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Multiple metastatic clones assessed by an integrative multiomics strategy in clear cell renal carcinoma: a case study.

Julien DagherAngelique BrunotBertrand EvrardSolene-Florence Kammerer-JacquetMarion BeaumontLaurence CornevinFanny DerquinGregory VerhoestKarim BensalahAlexandra LespagnolFrederic DugayMarc-Antoine Belaud-RotureauFrédéric ChalmelNathalie Rioux-Leclercq
Published in: Journal of clinical pathology (2021)
The dynamics of metastatic evolution in clear cell renal cell carcinoma (ccRCC) are complex. We report a case study where tumour heterogeneity resulting from clonal evolution is a frequent feature and could play a role in metastatic dissemination.We used an integrative multiomics strategy combining genomic and transcriptomic data to classify fourteen specimens from spatially different areas of a kidney tumour and three non-primary sites including a vein thrombus and two adrenal metastases.All sites were heterogeneous and polyclonal, each tumour site containing two different aggressive subclonal populations, with differentially expressed genes implicated in distinct biological functions. These are rare primary metastatic samples prior to any medical treatment, where we showed a multiple metastatic seeding of two subclonal populations.Multiple interdependent lineages could be the source of metastatic heterogeneity in ccRCC. By sampling metastases, patients with resistance to therapies could benefit a combination of targeted therapies based on more than one aggressive clone.
Keyphrases
  • squamous cell carcinoma
  • small cell lung cancer
  • single cell
  • healthcare
  • machine learning
  • gene expression
  • deep learning
  • copy number
  • rna seq
  • network analysis
  • combination therapy