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Somatic evolution of marine transmissible leukemias in the common cockle, Cerastoderma edule

Nature Cancer volume 4, pages 1575–1591 (2023)Cite this article

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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.

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Fig. 1: Distribution, origins and clonal structure of transmissible neoplasia in common cockles.
Fig. 2: mtDNA phylogeny, mtDNA HT and host co-infection in CedBTN.
Fig. 3: Mutational processes in CedBTN.
Fig. 4: Chromosomal, CN and structural variation in cockle BTN.

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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).

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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

Author notes

  1. These authors contributed equally: Alicia L. Bruzos, Martín Santamarina, Daniel García-Souto, Seila Díaz, Sara Rocha.

  2. These authors jointly supervised this work: Adrian Baez-Ortega, Jose M. C. Tubio.

Authors and Affiliations

  1. Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Alicia L. Bruzos, Martín Santamarina, Daniel García-Souto, Seila Díaz, Jorge Zamora, Alejandro Viña-Feás, Iago Otero, Ana Pequeño-Valtierra, Javier Temes, Jorge Rodriguez-Castro, Leyre Aramburu & Jose M. C. Tubio

  2. Department of Zoology, Genetics and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Alicia L. Bruzos, Martín Santamarina, Daniel García-Souto, Iago Otero & Jose M. C. Tubio

  3. Instituto de Investigaciones Sanitarias de Santiago de Compostela (IDIS), Santiago de Compostela, Spain

    Alicia L. Bruzos, Martín Santamarina, Daniel García-Souto, Alejandro Viña-Feás, Iago Otero, Ana Pequeño-Valtierra, Javier Temes, Jorge Rodriguez-Castro & Jose M. C. Tubio

  4. Wellcome Sanger Institute, Hinxton, UK

    Daniel García-Souto, Michael A. Quail, Zemin Ning & Adrian Baez-Ortega

  5. ECOMARE, Centre for Environmental and Marine Studies (CESAM) & Department of Biology, University of Aveiro, Aveiro, Portugal

    Seila Díaz, Ricardo Calado & Fernando Ricardo

  6. CINBIO, Universidade de Vigo, Vigo, Spain

    Sara Rocha, Tamara Prieto, Laura Tomás, Pilar Alvariño, Juana Alonso & David Posada

  7. Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

    Yunah Lee & Young Seok Ju

  8. Department of Biochemistry, Genetics and Immunology, Universidade de Vigo, Vigo, Spain

    André Vidal-Capón, Juan J. Pasantes & David Posada

  9. Centro de Investigación Mariña (CIM-ECIMAT), Universidade de Vigo, Vigo, Spain

    Antonio Villanueva, Damián Costas, Rosana Rodríguez & Juan J. Pasantes

  10. Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Vigo, Spain

    Tamara Prieto, Laura Tomás, Pilar Alvariño, Juana Alonso & David Posada

  11. New York Genome Center, New York, NY, USA

    Tamara Prieto

  12. Centro de Investigacións Mariñas (CIMA), Consellería do Mar, Xunta de Galicia, Vilanova de Arousa, Spain

    Asunción Cao, David Iglesias, María J. Carballal & Antonio Villalba

  13. Centro de Ciencias do Mar do Algarve (CCMAR), Universidade do Algarve, Faro, Portugal

    Ana M. Amaral

  14. Department of Biological Sciences, University of Bergen, Bergen, Norway

    Pablo Balseiro

  15. NORCE AS, Bergen, Norway

    Pablo Balseiro

  16. Laboratory of Physiopathology, Molecular Genetics & Biotechnology, Faculty of Sciences Ain Chock, Health and Biotechnology Research Centre, Hassan II University of Casablanca, Casablanca, Morocco

    Bouchra El Khalfi

  17. Research Centre for Experimental Marine Biology and Biotechnology (PiE-UPV/EHU), University of the Basque Country (UPV/EHU), Plenzia-Bitzkaia, Spain

    Urtzi Izagirre, Pamela Ruiz & Antonio Villalba

  18. Cell Biology in Environmental Toxicology Research Group, University of the Basque Country (UPV/EHU), Leioa-Bizkaia, Spain

    Urtzi Izagirre & Pamela Ruiz

  19. UMR EPOC5805, University of Bordeaux, Arcachon, France

    Xavier de Montaudouin

  20. European Marine Biology Resources Centre (EMBRC-ERIC), Paris, France

    Nicolas G. Pade

  21. FR2424 Station Biologique de Roscoff, Sorbonne University/CNRS, Roscoff, France

    Ian Probert

  22. Department of Applied Ecology, St Petersburg State University, St Petersburg, Russia

    Maria Skazina

  23. Department of Marine Ecosystem Functioning, University of Gdańsk, Gdynia, Poland

    Katarzyna Smolarz

  24. Department of Life Sciences, Universidad de Alcalá, Alcalá de Henares, Spain

    Antonio Villalba

  25. VIB–KU Leuven Center for Cancer Biology, Leuven, Belgium

    Jonas Demeulemeester

  26. Department of Oncology, KU Leuven, Leuven, Belgium

    Jonas Demeulemeester

  27. The Francis Crick Institute, London, UK

    Jonas Demeulemeester

  28. Magdalene College, University of Cambridge, Cambridge, UK

    Adrian Baez-Ortega

Authors
  1. Alicia L. Bruzos
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  2. Martín Santamarina
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  3. Daniel García-Souto
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  4. Seila Díaz
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  5. Sara Rocha
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  7. Yunah Lee
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  16. Antonio Villanueva
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  17. Damián Costas
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  18. Rosana Rodríguez
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  19. Tamara Prieto
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  20. Laura Tomás
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  21. Pilar Alvariño
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  22. Juana Alonso
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  28. Ricardo Calado
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  29. Bouchra El Khalfi
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  30. Urtzi Izagirre
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  31. Xavier de Montaudouin
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  32. Nicolas G. Pade
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  33. Ian Probert
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  34. Fernando Ricardo
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  35. Pamela Ruiz
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  36. Maria Skazina
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  37. Katarzyna Smolarz
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  38. Juan J. Pasantes
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  39. Antonio Villalba
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  40. Zemin Ning
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  41. Young Seok Ju
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  42. David Posada
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  43. Jonas Demeulemeester
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  44. Adrian Baez-Ortega
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  45. Jose M. C. Tubio
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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

Correspondence to Adrian Baez-Ortega or Jose M. C. Tubio.

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Competing interests

The authors declare no competing interests.

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Nature Cancer thanks Andreas Bergthaler, Kelley Thomas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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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.

Source data

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%).

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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.

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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.

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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.

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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.

Source data

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.

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Supplementary information

Supplementary Information

Supplementary Note 1.

Reporting Summary

Supplementary Table

Supplementary Tables 1–15.

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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

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