BMC Genomics (Nov 2012)

Molecular evidence for the bi-clonal origin of neuroendocrine tumor derived metastases

  • Rinner Beate,
  • Gallè Birgit,
  • Trajanoski Slave,
  • Fischer Carina,
  • Hatz Martina,
  • Maierhofer Theresa,
  • Michelitsch Gabriele,
  • Moinfar Farid,
  • Stelzer Ingeborg,
  • Pfragner Roswitha,
  • Guelly Christian

DOI
https://doi.org/10.1186/1471-2164-13-594
Journal volume & issue
Vol. 13, no. 1
p. 594

Abstract

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Abstract Background Reports on common mutations in neuroendocrine tumors (NET) are rare and clonality of NET metastases has not been investigated in this tumor entity yet. We selected one NET and the corresponding lymph node and liver metastases as well as the derivative cell lines to screen for somatic mutations in the primary NET and to track the fate of genetic changes during metastasis and in vitro progression. Results Applying microarray based sequence capture resequencing including 4,935 Exons from of 203 cancer-associated genes and high-resolution copy number and genotype analysis identified multiple somatic mutations in the primary NET, affecting BRCA2, CTNNB1, ERCC5, HNF1A, KIT, MLL, RB1, ROS1, SMAD4, and TP53. All mutations were confirmed in the patients’ lymph node and liver metastasis tissue as well as early cell line passages. In contrast to the tumor derived cell line, higher passages of the metastases derived cell lines lacked somatic mutations and chromosomal alterations, while expression of the classical NET marker serotonin was maintained. Conclusion Our study reveals that both metastases have evolved from the same pair of genetically differing NET cell clones. In both metastases, the in vivo dominating “mutant” tumor cell clone has undergone negative selection in vitro being replaced by the “non-mutant” tumor cell population. This is the first report of a bi-clonal origin of NET derived metastases, indicating selective advantage of interclonal cooperation during metastasis. In addition, this study underscores the importance to monitor cell line integrity using high-resolution genome analysis tools.

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