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Molecular Biology of Ovarian Cancer

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Oncology".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 3441

Special Issue Editor

Special Issue Information

Dear Colleagues,

Epithelial ovarian cancer (EOC) represents the most lethal malignancy of the female genital tract. Nowadays, ovarian cancer patients’ prognosis mostly relies on the completeness of surgical tumor resection, clinical staging, and histological tumor grading. Thus, there is a compelling need to identify and validate tumor-specific mechanisms and molecules that are suitable to individualize therapeutic strategies. Interestingly, during EOC evolvement and progression, host anti-tumor immune defence seems to be actively blocked by tumor-derived mediators. By creating this highly suppressive environment, EOC manages to extensively grow and spread in the peritoneal cavity. In addition, recommended therapeutic approaches include beneath primary cytoreductive surgery, a platinum-based chemotherapy with anti-angiogenic agents, or PARP inhibitors. EOC is classified as serous, mucinous, endometrioid, and clear-cell histology, being distinguished in terms of phenotype, molecular background, and aetiology.  Research to identify new molecular prognostic markers needs to take this heterogeneity of ovarian cancer into account. A better understanding of the different mechanisms in ovarian cancer subtypes appears crucial to enable new diagnostic and therapeutic approaches.

Prof. Dr. Udo Jeschke
Guest Editor

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Keywords

  • Epithelial ovarian cancer (EOC)
  • Tumor-specific mechanism
  • Heterogeneity of ovarian cancer
  • Tumor-immune cell micro environment
  • New therapeutic strategies in EOC treatment.

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Published Papers (1 paper)

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Research

14 pages, 2915 KiB  
Article
Identification of Candidate Genes Associated with Susceptibility to Ovarian Clear Cell Adenocarcinoma Using cis-eQTL Analysis
by Jihye Kim, Joon-Yong Chung, Jae Ryoung Hwang, Yoo-Young Lee, Tae-Joong Kim, Jeong-Won Lee, Byoung-Gie Kim, Duk-Soo Bae, Chel Hun Choi and Stephen M. Hewitt
J. Clin. Med. 2020, 9(4), 1137; https://doi.org/10.3390/jcm9041137 - 16 Apr 2020
Cited by 3 | Viewed by 2747
Abstract
Ovarian clear cell adenocarcinoma (Ov-CCA) has a higher prevalence in the Japanese ancestry than other populations. The ancestral disparities in Ov-CCA prevalence suggests the presence of Ov-CCA-specific genetic alterations and may provide an opportunity to identify the novel genes associated with Ov-CCA tumorigenesis. [...] Read more.
Ovarian clear cell adenocarcinoma (Ov-CCA) has a higher prevalence in the Japanese ancestry than other populations. The ancestral disparities in Ov-CCA prevalence suggests the presence of Ov-CCA-specific genetic alterations and may provide an opportunity to identify the novel genes associated with Ov-CCA tumorigenesis. Using 94 previously reported genes as the phenotypic trait, we conducted multistep expression quantitative trait loci (eQTL) analysis with the HapMap3 project datasets. Four single-nucleotide polymorphisms (SNPs) (rs4873815, rs12976454, rs11136002, and rs13259097) that had different allele frequencies in the Japanese ancestry and seven genes associated in cis (APBA3, C8orf58, KIAA1967, NAPRT1, RHOBTB2, TNFRSF10B, and ZNF707) were identified. In silico functional annotation analysis and in vitro promoter assay validated the regulatory effect of rs4873815-TT on ZNF707 and rs11136002-TT on TNFRSF10B. Furthermore, ZNF707 was highly expressed in Ov-CCA and had a negative prognostic value in disease recurrence in our sample cohort. This prognostic power was consistently observed in The Cancer Genome Atlas (TCGA) clear cell renal cell carcinoma dataset, suggesting that ZNF707 may have prognostic value in clear cell histology regardless of tissue origin. In conclusion, rs4873815-TT/ZNF707 may have clinical significance in the prognosis and tumorigenesis of Ov-CCA, which may be more relevant to clear cell histology. Besides, this study may underpin the evidence that cis-eQTL analysis based on ancestral disparities can facilitate the discovery of causal genetic alterations in complex diseases, such as cancer. Full article
(This article belongs to the Special Issue Molecular Biology of Ovarian Cancer)
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