Research ArticleArticles
Open Access

MiR-575 in Exosomes of Vaginal Discharge Is Downregulated in Ovarian Cancer Patients

MAHO AZUMI, SACHIKO INUBUSHI, YOKO YANO, KENTA OBATA, KEITARO YAMANAKA and YOSHITO TERAI
Cancer Genomics & Proteomics May 2025, 22 (3) 382-396; DOI: https://doi.org/10.21873/cgp.20508

Abstract

Background/Aim: Ovarian cancer is asymptomatic in its early stages, and often diagnosed at advanced stages, leading to a high recurrence rate. In recent years, exosomes have been shown to be useful for early-detection, prognosis prediction, and treatment of cancer. Although many studies of cancer-related exosomes using other bodily fluids have been reported, there are few studies examining vaginal discharge, but none related to ovarian cancer. In this study, we investigated a method for early-detection of ovarian cancer using vaginal discharge, which are physically close to the fallopian tubes, where ovarian cancer originates, and can be easily collected from outside the body.

Materials and Methods: Vaginal discharge was collected from 30 patients with ovarian cancer and 29 patients with benign gynecological diseases, and exosomal miRNAs were extracted. Samples from each group were submitted to miRNA microarray in order to examine miRNAs with significant differences in expression levels. We further narrowed down the list to four miRNAs based on literature and microarray data and examined the expression levels of miRNAs in the malignant and benign groups by RT-qPCR.

Results: MiR-575 expression was significantly decreased in the malignant group compared to the benign group (p=0.00861). qPCR results were analyzed for several patient characteristics and no significant differences were found.

Conclusion: This is the first study to investigate exosomal miRNAs in vaginal discharge of ovarian cancer. Exosomal miR-575 in vaginal discharge may be used as a biomarker for ovarian cancer.

Keywords:

Introduction

Epithelial ovarian cancer is the second leading cause of death among gynecological cancers. A total of 310,000 people worldwide is affected and 210,000 people die from the disease annually. Early detection is difficult, and approximately 75% of cases are diagnosed at an advanced stage, thus making treatment difficult (1).

CA125 is often used as a tumor marker for ovarian cancer, but it can also be elevated in benign diseases such as endometriosis, pregnancy, and liver disease, and is not a specific marker for ovarian cancer, so it has a high false-positive rate (2). In addition, CA125 is often normal in early-stage ovarian cancer, so it is difficult to use for early diagnosis (2). HE4 is said to have high specificity for ovarian cancer, and when combined with CA125 to calculate the ROMA score, it is useful for predicting the malignancy of ovarian cancer and is expected to detect early-stage ovarian cancer, but the data is not yet sufficient (2). In Japan, the use of ctDNA to assess the risk of recurrence of colorectal cancer is covered by insurance, and it has been reported that ctDNA may also be used to predict prognosis in ovarian cancer (3). However, because it is a biomarker that depends on tumor volume, it is difficult to use for early diagnosis.

Exosomes are nano-sized extracellular vesicles (30-150 nm) secreted by almost all cells and are secreted into various body fluids such as blood, saliva, cerebrospinal fluid, urine, breast milk, and tears, and they are recognized as important mediators of intercellular communication (4-9). Exosomes contain proteins, RNA, DNA, and lipids (10). Exosomes secreted from cancer cells may contain substances specific to cancer, and it is hoped that detecting these may lead to early-detection of cancer (10, 11). Exosomes are also involved in cancer metastasis, inflammatory response, and tissue repair (10). Exosomes are expected to be used as biomarkers for diagnosis and prognosis prediction, cell-free therapy (exosome therapy), drug delivery systems, and cancer vaccines (10, 12).

MiRNAs are small non-coding RNAs with a length of approximately 22 nucleotides that mainly bind to the 3′ untranslated region (3′ UTR) of target mRNAs to suppress gene expression (13). MiRNAs are secreted into extracellular fluids and transported to target cells via vesicles such as exosomes (13). Extracellular miRNAs function as chemical messengers that mediate intercellular communication (13).

According to Salvi et al., the surface antigens of exosomes differ between serum and urine, thus suggesting that the origin of exosomes is different (14). Urinary exosome research has been frequently conducted in prostate cancer, and several biomarkers from serum exosomes have been reported (14, 15). We hypothesized that, like urine, vaginal exosomes have a different composition from serum and may provide new biomarkers for ovarian cancer, as they do for prostate cancer. Unlike other medical specialties, gynecology frequently involves pelvic examinations, allowing for the relatively easy collection of vaginal discharge, which are one of the readily accessible body fluids. In addition, the vagina is connected to the abdominal cavity through the uterus and fallopian tubes, and we thought that there is a high possibility that exosomes originating from ovarian cancer tumor cells could be obtained. This is the first study to examine exosomes in the vaginal discharge of ovarian cancer patients. Exosomes in vaginal discharge have been reported in endometriosis and cervical cancer, but not in ovarian cancer (16). We conducted this study to examine exosomes in the vaginal discharge of ovarian cancer patients and benign patients, with the idea that differences in the relative amounts of certain miRNAs may lead to a novel early-detection method.

Materials and Methods

Study population. Thirty patients with epithelial ovarian cancer and 30 patients with benign gynecological diseases who visited the Gynecology Department of the Kobe University Hospital from July 2022 to October 2023 participated in the study. The benign group consisted of 20 uterine leiomyomas, four adenomyosis, seven mature cystic teratomas, one functional cyst, two endometriotic cysts, and three endometrial polyps. Seven patients had more than one benign disease. The malignant group consisted of 17 high-grade serous carcinomas, two endometrioid carcinomas, eight clear cell carcinomas, one mucinous carcinoma, and one low-grade serous carcinoma. One case in the malignant group was suspected to be endometrioid or clear cell carcinoma, but the histological type could not be determined. In the malignant group, seven patients were early stage (International Federation of Gynecology and Obstetrics (FIGO) stage I or II) and 23 were advanced stage (FIGO stage III or IV). Four patients were BRCA positive, and 12 were homologous recombination deficiency (HRD) positive. 10 patients had not been tested and their genetic status was unknown (Table I).

View this table:
Table I.

Clinical characteristics of ovarian cancer patients and benign gynecological disease patients in the study.

Vaginal discharge samples. Vaginal discharge was collected at the time of examination at the Kobe University Hospital by wiping the inside of the vagina with swabs. The collected swabs were soaked in 4 ml of phosphate-buffered saline (PBS) (FUJIFILM Wako Pure Chemical Corporation, Osaka, Japan). The solution was collected, including the liquid squeezed from the swab. They were centrifuged at 3,000 × g for 15 min at 4°C, and the supernatant was collected. Subsequently, the samples were then centrifuged at 12,000 × g for 15 min at 4°C and the supernatant was collected (Figure 1). The centrifuged samples were stored at −80°C until further use. If centrifugation was not possible immediately after collection, the collection tubes containing the soaked swabs were stored at 4°C. In all cases, centrifugation was performed within one week.

Figure 1.
Figure 1.

Extraction of exosomal miRNA from vaginal discharge. Vaginal discharge was collected with a swab and soaked in 4 ml of PBS. The swabs were centrifuged at 3,000 × g for 15 min at 4°C, and the supernatant was collected. The swab was then centrifuged again at 12,000 × g for 15 min at 4°C, and that supernatant was collected. Exosomes were extracted using the SmartSEC HT EV Isolation System. miRNA was extracted using an miRNeasy Mini Kit.

Exosome extraction. Exosomes were extracted using the SmartSEC HT EV Isolation System (System Biosciences, Palo Alto, CA, USA) according to the manufacturer’s protocol (Figure 1). The extracted exosomes were stored at −80°C. Exosomal protein concentration was measured using Qubit 3.0 Fluorometer (Thermo Fisher Scientific Inc., Waltham, MA, USA).

Exosomal miRNA microarray. MiRNA microarrays using 3D-Gene® Human miRNA Oligo chip (Toray Industries, Inc., Tokyo, Japan) was performed and analyzed by Kamakura Techno–Science, Inc. (Kanagawa, Japan). A total of four vaginal discharge samples were examined, two each from both the malignant and benign samples. The chip is a high-performance DNA chip substrate on which antisense oligonucleotides that detect human miRNAs selected from the miRBase database are spotted. Using 3D-Gene® miRNA labeling kit, miRNAs extracted from exosomes were labeled with green fluorescent dye, and the standard sample was labeled with red fluorescent dye. Hybridization reaction was then performed with the DNA chip. After the reaction, the washed chip was read with a 3D-Gene® Scanner 3000 (Toray Industries) to detect the signal. The analysis software used was GeneSpring GX (Agilent Technologies, Santa Clara, CA, USA). Each value was used as the global normalization when the signal intensity was corrected to a median of 25. A Log2 value when the 75 percentile was corrected to 1 was used as the Log2 (75th percentile normalization), and the difference in the averages between the benign and malignant groups was used as the Log2 ratio. This was converted to an antilogarithmic number to use as a ratio. A ratio of global normalization of 0.5 or less was considered significant for downregulation, and 2 or more for upregulation. The raw data are available in the Gene Expression Omnibus database (GSE271256).

MiRNA extraction. MiRNAs were extracted using the QIAzol Lysis Reagent (QIAgen, Hilden, Germany) and miRNeasy Mini Kit (QIAgen) according to the protocol. An miRNA quality check was performed using a Bioanalyzer 2100 (Agilent Technologies). Total RNA obtained from exosomes was analyzed using a RNA 6000 Pico Kit (Agilent Technologies). Most of the RNA contained in exosomes was small RNA less than 200 nt (Figure 2).

Figure 2.
Figure 2.

MiRNA extracted from the exosomes of the vaginal discharge was analyzed using a Bioanalizer 2100 instrument. Most of the RNA contained in the exosomes was small RNA less than 200 nt. nt, Nucleotide.

qRT-PCR. A TaqMan® MicroRNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA) was used to create cDNA from total RNA, according to the manufacturer’s protocol. cDNA was stored at −20°C until further use. qPCR was performed in triplicates using diluted cDNA with the TaqMan® Universal Master Mix II, no UNG (Applied Biosystems) and TaqMan® Fast Advanced Master Mix (Applied Biosystems). When comparing miRNA expression, syn-cel-miR-39, an external standard, was used to normalize the data according to previous reports (9, 17, 18). The ΔΔCt method was used to compare miRNA expression levels.

Statistical analysis. The Mann-Whitney U-test was used to examine the differences in miRNA expression levels (the ΔΔCt value) between the benign and malignant groups. The Spearman’s correlation coefficient was used to examine any correlation between the ΔΔCt value and patient age or CA125 value. The Kruskal-Wallis test was used to examine whether there were significant differences in ΔΔCt values by histological type in the malignant group. The Mann-Whitney U-test was also used to examine whether there were significant differences in ΔΔCt values based on lymph node metastasis, BRCA, or HRD status in the malignant group. p-Values of 0.05 or less were considered significant. Statistical analysis was performed using EZR version 1.66 (Jichi Medical University Saitama Medical Center, Saitama, Japan).

Functional enrichment analysis. To investigate the target genes of miR-575, we used the miRNA database miRDB (https://mirdb.org/, accessed on January 28, 2025). To analyze which biological processes those target genes are involved in, Gene Ontology enrichment analysis was performed using FunRich (version 3.1.4).

Approval of the research protocol by an Institutional Reviewer Board. Ethical consent was granted from the Ethical Committee Review Board of the Clinical and Translational Research Center of Kobe University Hospital (permit number: No. B220071)

Informed consent. Because this study was an observational study using existing samples and information at the Kobe University, written consent was not sought from individual research subjects, but for those research subjects who had an opportunity to receive an explanation after the date on which the head of the research institution gave permission to conduct the study, an information disclosure document was provided, which was used to provide an easy-to-understand explanation, and oral consent was obtained and recorded in the patient’s chart. Information regarding this study was also appropriately disclosed, and research subjects were given the opportunity to refuse to register for this study. Opportunities for refusal in this study were handled by phone or email.

Results

Microarray analysis of miRNAs. Of the 2632 miRNAs, 538 were considered to have significant differences. Of the 538 miRNAs, 144 were selected that had a global normalization of 100 or higher in at least one of the four samples to exclude miRNAs with weak or almost no signal intensity. Additionally, of the 144 miRNAs, 25 that have been previously reported to be related to ovarian cancer were selected. Of the 25 miRNAs, 14 were selected for which papers reported data on qPCR in human samples (Figure 3 and Figure 4).

Figure 3.
Figure 3.

Of the 2,632 miRNAs examined by miRNA microarray, 538 were considered to have significant differences. Furthermore, 144 were selected for which the global normalization value was 100 or higher in at least one of the four samples submitted to the array. Of these, 25 miRNAs were selected for which there was at least one ovarian cancer-related paper published. 14 miRNAs were selected for which PCR was performed on human samples. Three miRNAs were determined for which the PCR probe worked.

Figure 4.
Figure 4.

Global normalization and ratio of 14 miRNAs selected by microarray analysis. A ratio of 2 or more indicates up-regulation in malignant samples compared to benign samples, and a ratio of less than 0.5 indicates down-regulation.

Comparison of relative miRNAs expression of vaginal discharge samples between malignant and benign groups. RT-qPCR was performed for four miRNAs: miR-575, miR-572, miR-1290 and miR-21. MiR-575, miR-572 and miR-1290 were the three miRNAs that the probe worked on out of 14 miRNAs. MiR-21 was not significantly different according to the miRNA microarray analysis but was additionally performed because it has previously been reported as a possible cancer-related miRNA. In the miRNA microarray, all four miRNAs were upregulated in the malignant group.

RT-qPCR was finally performed on 30 malignant and 29 benign samples, the difference due to one sample being used up in the benign group. MiR-575 was strongly downregulated with significant differences in the malignant group, whereas the expression of three miRNAs (miR-572, miR-1290, and miR-21) did not show significant differences between the malignant and benign groups (Figure 5).

Figure 5.
Figure 5.

Comparison of the relative levels of miRNAs in patients with benign gynecological disease and ovarian cancer. The expression of miR-575, miR-572, miR-1290, and miR-21 in exosomes from vaginal discharge was examined by qRT-PCR and assessed using the ΔΔCt method. Data were statistically analyzed by the Mann-Whitney U test and presented as box plots. The horizontal line represents the median. The height of the box is the interquartile range, which represents the 75th to 25th percentile of individual changes.

Relative miR-575 expression and patient background of malignant group. The qPCR results were analyzed with respect to age, CA125, histological type, stage, presence or absence of lymph node metastasis, and BRCA and HRD status; however, no significant differences were found (Figure 6 and Figure 7).

Figure 6.
Figure 6.

Comparison of relative miR-575 levels was performed based on patient background of cases in the malignant group. The qPCR results were analyzed with respect to histological type, stage, presence or absence of metastasis, and BRCA and HRD status; however, no significant differences were found. Data were statistically analyzed using the Mann-Whitney U-test for two groups and the Kruskal-Wallis test for three or more groups and are displayed as box plots. Horizontal lines represent medians. Box heights are interquartile ranges, representing the 75th to 25th percentiles of individual changes.

Figure 7.
Figure 7.

Statistical examination of correlation between relative expression of miR-575 and age or CA125 levels using the Spearman’s rank correlation coefficient. No clear correlation was found. Data were statistically analyzed also using the Spearman’s rank correlation coefficient and are presented as box plots and regression lines. Horizontal lines in box plots represent medians. Box heights are interquartile ranges, representing the 75th to 25th percentiles of individual variation.

Target genes and functional enrichment analysis. A search for miR-575 in miRDB identified 118 miRNAs with a Target Score of 70 or higher, of which 116 were available in the Gene Ontology database, and 109 were available in the Biological process database (Supplementary Table I). The corrected p-value for “positive regulation of epithelial cell migration” was less than 0.05 for both the Bonferroni and Benjamini-Hochberg (BH) methods (p=0.046, 0.036). The only items that showed significant differences only with the BH method were “CD8-positive, alpha-beta T cell lineage commitment” (p=0.036) and “regulation of sarcomere tissue” (p=0.036) (Figure 8, Figure 9 and Table II).

Figure 8.
Figure 8.

Corrected p-values of Bonferroni method. The primary axis represents the percentage of genes, and the secondary axis is −log10(p-value). The blue line indicates the p=0.05 line. The bar graph shows the percentage of genes for each biological process.

Figure 9.
Figure 9.

Corrected p-values of BH method. The primary axis represents the percentage of genes, and the secondary axis is −log10(p-value). The blue line indicates the p=0.05 line. The bar graph shows the percentage of genes for each biological process. BH, Benjamini-Hochberg.

View this table:
Table II.

Gene Ontology analysis of miRDB for miR-575 was performed using FunRich.

Discussion

There is one report on miR-575 in ovarian cancer where miRNA expression was profiled using miRNA microarrays, and it was reported to be one of the miRNAs significantly upregulated in tumor tissues of recurrent ovarian high grade serous carcinoma (HGSC) (19). MiR-575 has been reported in other carcinomas, and in some cases it has been upregulated in cancer tissues and cell lines, while in others it has been down-regulated. Qin et al. found that inhibiting miR-575 reduced the proliferation and invasion of gallbladder cancer cells. They also found that p27Kip1 was a direct target of miR-575 by luciferase reporter assay (20). Liu et al. found that patients with high miR-575 expression in breast cancer had significantly poorer outcomes than those with low miR-575 expression. Tamoxifen treatment also downregulated miR-575 expression in ER-positive breast cancer. Overexpression of miR-575 reduced tamoxifen sensitivity by targeting CDKN1B and BRCA1 (21). Wang et al. reported that miR-575 was upregulated in gastric cancer tissues and cell lines, and PTEN was found to be a downstream target of miR-575 by luciferase reporter assay (22). Zhang et al. reported that RPL34-AS1 acts as a competitive endogenous RNA (ceRNA) of miR-575 in esophageal squamous cell carcinoma, alleviating the inhibitory effect of miR-575 on the target gene ACAA2, and suppresses the tumorigenesis of esophageal squamous cell carcinoma (23). These four reports indicate that miR-575 is upregulated in cancer and poor prognosis cases, but there are also reports showing the opposite. Wang et al. found that RIPK4 was increased in colon cancer tissues and cell lines, and RIPK4 was negatively regulated as a downstream target of miR-575 by luciferase reporter assay. MiR-575/RIPK4 axis inactivates the Wnt/β-catenin pathway through the downregulation of RUNX1, thus suppressing the progression of colorectal cancer (24). Huang et al. found that miR-575 suppresses tumor growth and metastasis by negatively regulating its downstream target DRP1 in head and neck cancer (25). Previous reports have also shown that miR-575 is upregulated in cancer tissues and cell lines, but there have been other reports of it being down-regulated, as in our study.

There have been two reports on exosomal miR-575, but neither were reports on malignant tumors. One reported that exosomal miR-575 was significantly downregulated in the breast milk from obese mothers, compared to normal weight mothers (26). The other reported that serum exosomal miR-575 was significantly downregulated in patients with Kawasaki disease and upregulated after IVIg (27). As mentioned above, there have been reports of miR-575 directly extracted from tissues, cell lines, and serum in several carcinomas, but exosomal miR-575 has never been reported in the context of malignancies such as ovarian cancer. This is the first time such information has been reported (20-25, 28, 29).

MiR-575 was upregulated in the microarray but downregulated in the RT-qPCR test results. When we checked with the analysis contractor, we were told that there are cases where the results of the array and PCR do not match and that the reasons are several. One is the difference in the correction method. The data of the array is corrected (standardized) using the expression level of the whole gene by a method called global normalization; however, in the case of PCR, correction is usually performed using a specific gene or spike. Therefore, the difference in the correction method between the array and PCR may be the cause of the difference in the results (30, 31). The other is the influence of the difference in the detection method. For miRNA in body fluids, there are miRNAs called isomiRs, which are sequences with a few base sequences that are slightly different at the end of the miRNA. For such isomiRs, the array detects them by allowing subtle differences in the base sequence at the end; however, PCR does not allow subtle differences in the base sequence at the end and cannot detect them. As several papers have reported, isomiRs are more abundant than canonical miRNA subtypes (32, 33). Such differences in the detection method may affect the difference in the results of the array and PCR (34).

The advantage of diagnosing ovarian cancer from vaginal discharge is that it allows for liquid biopsy relatively close to the affected area. Shao et al. investigated the long non-coding RNA (lncRNA) AA174084 in gastric juice and reported that, although there was no difference in the concentration of AA174084 in plasma between gastric cancer patients and control groups, it could be detected at significantly higher concentrations in gastric juice (35). The vagina and peritoneal cavity are also connected via the uterus and fallopian tubes, so it may be possible to detect substances secreted from primary tumor tissue at higher concentrations.

A search in the miRDB database revealed that PTEN had a target score of 78% for miR-575, and the Gene Ontology analysis by FunRich also showed that PTEN was listed as a mapped gene name for two of the top 10 related biological processes. It is also interesting to note that MDM4, which has a p53-binding domain at its N-terminus, also had a Target score of 78% in miRDB, although it was not listed in the mapped gene names of biological process. RIPK4 had a target score of 75% and was also listed as a mapped gene name for the chromatin remodeling process among the top 10 related biological processes in FunRich’s Gene Ontology analysis.

In this study, miR-575 was downregulated in malignant samples. However, further research is needed to determine the mechanism by which it is downregulated and its function in ovarian cancer. Since it was suggested that miR-575 may be significantly involved in the positive regulation of epithelial cell migration, we plan to continue research into migration and invasive abilities using cell lines. The results of this study are very interesting and promising, but their usefulness is limited by the small number of samples used in this study. In the future, we plan to analyze more vaginal discharge exosomes by dividing the histological type and stage of ovarian cancer and analyze whether they contribute to prognosis and diagnosis. If further research can be used for early detection, samples could be collected at the same time as cervical cancer screening, which could reduce the burden on patients.

Conclusion

This is the first study to investigate exosomal miRNAs in vaginal discharge of ovarian cancer. Exosomal miR-575 in vaginal discharge may be used as a biomarker for ovarian cancer.

Acknowledgements

We thank the staff at Department of Obstetrics and Gynecology, Kobe University Hospital for assisting in sample collection.

Footnotes

  • Authors’ Contributions

    MA: sample collection; data curation; investigation; methodology; writing – original draft. SI: research technology guidance; supervision; writing – review and editing. YY: data curation. KO: sample collection. KY: sample collection. YT: Supervision. All Authors read and approved the final manuscript.

  • Supplementary Material

    Available at: https://figshare.com/articles/online_resource/Gene_Ontology_Analysis_of_miR-575_target_genes_xlsx/28360088?file=52178723

  • Conflicts of Interest

    The Authors declare no potential conflicts of interest in relation to this study.

  • Funding

    This work was supported by JSPS KAKENHI Grant Number JP20K09643.

  • Received January 8, 2025.
  • Revision received January 28, 2025.
  • Accepted February 7, 2025.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Sambasivan S
    : Epithelial ovarian cancer: Review article. Cancer Treat Res Commun 33: 100629, 2022. DOI: 10.1016/j.ctarc.2022.100629
    OpenUrlCrossRef
  2. ↵
    1. Dochez V,
    2. Caillon H,
    3. Vaucel E,
    4. Dimet J,
    5. Winer N,
    6. Ducarme G
    : Biomarkers and algorithms for diagnosis of ovarian cancer: CA125, HE4, RMI and ROMA, a review. J Ovarian Res 12(1): 28, 2019. DOI: 10.1186/s13048-019-0503-7
    OpenUrlCrossRefPubMed
  3. ↵
    1. Dobilas A,
    2. Chen Y,
    3. Brueffer C,
    4. Leandersson P,
    5. Saal LH,
    6. Borgfeldt C
    : Preoperative ctDNA levels are associated with poor overall survival in patients with ovarian cancer. Cancer Genomics Proteomics 20(6suppl): 763-770, 2023. DOI: 10.21873/cgp.20423
    OpenUrlAbstract/FREE Full Text
  4. ↵
    1. Rabinowits G,
    2. Gerçel-Taylor C,
    3. Day JM,
    4. Taylor DD,
    5. Kloecker GH
    : Exosomal microRNA: a diagnostic marker for lung cancer. Clin Lung Cancer 10(1): 42-46, 2009. DOI: 10.3816/CLC.2009.n.006
    OpenUrlCrossRefPubMed
    1. Ogawa Y,
    2. Kanai-Azuma M,
    3. Akimoto Y,
    4. Kawakami H,
    5. Yanoshita R
    : Exosome-like vesicles with dipeptidyl peptidase IV in human saliva. Biol Pharm Bull 31(6): 1059-1062, 2008. DOI: 10.1248/bpb.31.1059
    OpenUrlCrossRefPubMed
    1. Street JM,
    2. Barran PE,
    3. Mackay CL,
    4. Weidt S,
    5. Balmforth C,
    6. Walsh TS,
    7. Chalmers RT,
    8. Webb DJ,
    9. Dear JW
    : Identification and proteomic profiling of exosomes in human cerebrospinal fluid. J Transl Med 10: 5, 2012. DOI: 10.1186/1479-5876-10-5
    OpenUrlCrossRefPubMed
    1. Dimov I,
    2. Jankovic Velickovic L,
    3. Stefanovic V
    : Urinary exosomes. ScientificWorldJournal 9: 1107-1118, 2009. DOI: 10.1100/tsw.2009.128
    OpenUrlCrossRef
    1. Admyre C,
    2. Johansson SM,
    3. Qazi KR,
    4. Filén JJ,
    5. Lahesmaa R,
    6. Norman M,
    7. Neve EPA,
    8. Scheynius A,
    9. Gabrielsson S
    : Exosomes with immune modulatory features are present in human breast milk. J Immunol 179(3): 1969-1978, 2007. DOI: 10.4049/jimmunol.179.3.1969
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Inubushi S,
    2. Kawaguchi H,
    3. Mizumoto S,
    4. Kunihisa T,
    5. Baba M,
    6. Kitayama Y,
    7. Takeuchi T,
    8. Hoffman RM,
    9. Sasaki R
    : Oncogenic miRNAs identified in tear exosomes from metastatic breast cancer patients. Anticancer Res 40(6): 3091-3096, 2020. DOI: 10.21873/anticanres.14290
    OpenUrlAbstract/FREE Full Text
  10. ↵
    1. Rezaie J,
    2. Feghhi M,
    3. Etemadi T
    : A review on exosomes application in clinical trials: perspective, questions, and challenges. Cell Commun Signal 20(1): 145, 2022. DOI: 10.1186/s12964-022-00959-4
    OpenUrlCrossRefPubMed
  11. ↵
    1. Inubushi S,
    2. Kunihisa T,
    3. Kuniyasu M,
    4. Inoue S,
    5. Yamamoto M,
    6. Yamashita Y,
    7. Miki M,
    8. Mizumoto S,
    9. Baba M,
    10. Hoffman RM,
    11. Tanino H
    : Serum exosomes expressing CD9, CD63 and HER2 from breast-cancer patients decreased after surgery of the primary tumor: a potential biomarker of tumor burden. Cancer Genomics Proteomics 21(6): 580-584, 2024. DOI: 10.21873/cgp.20474
    OpenUrlAbstract/FREE Full Text
  12. ↵
    1. Konishi H,
    2. Hayashi M,
    3. Taniguchi K,
    4. Nakamura M,
    5. Kuranaga Y,
    6. Ito Y,
    7. Kondo Y,
    8. Sasaki H,
    9. Terai Y,
    10. Akao Y,
    11. Ohmichi M
    : The therapeutic potential of exosomal miR-22 for cervical cancer radiotherapy. Cancer Biol Ther 21(12): 1128-1135, 2020. DOI: 10.1080/15384047.2020.1838031
    OpenUrlCrossRefPubMed
  13. ↵
    1. O’Brien J,
    2. Hayder H,
    3. Zayed Y,
    4. Peng C
    : Overview of microRNA biogenesis, mechanisms of actions, and circulation. Front Endocrinol (Lausanne) 9: 402, 2018. DOI: 10.3389/fendo.2018.00402
    OpenUrlCrossRefPubMed
  14. ↵
    1. Salvi S,
    2. Bandini E,
    3. Carloni S,
    4. Casadio V,
    5. Battistelli M,
    6. Salucci S,
    7. Erani I,
    8. Scarpi E,
    9. Gunelli R,
    10. Cicchetti G,
    11. Guescini M,
    12. Bonafè M,
    13. Fabbri F
    : Detection and investigation of extracellular vesicles in serum and urine supernatant of prostate cancer patients. Diagnostics (Basel) 11(3): 466, 2021. DOI: 10.3390/diagnostics11030466
    OpenUrlCrossRefPubMed
  15. ↵
    1. Hatano K,
    2. Fujita K
    : Extracellular vesicles in prostate cancer: a narrative review. Transl Androl Urol 10(4): 1890-1907, 2021. DOI: 10.21037/tau-20-1210
    OpenUrlCrossRefPubMed
  16. ↵
    1. Kok VC,
    2. Yu CC
    : Cancer-derived exosomes: their role in cancer biology and biomarker development. Int J Nanomedicine 15: 8019-8036, 2020. DOI: 10.2147/IJN.S272378
    OpenUrlCrossRefPubMed
  17. ↵
    1. Eichelser C,
    2. Stückrath I,
    3. Müller V,
    4. Milde-Langosch K,
    5. Wikman H,
    6. Pantel K,
    7. Schwarzenbach H
    : Increased serum levels of circulating exosomal microRNA-373 in receptor-negative breast cancer patients. Oncotarget 5(20): 9650-9663, 2014. DOI: 10.18632/oncotarget.2520
    OpenUrlCrossRefPubMed
  18. ↵
    1. Sueta A,
    2. Yamamoto Y,
    3. Tomiguchi M,
    4. Takeshita T,
    5. Yamamoto-Ibusuki M,
    6. Iwase H
    : Differential expression of exosomal miRNAs between breast cancer patients with and without recurrence. Oncotarget 8(41): 69934-69944, 2017. DOI: 10.18632/oncotarget.19482
    OpenUrlCrossRefPubMed
  19. ↵
    1. Nam EJ,
    2. Kim S,
    3. Lee TS,
    4. Kim HJ,
    5. Lee JY,
    6. Kim SW,
    7. Kim JH,
    8. Kim YT
    : Primary and recurrent ovarian high-grade serous carcinomas display similar microRNA expression patterns relative to those of normal ovarian tissue. Oncotarget 7(43): 70524-70534, 2016. DOI: 10.18632/oncotarget.12045
    OpenUrlCrossRefPubMed
  20. ↵
    1. Qin Y,
    2. Mi W,
    3. Huang C,
    4. Li J,
    5. Zhang Y,
    6. Fu Y
    : Downregulation of miR-575 inhibits the tumorigenesis of gallbladder cancer via targeting p27 Kip1. Onco Targets Ther 13: 3667-3676, 2020. DOI: 10.2147/OTT.S229614
    OpenUrlCrossRefPubMed
  21. ↵
    1. Liu SS,
    2. Li Y,
    3. Zhang H,
    4. Zhang D,
    5. Zhang XB,
    6. Wang X,
    7. Yu Y
    : The ERα-miR-575-p27 feedback loop regulates tamoxifen sensitivity in ER-positive Breast Cancer. Theranostics 10(23): 10729-10742, 2020. DOI: 10.7150/thno.46297
    OpenUrlCrossRefPubMed
  22. ↵
    1. Wang Y,
    2. Xu F,
    3. Zhang P,
    4. Wang P,
    5. Wei Y,
    6. Wu C,
    7. Cheng S
    : MicroRNA-575 regulates development of gastric cancer by targeting PTEN. Biomed Pharmacother 113: 108716, 2019. DOI: 10.1016/j.biopha.2019.108716
    OpenUrlCrossRefPubMed
  23. ↵
    1. Zhang H,
    2. Pan E,
    3. Zhang Y,
    4. Zhao C,
    5. Liu Q,
    6. Pu Y,
    7. Yin L
    : LncRNA RPL34-AS1 suppresses the proliferation, migration and invasion of esophageal squamous cell carcinoma via targeting miR-575/ACAA2 axis. BMC Cancer 22(1): 1017, 2022. DOI: 10.1186/s12885-022-10104-6
    OpenUrlCrossRefPubMed
  24. ↵
    1. Wang Q,
    2. Lu W,
    3. Lu L,
    4. Wu R,
    5. Wu D
    : miR-575/RIPK4 axis modulates cell cycle progression and proliferation by inactivating the Wnt/β-catenin signaling pathway through inhibiting RUNX1 in colon cancer. Mol Cell Biochem 479(7): 1747-1766, 2024. DOI: 10.1007/s11010-024-04938-w
    OpenUrlCrossRefPubMed
  25. ↵
    1. Huang TL,
    2. Chang CR,
    3. Chien CY,
    4. Huang GK,
    5. Chen YF,
    6. Su LJ,
    7. Tsai HT,
    8. Lin YS,
    9. Fang FM,
    10. Chen CH
    : DRP1 contributes to head and neck cancer progression and induces glycolysis through modulated FOXM1/MMP12 axis. Mol Oncol 16(13): 2585-2606, 2022. DOI: 10.1002/1878-0261.13212
    OpenUrlCrossRefPubMed
  26. ↵
    1. Cho YE,
    2. Vorn R,
    3. Chimenti M,
    4. Crouch K,
    5. Shaoshuai C,
    6. Narayanaswamy J,
    7. Harken A,
    8. Schmidt R,
    9. Gill J,
    10. Lee H
    : Extracellular vesicle miRNAs in breast milk of obese mothers. Front Nutr 9: 976886, 2022. DOI: 10.3389/fnut.2022.976886
    OpenUrlCrossRefPubMed
  27. ↵
    1. Zhang X,
    2. Xin G,
    3. Sun D
    : Serum exosomal miR-328, miR-575, miR-134 and miR-671-5p as potential biomarkers for the diagnosis of Kawasaki disease and the prediction of therapeutic outcomes of intravenous immunoglobulin therapy. Exp Ther Med 16(3): 2420-2432, 2018. DOI: 10.3892/etm.2018.6458
    OpenUrlCrossRefPubMed
  28. ↵
    1. Wang S,
    2. Zou C,
    3. Lin X,
    4. Hu D,
    5. Su Y,
    6. He H,
    7. Zheng X,
    8. Zhang L,
    9. Huang T,
    10. Liao JR,
    11. Lin X
    : RNU12 inhibits gastric cancer progression via sponging miR-575 and targeting BLID. Sci Rep 13(1): 7523, 2023. DOI: 10.1038/s41598-023-34539-4
    OpenUrlCrossRefPubMed
  29. ↵
    1. Dong H,
    2. Wu YL,
    3. Zhang X,
    4. Li HL,
    5. Zheng WH
    : MicroRNA-575 targets Derlin 1 to regulate proliferation, migration and invasion of human thyroid cancer cells. Arch Med Sci 19(4): 1108-1115, 2020. DOI: 10.5114/aoms.2020.92867
    OpenUrlCrossRefPubMed
  30. ↵
    1. D’haene B,
    2. Mestdagh P,
    3. Hellemans J,
    4. Vandesompele J
    : miRNA expression profiling: from reference genes to global mean normalization. Methods Mol Biol 822: 261-272, 2012. DOI: 10.1007/978-1-61779-427-8_18
    OpenUrlCrossRefPubMed
  31. ↵
    1. Abbas-Aghababazadeh F,
    2. Li Q,
    3. Fridley BL
    : Comparison of normalization approaches for gene expression studies completed with high-throughput sequencing. PLoS One 13(10): e0206312, 2018. DOI: 10.1371/journal.pone.0206312
    OpenUrlCrossRefPubMed
  32. ↵
    1. Bhardwaj A,
    2. Singh H,
    3. Trinidad CM,
    4. Albarracin CT,
    5. Hunt KK,
    6. Bedrosian I
    : The isomiR-140-3p-regulated mevalonic acid pathway as a potential target for prevention of triple negative breast cancer. Breast Cancer Res 20(1): 150, 2018. DOI: 10.1186/s13058-018-1074-z
    OpenUrlCrossRefPubMed
  33. ↵
    1. Jiang G,
    2. Reiter JL,
    3. Dong C,
    4. Wang Y,
    5. Fang F,
    6. Jiang Z,
    7. Liu Y
    : Genetic regulation of human isomiR biogenesis. Cancers (Basel) 15(17): 4411, 2023. DOI: 10.3390/cancers15174411
    OpenUrlCrossRefPubMed
  34. ↵
    1. Llorens F,
    2. Hummel M,
    3. Pantano L,
    4. Pastor X,
    5. Vivancos A,
    6. Castillo E,
    7. Mattlin H,
    8. Ferrer A,
    9. Ingham M,
    10. Noguera M,
    11. Kofler R,
    12. Dohm JC,
    13. Pluvinet R,
    14. Bayés M,
    15. Himmelbauer H,
    16. del Rio JA,
    17. Martí E,
    18. Sumoy L
    : Microarray and deep sequencing cross-platform analysis of the mirRNome and isomiR variation in response to epidermal growth factor. BMC Genomics 14: 371, 2013. DOI: 10.1186/1471-2164-14-371
    OpenUrlCrossRefPubMed
  35. ↵
    1. Shao Y,
    2. Ye M,
    3. Jiang X,
    4. Sun W,
    5. Ding X,
    6. Liu Z,
    7. Ye G,
    8. Zhang X,
    9. Xiao B,
    10. Guo J
    : Gastric juice long noncoding RNA used as a tumor marker for screening gastric cancer. Cancer 120(21): 3320-3328, 2014. DOI: 10.1002/cncr.28882
    OpenUrlCrossRefPubMed
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MiR-575 in Exosomes of Vaginal Discharge Is Downregulated in Ovarian Cancer Patients
MAHO AZUMI, SACHIKO INUBUSHI, YOKO YANO, KENTA OBATA, KEITARO YAMANAKA, YOSHITO TERAI
Cancer Genomics & Proteomics May 2025, 22 (3) 382-396; DOI: 10.21873/cgp.20508
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