A extracellular secretion of miR-1825 wrapped by exosomes increases CLEC5A expression: a potential oncogenic mechanism in ovarian cancer

A extracellular secretion of miR-1825 wrapped by exosomes increases CLEC5A expression: a potential oncogenic mechanism in ovarian cancer | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A extracellular secretion of miR-1825 wrapped by exosomes increases CLEC5A expression: a potential oncogenic mechanism in ovarian cancer Qiaoling Wu, Zhaolei Cui, Hongmei Xia, Shan Jiang, Jing Bai, Zhuo Shao, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2217739/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 (OC) is an important cause of gynecologic cancer-related mortality worldwide. Exosomal miR-1825 and its target gene CLEC5A have been shown to have a significant association with tumorigenesis in other cancers. Methods: Exosomal miR-1825 expression and its ability in overall survival(OS) prediction were determined using GEO and TCGA data. Target genes of miR-1825 were searched in five prediction databases, and differentially expressed prognostic genes were identified. We performed GO and KEGG enrichment analyses. The ability of CLEC5A in OS prediction was assessed using univariate and multivariate Cox regression and Kaplan-Meier curves. Immunohistochemistry was applied to validate the CLEC5A expression pattern in OC. The immune cell landscape was compared using the CIBERSORT algorithm, and the results were validated in a GEO cohort. Finally, the predicted IC50 of five common chemotherapy agents was compared. Results: MiR-1825 was elevated in exosomes derived from OC cells and served as a tumor suppressor. The CLEC5A gene was confirmed as a target of miR-1825 , whose upregulation was correlated with a poor prognosis. M2 macrophage infiltration was significantly enhanced in CLEC5A high expression group, and T follicular helper cell infiltration was reduced in it. The predicted IC50 for cisplatin and doxorubicin was higher in CLEC5A high expression group, and that for docetaxel, gemcitabine, and paclitaxel was lower. Conclusion: MiR-1825 may promote OC progression by increasing CLEC5A expression through exosome-mediated efflux from tumor cells and could be a promising biomarker for OC. Exosome microRNA-1825 C-type lectin domain family 5 member A PI3K-Akt pathway tumor immune microenvironment Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Ovarian cancer (OC) is the second leading cause of gynecologic cancer death in the world. It is estimated that the prevalence has reached 3.4% and the annual mortality rate has reached 4.7% of all female cases in 2020. [ 1 ] Most ovarian cancers are often diagnosed at stage III or IV, and these patients only have a 5-year survival rate of < 25%. [ 2 , 3 ] Comprehensive surgical staging and debulking are preferred, followed by systemic chemotherapy according to NCCN Guidelines on Treatment of OC (Version 3.2021, [DB/OL]. http://www.nccn.org ). However, more than 80% of late-stage tumors initially responsive to conventional treatment develop resistance over time. [ 3 ] Therefore, there is an urgent need to identify effective biomarkers for early diagnosis based on a better understanding of the underlying molecular mechanisms of ovarian cancer development. Exosomes are extracellular vesicles (EVs) actively secreted by cells with an approximately 40–160 nm in diameter, which have been implicated in intercellular communication by carrying RNA, lipids, proteins, and other bioactive substances. They can deliver curcumin to activated myeloid cells and deliver doxorubicin specifically to tumor tissues, leading to growth inhibition of tumors without overt toxicity. [ 4 , 5 ] Its RNA content varies dramatically according to the cell types of origin, reflecting one of the reasons for exosome heterogeneity. [ 6 – 8 ] MicroRNAs, which can inhibit protein synthesis by targeting the complementary sequences located at the 3'-end untranslated regions of messenger RNAs (mRNAs), [ 9 , 10 ] play an important role in regulating cancer progression. Exosomal microRNAs, which are microRNAs encapsulated by exosomes, can promote tumor progression by enhancing mesothelial-to-mesenchymal transition, conferring drug resistance, inducing vascular permeability and angiogenesis, inducing macrophage M2 polarization, and participating in tumor immune escape by delivering immunosuppressive molecules and factors; It has been reported that exosomal microRNAs can also inhibit tumor progression by reversing drug resistance and increasing tumor chemosensitivity. The potential role of exosomal microRNAs as biomarkers in cancer diagnosis and prognosis has been noted in several tumor types including ovarian cancer. [ 11 – 18 ] Upregulation of miR-1825 has been shown to be able to inhibit the progression of glioblastoma and promote proliferation of naturally quiescent adult cardiomyocytes. However, the role of miR-1825 and its target gene in OC has not been explored so far. [ 19 , 20 ] C-type lectin domain family 5 member A ( CLEC5A ), a member of C-type lectin/C-type lectin-like domain (CTL/CTLD) superfamily, also named C-type lectin superfamily member 5 (CLECSF5) and myeloid DAP12-associating lectin 1 (MDL1). Members of CTL/CTLD superfamily share a typical protein fold pattern and have diverse functions, such as cell adhesion, cell-cell signaling, glycoprotein turnover, and roles in inflammation and immune response. CLEC5A has been proven to promote brain glioblastoma tumorigenesis and gastric cancer cells proliferation by regulating PI3K/Akt signaling. [ 21 – 23 ] However, the mechanism by which CLEC5A regulates OC awaits further clarification. The goals of this study were three-folded: 1) to determine the expression pattern and prognostic value of miR-1825 in OC exosomes; 2) to confirm CLEC5A as a miR-1825 target; 3) to assess the performances of the CLEC5A gene in predicting overall survival and TIME characteristics for labeling patients who might benefit from immuno- or chemotherapy. In this study, we performed a bioinformatics analysis of the expression patterns of exosomal miRNAs and focused on its target gene CLEC5A . We found that miR-1825 , as an tumor-suppressor, was highly enriched in OC exosomes, and the downstream oncogenic target gene CLEC5A was highly expressed in OC cells. MiR-1825 affected the expression of CLEC5A and the latter further led to the change of immune environment. Its ability in transforming immune environment may be an important mechanism in the development of OC. The Suppression of draining miRNAs through exosomes from OC cells may be a suitable direction for anti-tumor therapy as decreased expression of miR-1825 in OC cells can promote tumor progression. We also noted that CLEC5A could promote the development of an immune microenvironment in OC and thus has a potential role in the prognosis of OC. Methods Data Retrieval And Preprocessing Affymetrix miRNA microarray data from OC exosomes and cells were available from Gene Expression Omnibus (GEO; series GSE76449). [ 24 ] Exosomal and original samples of chemo-sensitive OC cells and normal ovarian cells (n = 16) were included to rule out the influence of chemotherapy on prediction results. RNA-seq data from normal ovarian tissues were obtained from Genotype-Tissue Expression (GTEx). RNA-sequencing (RNA-seq) data and clinical data from OC patients were downloaded from GEO (series GSE9891), Clinical Cancer Research Online ( http://clincancerres.aacrjournals.org/ ), [ 25 ] International Cancer Genome Consortium (ICGC) [ 26 ] , The Cancer Genome Atlas (TCGA) [ 27 ] , as detailed below. Bioinformatics analyses of RNA-seq data from TCGA patients were performed using the UCSC bioinformatic pipeline (TOIL RNA-seq). Each dataset was processed identically after removing unavailable data. Clinical data from TCGA were prepared using the TCGA-GDC(Genomic Data Commons) server for subsequent analysis. [ 28 ] Finally, all datasets underwent identical processing to achieve an average expression level of samples from the same patient and unavailable data were deleted (NA). Identification Of Differentially Expressed Rna In this experiment, RNA-seq data were obtained from TCGA and GTEx. Differentially expressed miRNAs (DEMIs) between exosomal and original samples of OC cells were identified with limma R Bioconductor package (version 3.48.3, P 4, Student's t-test). [ 29 ] Differentially expressed mRNAs (DEMs) were screened using the same method (adjusted P 3). A boxplot was generated with ggplot2 in R. Target Gene Prediction Five target gene prediction databases were employed to predict the downstream targets of miR-1825 , including TargetScan 7.2, miRDB, TarBasev.8, miRmap, and miRwalk 3.0. Intersections among the five databases were regarded as miR-1825 targets. [ 30 – 34 ] Survival Analysis Survival data (age, clinical stage, histologic grade, survival status, and length of overall survival) of OC patients were collected from TCGA, GEO, and ICGC and merged with gene expression data. We assessed the prognostic ability of miRNAs or CLEC5A in OC using univariate and multivariate Cox regression hazard analysis combined with Kaplan-Meier survival curves. Function Enrichment Analysis We performed Gene Ontology Biological Process (GOBP) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses with clusterProfiler in R to identify CLEC5A targets (P < 0.05) and explore mechanisms for CLEC5A ’s role in OC. [ 35 ] Then, Gene Set Enrichment Analysis (GSEA) was utilized to confirmed whether there were target genes not selected by GO or KEGG analyses (P < 0.05 and false discovery rate [FDR] < 0.25) and characterize the activity of KEGG pathways between low and high CLEC5A expression group in OC, as described in detail elsewhere. [ 36 ] Evaluation of correlation with immune characteristics of CLEC5A in OC We assessed correlations of CLEC5A gene expression with immune cell infiltrates and expressions of immune suppressors to explore the ability of CLEC5A to predict TIME characteristics in low and high CLEC5A expression in OC. TCGA RNA-Seq expression profiles of immune and stromal cells were utilized. Tumor-infiltrating lymphocytes (TILs) and stromal cells were identified with ESTIMATE (Estimation of Stromal and Immune cells in malignant Tumor tissues using Expression data) in R. Correlations of CLEC5A with immune/stromal cell infiltration were assessed, and the results were validated in a GEO cohort of 276 qualified OC cases whose expression and survival data were available for review (GSE9891). This cohort was also used for subsequent immune cell infiltration analysis. [ 37 ] The infiltration of 22 immune cell subpopulations in OC tissues was estimated using the CIBERSORT algorithm that can accurately quantify TILs in biopsied tumor tissues and the LM22 signature matrix file containing 22 immune cell reference profiles from TCGA and GEO. [ 38 ] Patients were categorized into the low and high CLEC5A expression groups according to the cutoff of CLEC5A gene expression. The immune cell landscape was compared between the two groups. Sixteen tumor immune suppressors have been shown to exert suppressive effects on solid tumors. [ 39 ] Among them, 11 (IL6, TNF, IFNG, EGF, MCH-I, CD96, LIR1, PDCD1, PDCD1LG2, CD80, and CD86) frequently reported in OC were selected and their expressions were compared between the two groups. Estimation Of Chemotherapy Response We selected five agents (cisplatin, docetaxel, doxorubicin, gemcitabine, and paclitaxel) from 22 recommended options in the 2020 NCCN clinical practice guidelines in oncology on ovarian cancer. [ 40 ] The predicted IC50 was estimated with pRRophetic (version 0.5; https://doi.org/10.1371/journal.pone.0107468 ) in R and compared between low and high CLEC5A expression OC patients from TCGA. [ 41 ] Clinical Specimens Between May 2019 and May 2021, 9 patients who had pathologically confirmed OC and underwent radical excision at Fujian Medical University Cancer Hospital (or Fujian Cancer Hospital) without prior therapy were selected. 7 OC and 2 peritumoral tissue specimens were collected, flash frozen in liquid nitrogen, and reviewed independently by two senior pathologists. The study protocol was approved by the Ethics Committee of Fujian Cancer Hospital. Immunohistochemistry (Ihc) IHC analysis was performed as previously described. [ 42 ] Briefly, formalin-fixed paraffin-embedded sections were dewaxed, dehydrated and rehydrated. The slides were incubated overnight at 4°C with an anti- CLEC5A antibodies (ab203200, Abcam, China, 1:500). Then incubate at 37°C with an secondary antibodies (ab7090, Abcam, China, 1:500).Immunostaining was performed using a SABC(Strept Avidin-Biotin Complex) kit(SA0025,Solarbio, China). Next, the slides were counterstained with Mayer hematoxylin solution (Solarbio, China) for nuclear staining. Images were obtained using VANOX microscope (Olympus, Japan) and scored as 0 points (no staining), 1 point (light yellow), 2 points (brownish yellow), and 3 points (brown). For each specimen, fields were randomly selected, and the proportion of CLEC5A -positive ( CLEC5A +) cells was calculated and scored (1 point, 0%-25% of CLEC5A + cells; 2 points, 26%-50% of CLEC5A + cells; 3 points, 51%-75% of CLEC5A + cells; 4 points, 76%-100% of CLEC5A + cells). Specimens with a pathological IHC score greater than the cutoff were identified as high CLEC5A + OC, or otherwise, low CLEC5A + OC. Statistical analysis Categorical variables were expressed as numbers (percentage) and compared using Spearman’s test. Overall survival data were analyzed using Kaplan-Meier survival curves and compared using the log-rank test. Continuous variables following normal distribution were presented in mean ± standard error of measurement (SEM) and compared using the Student’s t-test. Correlations of CLEC5A gene expression with immune/stromal cell infiltration were assessed using Spearman’s correlation test. All statistical analyses were performed using R 4.1.0, and a two-tailed P-value of < 0.05 was deemed statistically significant. Results 1. MiR-1825 was abundant in exosomes from ovarian cancer cells and associated with improved prognosis. We explored expression patterns during four group samples using the GSE76449 dataset:1) normal ovarian cells;2) exosomes outflowed from normal ovarian cells;3) ovarian cancer cells and 4) exosomes outflowed from ovarian cancer cells. Then identified DEMIs between the four groups of samples. Nineteen microRNAs were screened out, The result indicated that microRNAs exhibited a specific distribution pattern in exosomes and their original cells. The expression pattern of 11/19 DEMIs ( miR-30c-5p, miR-99b-5p, miR-10a-5p, miR-125a-5p, miR-27a-5p, miR-151b, let-7e-5p, miR-151a-5p, miR-4521, miR-15a-5p, and miR-28-5p ) was not correlated with cancer, both high expression in no matter cancer cells or normal cells. The expression pattern of miR-6216 , miR-1246 , miR-122-5p , and miR-1290 was irrelevant with cancer too, they were always highly expressed in exosomes which outflowed no matter from OC cells or normal ovarian cells. (Fig. 1A) This indicated that their expression modes were cell-specific or exosome-specific but not ovarian cancer exosome-specific. Interestingly, miR-1281, miR-1825, miR-6877-3p , and miR-3921 expressions were upregulated in exosomes outflowed from ovarian cancer cells, and significantly downregulated in the other three samples (Fig. 1B), as supported by a previous study. [ 43 ] Further, the prognostic significance of miR-1281 , miR-1825 , and miR-6877-3p was evaluated in the high versus low expression groups using TCGA survival data. MiR-3921 was ruled out due to the absence of MiR-3921 expression in most OC samples. (Fig. 1C) In KM survival analysis, miR-1825 upregulation in OC cells was correlated with improved overall survival (P < 0.05) (Fig. 1D). It might act as a tumor suppressor in OC. 2. CLEC5A was the target gene of miR-1825 and had a prognostic value We performed target gene predictions to identify miR-1825 targets using TargetScan7.2, miRDB, TarBase v.8, miRmap, and miRwalk3.0. The results displayed 52 genes (Fig. 2A). Differential expression analysis for 52 target genes using limma method revealed that the mRNA expression levels of CACNB2 and KIT were downregulated and those of N4BP3, CLEC5A, NOTUM , and DCDC2 were upregulated in the tumor group from TCGA database in comparison with normal ovarian samples from the GTEx database (|logFC| >3 and adjusted p value < 0.001) (Fig. 2B). Due to the tumor-suppressive effect of miR-1825 , the prognostic potential of the four elevated genes ( N4BP3, CLEC5A, NOTUM , and DCDC2 ) was assessed. KM curves showed that among the four genes, CLEC5A appeared to be a prognostic potential marker for OC, as validated using the validation cohort (GSE9891 and ICGC dataset OV-AU) (Fig. 2C), and was significantly associated with worse overall survival of OC patients (P < 0.05). Moreover, CLEC5A could serve as a prognostic biomarker independent of clinicopathological parameters (age, clinical stage, and histologic grade), as validated using GSE9891 and OV-AU validation cohorts (Fig. 2D). In IHC assays, CLEC5A protein expression was significantly increased in OC versus normal ovarian tissues (Fig. 2E). 3 . CLEC5A was related to Immune Microenvironment To clarify the functions of CLEC5A expression signatures associated with OC, we performed biological processes of GO and KEGG pathways enrichment analyses of genes highly correlated to CLEC5A based on the TCGA dataset. As shown in Fig. 3A-B, the intersection of GO terms and KEGG pathways showed that a proportion of highly correlated genes was associated with immune response that plays an important role in tumor inhibition and promotion. These results suggested that immune alterations might contribute to OC occurrence and development. However, the mechanism by which CLEC5A plays in immunity in OC is not clear. To further verify the results of GO/KEGG enrichment analyses, we conducted a GSEA with the low and high CLEC5A expression datasets. GSEA analyses showed significant differences (p < 0.05) in the enrichment of immune-related pathways and biological processes (Fig. 3C-D). Interestingly, CLEC5A also seems to activate the PI3K − Akt pathway in OC which has been confirmed by experiments in brain glioblastoma by Hong-Wei Fan et al. Given the importance of the PI3K − Akt signaling pathway and the impact of immune on OC, we speculate that activated PI3K − Akt signaling pathway may contribute in part to the development of immune environment in OC. [ 22 ] 4.High level expression of CLEC5A led to enhanced M2 macrophage infiltration To investigate in which way the interaction between CLEC5A and immune microenvironment plays in OC, R package ESTIMATE was used to examine correlations between immune cell/stromal cells infiltration levels and CLEC5A level. Notably, we observed a positive correlation between CLEC5A level and immune cell/stromal cell infiltration. A similar result was obtained based on the GSE9891 dataset (Fig. 4A-B). These results indicated that CLEC5A might play a role in mediating the immune response and immune cells/stromal cells infiltration in ovarian tumors. To further explore which immune cell subtype correlated to CLEC5A expression, we utilized CIBERSORT to calculate the infiltration levels of 22 immune cell subtypes, including B cells (naive B cell, memory B cell, and plasma cell), T cells [CD8 T cell, naive CD4 T cell, memory resting CD4 T cell, memory activated CD4 T cell, follicular helper T cell (Tfh), regulatory T cells (Tregs), and gamma delta T cell], natural killer (NK) cells (resting NK T cell and activated NK cell), and myeloid subsets [monocyte, MO macrophage, M1 macrophage, M2 macrophage, and resting dendritic cell (DC), activated DC, resting mast cell, activated mast cell, eosinophils, and neutrophil]. After integrating the CIBERSORT’s results (p < 0.05) based on the TCGA and GEO databases, we found that the proportions of M2 macrophages were higher in the CLEC5A high expression group than those in the CLEC5A low expression group. In contrast, the plasma cells and Tfh cells were lower in the CLEC5A high expression group (Fig. 4C). The accumulation of M2 macrophages has been reported as a pivotal part in promoting tumor progression. [ 44 ] CLEC5A expression level may affect the function of M2 tumor-associated macrophages (TAMs). We thus analyzed the correlations between CLEC5A expression level and 16 factors involved in TAMs-assisting solid tumors. In accordance with our presumption, CLEC5A was found to be positively correlated with inhibiting factors based on the TCGA and GEO database (Fig. 4D). These results suggest that raising CLEC5A expression can promote tumors via TAMs. Collectively, CLEC5A was strongly correlated with the immune environment in OC and its expression level could affect the type of immune cells infiltrated in the tumor, such as significant accumulation of M2 macrophages followed with increased CLEC5A expression. One possible explanation for the accumulation of M2 macrophages might be that activated PI3K − Akt signaling pathway could cause macrophage M2 polarization. [ 45 ] 5.new Suggestions For Clinical Drug Sensitivity We then evaluated the responses of CLEC5A high expression group and low expression group to 5 chemotherapeutic drugs that were included in the list of built-in R package pRRophetic and recommended chemotherapeutic regimens named cisplatin, docetaxel, doxorubicin, gemcitabine, and paclitaxel. Interestingly, the high CLEC5A expression group showed more sensitivity to paclitaxel, gemcitabine, and docetaxel with lower IC50. To the contrary, cisplatin and doxorubicin were more sensitive in the low CLEC5A expression group (Fig. 4E). This finding gives physicians a hint about offering OC patients individualized therapy. Discussion In this study, we described miRNAs transported by exosomes in the context of OC, explored their influence on tumor microenviroment, and evaluated their potential prognostic value. We hypothesize that draining miR-1825 from exosomes leads to elevated expression of intracellular target gene CLEC5A . In addition, we demonstrated that CLEC5A not only could provide value as a prognostic factor, but also present a direction for immunotherapy and an efficacy reference for chemotherapy drug treatment. A plethora of studies have implied that exosomal miRNAs can serve as vehicles for intercellular communication by regulating the biological behaviors of target tumor cells to promote proliferation, metastasis, and angiogenesis, and conferring radioresistance and drug-resistance of cancer cells. [ 46 – 51 ] However, the mechanisms relating to the regulation of origin cells secreting exosomes is largely unknown until recently. It has been illustrated that miRNAs inhibition promoted oncogenic behavior by leading cancer cells to release more exosomes. [ 24 , 43 , 52 ] Here, we showed that miR-1825 was abundant in exosomes derived from OC cells, but presented in low levels in the other three groups(normal ovarian cells, exosomes outflowed from normal ovarian cells, and ovarian cancer cells). MiR-1825 also showed a prognostic value as a tumor suppressor. Therefore, we suggest that OC cells secrete the miR-1825 into the extracellular environment via exosomes to maintain their tumorigenic phenotype. C-type lectin domain family 5 member A ( CLEC5A ), a member of C-type lectin/C-type lectin-like domain (CTL/CTLD) superfamily, with high expression level and ability to promote cancer, has been confirmed in several tumors . [ 22 , 23 , 53 ] However, its expression level and function in OC have not been reported previously. In our cohort, we found that CLEC5A acted as the target gene of miR-1825 and was significantly upregulated in OC patients. The upregulation of CLEC5A was further linked to poor OS of OC patients and could serve as a risk factor. These results indicated that CLEC5A has prognostic value in OC and could be a potential biomarker for OC diagnosis. There has been accumulated evidence that the immune microenvironment contributes to the OC development and progression; recent years immune checkpoint inhibitors have shown remarkable promise in many types of cancers. However, there are currently no approved immune therapies for OC. [ 3 , 54 ] Other significant findings of our functional analyses were that CLEC5A played a role in tumor-immune interactions and that CLEC5A expression was correlated with the immune infiltration level in OC. Our results revealed that there was a significant positive correlation between CLEC5A expression level and the level of infiltration of M2 macrophages and a negative correlation between CLEC5A expression level and the level of infiltration of Tfh cells in OC. M2 macrophages (also called alternatively activated macrophages) have contributed to the progression of many tumors, including OC. [ 55 – 60 ] It has been reported that M2 macrophages are part of TAMs, a view that TAMs are not completely following the M1 and M2 subtypes; they are in general M2-like. [ 61 , 62 ] Increased infiltration of M2 macrophages may be one of the mechanisms that miR-1825/CLEC5A promotes the development of OC. Recent studies also validate our view that exosomes can deliver tumor suppressor microRNAs to induce M2 macrophage polarization and promote tumor progression. [ 63 ] Our study also demonstrated a positive correlation between the high expression level of CLEC5A and the process of tumor-associated macrophages (TAMs) promoting solid tumors. It has been found that activating the PI3K/Akt signaling pathway can promote M2-type polarization in macrophages. [ 45 , 64 ] Aberrant activation of this signaling network is one of the most frequent events in human cancer and disconnects the control of cell growth, survival, and metabolism from exogenous growth stimuli. [ 65 ] PI3K/Akt signaling pathway has been shown to exert a pivotal role as an immunomodulator. Blockade of the PI3K might maximize the IFN-γ-mediated anti-tumor effect. To the contrary, activating PI3K/Akt signaling in the neoplastic epithelium can promote nuclear translocation of β-catenin, cellular proliferation, and resistance to apoptosis. Inhibition of PI3K/Akt signaling with immunomodulatory agents may provide a new therapeutic approach for cancer. [ 66 , 67 ] In our study, activation of PI3K/Akt pathway and increased infiltration of M2 macrophages were associated with elevated expression of CLEC5A . Tfh cells are a subset of CD4 + T cells that specialize in helping B cells to produce antibodies in the face of antigenic challenge. Their presence in tumor tissue is often associated with a better outcome in several solid tumor entities. [ 68 , 69 ] It has been shown to be positively associated with the long-term survival of humans with breast cancer or non-small cell lung cancer. In our study, high level expression of CLEC5A led to reduced infiltration of Tfh cells, which might be a potential molecular mechanism of protecting tumor by inhibiting ectopic lymphoid structures (ELSs), a site of recruitment for CD8 + T cells, NK cells, and macrophages that engage in anti-tumor immunity, or by reducing anti-tumor antibody responses by B cells. However, there is limited data available regarding Tfh cells supporting anti-tumor antibody responses. [ 70 – 72 ] Taken together, our results indicate that efflux of miR-1825 may trigger elevated expression of intracellular target genes and thus induce immune-related behaviors in tumors that result in tumor progression. Declarations Acknowledgement The authors acknowledge partial support of projects by, the National Natural Science Foundation of China (81873045), the Natural Science Foundation of Fujian Province of China (2020J011115), and the Medicine Innovation Foundation of Fujian Province of China (2020CXB007). Funding This project was funded by grant from the National Natural Science Foundation of China (81873045)，the Natural Science Foundation of Fujian Province of China (2020J011115) and the Medicine Innovation Project of Fujian Province of China (2020CXB007). Availability of data and materials All data generated or analyzed during this study were included in this published article and its additional files. Authors’ contributions YS and QW were responsible for conception, analysis and data interpretation. ZC contributed substantially to the conception, design, data interpretation, and revision of the work. All authors wrote different parts of the manuscript, and all read and approved the final manuscript. Ethics approval and consent to participate This study was approved by the Ethics Committee of the Fujian Cancer Hospital(Reference number: K2022-002-01). Consent for publication The authors declare that they both agree to publish. Competing interests The authors declare that they have no competing interests to disclose. References Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021. 71(3): 209-249. 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Tumor-associated macrophages of the M2 phenotype contribute to progression in gastric cancer with peritoneal dissemination. Gastric Cancer. 2016. 19(4): 1052-1065. Chen Y, Zhang S, Wang Q, Zhang X. Tumor-recruited M2 macrophages promote gastric and breast cancer metastasis via M2 macrophage-secreted CHI3L1 protein. J Hematol Oncol. 2017. 10(1): 36. Yeung OW, Lo CM, Ling CC, et al. Alternatively activated (M2) macrophages promote tumour growth and invasiveness in hepatocellular carcinoma. J Hepatol. 2015. 62(3): 607-16. Zeng XY, Xie H, Yuan J, et al. M2-like tumor-associated macrophages-secreted EGF promotes epithelial ovarian cancer metastasis via activating EGFR-ERK signaling and suppressing lncRNA LIMT expression. Cancer Biol Ther. 2019. 20(7): 956-966. Baek SH, Lee HW, Gangadaran P, et al. Role of M2-like macrophages in the progression of ovarian cancer. Exp Cell Res. 2020. 395(2): 112211. Zhou Q, Xian M, Xiang S, et al. All-Trans Retinoic Acid Prevents Osteosarcoma Metastasis by Inhibiting M2 Polarization of Tumor-Associated Macrophages. Cancer Immunol Res. 2017. 5(7): 547-559. Lin Y, Xu J, Lan H. Tumor-associated macrophages in tumor metastasis: biological roles and clinical therapeutic applications. J Hematol Oncol. 2019. 12(1): 76. Mehla K, Singh PK. Metabolic Regulation of Macrophage Polarization in Cancer. Trends Cancer. 2019. 5(12): 822-834. Li M, Xu H, Qi Y, et al. Tumor-derived exosomes deliver the tumor suppressor miR-3591-3p to induce M2 macrophage polarization and promote glioma progression. Oncogene. 2022. 41(41): 4618-4632. Zhao SJ, Kong FQ, Jie J, et al. Macrophage MSR1 promotes BMSC osteogenic differentiation and M2-like polarization by activating PI3K/AKT/GSK3β/β-catenin pathway. Theranostics. 2020. 10(1): 17-35. Hoxhaj G, Manning BD. The PI3K-AKT network at the interface of oncogenic signalling and cancer metabolism. Nat Rev Cancer. 2020. 20(2): 74-88. Caforio M, de Billy E, De Angelis B, et al. PI3K/Akt Pathway: The Indestructible Role of a Vintage Target as a Support to the Most Recent Immunotherapeutic Approaches. Cancers (Basel). 2021. 13(16). Bishnupuri KS, Alvarado DM, Khouri AN, et al. IDO1 and Kynurenine Pathway Metabolites Activate PI3K-Akt Signaling in the Neoplastic Colon Epithelium to Promote Cancer Cell Proliferation and Inhibit Apoptosis. Cancer Res. 2019. 79(6): 1138-1150. Song W, Craft J. T follicular helper cell heterogeneity: Time, space, and function. Immunol Rev. 2019. 288(1): 85-96. Baumjohann D, Brossart P. T follicular helper cells: linking cancer immunotherapy and immune-related adverse events. J Immunother Cancer. 2021. 9(6). Gu-Trantien C, Loi S, Garaud S, et al. CD4⁺ follicular helper T cell infiltration predicts breast cancer survival. J Clin Invest. 2013. 123(7): 2873-92. Ma QY, Huang DY, Zhang HJ, Chen J, Miller W, Chen XF. Function of follicular helper T cell is impaired and correlates with survival time in non-small cell lung cancer. Int Immunopharmacol. 2016. 41: 1-7. Crotty S. T Follicular Helper Cell Biology: A Decade of Discovery and Diseases. Immunity. 2019. 50(5): 1132-1148. Walter W, Sánchez-Cabo F, Ricote M. GOplot: an R package for visually combining expression data with functional analysis. Bioinformatics. 2015. 31(17): 2912-4. 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies 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-2217739","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":148211339,"identity":"2003b574-9baf-4b49-8443-1f466f5b60d9","order_by":0,"name":"Qiaoling Wu","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qiaoling","middleName":"","lastName":"Wu","suffix":""},{"id":148211340,"identity":"12037733-910e-4ddc-9247-f1b721e83fb3","order_by":1,"name":"Zhaolei Cui","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhaolei","middleName":"","lastName":"Cui","suffix":""},{"id":148211341,"identity":"dbf9408e-7ee4-4262-9153-618ba75c9621","order_by":2,"name":"Hongmei Xia","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hongmei","middleName":"","lastName":"Xia","suffix":""},{"id":148211342,"identity":"8c956b54-f36a-499e-9b71-21183157f395","order_by":3,"name":"Shan Jiang","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shan","middleName":"","lastName":"Jiang","suffix":""},{"id":148211343,"identity":"8396ba34-c13b-4700-bf37-55ba25987e8e","order_by":4,"name":"Jing Bai","email":"","orcid":"","institution":"Geneplus-Beijing Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Bai","suffix":""},{"id":148211344,"identity":"37f9695a-5886-466a-9cba-670b386e12da","order_by":5,"name":"Zhuo Shao","email":"","orcid":"","institution":"Geneplus-Beijing Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhuo","middleName":"","lastName":"Shao","suffix":""},{"id":148211345,"identity":"9d1b00b9-2170-44f9-b114-b401f0d6a606","order_by":6,"name":"Yang Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIie3RsUrDQBzH8V+opMtF1yui9wophSz2TVzSpV2SUujikIZA4Vzintdwc/MvB5clD1C3iKtCVgfBMy4uiRkL3nc4ErgPuX8OsNmOuMtxRo76fnIBh4aQGSPCDzFmEFnkZltL8BcRRaz5x8NulTtlrTY36fpU7GtCMr/uIv5hvZzcVWWcg0JVVGrruq5P0Ms46yI8CrgndfwIIuVJWkgXPjmZ6iSiiILJp9QrhqfMkNSQcdNLcIiCc08mITPDGzIyhPV/xa/eZlcXkqY5NBRrZ4k2FPbMIm6j6fO7TAXj5csrM39M7Mv7uknm3QcDTnh7I5zat/DX2tmoAVLgLBuy2Waz2f5jXx7UYkiX2huvAAAAAElFTkSuQmCC","orcid":"","institution":"Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2022-10-30 05:59:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2217739/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2217739/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":28627455,"identity":"f21960b9-a63b-4c12-bcb7-ea0cd234b416","added_by":"auto","created_at":"2022-11-03 19:01:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":157440,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe expression of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ehsa-miR-1825\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ein ovarian cancer (OC) cell-derived exosomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) The heatmap shows differences in expressions of differentially expressed microRNAs (DEMIs) in four samples (NOcell, normal ovarian cells; NOexo, exosomes from normal ovarian cells; OCcell, ovarian cancer cells; OCexo, exosomes from ovarian cancer cells).\u003c/p\u003e\n\u003cp\u003e(C) The expression level of four microRNAs based on the TCGA database\u003c/p\u003e\n\u003cp\u003e(D) Kaplan-Meier (KM) survival curves show the overall survival of OC patients with high versus low \u003cem\u003emiR-1825\u003c/em\u003e/miR-1281 expression. (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, and ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.)\u003c/p\u003e","description":"","filename":"Onlinefigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2217739/v1/cdc63e731e777603350f2388.png"},{"id":28627446,"identity":"f9192131-680a-4796-828e-caa4db44aad0","added_by":"auto","created_at":"2022-11-03 19:01:34","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1789922,"visible":true,"origin":"","legend":"\u003cp\u003ePrognostic value of \u003cstrong\u003ethe \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003emiR-1825\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e target \u003c/strong\u003e\u003cem\u003eCLEC5A\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(A) The Venn diagram reveals the intersection of \u003cem\u003emiR-1825\u003c/em\u003etarget genes predicted by five databases.\u003c/p\u003e\n\u003cp\u003e(B) Differential analysis identifies six \u003cem\u003emiR-1825\u003c/em\u003etargets differentially expressed in OC versus normal ovarian tissues. GTEx and TCGA gene expression data are processed and analyzed in UCSC Xena.\u003c/p\u003e\n\u003cp\u003e(C) KM survival curves reveal the overall survival of OC patients with high versus low \u003cem\u003eCLEC5A\u003c/em\u003e expression. As m\u003cem\u003eiR-1825 \u003c/em\u003eis elevated in OC, four upregulated targets are selected for survival analysis (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01, and ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001)\u003c/p\u003e\n\u003cp\u003e(D) Univariate and multivariate Cox regression analyses confirm the independence of \u003cem\u003eCLEC5A\u003c/em\u003e in predicting the overall survival\u003cstrong\u003e \u003c/strong\u003eof OC patients. (CI, confidence interval; HR, hazard ratio)\u003c/p\u003e\n\u003cp\u003e(E) IHC assays show enhanced expression of \u003cem\u003eCLEC5A\u003c/em\u003eprotein in OC versus normal ovarian tissues.\u003c/p\u003e","description":"","filename":"figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2217739/v1/066bf8e88c479b348ce71edd.jpg"},{"id":28627454,"identity":"95f5d40a-854c-41c1-9fd2-e74eb6f795f5","added_by":"auto","created_at":"2022-11-03 19:01:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1630182,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCLEC5A\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-related genes and biofunctions of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCLEC5A\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e in OC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) GO and KEGG enrichment analyses identify 12 genes significantly correlated with \u003cem\u003eCLEC5A\u003c/em\u003e in OC (Spearman’s correlation analysis; Spearman |R| \u0026gt; 0.4, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001).\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(C-D) GSEA analysis identifies 15 \u003cem\u003eCLEC5A\u003c/em\u003e targets and shows their expression differences between low and high \u003cem\u003eCLEC5A\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e OC. All enrichment analyses were performed with clusterProfiler, org.Hs.eg.db, ggstatsplot, enrichplot, and GOplot in R.\u003csup\u003e[73]\u003c/sup\u003e\u003c/p\u003e","description":"","filename":"Onlinefigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2217739/v1/acf65a2c759ab2cbabde4f5f.png"},{"id":28627456,"identity":"2b133ff2-c878-4dbb-b5b9-64118b557d2e","added_by":"auto","created_at":"2022-11-03 19:01:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2149543,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelations of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCLEC5A\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e with tumor-infiltrating lymphocytes in OC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) Correlations of \u003cem\u003eCLEC5A\u003c/em\u003e RNA expression with immune/stromal cell infiltration.\u003c/p\u003e\n\u003cp\u003e(C) Infiltration of 22 immune cell phenotypes in OC using the CIBERSORT algorithm in R (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Their differences between low and high \u003cem\u003eCLEC5A\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e OC are compared with ggplot2 in R (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e(D) Correlations of \u003cem\u003eCLEC5A\u003c/em\u003e with 16 factors associated with M2 tumor-associated macrophage infiltration. The colors represent the magnitude of positive and negative correlations (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e(E) Predicted IC\u003csub\u003e50\u003c/sub\u003e of five common chemotherapy agents against low and high \u003cem\u003eCLEC5A\u003c/em\u003e\u003csup\u003e \u003c/sup\u003eexpression in OC.\u003c/p\u003e","description":"","filename":"Onlinefigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-2217739/v1/d178eb4edb0c0be87a67a1a5.png"},{"id":29716454,"identity":"a4639ecc-2701-43e2-a674-8715fa84150d","added_by":"auto","created_at":"2022-11-30 12:44:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1959431,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2217739/v1/87c5c368-408b-44df-ba25-69daaec6f2b3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A extracellular secretion of miR-1825 wrapped by exosomes increases CLEC5A expression: a potential oncogenic mechanism in ovarian cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian cancer (OC) is the second leading cause of gynecologic cancer death in the world. It is estimated that the prevalence has reached 3.4% and the annual mortality rate has reached 4.7% of all female cases in 2020.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e Most ovarian cancers are often diagnosed at stage III or IV, and these patients only have a 5-year survival rate of \u0026lt;\u0026thinsp;25%.\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e Comprehensive surgical staging and debulking are preferred, followed by systemic chemotherapy according to NCCN Guidelines on Treatment of OC (Version 3.2021, [DB/OL]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.nccn.org\u003c/span\u003e\u003cspan address=\"http://www.nccn.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). However, more than 80% of late-stage tumors initially responsive to conventional treatment develop resistance over time.\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003eTherefore, there is an urgent need to identify effective biomarkers for early diagnosis based on a better understanding of the underlying molecular mechanisms of ovarian cancer development.\u003c/p\u003e \u003cp\u003eExosomes are extracellular vesicles (EVs) actively secreted by cells with an approximately 40\u0026ndash;160 nm in diameter, which have been implicated in intercellular communication by carrying RNA, lipids, proteins, and other bioactive substances. They can deliver curcumin to activated myeloid cells and deliver doxorubicin specifically to tumor tissues, leading to growth inhibition of tumors without overt toxicity.\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e Its RNA content varies dramatically according to the cell types of origin, reflecting one of the reasons for exosome heterogeneity.\u003csup\u003e[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMicroRNAs, which can inhibit protein synthesis by targeting the complementary sequences located at the 3'-end untranslated regions of messenger RNAs (mRNAs),\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e play an important role in regulating cancer progression. Exosomal microRNAs, which are microRNAs encapsulated by exosomes, can promote tumor progression by enhancing mesothelial-to-mesenchymal transition, conferring drug resistance, inducing vascular permeability and angiogenesis, inducing macrophage M2 polarization, and participating in tumor immune escape by delivering immunosuppressive molecules and factors; It has been reported that exosomal microRNAs can also inhibit tumor progression by reversing drug resistance and increasing tumor chemosensitivity. The potential role of exosomal microRNAs as biomarkers in cancer diagnosis and prognosis has been noted in several tumor types including ovarian cancer.\u003csup\u003e[\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15 CR16 CR17\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e Upregulation of \u003cem\u003emiR-1825\u003c/em\u003e has been shown to be able to inhibit the progression of glioblastoma and promote proliferation of naturally quiescent adult cardiomyocytes. However, the role of \u003cem\u003emiR-1825\u003c/em\u003e and its target gene in OC has not been explored so far.\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eC-type lectin domain family 5 member A (\u003cem\u003eCLEC5A\u003c/em\u003e), a member of C-type lectin/C-type lectin-like domain (CTL/CTLD) superfamily, also named C-type lectin superfamily member 5 (CLECSF5) and myeloid DAP12-associating lectin 1 (MDL1). Members of CTL/CTLD superfamily share a typical protein fold pattern and have diverse functions, such as cell adhesion, cell-cell signaling, glycoprotein turnover, and roles in inflammation and immune response. \u003cem\u003eCLEC5A\u003c/em\u003e has been proven to promote brain glioblastoma tumorigenesis and gastric cancer cells proliferation by regulating PI3K/Akt signaling.\u003csup\u003e[\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e However, the mechanism by which \u003cem\u003eCLEC5A\u003c/em\u003e regulates OC awaits further clarification.\u003c/p\u003e \u003cp\u003eThe goals of this study were three-folded: 1) to determine the expression pattern and prognostic value of \u003cem\u003emiR-1825\u003c/em\u003e in OC exosomes; 2) to confirm \u003cem\u003eCLEC5A\u003c/em\u003e as a \u003cem\u003emiR-1825\u003c/em\u003e target; 3) to assess the performances of the \u003cem\u003eCLEC5A\u003c/em\u003e gene in predicting overall survival and TIME characteristics for labeling patients who might benefit from immuno- or chemotherapy. In this study, we performed a bioinformatics analysis of the expression patterns of exosomal miRNAs and focused on its target gene \u003cem\u003eCLEC5A\u003c/em\u003e. We found that \u003cem\u003emiR-1825\u003c/em\u003e, as an tumor-suppressor, was highly enriched in OC exosomes, and the downstream oncogenic target gene \u003cem\u003eCLEC5A\u003c/em\u003e was highly expressed in OC cells. \u003cem\u003eMiR-1825\u003c/em\u003e affected the expression of \u003cem\u003eCLEC5A\u003c/em\u003e and the latter further led to the change of immune environment. Its ability in transforming immune environment may be an important mechanism in the development of OC. The Suppression of draining miRNAs through exosomes from OC cells may be a suitable direction for anti-tumor therapy as decreased expression of \u003cem\u003emiR-1825\u003c/em\u003e in OC cells can promote tumor progression. We also noted that \u003cem\u003eCLEC5A\u003c/em\u003e could promote the development of an immune microenvironment in OC and thus has a potential role in the prognosis of OC.\u003c/p\u003e "},{"header":"Methods","content":"\u003ch3\u003eData Retrieval And Preprocessing\u003c/h3\u003e\n\u003cp\u003eAffymetrix miRNA microarray data from OC exosomes and cells were available from Gene Expression Omnibus (GEO; series GSE76449).\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e Exosomal and original samples of chemo-sensitive OC cells and normal ovarian cells (n\u0026thinsp;=\u0026thinsp;16) were included to rule out the influence of chemotherapy on prediction results. RNA-seq data from normal ovarian tissues were obtained from Genotype-Tissue Expression (GTEx). RNA-sequencing (RNA-seq) data and clinical data from OC patients were downloaded from GEO (series GSE9891), Clinical Cancer Research Online (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://clincancerres.aacrjournals.org/\u003c/span\u003e\u003cspan address=\"http://clincancerres.aacrjournals.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e),\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e International Cancer Genome Consortium (ICGC)\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e, The Cancer Genome Atlas (TCGA)\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e, as detailed below.\u003c/p\u003e \u003cp\u003eBioinformatics analyses of RNA-seq data from TCGA patients were performed using the UCSC bioinformatic pipeline (TOIL RNA-seq). Each dataset was processed identically after removing unavailable data. Clinical data from TCGA were prepared using the TCGA-GDC(Genomic Data Commons) server for subsequent analysis.\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFinally, all datasets underwent identical processing to achieve an average expression level of samples from the same patient and unavailable data were deleted (NA).\u003c/p\u003e\n\u003ch3\u003eIdentification Of Differentially Expressed Rna\u003c/h3\u003e\n\u003cp\u003eIn this experiment, RNA-seq data were obtained from TCGA and GTEx. Differentially expressed miRNAs (DEMIs) between exosomal and original samples of OC cells were identified with limma R Bioconductor package (version 3.48.3, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and log2-fold change [logFC]\u0026thinsp;\u0026gt;\u0026thinsp;4, Student's t-test).\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e Differentially expressed mRNAs (DEMs) were screened using the same method (adjusted P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and logFC\u0026thinsp;\u0026gt;\u0026thinsp;3). A boxplot was generated with ggplot2 in R.\u003c/p\u003e\n\u003ch3\u003eTarget Gene Prediction\u003c/h3\u003e\n\u003cp\u003eFive target gene prediction databases were employed to predict the downstream targets of \u003cem\u003emiR-1825\u003c/em\u003e, including TargetScan 7.2, miRDB, TarBasev.8, miRmap, and miRwalk 3.0. Intersections among the five databases were regarded as \u003cem\u003emiR-1825\u003c/em\u003e targets.\u003csup\u003e[\u003cspan additionalcitationids=\"CR31 CR32 CR33\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eSurvival Analysis\u003c/h3\u003e\n\u003cp\u003eSurvival data (age, clinical stage, histologic grade, survival status, and length of overall survival) of OC patients were collected from TCGA, GEO, and ICGC and merged with gene expression data. We assessed the prognostic ability of miRNAs or \u003cem\u003eCLEC5A\u003c/em\u003e in OC using univariate and multivariate Cox regression hazard analysis combined with Kaplan-Meier survival curves.\u003c/p\u003e\n\u003ch3\u003eFunction Enrichment Analysis\u003c/h3\u003e\n\u003cp\u003eWe performed Gene Ontology Biological Process (GOBP) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses with clusterProfiler in R to identify \u003cem\u003eCLEC5A\u003c/em\u003e targets (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and explore mechanisms for \u003cem\u003eCLEC5A\u003c/em\u003e\u0026rsquo;s role in OC.\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e Then, Gene Set Enrichment Analysis (GSEA) was utilized to confirmed whether there were target genes not selected by GO or KEGG analyses (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and false discovery rate [FDR]\u0026thinsp;\u0026lt;\u0026thinsp;0.25) and characterize the activity of KEGG pathways between low and high \u003cem\u003eCLEC5A\u003c/em\u003e expression group in OC, as described in detail elsewhere.\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eEvaluation of correlation with immune characteristics of\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eCLEC5A\u003c/span\u003e \u003cb\u003ein OC\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe assessed correlations of \u003cem\u003eCLEC5A\u003c/em\u003e gene expression with immune cell infiltrates and expressions of immune suppressors to explore the ability of \u003cem\u003eCLEC5A\u003c/em\u003e to predict TIME characteristics in low and high \u003cem\u003eCLEC5A\u003c/em\u003e expression in OC. TCGA RNA-Seq expression profiles of immune and stromal cells were utilized. Tumor-infiltrating lymphocytes (TILs) and stromal cells were identified with ESTIMATE (Estimation of Stromal and Immune cells in malignant Tumor tissues using Expression data) in R. Correlations of \u003cem\u003eCLEC5A\u003c/em\u003e with immune/stromal cell infiltration were assessed, and the results were validated in a GEO cohort of 276 qualified OC cases whose expression and survival data were available for review (GSE9891). This cohort was also used for subsequent immune cell infiltration analysis.\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe infiltration of 22 immune cell subpopulations in OC tissues was estimated using the CIBERSORT algorithm that can accurately quantify TILs in biopsied tumor tissues and the LM22 signature matrix file containing 22 immune cell reference profiles from TCGA and GEO.\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e Patients were categorized into the low and high \u003cem\u003eCLEC5A\u003c/em\u003e expression groups according to the cutoff of \u003cem\u003eCLEC5A\u003c/em\u003e gene expression. The immune cell landscape was compared between the two groups. Sixteen tumor immune suppressors have been shown to exert suppressive effects on solid tumors.\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e Among them, 11 (IL6, TNF, IFNG, EGF, MCH-I, CD96, LIR1, PDCD1, PDCD1LG2, CD80, and CD86) frequently reported in OC were selected and their expressions were compared between the two groups.\u003c/p\u003e\n\u003ch3\u003eEstimation Of Chemotherapy Response\u003c/h3\u003e\n\u003cp\u003e We selected five agents (cisplatin, docetaxel, doxorubicin, gemcitabine, and paclitaxel) from 22 recommended options in the 2020 NCCN clinical practice guidelines in oncology on ovarian cancer.\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e The predicted IC50 was estimated with pRRophetic (version 0.5; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0107468\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0107468\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) in R and compared between low and high \u003cem\u003eCLEC5A\u003c/em\u003e expression OC patients from TCGA.\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eClinical Specimens\u003c/h3\u003e\n\u003cp\u003eBetween May 2019 and May 2021, 9 patients who had pathologically confirmed OC and underwent radical excision at Fujian Medical University Cancer Hospital (or Fujian Cancer Hospital) without prior therapy were selected. 7 OC and 2 peritumoral tissue specimens were collected, flash frozen in liquid nitrogen, and reviewed independently by two senior pathologists. The study protocol was approved by the Ethics Committee of Fujian Cancer Hospital.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry (Ihc)\u003c/h3\u003e\n\u003cp\u003eIHC analysis was performed as previously described.\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e Briefly, formalin-fixed paraffin-embedded sections were dewaxed, dehydrated and rehydrated. The slides were incubated overnight at 4\u0026deg;C with an anti-\u003cem\u003eCLEC5A\u003c/em\u003e antibodies (ab203200, Abcam, China, 1:500). Then incubate at 37\u0026deg;C with an secondary antibodies (ab7090, Abcam, China, 1:500).Immunostaining was performed using a SABC(Strept Avidin-Biotin Complex) kit(SA0025,Solarbio, China). Next, the slides were counterstained with Mayer hematoxylin solution (Solarbio, China) for nuclear staining. Images were obtained using VANOX microscope (Olympus, Japan) and scored as 0 points (no staining), 1 point (light yellow), 2 points (brownish yellow), and 3 points (brown). For each specimen, fields were randomly selected, and the proportion of \u003cem\u003eCLEC5A\u003c/em\u003e-positive (\u003cem\u003eCLEC5A\u003c/em\u003e+) cells was calculated and scored (1 point, 0%-25% of \u003cem\u003eCLEC5A\u003c/em\u003e\u0026thinsp;+\u0026thinsp;cells; 2 points, 26%-50% of \u003cem\u003eCLEC5A\u003c/em\u003e\u0026thinsp;+\u0026thinsp;cells; 3 points, 51%-75% of \u003cem\u003eCLEC5A\u003c/em\u003e\u0026thinsp;+\u0026thinsp;cells; 4 points, 76%-100% of \u003cem\u003eCLEC5A\u003c/em\u003e\u0026thinsp;+\u0026thinsp;cells). Specimens with a pathological IHC score greater than the cutoff were identified as high \u003cem\u003eCLEC5A\u003c/em\u003e\u0026thinsp;+\u0026thinsp;OC, or otherwise, low \u003cem\u003eCLEC5A\u003c/em\u003e\u0026thinsp;+\u0026thinsp;OC.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eCategorical variables were expressed as numbers (percentage) and compared using Spearman\u0026rsquo;s test. Overall survival data were analyzed using Kaplan-Meier survival curves and compared using the log-rank test. Continuous variables following normal distribution were presented in mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of measurement (SEM) and compared using the Student\u0026rsquo;s t-test. Correlations of \u003cem\u003eCLEC5A\u003c/em\u003e gene expression with immune/stromal cell infiltration were assessed using Spearman\u0026rsquo;s correlation test. All statistical analyses were performed using R 4.1.0, and a two-tailed P-value of \u0026lt;\u0026thinsp;0.05 was deemed statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003e1.\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eMiR-1825\u003c/span\u003e \u003cb\u003ewas abundant in exosomes from ovarian cancer cells and associated with improved prognosis.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe explored expression patterns during four group samples using the GSE76449 dataset:1) normal ovarian cells;2) exosomes outflowed from normal ovarian cells;3) ovarian cancer cells and 4) exosomes outflowed from ovarian cancer cells. Then identified DEMIs between the four groups of samples. Nineteen microRNAs were screened out, The result indicated that microRNAs exhibited a specific distribution pattern in exosomes and their original cells. The expression pattern of 11/19 DEMIs (\u003cem\u003emiR-30c-5p, miR-99b-5p, miR-10a-5p, miR-125a-5p, miR-27a-5p, miR-151b, let-7e-5p, miR-151a-5p, miR-4521, miR-15a-5p, and miR-28-5p\u003c/em\u003e) was not correlated with cancer, both high expression in no matter cancer cells or normal cells. The expression pattern of \u003cem\u003emiR-6216\u003c/em\u003e, \u003cem\u003emiR-1246\u003c/em\u003e, \u003cem\u003emiR-122-5p\u003c/em\u003e, and \u003cem\u003emiR-1290\u003c/em\u003e was irrelevant with cancer too, they were always highly expressed in exosomes which outflowed no matter from OC cells or normal ovarian cells. (Fig.\u0026nbsp;1A) This indicated that their expression modes were cell-specific or exosome-specific but not ovarian cancer exosome-specific. Interestingly, \u003cem\u003emiR-1281, miR-1825, miR-6877-3p\u003c/em\u003e, and \u003cem\u003emiR-3921\u003c/em\u003e expressions were upregulated in exosomes outflowed from ovarian cancer cells, and significantly downregulated in the other three samples (Fig.\u0026nbsp;1B), as supported by a previous study.\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurther, the prognostic significance of \u003cem\u003emiR-1281\u003c/em\u003e, \u003cem\u003emiR-1825\u003c/em\u003e, and \u003cem\u003emiR-6877-3p\u003c/em\u003e was evaluated in the high versus low expression groups using TCGA survival data. \u003cem\u003eMiR-3921\u003c/em\u003e was ruled out due to the absence of \u003cem\u003eMiR-3921\u003c/em\u003e expression in most OC samples. (Fig.\u0026nbsp;1C) In KM survival analysis, \u003cem\u003emiR-1825\u003c/em\u003e upregulation in OC cells was correlated with improved overall survival (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1D). It might act as a tumor suppressor in OC.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eCLEC5A\u003c/span\u003e \u003cb\u003ewas the target gene of\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003emiR-1825\u003c/span\u003e \u003cb\u003eand had a prognostic value\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe performed target gene predictions to identify \u003cem\u003emiR-1825\u003c/em\u003e targets using TargetScan7.2, miRDB, TarBase v.8, miRmap, and miRwalk3.0. The results displayed 52 genes (Fig.\u0026nbsp;2A). Differential expression analysis for 52 target genes using limma method revealed that the mRNA expression levels of \u003cem\u003eCACNB2\u003c/em\u003e and \u003cem\u003eKIT\u003c/em\u003e were downregulated and those of \u003cem\u003eN4BP3, CLEC5A, NOTUM\u003c/em\u003e, and \u003cem\u003eDCDC2\u003c/em\u003e were upregulated in the tumor group from TCGA database in comparison with normal ovarian samples from the GTEx database (|logFC| \u0026gt;3 and adjusted p value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;2B).\u003c/p\u003e \u003cp\u003eDue to the tumor-suppressive effect of \u003cem\u003emiR-1825\u003c/em\u003e, the prognostic potential of the four elevated genes (\u003cem\u003eN4BP3, CLEC5A, NOTUM\u003c/em\u003e, and \u003cem\u003eDCDC2\u003c/em\u003e) was assessed. KM curves showed that among the four genes, \u003cem\u003eCLEC5A\u003c/em\u003e appeared to be a prognostic potential marker for OC, as validated using the validation cohort (GSE9891 and ICGC dataset OV-AU) (Fig.\u0026nbsp;2C), and was significantly associated with worse overall survival of OC patients (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, \u003cem\u003eCLEC5A\u003c/em\u003e could serve as a prognostic biomarker independent of clinicopathological parameters (age, clinical stage, and histologic grade), as validated using GSE9891 and OV-AU validation cohorts (Fig.\u0026nbsp;2D). In IHC assays, \u003cem\u003eCLEC5A\u003c/em\u003e protein expression was significantly increased in OC versus normal ovarian tissues (Fig.\u0026nbsp;2E).\u003c/p\u003e \u003cp\u003e \u003cb\u003e3\u003c/b\u003e.\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eCLEC5A\u003c/span\u003e \u003cb\u003ewas related to Immune Microenvironment\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo clarify the functions of \u003cem\u003eCLEC5A\u003c/em\u003e expression signatures associated with OC, we performed biological processes of GO and KEGG pathways enrichment analyses of genes highly correlated to \u003cem\u003eCLEC5A\u003c/em\u003e based on the TCGA dataset. As shown in Fig.\u0026nbsp;3A-B, the intersection of GO terms and KEGG pathways showed that a proportion of highly correlated genes was associated with immune response that plays an important role in tumor inhibition and promotion. These results suggested that immune alterations might contribute to OC occurrence and development. However, the mechanism by which \u003cem\u003eCLEC5A\u003c/em\u003e plays in immunity in OC is not clear.\u003c/p\u003e \u003cp\u003eTo further verify the results of GO/KEGG enrichment analyses, we conducted a GSEA with the low and high \u003cem\u003eCLEC5A\u003c/em\u003e expression datasets. GSEA analyses showed significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the enrichment of immune-related pathways and biological processes (Fig.\u0026nbsp;3C-D). Interestingly, \u003cem\u003eCLEC5A\u003c/em\u003e also seems to activate the PI3K\u0026thinsp;\u0026minus;\u0026thinsp;Akt pathway in OC which has been confirmed by experiments in brain glioblastoma by Hong-Wei Fan et al. Given the importance of the PI3K\u0026thinsp;\u0026minus;\u0026thinsp;Akt signaling pathway and the impact of immune on OC, we speculate that activated PI3K\u0026thinsp;\u0026minus;\u0026thinsp;Akt signaling pathway may contribute in part to the development of immune environment in OC.\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e4.High level expression of\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eCLEC5A\u003c/span\u003e \u003cb\u003eled to enhanced M2 macrophage infiltration\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo investigate in which way the interaction between \u003cem\u003eCLEC5A\u003c/em\u003e and immune microenvironment plays in OC, R package ESTIMATE was used to examine correlations between immune cell/stromal cells infiltration levels and \u003cem\u003eCLEC5A\u003c/em\u003e level. Notably, we observed a positive correlation between \u003cem\u003eCLEC5A\u003c/em\u003e level and immune cell/stromal cell infiltration. A similar result was obtained based on the GSE9891 dataset (Fig.\u0026nbsp;4A-B). These results indicated that \u003cem\u003eCLEC5A\u003c/em\u003e might play a role in mediating the immune response and immune cells/stromal cells infiltration in ovarian tumors. To further explore which immune cell subtype correlated to \u003cem\u003eCLEC5A\u003c/em\u003e expression, we utilized CIBERSORT to calculate the infiltration levels of 22 immune cell subtypes, including B cells (naive B cell, memory B cell, and plasma cell), T cells [CD8 T cell, naive CD4 T cell, memory resting CD4 T cell, memory activated CD4 T cell, follicular helper T cell (Tfh), regulatory T cells (Tregs), and gamma delta T cell], natural killer (NK) cells (resting NK T cell and activated NK cell), and myeloid subsets [monocyte, MO macrophage, M1 macrophage, M2 macrophage, and resting dendritic cell (DC), activated DC, resting mast cell, activated mast cell, eosinophils, and neutrophil]. After integrating the CIBERSORT\u0026rsquo;s results (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) based on the TCGA and GEO databases, we found that the proportions of M2 macrophages were higher in the \u003cem\u003eCLEC5A\u003c/em\u003e high expression group than those in the \u003cem\u003eCLEC5A\u003c/em\u003e low expression group. In contrast, the plasma cells and Tfh cells were lower in the \u003cem\u003eCLEC5A\u003c/em\u003e high expression group (Fig.\u0026nbsp;4C).\u003c/p\u003e \u003cp\u003eThe accumulation of M2 macrophages has been reported as a pivotal part in promoting tumor progression.\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e \u003cem\u003eCLEC5A\u003c/em\u003e expression level may affect the function of M2 tumor-associated macrophages (TAMs). We thus analyzed the correlations between \u003cem\u003eCLEC5A\u003c/em\u003e expression level and 16 factors involved in TAMs-assisting solid tumors. In accordance with our presumption, \u003cem\u003eCLEC5A\u003c/em\u003e was found to be positively correlated with inhibiting factors based on the TCGA and GEO database (Fig.\u0026nbsp;4D). These results suggest that raising \u003cem\u003eCLEC5A\u003c/em\u003e expression can promote tumors via TAMs.\u003c/p\u003e \u003cp\u003eCollectively, \u003cem\u003eCLEC5A\u003c/em\u003e was strongly correlated with the immune environment in OC and its expression level could affect the type of immune cells infiltrated in the tumor, such as significant accumulation of M2 macrophages followed with increased \u003cem\u003eCLEC5A\u003c/em\u003e expression. One possible explanation for the accumulation of M2 macrophages might be that activated PI3K\u0026thinsp;\u0026minus;\u0026thinsp;Akt signaling pathway could cause macrophage M2 polarization.\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003e5.new Suggestions For Clinical Drug Sensitivity\u003c/h3\u003e\n\u003cp\u003eWe then evaluated the responses of \u003cem\u003eCLEC5A\u003c/em\u003e high expression group and low expression group to 5 chemotherapeutic drugs that were included in the list of built-in R package pRRophetic and recommended chemotherapeutic regimens named cisplatin, docetaxel, doxorubicin, gemcitabine, and paclitaxel. Interestingly, the high \u003cem\u003eCLEC5A\u003c/em\u003e expression group showed more sensitivity to paclitaxel, gemcitabine, and docetaxel with lower IC50. To the contrary, cisplatin and doxorubicin were more sensitive in the low \u003cem\u003eCLEC5A\u003c/em\u003e expression group (Fig.\u0026nbsp;4E). This finding gives physicians a hint about offering OC patients individualized therapy.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we described miRNAs transported by exosomes in the context of OC, explored their influence on tumor microenviroment, and evaluated their potential prognostic value. We hypothesize that draining \u003cem\u003emiR-1825\u003c/em\u003e from exosomes leads to elevated expression of intracellular target gene \u003cem\u003eCLEC5A\u003c/em\u003e. In addition, we demonstrated that \u003cem\u003eCLEC5A\u003c/em\u003e not only could provide value as a prognostic factor, but also present a direction for immunotherapy and an efficacy reference for chemotherapy drug treatment.\u003c/p\u003e \u003cp\u003eA plethora of studies have implied that exosomal miRNAs can serve as vehicles for intercellular communication by regulating the biological behaviors of target tumor cells to promote proliferation, metastasis, and angiogenesis, and conferring radioresistance and drug-resistance of cancer cells.\u003csup\u003e[\u003cspan additionalcitationids=\"CR47 CR48 CR49 CR50\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e However, the mechanisms relating to the regulation of origin cells secreting exosomes is largely unknown until recently. It has been illustrated that miRNAs inhibition promoted oncogenic behavior by leading cancer cells to release more exosomes.\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e Here, we showed that \u003cem\u003emiR-1825\u003c/em\u003e was abundant in exosomes derived from OC cells, but presented in low levels in the other three groups(normal ovarian cells, exosomes outflowed from normal ovarian cells, and ovarian cancer cells). \u003cem\u003eMiR-1825\u003c/em\u003e also showed a prognostic value as a tumor suppressor. Therefore, we suggest that OC cells secrete the \u003cem\u003emiR-1825\u003c/em\u003e into the extracellular environment via exosomes to maintain their tumorigenic phenotype.\u003c/p\u003e \u003cp\u003eC-type lectin domain family 5 member A (\u003cem\u003eCLEC5A\u003c/em\u003e), a member of C-type lectin/C-type lectin-like domain (CTL/CTLD) superfamily, with high expression level and ability to promote cancer, has been confirmed in several tumors .\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/sup\u003e However, its expression level and function in OC have not been reported previously. In our cohort, we found that \u003cem\u003eCLEC5A\u003c/em\u003e acted as the target gene of \u003cem\u003emiR-1825\u003c/em\u003e and was significantly upregulated in OC patients. The upregulation of \u003cem\u003eCLEC5A\u003c/em\u003e was further linked to poor OS of OC patients and could serve as a risk factor. These results indicated that \u003cem\u003eCLEC5A\u003c/em\u003e has prognostic value in OC and could be a potential biomarker for OC diagnosis.\u003c/p\u003e \u003cp\u003eThere has been accumulated evidence that the immune microenvironment contributes to the OC development and progression; recent years immune checkpoint inhibitors have shown remarkable promise in many types of cancers. However, there are currently no approved immune therapies for OC.\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e Other significant findings of our functional analyses were that \u003cem\u003eCLEC5A\u003c/em\u003e played a role in tumor-immune interactions and that \u003cem\u003eCLEC5A\u003c/em\u003e expression was correlated with the immune infiltration level in OC. Our results revealed that there was a significant positive correlation between \u003cem\u003eCLEC5A\u003c/em\u003e expression level and the level of infiltration of M2 macrophages and a negative correlation between \u003cem\u003eCLEC5A\u003c/em\u003e expression level and the level of infiltration of Tfh cells in OC.\u003c/p\u003e \u003cp\u003eM2 macrophages (also called alternatively activated macrophages) have contributed to the progression of many tumors, including OC.\u003csup\u003e[\u003cspan additionalcitationids=\"CR56 CR57 CR58 CR59\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/sup\u003e It has been reported that M2 macrophages are part of TAMs, a view that TAMs are not completely following the M1 and M2 subtypes; they are in general M2-like.\u003csup\u003e[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]\u003c/sup\u003e Increased infiltration of M2 macrophages may be one of the mechanisms that \u003cem\u003emiR-1825/CLEC5A\u003c/em\u003e promotes the development of OC. Recent studies also validate our view that exosomes can deliver tumor suppressor microRNAs to induce M2 macrophage polarization and promote tumor progression.\u003csup\u003e[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]\u003c/sup\u003e Our study also demonstrated a positive correlation between the high expression level of \u003cem\u003eCLEC5A\u003c/em\u003e and the process of tumor-associated macrophages (TAMs) promoting solid tumors.\u003c/p\u003e \u003cp\u003eIt has been found that activating the PI3K/Akt signaling pathway can promote M2-type polarization in macrophages.\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]\u003c/sup\u003e Aberrant activation of this signaling network is one of the most frequent events in human cancer and disconnects the control of cell growth, survival, and metabolism from exogenous growth stimuli.\u003csup\u003e[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]\u003c/sup\u003e PI3K/Akt signaling pathway has been shown to exert a pivotal role as an immunomodulator. Blockade of the PI3K might maximize the IFN-γ-mediated anti-tumor effect. To the contrary, activating PI3K/Akt signaling in the neoplastic epithelium can promote nuclear translocation of β-catenin, cellular proliferation, and resistance to apoptosis. Inhibition of PI3K/Akt signaling with immunomodulatory agents may provide a new therapeutic approach for cancer.\u003csup\u003e[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]\u003c/sup\u003e In our study, activation of PI3K/Akt pathway and increased infiltration of M2 macrophages were associated with elevated expression of \u003cem\u003eCLEC5A\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eTfh cells are a subset of CD4\u0026thinsp;+\u0026thinsp;T cells that specialize in helping B cells to produce antibodies in the face of antigenic challenge. Their presence in tumor tissue is often associated with a better outcome in several solid tumor entities.\u003csup\u003e[\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]\u003c/sup\u003e It has been shown to be positively associated with the long-term survival of humans with breast cancer or non-small cell lung cancer. In our study, high level expression of \u003cem\u003eCLEC5A\u003c/em\u003e led to reduced infiltration of Tfh cells, which might be a potential molecular mechanism of protecting tumor by inhibiting ectopic lymphoid structures (ELSs), a site of recruitment for CD8\u0026thinsp;+\u0026thinsp;T cells, NK cells, and macrophages that engage in anti-tumor immunity, or by reducing anti-tumor antibody responses by B cells. However, there is limited data available regarding Tfh cells supporting anti-tumor antibody responses.\u003csup\u003e[\u003cspan additionalcitationids=\"CR71\" citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTaken together, our results indicate that efflux of \u003cem\u003emiR-1825\u003c/em\u003e may trigger elevated expression of intracellular target genes and thus induce immune-related behaviors in tumors that result in tumor progression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge partial support of projects by, the National Natural Science Foundation of China (81873045), the Natural Science Foundation of Fujian Province of China (2020J011115), and the Medicine Innovation Foundation of Fujian Province of China (2020CXB007).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by grant from the National Natural Science Foundation of China (81873045)，the Natural Science Foundation of Fujian Province of China (2020J011115) and the Medicine Innovation Project of Fujian Province of China (2020CXB007).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study were included in this published article and its additional files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYS and QW were responsible for conception, analysis and data interpretation. ZC contributed substantially to the conception, design, data interpretation, and revision of the work. All authors wrote different parts of the manuscript, and all read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the Fujian Cancer Hospital(Reference number: K2022-002-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they both agree to publish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSung H, Ferlay J, Siegel RL, et al. 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Bioinformatics. 2015. 31(17): 2912-4.\u003c/li\u003e\n\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":"Exosome, microRNA-1825, C-type lectin domain family 5 member A, PI3K-Akt pathway, tumor immune microenvironment","lastPublishedDoi":"10.21203/rs.3.rs-2217739/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2217739/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eOvarian cancer (OC) is an important cause of gynecologic cancer-related mortality worldwide. Exosomal \u003cem\u003emiR-1825\u003c/em\u003e and its target gene \u003cem\u003eCLEC5A\u003c/em\u003e have been shown to have a significant association with tumorigenesis in other cancers.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eExosomal \u003cem\u003emiR-1825\u003c/em\u003e expression and its ability in overall survival(OS) prediction were determined using GEO and TCGA data. Target genes of \u003cem\u003emiR-1825\u003c/em\u003e were searched in five prediction databases, and differentially expressed prognostic genes were identified. We performed GO and KEGG enrichment analyses. The ability of \u003cem\u003eCLEC5A\u003c/em\u003e in OS prediction was assessed using univariate and multivariate Cox regression and Kaplan-Meier curves. Immunohistochemistry was applied to validate the \u003cem\u003eCLEC5A\u003c/em\u003e expression pattern in OC. The immune cell landscape was compared using the CIBERSORT algorithm, and the results were validated in a GEO cohort. Finally, the predicted IC50 of five common chemotherapy agents was compared.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003e \u003cem\u003eMiR-1825\u003c/em\u003e was elevated in exosomes derived from OC cells and served as a tumor suppressor. The \u003cem\u003eCLEC5A\u003c/em\u003e gene was confirmed as a target of \u003cem\u003emiR-1825\u003c/em\u003e, whose upregulation was correlated with a poor prognosis. M2 macrophage infiltration was significantly enhanced in \u003cem\u003eCLEC5A\u003c/em\u003e high expression group, and T follicular helper cell infiltration was reduced in it. The predicted IC50 for cisplatin and doxorubicin was higher in \u003cem\u003eCLEC5A\u003c/em\u003e high expression group, and that for docetaxel, gemcitabine, and paclitaxel was lower.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003e \u003cem\u003eMiR-1825\u003c/em\u003e may promote OC progression by increasing \u003cem\u003eCLEC5A\u003c/em\u003e expression through exosome-mediated efflux from tumor cells and could be a promising biomarker for OC.\u003c/p\u003e","manuscriptTitle":"A extracellular secretion of miR-1825 wrapped by exosomes increases CLEC5A expression: a potential oncogenic mechanism in ovarian cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-03 19:01:29","doi":"10.21203/rs.3.rs-2217739/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":"ea7e4624-ea9e-4ccf-8f5b-7275c07731bd","owner":[],"postedDate":"November 3rd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-11-30T12:44:17+00:00","versionOfRecord":[],"versionCreatedAt":"2022-11-03 19:01:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2217739","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2217739","identity":"rs-2217739","version":["v1"]},"buildId":"ovgMLWzx4BRi8jVfwJvTw","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}