In this study, we aimed to investigate the molecular mechanisms underlying OCCC tumorigenesis toward the early detection and novel therapeutic strategy for OCCC. We performed genetic and epigenetic analyses of the PRELP gene using OCCC cell lines and clinical samples. To our knowledge, this is the first study to focus on the PRELP gene in OCCC.
4. DiscussionIn this study, we provided a novel perspective on the molecular features of the pathogenesis of OCCC. We first showed that the PRELP gene expression is repressed using public datasets of clinical tissues from patients with ovarian cancer compared with normal tissues. Furthermore, all OCCC cell lines we tested exhibited a significant downregulation of the PRELP expression compared with ovarian endometriotic epithelial cells and the putative progenitor of OCCC, which reflects that PRELP repression may be involved in early OCCC tumorigenesis. Thus, studying PRELP as a biomarker for the early detection of OCCC is intriguing.
How is PRELP expression suppressed during OCCC tumorigenesis? Deletions and somatic mutations in the PRELP gene are relatively rare (Figure 1), making it unlikely that genetic alterations are the primary cause of the suppression of PRELP expression. Indeed, ChIP-seq analyses revealed that using normal ovary and OCCC tissues and transcriptionally active marks, such as H3K4me3 and H3K27ac, were diminished at the PRELP gene promoter region in OCCC compared with those in normal ovary tissues, indicating that the PRELP gene is repressed, at least in part, by an epigenetic mechanism.Epigenetic mechanisms have been shown to contribute profoundly to OCCC tumorigenesis. For example, mutations in the AT–rich interaction domain 1A (ARID1A) and phosphatidylinositol-4,5-bisphosphate 3-kinase (PIK3) catalytic subunit alpha (PIK3CA) have been frequently detected in OCCC cases [31,32,33]. ARID1A encodes the BAF250 protein as a subunit of the switch/sucrose non-fermentable chromatin–remodeling complex that facilitates the epigenetic regulation of the chromatin structure and transcription factors [34,35]. BAF250 protein loss can be detected in atypical endometriosis but not in distant endometriotic lesions [34]. ARID1A and PIK3CA mutations may contribute to OCCC tumorigenesis through sustained interleukin (IL)-6 production [35]. Moreover, Yano et al. showed that histone deacetylases, HDAC6 and HDAC7, are more strongly expressed in OCCC than in other subtypes of ovarian cancer [36]. How these epigenetic alterations and PRELP suppression contribute to OCCC tumorigenesis are currently unclear; however, one scenario is that the interplay between ARID1A and HDACs could significantly contribute to OCCC tumorigenesis [37]. Therefore, it is possible that the dysregulation of HDACs directly suppresses PRELP gene expression.Using conditionally, PRELP-expressing cells derived from OCCC cell lines in which the ARID1A protein expression was repressed [38], we revealed that PRELP significantly altered the gene expression of more than 1000 genes. Particularly, it regulates a set of genes related to the PI3K-AKT signaling pathway (Figure 5). How PRELP can alter these pathways is unclear, even though it is a secreted ECM protein. However, recent proteomic studies have suggested that PRELP interacts with two growth factor receptors: insulin-like growth factor I receptor and low-affinity nerve growth factor receptor (p75NTR) [39], suggesting that PRELP functions as a ligand. Although many questions remain unanswered, elucidating the subcellular localization of PRELP may provide clues to the answers to these questions.Although the aforementioned results provide the unexpected finding that PRELP is not only a connective tissue-anchored molecule but also a tumor-suppressive signaling molecule in OCCC, many unresolved issues remain. For example, experiments, such as the cell-cycle analysis, are needed to elucidate more detailed molecular mechanisms. In future studies, we plan to comprehensively analyze the protein expression level of a group of genes involved in the PI3K-AKT signaling pathway with or without PRELP using immunoblotting. Moreover, the anticancer mechanisms of the PRELP protein in OCCC have not been elucidated. The xenograft mouse model in the OCCC cell line is one of the next studies we wish to conduct for further validation of the function of PRELP. Lastly, due to the limited number of clinical samples used in this study, conducting clinical studies is impossible, such as validating a biomarker. Most of the cohort databases of ovarian cancer correspond to HGSOC patients, and there is no big dataset of OCCC patients. Several PI3K/AKT/mammalian target rapamycin (mTOR) pathway inhibitors have been used in clinical trials for OCCC [40]. To validate the clinical function of PRELP, we have to perform a prospective study to establish a dataset of OCCC patients for genetic and epigenetic analyses.Although we analyzed pathways at the induction of PRELP expression, specifically in OCCC, there have been some studies reporting PRELP in other cancer types. HDAC inhibitors show anti-cancer effects by partially regulating the function of PRELP in bladder cancer. Furthermore, the acetylation of lysine residue 5 of histone H2B in the PRELP gene promoter region is a marker for the restoration of PRELP expression [23]. The overexpression of PRELP correlates with better patient survival and inhibits both cell proliferation and migration in hepatocellular carcinoma [41]. A peptide corresponding to the N-terminal heparin-binding domain of PRELP inhibits osteoclastogenesis in breast cancer metastases [42]. Thus, PRELP may regulate a set of genes related to the PI3K-AKT signaling pathway regardless of carcinoma type to some extent. However, no single data type, such as somatic mutations or gene expression, can capture the complexity of all the factors relevant to understanding phenomena such as cancer. Recently, integrated genetic and epigenetic dataset analyses using machine learning algorithms have emerged [43]. Our future directions may focus on epigenetics combined with RNA-seq and ChIP-seq, which may become part of the data to predict clinical outcomes. Elucidating the roles of PRELP in cancer may help understand the clinical significance of the classified genes identified by machine learning algorithms.
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