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Gene expression microarray analysis of adult testicular germ cell tumor: a comparison between pure-type seminomas and seminoma components in mixed tumors.

Kosuke MiyaiYuiko YonekuraKeiichi ItoSusumu MatsukumaHitoshi Tsuda
Published in: Virchows Archiv : an international journal of pathology (2021)
We previously demonstrated a genetic evidence of the progression from seminoma to embryonal carcinoma in mixed testicular germ cell tumors (TGCTs). This process, the "reprogramming" of seminoma cells, is crucial for pathological tumorigenesis and should be kept in mind while designing clinical therapeutic strategies. We hypothesized that a comparison between pure-type seminomas and seminoma components in mixed tumors (mixed-type seminomas) could reveal early changes in the reprogramming process. In the present study, we performed gene expression microarray analysis of six pure-type and six mixed-type seminomas. Hierarchical clustering analysis properly grouped each type of seminomas into a separated cluster. Supervised analysis between pure-type and mixed-type seminomas revealed 154 significantly dysregulated genes (Storey-adjusted q < 0.05). The genes with the highest overexpression in mixed-type seminomas compared with the pure-type seminomas included MT1 isoforms, PRSS8, TSC22D1, and SLC39A4; downregulated genes included DEFB123, LMTK2, and MYRF. Functional annotation analysis of the differentially expressed genes revealed that the top-ranked functional categories were related to cellular zinc metabolism and consisted of MT1 isoforms and SLC39A4, the results of which were validated using quantitative polymerase chain reaction and immunohistochemical analysis. In conclusion, this research provides further evidence that pure and mixed types of seminomas are molecularly different, which may contribute to elucidate the reprogramming mechanism in the progression of TGCTs.
Keyphrases
  • germ cell
  • gene expression
  • genome wide
  • single cell
  • machine learning
  • cell proliferation
  • cell death
  • young adults
  • data analysis