Clinical significance of tumor infiltrating lymphocytes in association with hormone receptor expression patterns in epithelial ovarian cancer

Gwan Hee Han, Ilseon Hwang, Hanbyoul Cho, Kris Ylaya, Jung A. Choi, Hyunja Kwon, Joon Yong Chung, Stephen M. Hewitt, Jae Hoon Kim

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Hormone receptor expression patterns often correlate with infiltration of specific lymphocytes in tumors. Specifically, the presence of specific tumor-infiltrating lymphocytes (TILs) with particular hormone receptor expression is reportedly associated with breast cancer, however, this has not been revealed in epithelial ovarian cancer (EOC). Therefore, we investigated the association between hormone receptor expression and TILs in EOC. Here we found that ERα, AR, and GR expression increased in EOC, while PR was significantly reduced and ERβ expression showed a reduced trend compared to normal epithelium. Cluster analysis indicated poor disease-free survival (DFS) in AR+/GR+/PR+ subgroup (triple dominant group); while the Cox proportional-hazards model high-lighted the triple dominant group as an independent prognostic factor for DFS. In addition, significant upregulation of FoxP3+ TILs, PD-1, and PD-L1 was observed in the triple dominant group compared to other groups. NanoString analyses further suggested that tumor necrosis factor (TNF) and/or NF-κB signaling pathways were activated with significant upregulation of RELA, MAP3K5, TNFAIP3, BCL2L1, RIPK1, TRAF2, PARP1, and AKT1 in the triple dominant EOC group. The triple dominant subgroup correlates with poor prognosis in EOC. Moreover, the TNF and/or NF-κB signaling pathways may be responsible for hormone-mediated inhibition of the immune microenvironment.

Original languageEnglish
Article number5714
JournalInternational journal of molecular sciences
Volume22
Issue number11
DOIs
Publication statusPublished - 2021 Jun 1

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Catalysis
  • Molecular Biology
  • Spectroscopy
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry
  • Inorganic Chemistry

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