galician University System (2019–2022). A.L.B. was supported by a predoctoral fellowship from the Spanish Ministry of Economy, Industry, and Competitiveness (grant no. BES2016/078166); received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 730984 ASSEMBLE PLUS Transnational Access; and received a travel grant from Boehringer Ingelheim Fonds. M. Santamarina was supported by a predoctoral fellowship from the Spanish regional government of Xunta de Galicia (grant no. ED481A-2017/299). D.G.-S. was supported by postdoctoral contracts from Xunta de Galicia (grant nos. ED481B-2018/091 and ED481D 2022/001). S.D. received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 730984 ASSEMBLE PLUS Transnational Access. I.O. was supported by a predoctoral fellowship from the Spanish regional government of Xunta de Galicia Consellería de Cultura, Educación y Universidad (grant no. ED481A 2021/096). J.R.-C. was partially supported by the program to structure and improve research centers (Centros Singulares 2019, CiMUS). T.P. was supported by a predoctoral fellowship from the Spanish Government (grant no. FPU15/03709) and a predoctoral fellowship from the Spanish regional government of Xunta de Galicia (grant no. ED481A-2015/083). L.T. was supported by a predoctoral fellowship from the Spanish regional government of Xunta de Galicia (grant no. ED481A-2018/303). A.M.A. received funding from Portuguese national funds FCT (Foundation for Science and Technology) through project nos. UIDB/04326/2020, UIDP/04326/2020 and LA/P/0101/2020; and from the operational programs CRESC Algarve 2020 and COMPETE 2020 through project no. EMBRC-PT ALG-01-0145-FEDER-022121. R.C. was supported by FCT/MCTES (grant nos. UIDP/50017/2020, UIDB/50017/2020, LA/P/0094/2020), through national Portuguese funds. M. Skazina was supported by the Russian Science Foundation, grant no. 19-74-20024. N.G.P. provided biological resources supplied by EMBRC-ERIC. K.S. was supported by the National Centre of Science (Poland) with grant no. UMO-2017/26/M/NZ8/00478. J.J.P. was supported by the Spanish regional government of Xunta de Galicia (grant no. ED431C 2020/05), and Fondos Feder ‘Unha maneira de facer Europa’. Z.N. was supported by Wellcome grant no. WT098051. Y.S.J. was supported by a grant from the National Research Foundation of Korea funded by the Korean Government (grant no. NRF-2020R1A3B2078973). D.P. was supported by the Spanish Ministry of Science and Innovation, MICINN (grant no. PID2019-106247GB-I00 awarded to D.P.), the ERC (grant no. ERC-617457-PHYLOCANCER awarded to D.P.) and the Spanish regional government of Xunta de Galicia. J.D. was supported by a postdoctoral fellowship from the Belgian Research Foundation, Flanders (FWO; grant no. 12J6921N), and the Flemish Institute for Biotechnology (VIB). We thank the staff of the fishermen’s associations (‘cofradías’) of Galicia for their advice and assistance with sampling, especially L. Solís, J. Alfaya and A. Simón; and the Galicia Supercomputing Centre (CESGA) for the availability of informatic resources. We thank L. F. Møller (National Institute of Aquatic Resources, Denmark), B. Hussel (Alfred Wegener Institute), M. Wolowicz (University of Gdansk), T. Verstraeten (Ghent University), M. L. Martínez and A. M. Insua Pombo (Universidade da Coruña), C. García de Leaniz (Swansea University), A. Smith and A. Harvey (Marine Biological Association, UK), R. Parks (Centre for Environment, Fisheries and Aquaculture Science, UK) and T. Magnesen (Universitetet i Bergen) for providing samples for this project. We thank C. Canchaya (Universidade de Vigo), M. Rey, J. Quinteiro, M. Hermida and P. Martínez (Universidade de Santiago de Compostela) for advice on genome assembly and annotation; M. Rodríguez (Universidade de Vigo) for administrative support; and E. P. Murchison (University of Cambridge) for discussion and critical reading of the manuscript.
Author information
Authors and Affiliations
Contributions
A. Villalba, D.P. and J.M.C.T. designed the project. A.L.B., M. Santamarina, D.G.-S., S.D., S.R., J.Z., M.A.Q., I.O., J.J.P., J.D. and A.B.-O. developed methods. A.L.B., M. Santamarina, D.G.-S., S.D., S.R., J.Z., Y.L., I.O., J.T., Y.S.J., J.D. and A.B.-O. performed computational analyses. T.P., L.T., J.A., Z.N. and D.P. assisted with analyses. A.L.B., M. Santamarina, D.G.-S., S.D., L.A., A.V.-C., A. Villanueva, A.P.-V., A.V.-F., J.T., J.R.-C., P.A., J.A. and J.J.P. performed laboratory work. A.L.B., D.G.-S., S.D., M.A.Q., A.P.-V., J.T. and J.R.-C. performed sequencing methods. A.L.B., D.G.-S., S.D., A.V.-F., A. Villanueva, D.C., R.R., J.A., A.M.A., P.B., R.C., B.E.K., U.I., X.M., N.G.P., I.P., F.R., P.R., M. Skazina and K.S. provided samples. A.L.B., M. Santamarina, D.G.-S., S.D., S.R., J.Z., Y.L., J.J.P., Y.S.J., D.P., J.D. and A.B.-O. helped with interpretation of results. A.L.B., D.G.-S., S.D., A.P.-V., J.R.-C., A. Villanueva, P.A. and J.A. performed sample management. A.C., D.I., M.J.C., A. Villalba, Z.N. and D.P. provided technical advice. A.L.B., M. Santamarina, D.G.-S., S.D., Y.L., J.Z., J.D. and A.B.-O. generated figures. A.B.-O. and J.M.C.T. wrote the manuscript with contributions from all other authors. A.L.B., M. Santamarina, D.G.-S., S.D. and S.R. contributed equally. J.Z., Y.L. and A.V.-F. contributed equally.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Cancer thanks Andreas Bergthaler, Kelley Thomas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Frequency and progression stages of disseminated neoplasia in C. edule.
a, Numbers of individuals diagnosed with each stage of cockle DN (early or N1, intermediate or N2, and late or N3) in each country where DN was detected. b–m, Micrographs of histological sections of cockle DN at different stages of progression: early stage, N1 (b, e, h, k); intermediate stage, N2 (c, f, i, l); and late stage, N3 (d, g, j, m). Histological sections show the gills (b–d), digestive gland (e–g), gonad (h–j) and foot (k–m). n–p, Hemolymph cell monolayers of cockle DN at stages N1 (n), N2 (o) and N3 (p). Arrows indicate neoplastic cells; asterisks mark mitotic phases of neoplastic cells.
Extended Data Fig. 2 Distribution of repetitive elements in the cockle genome.
Frequency of classifiable repeats (26% of all repeats) along the reference cockle genome, displayed in terms of number of copies per 100-kb genomic segment. Repetitive element types with more than 1000 annotated copies are represented: long interspersed nuclear elements (LINE, 172,722 copies, 33.0%), transfer RNA repeats (tRNA, 81,766 copies, 15.6%), long terminal repeat elements (LTR, 78,009 copies, 14.9%), simple repeats (70,016 copies, 13.3%), short interspersed nuclear elements (SINE, 55,434 copies, 10.6%), DNA repeat elements (42,917 copies, 8.2%), low complexity repeats (12,171 copies, 2.3%), rolling circle repeats (RC, 8,843 copies, 1.7%), satellite repeats (2,100 copies, 0.4%). Genomic segments along the ideogram are classified as GC-low or GC-high based on whether their average nucleotide content is below or above the estimated average genomic G+C content (35.6%).
Extended Data Fig. 3 Histology and cytology of disseminated neoplasia in C. edule.
a–j, Micrographs of histological sections of CedBTN1 (a–g) and CedBTN2 (h–j) samples included in the ‘golden set’ of high-purity tumors. Micrographs show gills (b, h, j) and connective tissue around gonadal follicles and digestive gland (a, c–g, i), showcasing the distinctive features of the two morphological types of cockle DN: type A (a–g) and type B (h–j). k–m, Representative cell monolayers for normal hemocytes (k), type A DN (CedBTN1) cells (l), and type B DN (CedBTN2) cells (m). Histological sections stained with hematoxylin and eosin; cell monolayers stained with Hemacolor kit (Merck). Scale bars, 50 µm for a–j, 25 µm for k–m.
Extended Data Fig. 4 Germline polymorphism and gene expression in cockles and CedBTN tumors.
a, Principal component analysis (PCA) of germline polymorphisms in CedBTN and healthy cockle samples. Logistic PCA was performed on a randomly selected subset of 100,000 germline exonic single-nucleotide polymorphisms, genotyped across 100 non-neoplastic cockles (covering all sampling locations), seven CedBTN1 tumors, and three CedBTN2 tumors. b, Heatmap and unsupervised clustering of normal cockle tissue samples and CedBTN tumor samples, based on normalized gene expression values for 420 genes with tissue-specific expression (60 genes per normal tissue type). c, Principal component analysis of tissue-specific gene expression; normal hemolymph and CedBTN samples are labeled. Both analyses indicate a clustering of CedBTN samples with normal hemolymph.
Extended Data Fig. 5 Maximum likelihood phylogenies of cockle mtDNA and CedBTN genomes.
a, Maximum likelihood cockle mtDNA phylogeny. Midpoint-rooted tree of deconvoluted mtDNA haplotypes, including sample codes for normal (‘N0’) and tumor samples (‘T’; colored by mtDNA lineage). The nine identified mtDNA lineages are labeled. Bootstrap support values (n = 1000 replicates) are shown for all nodes. b, Maximum likelihood CedBTN nuclear phylogeny from genotyped SNVs. Phylogenetic tree inferred from a subset of 833,007 BTN-specific SNVs, including 30,000 randomly selected SNVs from each of the ancestral variant sets (‘A0’, ‘A1’, ‘A2’) and all the non-ancestral (postdivergence) SNVs in each nuclear lineage, which were genotyped across 61 tumor samples. Tips are colored according to mtDNA lineage (where information is available); sample labels are colored according to nuclear CedBTN lineage. Bootstrap support values (n = 1000 replicates) are shown for all nodes. Samples subjected to whole-genome amplification (WGA) are indicated by asterisks. Sample EICE18_910H is a case of co-infection by cells from mtDNA lineages BTN1-HT4 and BTN2-HT2 (Fig. 2e,f).
Extended Data Fig. 6 Distributions of tumors from each CedBTN mtDNA lineage.
a, Percentages of tumor samples from each CedBTN mtDNA lineage in each cockle population. Sampled cockle populations (corresponding to sampling locations; Supplementary Table 1) are grouped by country, except for Spain. Populations from Spain are divided into two groups (northern and southern Galicia), and are also presented individually to demonstrate the variability in mtDNA lineage composition across populations. b, Maps displaying the locations of tumor samples and their sister taxa for each identified CedBTN mtDNA lineage.
Extended Data Fig. 7 Recurrent mtDNA D-loop amplification and host co-infection in CedBTN.
a, Sequence read depth along the mitochondrial genome in representative samples from four CedBTN mtDNA lineages, showing the independent mtDNA amplifications identified in three mtDNA lineages within CedBTN1. A sample from BTN2-HT2 (top) is shown as representative of the read depth distribution in CedBTN2 samples. Amplification lengths are indicated. b, Schematic representation of the three mtDNA amplification events, two of which share the same start coordinate. Identity among the start sequences is marked by underlining, while overlapping microhomology at the boundaries of two of the amplified regions is highlighted in bold. c, Diagonal plots of position along long sequence reads (Oxford Nanopore) against mtDNA coordinate, showing the number of copies gained in each mtDNA lineage (duplication in BTN1-HT1, triplication in BTN1-HT4 and BTN1-HT5). d, mtDNA allele frequency plots evidencing the presence of two tumor mtDNA haplotypes (green/yellow) and one host haplotype (gray) in hemolymph (left) and adductor muscle (right) samples from three cockles presenting evidence of co-occurrence of multiple CedBTN lineages (top to bottom: ENCE17/4528, PACE17/970, EICE18/910; Supplementary Table 10). Each dot represents a mitochondrial SNV. Identified tumor mtDNA haplotypes are labeled as in Fig. 2a. As expected, tumor and host mtDNA haplotypes present lower and higher allele frequencies, respectively, in adductor muscle compared to hemolymph.
Extended Data Fig. 8 Molecular cytogenetic results from metaphases of healthy and neoplastic specimens.
a–b, FISH of 28S ribosomal DNA (rDNA; violet), 5S rDNA (red) and H3 histone gene (green) probes mapped onto a metaphase plate of a healthy specimen of C. edule and its corresponding karyotype with 2n = 38 chromosomes. As previously described80, up to five chromosome pairs hold subtelomeric clusters of 5S rDNA on their long arms, while 28S rDNA and histone H3 probes hybridize to the short arm of subtelocentric chromosomes. c–d, FISH mapping of the probes above onto example neoplastic metaphases, revealing abnormal location and number of these clusters. Scale bars, 10 µm.
Extended Data Fig. 9 Copy number profiles of CedBTN samples.
Plots of unrounded copy number along the reference genome (left) and copy number density (right) for each sample in the ‘golden set’ of high-purity tumors, grouped by CedBTN lineage. Each dot represents a genomic bin containing 10 kb of mappable sequence.
Extended Data Fig. 10 Structural variant distribution and candidate driver gene expression in CedBTN.
a, Circos plots representing the distribution of BTN-specific structural variants within the predivergence (ancestral) and postdivergence phylogenetic variant sets in CedBTN1 and CedBTN2. Deletions and duplications of size <10 kb are omitted for interpretability. b, Distributions of structural variant frequency, density and type composition (top to bottom) per reference chromosome, for variants identified in CedBTN1 (left) and CedBTN2 (right). c, Expression of genes with potential early driver CN alterations in CedBTN. For each of the four genes with potential early driver CN alterations, normalized gene expression counts are shown for normal tissue samples (n = 28), CedBTN1 samples (n = 6) and CedBTN2 samples (n = 2). Each dot represents one sample, and gray lines denote the median expression for each group. Normal hemolymph samples (n = 4) are marked in light blue. Adjusted p-values are shown for comparisons between normal tissues and each CedBTN lineage, obtained via differential expression analysis (two-sided Wald tests with Benjamini–Hochberg correction). Seven normal tissue samples presented null MGMT expression: ENCE17/3572B (gill), EYCE21/503H (hemolymph), EYCE21/507B (gill), EYCE21/507G (gonad), EYCE21/514H (hemolymph), ENCE21/2M (mantle), ENCE21/5F (foot). Normalized gene count values are comparable across samples for the same gene, but are not comparable across genes.
Supplementary information
Supplementary Information
Supplementary Note 1.
Supplementary Table
Supplementary Tables 1–15.
Source data
Source Data Fig. 1
Statistical source data.
Source Data Fig. 2
Statistical source data.
Source Data Fig. 3
Statistical source data.
Source Data Fig. 4
Statistical source data.
Source Data Extended Data Fig. 1
Statistical source data.
Source Data Extended Data Fig. 2
Statistical source data.
Source Data Extended Data Fig. 4
Statistical source data.
Source Data Extended Data Fig. 6
Statistical source data.
Source Data Extended Data Fig. 7
Statistical source data.
Source Data Extended Data Fig. 9
Statistical source data.
Source Data Extended Data Fig. 10
Statistical source data.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Bruzos, A.L., Santamarina, M., García-Souto, D. et al. Somatic evolution of marine transmissible leukemias in the common cockle, Cerastoderma edule. Nat Cancer 4, 1575–1591 (2023). https://doi.org/10.1038/s43018-023-00641-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s43018-023-00641-9
This article is cited by
-
A deep dive into transmissible cancer evolution in bivalve mollusks
Nature Cancer (2023)