Differential expression of TRPV1, TRPV4, and TRPV6 across ovarian cancer subtypes

Differential expression of TRPV1, TRPV4, and TRPV6 across ovarian cancer subtypes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Differential expression of TRPV1, TRPV4, and TRPV6 across ovarian cancer subtypes Aida Aghazadeh, Mehdi Haghi, Mohammad Ali Hosseinpour Feizi, Behzad Baradaran This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7005174/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Ovarian cancer known as a heterogenous and lethal gynecological malignancies often identified at early stages. Emerging evidences suggest that Ca 2+ -permeable transient receptor potential (TRP) channels play pivotal roles in cancer progression. TRPV1, TRPV4 and TRPV6 have been indicated in various tumorigenic processes, still their subtype specific expression and clinical relevance in ovarian cancer remain unclear. Methods we investigated the expression patterns of TRPV1, TRPV4 and TRPV6 in ovarian cancer via integrative analyses. Publicly available microarray datasets were used for in silico comparison between subtypes of ovarian cancer and normal tissues. Expression levels were validated using qRT-PCR and western blotting samples representing high-grade serous, mucinous, endometroid and clear cell carcinoma subtypes. Clinical correlations were evaluated using data from the the GSE6008 database, Affymetrix Human Genome U133A Array database. Results TRPV1 was significantly up-regulated in high-grade serous, mucinous, and endometrioid ovarian carcinomas. TRPV4 showed elevated expression in mucinous carcinoma but it showed markable down-regulation in both high-grade serous and endometroid subtypes. TRPV6 expression was significantly elevated in mucinous and endometrioid carcinomas. ROC curve analysis showed significance diagnostic potential. increased levels of TRPV1 and TRPV4 expression were associated with improved overall survival in high-grade serous carcinoma patients. Conclusion our results reveal distinct, subtypes specific expression patterns of TRPV1, TRPV4 and TRPV6 in ovarian cancer, undercovering their potential as diagnostic biomarkers and therapeutic targets. These findings promote the further investigation of TRP channels in the context of personalized treatment strategies for ovarian cancer patients. TRPV1 TRPV4 TRPV6 Ovarian cancer biomarkers high-grade serous mucinous calcium signaling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Ovarian cancer is known as one of the lethal gynecological malignancies, which is mostly diagnosed in advanced stages ( 1 ). Epithelial ovarian cancers constitute almost 90% of ovarian cancers ( 2 ), and they are divided into five main types: high-grade serous, low-grade serous, mucinous, endometrioid, and clear cell carcinoma. In contrast, non-epithelial ovarian cancers originate from germ cells or sex-cord-stromal tissues ( 2 , 3 ). Preceding research has indicated that ovarian cancer originates from fallopian tubes rather than the ovary, as was thought before ( 4 , 5 ). Based on molecular genetics data, ovarian cancer can be divided into two main groups, i.e., type I and type II tumors. Type I tumors include low-grade serous, low-grade endometrioid, mucinous, and clear cell carcinomas, while type II tumors are high-grade serous ovarian cancer (HGSOC), high-grade endometroid, malignant-mixed mesodermal, and undifferentiated tumors ( 6 , 7 ). Type I tumors are characterized by large cystic masses that are restricted to one ovary. The mutations in KRAS , BRAF , PIK3CA, PTEN , ARID1A , CTNNB1 , and PPP2R1A are responsible for developing type I tumors ( 8 , 9 ). Type II tumors are characterized by chromosomal abnormalities. HGSOC is the most prevalent and invasive form of type II tumors ( 10 ). The available screening methods, including pelvic examination, serum CA-125 level, and transvaginal ultrasound, have limited significance in the diagnosis of HGSOC in its early stage ( 11 ). Therefore, there is an urgent need to identify potential biomarkers for this cancer ( 12 ). Calcium is a key second messenger that mediates the signal transduction essential for cell proliferation, migration, and apoptosis ( 13 ). It has been reported that dysregulation of plasma and organelle-based Ca 2+ signaling pathways is implicated in ovarian tumor development ( 14 ). Ca 2+ influx mediated by intracellular Ca 2+ channels can lead to the transition from G1/S to mitosis phase in the cell cycle; however, Ca 2+ deficiency arrests the cell cycle at G0/G1 and S phase ( 15 ). Transient receptor potential (TRP) channels are a group of non-selective cell membrane channels that permit Ca 2+ to pass through. Based on the analogy of their amino acid sequences, these channels are classified into 7 groups. TRP canonical (TRPC), TRP vanilloid (TRPV), TRP mestatin (TRPM), TRP polycystic protein (TRPPP), TRP mucin (TRPML), TRP anchor protein (TRPA), and TRP no mechanoreceptor potential C (TRPCN). The activation of the TRP channels temporarily increases intracellular Ca 2+ levels, highlighting the significance of TRP channels as important components of Ca 2+ signaling pathways ( 16 , 17 ). Consistent with these, growing studies have investigated the role of TRP channels in Ca 2+ -mediated signaling pathways and cancer development. Also, TRP channels have been identified as prognostic and therapeutic targets in various cancers ( 18 ). In this regard, we aimed to study the expression patterns of TRPV1 , TRPV4 , and TRPV6 in the different subtypes of ovarian cancers. The results of this study can provide valuable data for further elucidating the molecular mechanisms of ovarian cancer pathogenesis. Material and methods Tissue preparation The samples were obtained from patients at Alzahra Hospital, the teaching hospital affiliated with Tabriz University of Medical Sciences, Tabriz, Iran. The obtained samples were immediately frozen in liquid nitrogen and stored at -80°C for later use. The histopathological results were confirmed in the subsequent step by an experienced pathologist. Cell culture Five epithelial ovarian cancer cell lines, i.e., OCAR3, SKO3, 2008/C13, A2780-cp, and A2780S, were obtained from the Pasteur Institute in Tehran, Iran. All cells were cultured in RPMI-1640 medium, supplemented with 10% fetal bovine serum (FBS) (Gibco,00282508), and 1% antibiotics (penicillin at 100 U/ml and streptomycin at 100 µg/ml) (Gibco3810-74-0, Grand Island, NY 14072, USA). A humidified incubator at 37°C with 5% CO 2 was used to incubate cells. The assays were performed in the logarithmic phase of cell growth. RNA extraction and qRT-PCR Total RNA was extracted from tissues and cell lines using the TRI-zol™ Reagent following the manufacturer’s protocol. All equipment was RNase-free, and homogenizers were treated with 1% DEPC water for 24 hours and then autoclaved. The quality and concentration of the extracted RNA were assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific Life Science, Waltham, MA) by calculating absorbance ratios (A260/A280 and A260/A230); all RNA samples had 260/280 nm ≥ 1.8. The integrity assessment of the extracted RNA was determined via 2% agarose gel electrophoresis. Complementary DNA (cDNA) was synthesized from total RNA using a cDNA synthesis kit (SMOBIO, Taiwan) in a thermal cycler (Bio-Rad). The mRNA expression levels of TRPV1 , TRPV4 , and TRPV6 were evaluated using qRT-PCR (Applied Biosystems, USA) and SYBR Green MasterMix (Amplicon, Odense, Denmark). All tests were performed in triplicate, and the samples were normalized to the expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as the internal control. The primer sequences are listed in Table 1 . The \(\:\varDelta\:\varDelta\:qc\:\) method was used to calculate the relative expression changes. Table 1 The expression of TRPV1, TRPV4, and TRPV6 genes in ovarian cancer Gene Sample type N Relevant expression (2 −∆Ct ) MEAN ± SEM Statistical significance p-value TRPV1 Tumor Normal 54 54 0.01546 ± 0.002852 0.01244 ± 0.001988 ns 0.1233 TRPV4 Tumor Normal 54 54 0.0009747 ± 0.0001465 0.002109 ± 0.0003528 s **** < 0.0001 TRPV6 Tumor Normal 54 54 0.001269 ± 0.0003311 0.0009668 ± 0.0001942 ns 0.1715 Western blotting 500 mg of tissue and 10 6 cells were homogenized in 500 mg of RIPA lysis buffer containing (0/05 mmol/L Tris (pH 8), 150 mmol/L NaCl, 1% EGTA, 1% SDS, and 1% anti-protease cocktail containing PMSF (Roche) was used to extract total proteins. The lysed cells and tissue suspensions were vortexed for 15 seconds and incubated on ice for 10 minutes. Consequently, the suspensions were centrifuged at 12,000 rpm and 4°C for 10 minutes (Eppendorf 5415 R). Protein concentration was determined using the Bio-Rad Protein Assay kit, measuring absorbance at 595 nm. Afterward, the samples were diluted in a 1:1 ratio in loading sample buffer (50mmol Tris, pH 6.8, 2% SDS, 10% glycerol, 5% β-mercaptoethanol, 0/005 bromophenol blue) to detect protein expression. Samples were separated on a 10% polyacrylamide gel at 150 V and transferred onto a polyvinylidene difluoride (PVDF; Roche Diagnostics) membrane for 2 hours at 90 V. PVDF membranes were incubated with blocking buffer (3% BSA in TBSI) for 2 hours. After blocking, the membranes were treated overnight at 4°C with monoclonal antibodies against TRPV1 (E-8 cat.no: Sc- 398417) (Santa Cruz Biotechnology, INC) TRPV4 (ab39260, Abcam), TRPV6 (CAT-1 (2B9) cat.no: Sc-293226) as well as β-actin (C4: cat no: Sc-47778) as the internal control protein. The membranes were then washed and incubated with an anti-rabbit secondary antibody (IgG-HRP; cat. no. sc-2357, BP-HRP; cat. no. sc-516102) conjugated with horseradish peroxidase (1:5000; diluted in phosphate-buffered saline (PBS)) at room temperature for 1 hour on a shaker. Protein bands were detected using an electrochemiluminescence kit (Roche Diagnostics) and analyzed with a western blot imaging system (Sabz Co., Urmia, Iran). Band intensity was then measured with ImageJ software (NIH, Bethesda, MD). In silico study The Gene Expression Omnibus (GEO) database was searched to choose a dataset investigating mRNA expression in different ovarian cancer types. For this purpose, the GSE6008 database was selected; this microarray dataset used Affymetrix Human Genome U133A Array to study mRNA expression in 37 endometrioid, 41 serous, 13 mucinous, and 8 clear cell carcinomas and 4 normal ovary samples. We used R software (version 4.5) to normalize the expression values; then the expression values of TRPV1 , TRPV4 , and TRPV6 were analyzed in the different studied groups. Results TRPV1 , TRPV4 , and TRPV6 expression in normal and different types of ovarian cancer Our in-silico studies have shown that there is no statistically significant difference in TRPV1 expression between clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, serous ovarian cancer, and normal ovarian tissues (Fig. 1 A). However, clear cell ovarian cancer tissues have higher TRPV4 expression levels compared to endometrioid ovarian cancer, serous ovarian cancer and normal ovarian tissues (Fig. 1 B). In addition, endometrioid ovarian cancer tissues have higher expression levels of TRPV6 compared to serous ovarian cancer tissues (Fig. 1 C). TRPV1 , TRPV4 , and TRPV6 expression in different tumor grades of endometrioid ovarian cancer and serous ovarian cancer Our in-silico results have shown that there is no significant difference in TRPV1 , TRPV4 , and TRPV6 expression levels in different grades of endometrioid ovarian tissues (Fig. 2 A-C). In addition, there is no significant difference between grade 2 and grade 3 of serous ovarian cancer in terms of TRPV1 , TRPV4 , and TRPV6 expression (Fig. 2 D-F). TRPV1 , TRPV4 , and TRPV6 expression patterns and potential biomarkers in ovarian cancer Based on pathological findings, the 54 pairs of collected ovarian tissues were categorized into the following subtypes: 18 pairs (33.33%) of HGSOC, 8 pairs (14.81%) of granulosa cell tumor, 7 pairs (12.9%) of mucinous ovarian carcinoma, 7 pairs (12.9%) of endometrioid adenocarcinoma, 8 pairs (14.81%) of borderline serous carcinoma, and 6 pairs (11.11%) of borderline Brenner carcinoma. The mRNA expression results have shown that TRPV4 expression was significantly downregulated in tumoral tissues compared to non-tumoral ones (P-value \(\:0.05) (Fig. 3 ) (Table 1 ). After validating the downregulation of TRPV4 in ovarian tumor tissues, the ROC analysis has shown a weak diagnostic significance for ovarian tumors (Fig. 3 ) (Table 2 ). Table 2 The statistical analysis of the ROC curve for TRPV1, TRPV4, and TRPV6 genes Gene The area under the ROC curve Sensitivity (%) Specificity (%) Cutoff score Std. error 95% confidence interval P-value TRPV1 0.5365 54.17% 52.08% 0.001145 0.06018 0.4945–0.7304 0.0577 TRPV1 , TRPV4 , and TRPV6 mRNA expression in different subtypes of ovarian cancers We then studied the mRNA expression patterns of TRPV1 , TRPV4 , and TRPV6 in different ovarian tumor subtypes and their corresponding adjacent non-tumoral tissue. Our results have shown that TRPV1 expression level was significantly upregulated in HGSOC (P-value = 0.0085), mucinous ovarian carcinoma (P-value = 0.0005), and endometrioid adenocarcinoma (P-value = 0.0290) compared to their corresponding adjacent non-tumoral tissues. However, TRPV1 expression was significantly downregulated in granulosa cell tumors (P-value = 0.0018). There was no significant difference in the expression of TRPV1 in borderline serous carcinoma and borderline Brenner carcinoma tissues in comparison to relevant non-tumoral tissues (P-values > 0.05) (Fig. 4 )(Table 3 ). In addition, TRPV4 expression level was significantly upregulated in mucinous ovarian carcinoma compared to their adjacent non-tumoral tissues (P-value = 0.0072). In contrast, TRPV4 expression level was downregulated in HGSOC (P-value = 0.0002), borderline serous carcinoma (P-value = 0.0331), and borderline Brenner carcinoma tissues (P-value = 0.0097) compared to their corresponding adjacent tissues. TRPV4 expression level had no significant differences in granulosa cell tumor and endometrioid adenocarcinoma compared to their relevant non-tumoral tissues (P-values > 0.05) (Fig. 5 ) (Table 4 ). Furthermore, TRPV6 expression was significantly increased in mucinous ovarian carcinoma (P-value = 0.0174), endometrioid adenocarcinoma (P-value = 0.0039), and borderline Brenner carcinoma (P-value = 0.0106) tissues; whereas TRPV6 expression was significantly downregulated in borderline serous carcinoma (P-value = 0.0139). Besides, no significant differences were observed in HGSOC and granulosa cell tumor tissues compared to corresponding non-tumoral tissues (P-values > 0.05) (Fig. 6 )(Table 5 ). Table 3 TRPV1 expression pattern across ovarian cancer subtypes Ovarian cancer type N Relevant expression of TRPV-1 (2 −∆Ct ) MEAN ± SEM Statistical significance p-value HGSOC Marginal tissues 18 18 0.02441 ± 0.004918 0.01469 ± 0.002935 s ** 0.0085 GCT Marginal tissues 8 8 0.003755 ± 0.001018 0.01422 ± 0.002867 s ** 0.0018 MOC Marginal tissues 7 7 0.01521 ± 0.0004868 0.004483 ± 0.0006511 s *** 0.0005 EAC Marginal tissues 7 7 0.002299 ± 0.0002604 0.0005903 ± 4.106e-005 s * 0.0290 BSC Marginal tissues 8 8 0.001419 ± 0.0003175 0.001732 ± 0.0006335 ns 0.4249 BBC Marginal tissues 6 6 0.04343 ± 0.009567 0.04325 ± 0.002752 ns 0.9853 N: number SEM: standard error of mean s: significant ns: non-significant significance: *p < 0.05, **p < 0.01, ***p < 0.001 vs. Marginal tissues Table 4 TRPV4 expression pattern across ovarian cancer subtypes Ovarian cancer type N Relevant expression of TRPV-4 (2 −∆Ct ) MEAN ± SEM Statistical significance p-value HGSOC Marginal tissues 18 18 0.0009022 ± 0.0001475 0.002049 ± 0.0003792 s *** 0.0002 GCT Marginal tissues 8 8 0.001231 ± 0.0004301 0.002191 ± 0.0004963 ns 0.0953 MOC Marginal tissues 7 7 0.0003416 ± 3.496e-005 0.0001482 ± 1.762e-005 s ** 0.0072 EAC Marginal tissues 7 7 0.0001203 ± 2.263e-005 0.0001419 ± 3.947e-005 ns 0.7570 BSC Marginal tissues 8 8 0.001694 ± 0.0004498 0.004141 ± 0.001345 s * 0.0331 BBC Marginal tissues 6 6 4.320e-005 ± 2.154e-005 0.0001417 ± 1.431e-005 s ** 0.0097 Table 5 TRPV6 expression pattern across ovarian cancer subtypes Ovarian cancer type N Relevant expression of TRPV-6 (2 −∆Ct ) MEAN ± SEM Statistical significance p-value HGSOC Marginal tissues 18 18 0.001833 ± 0.0005841 0.001694 ± 0.0003149 ns 0.7553 GCT Marginal tissues 8 8 0.0002319 ± 0.0001016 0.0001619 ± 7.718e-005 ns 0.2429 MOC Marginal tissues 7 7 0.005999 ± 0.0002442 0.002960 ± 0.0004611 s * 0.0174 EAC Marginal tissues 7 7 0.0002663 ± 2.140e-005 0.0001070 ± 1.193e-005 s ** 0.0039 BSC Marginal tissues 8 8 6.273e-006 ± 1.014e-006 1.914e-005 ± 4.558e-006 s * 0.0139 BBC Marginal tissues 6 6 0.0007213 ± 3.625e-005 0.0001597 ± 2.417e-005 s * 0.0106 TRPV1, TRPV4, and TRPV6 protein expression patterns in epithelial ovarian cancer cell lines Moreover, we performed Western blot to study protein levels of TRPV1, TRPV4, and TRPV6 in epithelial ovarian cancer cell lines. Our results showed that TRPV1 is highly expressed in OVCAR3 cells, which is the cell line of HGSOC, compared to other epithelial ovarian cancer cell lines (Fig. 7 ). TRPV4 protein level was significantly higher in the OCAR3 cells compared to other epithelial ovarian cancer cell lines (Fig. 7 ). Besides, TRPV6 protein expression was highly expressed in the A780-S cell line compared to other cell lines of epithelial ovarian cancer (Fig. 7 ). TRPV1 , TRPV4 , and TRPV6 expression and clinicopathological characteristics in HGSOC patients Our results showed that the tumors of patients ≥ 50 years old and tumors with a size ≥ 4 cm have higher TRPV1 expression (P-value = 0.0232 and P-value = 0.0025, respectively) (Table 6 ). In addition, the tumors of patients who had bilateral ovarian involvement had higher TRPV4 expression levels (P-value = 0.0025) (Table 7 ). Also, tumors with lymphovascular invasion had increased TRPV6 expression compared with tumors without lymphovascular invasion (P-value = 0.0378) (Table 8 ). Table 6 The association between TRPV1 expression and the clinical features of HGSOC patients. Clinical features N Relevant expression of KMT2A (2 −∆Ct ) MEAN ± SEM Statistical significance p value Age (years) < 50 ≥ 50 9 9 0.01252 ± 0.001574 0.04026 ± 0.009032 s ** 0.0025 Ovarian involvement One ovary Both ovary 6 12 0.02411 ± 0.006177 0.02453 ± 0.006551 ns 0.9710 Tumor size < 4 ≥ 4 12 6 0.01004 ± 0.001644 0.03444 ± 0.009579 s * 0.0232 Stages II III IV 3 12 3 0.009524 ± 0.002641 0.03413 ± 0.007402 0.01527 ± 9.311e-005 ns 0.0609 Lymphovascular invasion Yes No 9 9 0.01396 ± 0.0008698 0.03225 ± 0.007968 ns 0.0638 Distant metastasis Yes No 4 14 0.01527 ± 9.311e-005 0.02593 ± 0.005678 ns 0.4622 Table 7 The association between TRPV4 expression and the clinical features of HGSOC patients. Clinical features N Relevant expression of KMT2A (2 −∆Ct ) MEAN ± SEM P-value Age (years) < 50 ≥ 50 9 9 0.001101 ± 0.0002098 0.0006379 ± 0.0001760 0.1233 Ovarian involvement One ovary Both ovary 6 12 0.0003767 ± 0.0001388 0.001112 ± 0.0001724 0.0199 Tumor size < 4 ≥ 4 11 7 0.0007322 ± 0.0001396 0.001129 ± 0.0002829 0.1901 Stages II III IV 3 12 3 0.0006350 ± 0.0002078 0.0009908 ± 0.0002263 0.001083 ± 0.0002786 0.5314 Lymphovascular invasion Yes No 9 9 0.001092 ± 0.0002881 0.0007601 ± 0.0001404 0.2768 Distant metastasis Yes No 4 14 0.001083 ± 0.0002786 0.0008722 ± 0.0001673 0.6300 Table 8 The association between TRPV6 expression and the clinical features of HGSOC patients. Clinical features N Relevant expression of KMT2A (2 −∆Ct ) MEAN ± SEM P-value Age (years) < 50 ≥ 50 9 9 0.001853 ± 0.0004456 0.001483 ± 0.0004527 0.5750 Ovarian involvement One ovary Both ovary 6 12 0.002150 ± 0.0004745 0.001512 ± 0.0003974 0.3737 Tumor size < 4 ≥ 4 12 6 0.001300 ± 0.0003545 0.002221 ± 0.0005362 0.1524 Stages II III IV 3 10 3 0.001562 ± 0.0007139 0.001963 ± 0.0004211 0.0008847 ± 6.232e-005 0.5176 Lymphovascular invasion Yes No 9 9 0.002436 ± 0.0004350 0.001138 ± 0.0003832 0.0378 Distant metastasis Yes No 4 14 0.0008847 ± 6.232e-005 0.001829 ± 0.0003586 0.3058 Discussion Epithelial ovarian cancer is associated with high tumor recurrence and mortality rates. Indeed, the 5-year survival rate of affected patients is about 30% ( 19 ). HGSOC is the most aggressive type of epithelial ovarian cancer that frequently develops chemoresistance, and approximately 80% of HGSOC patients experience tumor recurrence ( 3 ). Therefore, it is important to develop new biomarkers for these patients. Our study showed that TRPV1 was upregulated in HGSOC, granulosa cell tumors, mucinous ovarian carcinoma, and endometrioid adenocarcinoma. Also, tumors of patients with advanced age and larger tumors have higher TRPV1 expression. Regarding our results, it has been reported that TRPV1 expression is upregulated in epithelial ovarian cancer tissues compared to benign, borderline tumors, and normal epithelial tissues ( 20 ). In addition, it has been reported that TRPV1 expression is upregulated in tumors with advanced FIGO stage and CA125-positive patients. Also, TRPV1 expression is upregulated in breast and prostate cancers compared to normal tissues, and its expression is associated with poor prognosis ( 21 , 22 ). Morelli et al. have shown that androgen receptor and TRPV1 expression are elevated in advanced prostate cancer tissues compared to benign prostate hyperplasia ( 23 ). However, TRPV1 expression is downregulated in hepatocellular carcinoma, transitional cell carcinoma of the bladder, and renal cell carcinoma. Moreover, chromatin immunoprecipitation studies have identified TRPV1 as a unique androgen gene target in castration-resistant C4-2 prostate cancer cells ( 24 ). Besides, Zhu et. al have demonstrated that overexpression of androgen receptors is associated with increased proliferation and migration in OCAR3 and SKO3 cell lines of ovarian cancer ( 25 ). Bucak et. al have shown that cisplatin stimulates redox-sensitive TRPV1 channels and Ca 2+ influx, leading to mitochondrial and lysosomal injury, caspase 3/8/9 activation, and decreased survival of ovarian cancer cells ( 26 ). In addition, it has been shown that stimulation of TRPV1 + sensory innervation increases ovarian progression, growth, and metastasis, whereas the inhibition of TRPV1 + sensory nerves decreases tumor growth ( 27 ). Also, our results have shown that the TRPV4 expression pattern is increased in mucinous ovarian carcinoma, while it is downregulated in HGSOC, borderline serous carcinoma, and borderline Brenner carcinoma tumors compared to their non-adjacent tissues. Moreover, the tumors of patients who had bilateral ovarian involvement had higher TRPV4 expression levels. Besides, TRPV4 protein expression is higher in the OCAR3 cells, which originated from HGSOC. Thermo-sensation, mechano-sensation, nociception, shear stress control, endothelium vasomotor control, cell migration modulator, and adherents junction controller in the skin are the physiological functions of TRPV4 ( 28 ). In silico studies have shown that TRPV4 is upregulated in ovarian cancer, and this upregulation is associated with poor prognosis of affected patients. TRPV4 can interact with SH3RF3 , CHFR , ZTBI , and TRAFDI , leading to oncogenesis ( 29 ). It has been reported that SREBP1, a vital upstream transcription factor of fatty acid synthesis, is implicated in ovarian cancer development and is correlated with TRPV4 ( 30 ). TRPV4 enhances fatty acid synthesis through the mTOR/SREBP1 signaling pathway and increases the growth of ovarian cancer ( 31 ). Our results have revealed that TRPV6 is upregulated in mucinous ovarian carcinoma, endometrioid adenocarcinoma, and borderline Brenner carcinoma, while it is downregulated in borderline serous carcinoma. Besides, tumors with lymphovascular invasion have increased TRPV6 expression compared with tumors without lymphovascular invasion. Immunohistochemistry studies have shown that TRPV1 and TRPV6 are remarkably enhanced in ovarian tissues compared to non-tumoral ones ( 32 ). TRPV6 expression, both in mRNA and protein levels, is highly expressed in early and late-stage ovarian cancers ( 33 ). Our western blotting analysis has revealed that TRPV6 has the highest protein expression levels among the studied ovarian cancer cell lines; the highest protein expression level of TRPV6 is observed in the A2780S cell line, which is derived from endometroid carcinoma. Conclusion In summary, the potential role of TRP proteins as therapeutic targets in cancer has been proposed by various reports ( 34 ). The expression patterns of these channels, along with their continuous presence at the cell surface, make them a promising target in cancer treatment. These findings suggest that TRPVs may serve not only as diagnostic markers but also as potential targets for subtype specific therapeutic interventions. However, further in-depth investigation is needed to elucidate the exact molecular mechanism in ovarian cancer pathogenesis. Declarations Acknowledgments The authors would like to express their sincere gratitude to the Immunology Research Center (IRC) at Tabriz University of Medical Sciences and the Faculty of Natural Sciences at the University of Tabriz for providing the essential facilities for this study. They also extend their appreciation to the patients who participated in this research. Special thanks are given to Dr. Ali Dastranj Tabrizi, the pathologist, for his valuable contributions in evaluating the pathological features of the tumor samples and interpreting the results. Moreover, special thanks to SARA Investigation Lab and Dr. Pouran Karimi for their valuable cooperation and advice. Authors’ contributions AA and MH designed the study. AA performed the experimental work, collected and analyzed the data, and wrote the manuscript. MH and BB provided essential materials and revised the final version of the manuscript, offering technical guidance. MAH and MH supervised, directed, and managed the study. All authors reviewed and approved the final manuscript. Ethics approval and consent to participate All the experiments were conducted following the Iranian National Committee of Ethics in Biomedical Research and approved by the Bioethics Committee of Tabriz University(Approval Number: IR.TABRIZU.REC.1404.015), and Tabriz University guidelines for the laboratory projects. Conflict of interest the authors declare no conflict of interest References Siegel RL, Miller KD, Jemal A, Cancer statistics (2018) CA: a cancer journal for clinicians. 2018;68(1):7–30 Matulonis UA, Sood AK, Fallowfield L, Howitt BE, Sehouli J, Karlan BY (2016) Ovarian cancer. Nat reviews Disease primers 2(1):1–22 Lisio M-A, Fu L, Goyeneche A, Gao Z-h, Telleria C (2019) High-grade serous ovarian cancer: basic sciences, clinical and therapeutic standpoints. 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Tumor Biology 37:11147–11162 Zhu T, Yuan J, Xie Y, Li H, Wang Y (2016) Association of androgen receptor CAG repeat polymorphism and risk of epithelial ovarian cancer. Gene 575(2):743–746 Bucak M, Nazıroğlu M (2024) Cisplatin kills ovarium cancer cells through the TRPV1-mediated mitochondrial oxidative stress and apoptosis: TRPV1 inhibitor role of eicopentotaneoic acid Knarr M, Cummins K, Racordon D, Reavis H, Lippert T, Hausler R et al (2024) Abstract PR010: TRPV1 + sensory innervation as a novel driver of ovarian cancer progression. Cancer Res 84(22Supplement):PR010–PR Yu S, Huang S, Ding Y, Wang W, Wang A, Lu Y (2019) Transient receptor potential ion-channel subfamily V member 4: a potential target for cancer treatment. Cell Death Dis 10(7):497 Zhang C, Xu C, Ma C, Zhang Q, Bu S, Zhang D-L et al (2022) TRPs in ovarian serous cystadenocarcinoma: The expression patterns, prognostic roles, and potential therapeutic targets. Front Mol Biosci 9:915409 Nie L-Y, Lu Q-T, Li W-H, Yang N, Dongol S, Zhang X et al (2013) Sterol regulatory element-binding protein 1 is required for ovarian tumor growth. Oncol Rep 30(3):1346–1354 Lin L, Li X, Wu A-J, Xiu J-b, Gan Y-Z, Yang X-m et al (2023) TRPV4 enhances the synthesis of fatty acids to drive the progression of ovarian cancer through the calcium-mTORC1/SREBP1 signaling pathway. Iscience. ;26(11) Zhuang L, Peng J-B, Tou L, Takanaga H, Adam RM, Hediger MA et al (2002) Calcium-selective ion channel, CaT1, is apically localized in gastrointestinal tract epithelia and is aberrantly expressed in human malignancies. Lab Invest 82(12):1755–1764 Xue H, Wang Y, MacCormack TJ, Lutes T, Rice C, Davey M et al (2018) Inhibition of Transient Receptor Potential Vanilloid 6 channel, elevated in human ovarian cancers, reduces tumour growth in a xenograft model. J Cancer 9(17):3196 Chen J, Luan Y, Yu R, Zhang Z, Zhang J, Wang W (2014) Transient receptor potential (TRP) channels, promising potential diagnostic and therapeutic tools for cancer. Biosci Trends 8(1):1–10 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7005174","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482744612,"identity":"bf454f99-0b08-4bca-8ac0-a257cff22990","order_by":0,"name":"Aida Aghazadeh","email":"","orcid":"","institution":"University of Tabriz","correspondingAuthor":false,"prefix":"","firstName":"Aida","middleName":"","lastName":"Aghazadeh","suffix":""},{"id":482744614,"identity":"e0d16549-f98f-4c24-b02e-a4c1f1a03730","order_by":1,"name":"Mehdi Haghi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYFACHgaJxAYGBgNm5gMMjA1ALgRIEKOFLbGBeC2MIC0MPIYgLYSBbnvvwRsPd9jZbWfn+f7g5457MvIzEhg//GCwyMelxezMuWSLxDPJyTubeTc29p4p5mGckcAs2cMgYYnLRrMbOWYSiW3MyQaHeTc28LYl8DBLJDBIA/1igNOW+29AWuqBWngeNv4FamGTSGD+jVfLDR6QlsN2QC2MzSBbeCQS2PDbcibH2CKx7XiCwWE2w9myZxJ4JHgetln2GODRcvyM4c2fbdX2BucPP/j4dkeCvXx78uEbPyrqcGqBAVBswgAkmggCe8JKRsEoGAWjYMQCAMsBU8oajhheAAAAAElFTkSuQmCC","orcid":"","institution":"University of Tabriz","correspondingAuthor":true,"prefix":"","firstName":"Mehdi","middleName":"","lastName":"Haghi","suffix":""},{"id":482744615,"identity":"637ac6b7-12c4-4ed2-9a06-f925fc89cc19","order_by":2,"name":"Mohammad Ali Hosseinpour Feizi","email":"","orcid":"","institution":"University of Tabriz","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"Ali Hosseinpour","lastName":"Feizi","suffix":""},{"id":482744617,"identity":"838a019d-f645-4f10-ac02-38406e911c2f","order_by":3,"name":"Behzad Baradaran","email":"","orcid":"","institution":"Tabriz University of Medical Science","correspondingAuthor":false,"prefix":"","firstName":"Behzad","middleName":"","lastName":"Baradaran","suffix":""}],"badges":[],"createdAt":"2025-06-30 00:53:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7005174/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7005174/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86659130,"identity":"fa68e852-862a-4436-a6b6-3d7d549356fa","added_by":"auto","created_at":"2025-07-14 10:29:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":178040,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression levels of \u003cem\u003eTPRV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003ein ovarian cancer and normal ovarian tissues\u003c/p\u003e","description":"","filename":"FIG1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7005174/v1/2ad5b570ce85781669cd2098.jpg"},{"id":86656868,"identity":"a7eda404-ed65-4e00-9c04-8280245f65e0","added_by":"auto","created_at":"2025-07-14 10:21:36","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":306199,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression levels of \u003cem\u003eTPRV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003ein different grades of endometrioid ovarian cancer and serous ovarian cancer\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7005174/v1/10c538a0292b9b7aa0ef5b56.jpg"},{"id":86656873,"identity":"7b8e4851-a288-415b-8ce0-16007136af56","added_by":"auto","created_at":"2025-07-14 10:21:36","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182931,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTRPV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003eexpression levels in epithelial ovarian cancer and related ROC analysis\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7005174/v1/696e54e199f3b168c4332ef0.jpg"},{"id":86660865,"identity":"9209fe7b-f354-4264-b779-1e2d30df65b7","added_by":"auto","created_at":"2025-07-14 10:37:36","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":209278,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTRPV1\u003c/em\u003e expression pattern in different subtypes of ovarian cancer. High-grade serous carcinoma (HGSC), granulosa cell tumor (GCT), mucinous ovarian carcinoma (MOC), endometrioid adenocarcinoma (EAC), borderline serous carcinoma (BSC), and borderline Brenner carcinoma (BBC).\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7005174/v1/a903a5f913978de84b39b574.jpg"},{"id":86660866,"identity":"eed5efa4-b47a-4074-b56f-685202e55073","added_by":"auto","created_at":"2025-07-14 10:37:37","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":201427,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTRPV4\u003c/em\u003e expression pattern in 6 different subtypes of ovarian cancer. High-grade serous carcinoma (HGSC), granulosa cell tumor (GCT), mucinous ovarian carcinoma (MOC), endometrioid adenocarcinoma (EAC), borderline serous carcinoma (BSC), and borderline Brenner carcinoma (BBC).\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7005174/v1/dd7101b3c858c42673805c8a.jpg"},{"id":86656883,"identity":"0cdae8c0-38d0-4de2-9045-ef64c96541bf","added_by":"auto","created_at":"2025-07-14 10:21:37","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":206740,"visible":true,"origin":"","legend":"\u003cp\u003eTRPV6 expression pattern in 6 different subtypes of ovarian cancer. High-grade serous carcinoma (HGSC), granulosa cell tumor (GCT), mucinous ovarian carcinoma (MOC), endometrioid adenocarcinoma (EAC), borderline serous carcinoma (BSC), and borderline Brenner carcinoma (BBC).\u003c/p\u003e","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7005174/v1/14c790474da29345a2be1158.jpg"},{"id":86656892,"identity":"43e1b346-d656-47c5-8368-fd7c0088f9cb","added_by":"auto","created_at":"2025-07-14 10:21:37","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":123384,"visible":true,"origin":"","legend":"\u003cp\u003eTRPV1, TRPV4, and TRPV6 protein expression pattern in different cell lines of ovarian cancer\u003c/p\u003e","description":"","filename":"Fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7005174/v1/2bebb85cc106c95fc7336004.jpg"},{"id":86863050,"identity":"5491312e-bd44-4edc-95fa-7314657c2911","added_by":"auto","created_at":"2025-07-16 12:38:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2607455,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7005174/v1/80d1857d-a731-45ed-b2a9-da31f01f0347.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Differential expression of TRPV1, TRPV4, and TRPV6 across ovarian cancer subtypes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian cancer is known as one of the lethal gynecological malignancies, which is mostly diagnosed in advanced stages (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Epithelial ovarian cancers constitute almost 90% of ovarian cancers (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), and they are divided into five main types: high-grade serous, low-grade serous, mucinous, endometrioid, and clear cell carcinoma. In contrast, non-epithelial ovarian cancers originate from germ cells or sex-cord-stromal tissues (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Preceding research has indicated that ovarian cancer originates from fallopian tubes rather than the ovary, as was thought before (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Based on molecular genetics data, ovarian cancer can be divided into two main groups, i.e., type I and type II tumors. Type I tumors include low-grade serous, low-grade endometrioid, mucinous, and clear cell carcinomas, while type II tumors are high-grade serous ovarian cancer (HGSOC), high-grade endometroid, malignant-mixed mesodermal, and undifferentiated tumors (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Type I tumors are characterized by large cystic masses that are restricted to one ovary. The mutations in \u003cem\u003eKRAS\u003c/em\u003e, \u003cem\u003eBRAF\u003c/em\u003e, PIK3CA, \u003cem\u003ePTEN\u003c/em\u003e, \u003cem\u003eARID1A\u003c/em\u003e, \u003cem\u003eCTNNB1\u003c/em\u003e, and \u003cem\u003ePPP2R1A\u003c/em\u003e are responsible for developing type I tumors (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Type II tumors are characterized by chromosomal abnormalities. HGSOC is the most prevalent and invasive form of type II tumors (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The available screening methods, including pelvic examination, serum CA-125 level, and transvaginal ultrasound, have limited significance in the diagnosis of HGSOC in its early stage (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Therefore, there is an urgent need to identify potential biomarkers for this cancer (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Calcium is a key second messenger that mediates the signal transduction essential for cell proliferation, migration, and apoptosis (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). It has been reported that dysregulation of plasma and organelle-based Ca\u003csup\u003e2+\u003c/sup\u003e signaling pathways is implicated in ovarian tumor development (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Ca\u003csup\u003e2+\u003c/sup\u003e influx mediated by intracellular Ca\u003csup\u003e2+\u003c/sup\u003e channels can lead to the transition from G1/S to mitosis phase in the cell cycle; however, Ca\u003csup\u003e2+\u003c/sup\u003e deficiency arrests the cell cycle at G0/G1 and S phase (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Transient receptor potential (TRP) channels are a group of non-selective cell membrane channels that permit Ca\u003csup\u003e2+\u003c/sup\u003e to pass through. Based on the analogy of their amino acid sequences, these channels are classified into 7 groups. TRP canonical (TRPC), TRP vanilloid (TRPV), TRP mestatin (TRPM), TRP polycystic protein (TRPPP), TRP mucin (TRPML), TRP anchor protein (TRPA), and TRP no mechanoreceptor potential C (TRPCN). The activation of the TRP channels temporarily increases intracellular Ca\u003csup\u003e2+\u003c/sup\u003e levels, highlighting the significance of TRP channels as important components of Ca\u003csup\u003e2+\u003c/sup\u003e signaling pathways (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Consistent with these, growing studies have investigated the role of TRP channels in Ca\u003csup\u003e2+\u003c/sup\u003e-mediated signaling pathways and cancer development. Also, TRP channels have been identified as prognostic and therapeutic targets in various cancers (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In this regard, we aimed to study the expression patterns of \u003cem\u003eTRPV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003e in the different subtypes of ovarian cancers. The results of this study can provide valuable data for further elucidating the molecular mechanisms of ovarian cancer pathogenesis.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003e\u003cb\u003eTissue preparation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe samples were obtained from patients at Alzahra Hospital, the teaching hospital affiliated with Tabriz University of Medical Sciences, Tabriz, Iran. The obtained samples were immediately frozen in liquid nitrogen and stored at -80\u0026deg;C for later use. The histopathological results were confirmed in the subsequent step by an experienced pathologist.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCell culture\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFive epithelial ovarian cancer cell lines, i.e., OCAR3, SKO3, 2008/C13, A2780-cp, and A2780S, were obtained from the Pasteur Institute in Tehran, Iran. All cells were cultured in RPMI-1640 medium, supplemented with 10% fetal bovine serum (FBS) (Gibco,00282508), and 1% antibiotics (penicillin at 100 U/ml and streptomycin at 100 \u0026micro;g/ml) (Gibco3810-74-0, Grand Island, NY 14072, USA). A humidified incubator at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e was used to incubate cells. The assays were performed in the logarithmic phase of cell growth.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA extraction and qRT-PCR\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal RNA was extracted from tissues and cell lines using the TRI-zol\u0026trade; Reagent following the manufacturer\u0026rsquo;s protocol. All equipment was RNase-free, and homogenizers were treated with 1% DEPC water for 24 hours and then autoclaved. The quality and concentration of the extracted RNA were assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific Life Science, Waltham, MA) by calculating absorbance ratios (A260/A280 and A260/A230); all RNA samples had 260/280 nm\u0026thinsp;\u0026ge;\u0026thinsp;1.8. The integrity assessment of the extracted RNA was determined via 2% agarose gel electrophoresis. Complementary DNA (cDNA) was synthesized from total RNA using a cDNA synthesis kit (SMOBIO, Taiwan) in a thermal cycler (Bio-Rad). The mRNA expression levels of \u003cem\u003eTRPV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003e were evaluated using qRT-PCR (Applied Biosystems, USA) and SYBR Green MasterMix (Amplicon, Odense, Denmark). All tests were performed in triplicate, and the samples were normalized to the expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as the internal control. The primer sequences are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:\\varDelta\\:qc\\:\\)\u003c/span\u003e\u003c/span\u003emethod was used to calculate the relative expression changes.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe expression of TRPV1, TRPV4, and TRPV6 genes in ovarian cancer\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSample type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelevant expression (2\u003csup\u003e\u0026minus;∆Ct\u003c/sup\u003e) MEAN\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStatistical significance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTRPV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTumor\u003c/p\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.01546\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002852\u003c/p\u003e\u003cp\u003e0.01244\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1233\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTRPV4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTumor\u003c/p\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0009747\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001465\u003c/p\u003e\u003cp\u003e0.002109\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003528\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003es\u003csup\u003e****\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTRPV6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTumor\u003c/p\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001269\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003311\u003c/p\u003e\u003cp\u003e0.0009668\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001942\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1715\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eWestern blotting\u003c/b\u003e\u003c/p\u003e\u003cp\u003e500 mg of tissue and 10\u003csup\u003e6\u003c/sup\u003e cells were homogenized in 500 mg of RIPA lysis buffer containing (0/05 mmol/L Tris (pH 8), 150 mmol/L NaCl, 1% EGTA, 1% SDS, and 1% anti-protease cocktail containing PMSF (Roche) was used to extract total proteins. The lysed cells and tissue suspensions were vortexed for 15 seconds and incubated on ice for 10 minutes. Consequently, the suspensions were centrifuged at 12,000 rpm and 4\u0026deg;C for 10 minutes (Eppendorf 5415 R). Protein concentration was determined using the Bio-Rad Protein Assay kit, measuring absorbance at 595 nm. Afterward, the samples were diluted in a 1:1 ratio in loading sample buffer (50mmol Tris, pH 6.8, 2% SDS, 10% glycerol, 5% β-mercaptoethanol, 0/005 bromophenol blue) to detect protein expression. Samples were separated on a 10% polyacrylamide gel at 150 V and transferred onto a polyvinylidene difluoride (PVDF; Roche Diagnostics) membrane for 2 hours at 90 V. PVDF membranes were incubated with blocking buffer (3% BSA in TBSI) for 2 hours. After blocking, the membranes were treated overnight at 4\u0026deg;C with monoclonal antibodies against TRPV1 (E-8 cat.no: Sc- 398417) (Santa Cruz Biotechnology, INC) TRPV4 (ab39260, Abcam), TRPV6 (CAT-1 (2B9) cat.no: Sc-293226) as well as β-actin (C4: cat no: Sc-47778) as the internal control protein. The membranes were then washed and incubated with an anti-rabbit secondary antibody (IgG-HRP; cat. no. sc-2357, BP-HRP; cat. no. sc-516102) conjugated with horseradish peroxidase (1:5000; diluted in phosphate-buffered saline (PBS)) at room temperature for 1 hour on a shaker. Protein bands were detected using an electrochemiluminescence kit (Roche Diagnostics) and analyzed with a western blot imaging system (Sabz Co., Urmia, Iran). Band intensity was then measured with ImageJ software (NIH, Bethesda, MD).\u003c/p\u003e\u003cp\u003e\u003cb\u003eIn silico\u003c/b\u003e \u003cb\u003estudy\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe Gene Expression Omnibus (GEO) database was searched to choose a dataset investigating mRNA expression in different ovarian cancer types. For this purpose, the GSE6008 database was selected; this microarray dataset used Affymetrix Human Genome U133A Array to study mRNA expression in 37 endometrioid, 41 serous, 13 mucinous, and 8 clear cell carcinomas and 4 normal ovary samples. We used R software (version 4.5) to normalize the expression values; then the expression values of \u003cem\u003eTRPV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003e were analyzed in the different studied groups.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eTRPV1\u003c/strong\u003e, \u003cstrong\u003eTRPV4\u003c/strong\u003e, \u003cstrong\u003eand\u003c/strong\u003e \u003cstrong\u003eTRPV6\u003c/strong\u003e \u003cstrong\u003eexpression in normal and different types of ovarian cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur \u003cem\u003ein-silico\u003c/em\u003e studies have shown that there is no statistically significant difference in \u003cem\u003eTRPV1\u003c/em\u003e expression between clear cell ovarian cancer, endometrioid ovarian cancer, mucinous ovarian cancer, serous ovarian cancer, and normal ovarian tissues (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). However, clear cell ovarian cancer tissues have higher \u003cem\u003eTRPV4\u003c/em\u003e expression levels compared to endometrioid ovarian cancer, serous ovarian cancer and normal ovarian tissues (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB). In addition, endometrioid ovarian cancer tissues have higher expression levels of \u003cem\u003eTRPV6\u003c/em\u003e compared to serous ovarian cancer tissues (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTRPV1\u003c/strong\u003e, \u003cstrong\u003eTRPV4\u003c/strong\u003e, \u003cstrong\u003eand\u003c/strong\u003e \u003cstrong\u003eTRPV6\u003c/strong\u003e \u003cstrong\u003eexpression in different tumor grades of endometrioid ovarian cancer and serous ovarian cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur \u003cem\u003ein-silico\u003c/em\u003e results have shown that there is no significant difference in \u003cem\u003eTRPV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003e expression levels in different grades of endometrioid ovarian tissues (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). In addition, there is no significant difference between grade 2 and grade 3 of serous ovarian cancer in terms of \u003cem\u003eTRPV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003e expression (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD-F).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTRPV1\u003c/strong\u003e, \u003cstrong\u003eTRPV4\u003c/strong\u003e, \u003cstrong\u003eand\u003c/strong\u003e \u003cstrong\u003eTRPV6\u003c/strong\u003e \u003cstrong\u003eexpression patterns and potential biomarkers in ovarian cancer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on pathological findings, the 54 pairs of collected ovarian tissues were categorized into the following subtypes: 18 pairs (33.33%) of HGSOC, 8 pairs (14.81%) of granulosa cell tumor, 7 pairs (12.9%) of mucinous ovarian carcinoma, 7 pairs (12.9%) of endometrioid adenocarcinoma, 8 pairs (14.81%) of borderline serous carcinoma, and 6 pairs (11.11%) of borderline Brenner carcinoma. The mRNA expression results have shown that \u003cem\u003eTRPV4\u003c/em\u003e expression was significantly downregulated in tumoral tissues compared to non-tumoral ones (P-value \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lt;\\:\\)\u003c/span\u003e\u003c/span\u003e0.0001) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). However, there was no statistically significant difference in \u003cem\u003eTRPV1\u003c/em\u003e and \u003cem\u003eTRPV6\u003c/em\u003e expression between tumoral and normal tissues (P-value \u0026gt;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). After validating the downregulation of \u003cem\u003eTRPV4\u003c/em\u003e in ovarian tumor tissues, the ROC analysis has shown a weak diagnostic significance for ovarian tumors (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe statistical analysis of the ROC curve for TRPV1, TRPV4, and TRPV6 genes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eThe area under the ROC curve\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCutoff score\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStd. error\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% confidence interval\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTRPV1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.009075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4196\u0026ndash;0.6533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5382\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTRPV4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60.42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.001145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4945\u0026ndash;0.7304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTRPV1\u003c/strong\u003e, \u003cstrong\u003eTRPV4\u003c/strong\u003e, \u003cstrong\u003eand\u003c/strong\u003e \u003cstrong\u003eTRPV6\u003c/strong\u003e \u003cstrong\u003emRNA expression in different subtypes of ovarian cancers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe then studied the mRNA expression patterns of \u003cem\u003eTRPV1\u003c/em\u003e, \u003cem\u003eTRPV4\u003c/em\u003e, and \u003cem\u003eTRPV6\u003c/em\u003e in different ovarian tumor subtypes and their corresponding adjacent non-tumoral tissue. Our results have shown that \u003cem\u003eTRPV1\u003c/em\u003e expression level was significantly upregulated in HGSOC (P-value\u0026thinsp;=\u0026thinsp;0.0085), mucinous ovarian carcinoma (P-value\u0026thinsp;=\u0026thinsp;0.0005), and endometrioid adenocarcinoma (P-value\u0026thinsp;=\u0026thinsp;0.0290) compared to their corresponding adjacent non-tumoral tissues. However, \u003cem\u003eTRPV1\u003c/em\u003e expression was significantly downregulated in granulosa cell tumors (P-value\u0026thinsp;=\u0026thinsp;0.0018). There was no significant difference in the expression of \u003cem\u003eTRPV1\u003c/em\u003e in borderline serous carcinoma and borderline Brenner carcinoma tissues in comparison to relevant non-tumoral tissues (P-values\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e)(Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In addition, \u003cem\u003eTRPV4\u003c/em\u003e expression level was significantly upregulated in mucinous ovarian carcinoma compared to their adjacent non-tumoral tissues (P-value\u0026thinsp;=\u0026thinsp;0.0072). In contrast, \u003cem\u003eTRPV4\u003c/em\u003e expression level was downregulated in HGSOC (P-value\u0026thinsp;=\u0026thinsp;0.0002), borderline serous carcinoma (P-value\u0026thinsp;=\u0026thinsp;0.0331), and borderline Brenner carcinoma tissues (P-value\u0026thinsp;=\u0026thinsp;0.0097) compared to their corresponding adjacent tissues. \u003cem\u003eTRPV4\u003c/em\u003e expression level had no significant differences in granulosa cell tumor and endometrioid adenocarcinoma compared to their relevant non-tumoral tissues (P-values\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Furthermore, \u003cem\u003eTRPV6\u003c/em\u003e expression was significantly increased in mucinous ovarian carcinoma (P-value\u0026thinsp;=\u0026thinsp;0.0174), endometrioid adenocarcinoma (P-value\u0026thinsp;=\u0026thinsp;0.0039), and borderline Brenner carcinoma (P-value\u0026thinsp;=\u0026thinsp;0.0106) tissues; whereas \u003cem\u003eTRPV6\u003c/em\u003e expression was significantly downregulated in borderline serous carcinoma (P-value\u0026thinsp;=\u0026thinsp;0.0139). Besides, no significant differences were observed in HGSOC and granulosa cell tumor tissues compared to corresponding non-tumoral tissues (P-values\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e)(Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTRPV1 expression pattern across ovarian cancer subtypes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOvarian cancer type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRelevant expression of TRPV-1 (2\u003csup\u003e\u0026minus;∆Ct\u003c/sup\u003e) MEAN\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStatistical significance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHGSOC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02441\u0026thinsp;\u0026plusmn;\u0026thinsp;0.004918\u003c/p\u003e\n \u003cp\u003e0.01469\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGCT\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003755\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001018\u003c/p\u003e\n \u003cp\u003e0.01422\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMOC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01521\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004868\u003c/p\u003e\n \u003cp\u003e0.004483\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0006511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEAC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002299\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002604\u003c/p\u003e\n \u003cp\u003e0.0005903\u0026thinsp;\u0026plusmn;\u0026thinsp;4.106e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0290\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBSC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001419\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003175\u003c/p\u003e\n \u003cp\u003e0.001732\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0006335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4249\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBBC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04343\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009567\u003c/p\u003e\n \u003cp\u003e0.04325\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9853\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eN: number SEM: standard error of mean s: significant ns: non-significant\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003esignificance: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 vs. Marginal tissues\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTRPV4 expression pattern across ovarian cancer subtypes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOvarian cancer type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRelevant expression of TRPV-4 (2\u003csup\u003e\u0026minus;∆Ct\u003c/sup\u003e) MEAN\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStatistical significance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHGSOC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0009022\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001475\u003c/p\u003e\n \u003cp\u003e0.002049\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGCT\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001231\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004301\u003c/p\u003e\n \u003cp\u003e0.002191\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0953\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMOC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0003416\u0026thinsp;\u0026plusmn;\u0026thinsp;3.496e-005\u003c/p\u003e\n \u003cp\u003e0.0001482\u0026thinsp;\u0026plusmn;\u0026thinsp;1.762e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEAC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0001203\u0026thinsp;\u0026plusmn;\u0026thinsp;2.263e-005\u003c/p\u003e\n \u003cp\u003e0.0001419\u0026thinsp;\u0026plusmn;\u0026thinsp;3.947e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7570\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBSC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001694\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004498\u003c/p\u003e\n \u003cp\u003e0.004141\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0331\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBBC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.320e-005\u0026thinsp;\u0026plusmn;\u0026thinsp;2.154e-005\u003c/p\u003e\n \u003cp\u003e0.0001417\u0026thinsp;\u0026plusmn;\u0026thinsp;1.431e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTRPV6 expression pattern across ovarian cancer subtypes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOvarian cancer type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRelevant expression of TRPV-6 (2\u003csup\u003e\u0026minus;∆Ct\u003c/sup\u003e) MEAN\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStatistical significance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHGSOC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001833\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0005841\u003c/p\u003e\n \u003cp\u003e0.001694\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7553\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGCT\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0002319\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001016\u003c/p\u003e\n \u003cp\u003e0.0001619\u0026thinsp;\u0026plusmn;\u0026thinsp;7.718e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2429\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMOC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.005999\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002442\u003c/p\u003e\n \u003cp\u003e0.002960\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEAC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0002663\u0026thinsp;\u0026plusmn;\u0026thinsp;2.140e-005\u003c/p\u003e\n \u003cp\u003e0.0001070\u0026thinsp;\u0026plusmn;\u0026thinsp;1.193e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBSC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.273e-006\u0026thinsp;\u0026plusmn;\u0026thinsp;1.014e-006\u003c/p\u003e\n \u003cp\u003e1.914e-005\u0026thinsp;\u0026plusmn;\u0026thinsp;4.558e-006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBBC\u003c/p\u003e\n \u003cp\u003eMarginal tissues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0007213\u0026thinsp;\u0026plusmn;\u0026thinsp;3.625e-005\u003c/p\u003e\n \u003cp\u003e0.0001597\u0026thinsp;\u0026plusmn;\u0026thinsp;2.417e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0106\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTRPV1, TRPV4, and TRPV6 protein expression patterns in epithelial ovarian cancer cell lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMoreover, we performed Western blot to study protein levels of TRPV1, TRPV4, and TRPV6 in epithelial ovarian cancer cell lines. Our results showed that TRPV1 is highly expressed in OVCAR3 cells, which is the cell line of HGSOC, compared to other epithelial ovarian cancer cell lines (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). TRPV4 protein level was significantly higher in the OCAR3 cells compared to other epithelial ovarian cancer cell lines (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). Besides, TRPV6 protein expression was highly expressed in the A780-S cell line compared to other cell lines of epithelial ovarian cancer (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTRPV1\u003c/strong\u003e, \u003cstrong\u003eTRPV4\u003c/strong\u003e, \u003cstrong\u003eand\u003c/strong\u003e \u003cstrong\u003eTRPV6\u003c/strong\u003e \u003cstrong\u003eexpression and clinicopathological characteristics in HGSOC patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur results showed that the tumors of patients\u0026thinsp;\u0026ge;\u0026thinsp;50 years old and tumors with a size\u0026thinsp;\u0026ge;\u0026thinsp;4 cm have higher \u003cem\u003eTRPV1\u003c/em\u003e expression (P-value\u0026thinsp;=\u0026thinsp;0.0232 and P-value\u0026thinsp;=\u0026thinsp;0.0025, respectively) (Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). In addition, the tumors of patients who had bilateral ovarian involvement had higher \u003cem\u003eTRPV4\u003c/em\u003e expression levels (P-value\u0026thinsp;=\u0026thinsp;0.0025) (Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). Also, tumors with lymphovascular invasion had increased \u003cem\u003eTRPV6\u003c/em\u003e expression compared with tumors without lymphovascular invasion (P-value\u0026thinsp;=\u0026thinsp;0.0378) (Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\n\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe association between \u003cem\u003eTRPV1\u003c/em\u003e expression and the clinical features of HGSOC patients.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClinical features\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRelevant expression of KMT2A (2\u003csup\u003e\u0026minus;∆Ct\u003c/sup\u003e) MEAN\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStatistical significance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.01252\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001574\u003c/p\u003e\n \u003cp\u003e0.04026\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOvarian involvement\u003c/p\u003e\n \u003cp\u003eOne ovary\u003c/p\u003e\n \u003cp\u003eBoth ovary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.02411\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006177\u003c/p\u003e\n \u003cp\u003e0.02453\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;4\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.01004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001644\u003c/p\u003e\n \u003cp\u003e0.03444\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0232\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStages\u003c/p\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.009524\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002641\u003c/p\u003e\n \u003cp\u003e0.03413\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007402\u003c/p\u003e\n \u003cp\u003e0.01527\u0026thinsp;\u0026plusmn;\u0026thinsp;9.311e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0609\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymphovascular invasion\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.01396\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0008698\u003c/p\u003e\n \u003cp\u003e0.03225\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0638\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDistant metastasis\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.01527\u0026thinsp;\u0026plusmn;\u0026thinsp;9.311e-005\u003c/p\u003e\n \u003cp\u003e0.02593\u0026thinsp;\u0026plusmn;\u0026thinsp;0.005678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4622\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe association between \u003cem\u003eTRPV4\u003c/em\u003e expression and the clinical features of HGSOC patients.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClinical features\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRelevant expression of KMT2A (2\u003csup\u003e\u0026minus;∆Ct\u003c/sup\u003e) MEAN\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.001101\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002098\u003c/p\u003e\n \u003cp\u003e0.0006379\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1233\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOvarian involvement\u003c/p\u003e\n \u003cp\u003eOne ovary\u003c/p\u003e\n \u003cp\u003eBoth ovary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.0003767\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001388\u003c/p\u003e\n \u003cp\u003e0.001112\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0199\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;4\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.0007322\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001396\u003c/p\u003e\n \u003cp\u003e0.001129\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStages\u003c/p\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.0006350\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002078\u003c/p\u003e\n \u003cp\u003e0.0009908\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002263\u003c/p\u003e\n \u003cp\u003e0.001083\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5314\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymphovascular invasion\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.001092\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002881\u003c/p\u003e\n \u003cp\u003e0.0007601\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2768\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDistant metastasis\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.001083\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002786\u003c/p\u003e\n \u003cp\u003e0.0008722\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6300\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe association between \u003cem\u003eTRPV6\u003c/em\u003e expression and the clinical features of HGSOC patients.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClinical features\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRelevant expression of KMT2A (2\u003csup\u003e\u0026minus;∆Ct\u003c/sup\u003e) MEAN\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.001853\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004456\u003c/p\u003e\n \u003cp\u003e0.001483\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5750\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOvarian involvement\u003c/p\u003e\n \u003cp\u003eOne ovary\u003c/p\u003e\n \u003cp\u003eBoth ovary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.002150\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004745\u003c/p\u003e\n \u003cp\u003e0.001512\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3737\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;4\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.001300\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003545\u003c/p\u003e\n \u003cp\u003e0.002221\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0005362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1524\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStages\u003c/p\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.001562\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0007139\u003c/p\u003e\n \u003cp\u003e0.001963\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004211\u003c/p\u003e\n \u003cp\u003e0.0008847\u0026thinsp;\u0026plusmn;\u0026thinsp;6.232e-005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymphovascular invasion\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.002436\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004350\u003c/p\u003e\n \u003cp\u003e0.001138\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0378\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDistant metastasis\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e0.0008847\u0026thinsp;\u0026plusmn;\u0026thinsp;6.232e-005\u003c/p\u003e\n \u003cp\u003e0.001829\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0003586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eEpithelial ovarian cancer is associated with high tumor recurrence and mortality rates. Indeed, the 5-year survival rate of affected patients is about 30% (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). HGSOC is the most aggressive type of epithelial ovarian cancer that frequently develops chemoresistance, and approximately 80% of HGSOC patients experience tumor recurrence (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Therefore, it is important to develop new biomarkers for these patients.\u003c/p\u003e\u003cp\u003eOur study showed that \u003cem\u003eTRPV1\u003c/em\u003e was upregulated in HGSOC, granulosa cell tumors, mucinous ovarian carcinoma, and endometrioid adenocarcinoma. Also, tumors of patients with advanced age and larger tumors have higher \u003cem\u003eTRPV1\u003c/em\u003e expression. Regarding our results, it has been reported that \u003cem\u003eTRPV1\u003c/em\u003e expression is upregulated in epithelial ovarian cancer tissues compared to benign, borderline tumors, and normal epithelial tissues (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In addition, it has been reported that \u003cem\u003eTRPV1\u003c/em\u003e expression is upregulated in tumors with advanced FIGO stage and CA125-positive patients. Also, \u003cem\u003eTRPV1\u003c/em\u003e expression is upregulated in breast and prostate cancers compared to normal tissues, and its expression is associated with poor prognosis (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Morelli et al. have shown that androgen receptor and TRPV1 expression are elevated in advanced prostate cancer tissues compared to benign prostate hyperplasia (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). However, \u003cem\u003eTRPV1\u003c/em\u003e expression is downregulated in hepatocellular carcinoma, transitional cell carcinoma of the bladder, and renal cell carcinoma. Moreover, chromatin immunoprecipitation studies have identified TRPV1 as a unique androgen gene target in castration-resistant C4-2 prostate cancer cells (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Besides, Zhu et. al have demonstrated that overexpression of androgen receptors is associated with increased proliferation and migration in OCAR3 and SKO3 cell lines of ovarian cancer (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Bucak et. al have shown that cisplatin stimulates redox-sensitive TRPV1 channels and Ca\u003csup\u003e2+\u003c/sup\u003e influx, leading to mitochondrial and lysosomal injury, caspase 3/8/9 activation, and decreased survival of ovarian cancer cells (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In addition, it has been shown that stimulation of TRPV1\u003csup\u003e+\u003c/sup\u003e sensory innervation increases ovarian progression, growth, and metastasis, whereas the inhibition of TRPV1\u003csup\u003e+\u003c/sup\u003e sensory nerves decreases tumor growth (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlso, our results have shown that the TRPV4 expression pattern is increased in mucinous ovarian carcinoma, while it is downregulated in HGSOC, borderline serous carcinoma, and borderline Brenner carcinoma tumors compared to their non-adjacent tissues. Moreover, the tumors of patients who had bilateral ovarian involvement had higher \u003cem\u003eTRPV4\u003c/em\u003e expression levels. Besides, TRPV4 protein expression is higher in the OCAR3 cells, which originated from HGSOC. Thermo-sensation, mechano-sensation, nociception, shear stress control, endothelium vasomotor control, cell migration modulator, and adherents junction controller in the skin are the physiological functions of TRPV4 (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). \u003cem\u003eIn silico\u003c/em\u003e studies have shown that TRPV4 is upregulated in ovarian cancer, and this upregulation is associated with poor prognosis of affected patients. TRPV4 can interact with \u003cem\u003eSH3RF3\u003c/em\u003e, \u003cem\u003eCHFR\u003c/em\u003e, \u003cem\u003eZTBI\u003c/em\u003e, and \u003cem\u003eTRAFDI\u003c/em\u003e, leading to oncogenesis (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). It has been reported that SREBP1, a vital upstream transcription factor of fatty acid synthesis, is implicated in ovarian cancer development and is correlated with TRPV4 (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). TRPV4 enhances fatty acid synthesis through the mTOR/SREBP1 signaling pathway and increases the growth of ovarian cancer (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur results have revealed that TRPV6 is upregulated in mucinous ovarian carcinoma, endometrioid adenocarcinoma, and borderline Brenner carcinoma, while it is downregulated in borderline serous carcinoma. Besides, tumors with lymphovascular invasion have increased \u003cem\u003eTRPV6\u003c/em\u003e expression compared with tumors without lymphovascular invasion. Immunohistochemistry studies have shown that TRPV1 and TRPV6 are remarkably enhanced in ovarian tissues compared to non-tumoral ones (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). TRPV6 expression, both in mRNA and protein levels, is highly expressed in early and late-stage ovarian cancers (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Our western blotting analysis has revealed that TRPV6 has the highest protein expression levels among the studied ovarian cancer cell lines; the highest protein expression level of TRPV6 is observed in the A2780S cell line, which is derived from endometroid carcinoma.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, the potential role of TRP proteins as therapeutic targets in cancer has been proposed by various reports (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). The expression patterns of these channels, along with their continuous presence at the cell surface, make them a promising target in cancer treatment. These findings suggest that TRPVs may serve not only as diagnostic markers but also as potential targets for subtype specific therapeutic interventions. However, further in-depth investigation is needed to elucidate the exact molecular mechanism in ovarian cancer pathogenesis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to the Immunology Research Center (IRC) at Tabriz University of Medical Sciences and the Faculty of Natural Sciences at the University of Tabriz for providing the essential facilities for this study. They also extend their appreciation to the patients who participated in this research. Special thanks are given to Dr. Ali Dastranj Tabrizi, the pathologist, for his valuable contributions in evaluating the pathological features of the tumor samples and interpreting the results. Moreover, special thanks to SARA Investigation Lab and Dr. Pouran Karimi for their valuable cooperation and advice.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAA and MH designed the study. AA performed the experimental work, collected and analyzed the data, and wrote the manuscript. MH and BB provided essential materials and revised the final version of the manuscript, offering technical guidance. MAH and MH supervised, directed, and managed the study. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the experiments were conducted following the Iranian National Committee of Ethics in Biomedical Research and approved by the Bioethics Committee of Tabriz University(Approval Number: IR.TABRIZU.REC.1404.015), and Tabriz University guidelines for the laboratory projects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ethe authors declare no conflict of interest\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSiegel RL, Miller KD, Jemal A, Cancer statistics (2018) CA: a cancer journal for clinicians. 2018;68(1):7\u0026ndash;30\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMatulonis UA, Sood AK, Fallowfield L, Howitt BE, Sehouli J, Karlan BY (2016) Ovarian cancer. 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Biosci Trends 8(1):1\u0026ndash;10\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"TRPV1, TRPV4, TRPV6, Ovarian cancer, biomarkers, high-grade serous, mucinous, calcium signaling","lastPublishedDoi":"10.21203/rs.3.rs-7005174/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7005174/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eOvarian cancer known as a heterogenous and lethal gynecological malignancies often identified at early stages. Emerging evidences suggest that Ca\u003csup\u003e2+\u003c/sup\u003e-permeable transient receptor potential (TRP) channels play pivotal roles in cancer progression. TRPV1, TRPV4 and TRPV6 have been indicated in various tumorigenic processes, still their subtype specific expression and clinical relevance in ovarian cancer remain unclear.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003ewe investigated the expression patterns of TRPV1, TRPV4 and TRPV6 in ovarian cancer via integrative analyses. Publicly available microarray datasets were used for in silico comparison between subtypes of ovarian cancer and normal tissues. Expression levels were validated using qRT-PCR and western blotting samples representing high-grade serous, mucinous, endometroid and clear cell carcinoma subtypes. Clinical correlations were evaluated using data from the the GSE6008 database, Affymetrix Human Genome U133A Array database.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eTRPV1 was significantly up-regulated in high-grade serous, mucinous, and endometrioid ovarian carcinomas. TRPV4 showed elevated expression in mucinous carcinoma but it showed markable down-regulation in both high-grade serous and endometroid subtypes. TRPV6 expression was significantly elevated in mucinous and endometrioid carcinomas. ROC curve analysis showed significance diagnostic potential. increased levels of TRPV1 and TRPV4 expression were associated with improved overall survival in high-grade serous carcinoma patients.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eour results reveal distinct, subtypes specific expression patterns of TRPV1, TRPV4 and TRPV6 in ovarian cancer, undercovering their potential as diagnostic biomarkers and therapeutic targets. These findings promote the further investigation of TRP channels in the context of personalized treatment strategies for ovarian cancer patients.\u003c/p\u003e","manuscriptTitle":"Differential expression of TRPV1, TRPV4, and TRPV6 across ovarian cancer subtypes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 10:21:31","doi":"10.21203/rs.3.rs-7005174/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4675fc8c-656b-4d79-b283-089fed0ad7b3","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-16T12:38:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-14 10:21:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7005174","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7005174","identity":"rs-7005174","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}