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Patterns of gene expression characterize T1 and T3 clear cell renal cell carcinoma subtypes

Author

Listed:
  • Agnieszka M Borys
  • Michał Seweryn
  • Tomasz Gołąbek
  • Łukasz Bełch
  • Agnieszka Klimkowska
  • Justyna Totoń-Żurańska
  • Julita Machlowska
  • Piotr Chłosta
  • Krzysztof Okoń
  • Paweł P Wołkow

Abstract

Renal carcinoma is the 20th most common cancer worldwide. Clear cell renal cell carcinoma is the most frequent type of renal cancer. Even in patients diagnosed at an early stage, characteristics of disease progression remain heterogeneous. Up-to-date molecular classifications stratify the ccRCC samples into two clusters. We analyzed gene expression in 23 T1 or T3 ccRCC samples. Unsupervised clustering divided this group into three clusters, two of them contained pure T1 or T3 samples while one contained a mixed group. We defined a group of 36 genes that discriminate the mixed cluster. This gene set could be associated with tumor classification into a higher stage and it contained significant number of genes coding for molecular transporters, channel and transmembrane proteins. External data from TCGA used to test our findings confirmed that the expression levels of those 36 genes varied significantly between T1 and T3 tumors. In conclusion, we found a clustering pattern of gene expression, informative for heterogeneity among T1 and T3 tumors of clear cell renal cell carcinoma.

Suggested Citation

  • Agnieszka M Borys & Michał Seweryn & Tomasz Gołąbek & Łukasz Bełch & Agnieszka Klimkowska & Justyna Totoń-Żurańska & Julita Machlowska & Piotr Chłosta & Krzysztof Okoń & Paweł P Wołkow, 2019. "Patterns of gene expression characterize T1 and T3 clear cell renal cell carcinoma subtypes," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-19, May.
    • Handle: RePEc:plo:pone00:0216793
    DOI: 10.1371/journal.pone.0216793
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    References listed on IDEAS

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    1. Maciej Pietrzak & Grzegorz A. Rempała & Michał Seweryn & Jacek Wesołowski, 2016. "Limit theorems for empirical Rényi entropy and divergence with applications to molecular diversity analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 654-673, December.
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    Cited by:

    1. Sandra M. Rocha & Sílvia Socorro & Luís A. Passarinha & Cláudio J. Maia, 2022. "Comprehensive Landscape of STEAP Family Members Expression in Human Cancers: Unraveling the Potential Usefulness in Clinical Practice Using Integrated Bioinformatics Analysis," Data, MDPI, vol. 7(5), pages 1-48, May.

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