Abstract

   Background: FAM83D (family with sequence similarity 83, member D) is of
   particular interest in tumorigenesis and tumor progression. Ovarian
   cancer is the leading cause of cancer-related death in women all over
   the world. This study aims to research the association between FAM83D
   and ovarian cancer (OC).

   Methods: The gene expression data of OC and normal samples
   ([32]GSE81873 and [33]GSE27651) was downloaded from Gene Expression
   Omnibus (GEO) dataset. The bioinformatics analysis was performed to
   distinguish two differentially expressed genes (DEGs), prognostic
   candidate genes and functional enrichment pathways.
   Immunohistochemistry (IHC), Quantitative Real-time PCR (qPCR), and
   luciferase reporter assays were utilized for further study.

   Results: There were 56 DEMs and 63 DEGs in cancer tissues compared to
   normal tissues. According to the km-plot software, hsa-miR-142-3p and
   FAM83D were associated with the overall survival of patients with OC.
   Besides, Multivariate analysis included that hsa-miR-142-3p and FAM83D
   were independent risk factors for OC patients. Furthermore, qPCR
   demonstrated that miRNA-142-3p and FAM83D were differentially expressed
   in normal ovarian tissues (NOTs) and ovarian cancer tissues (OCTs). IHC
   results indicated that FAM83D was overexpressed in OCTs compared with
   NOTs. Last but not least, luciferase reporter assays verified that
   FAM83D was a direct target of hsa-miRNA-142-3p in OC cells.

   Conclusions: The prognostic model based on the miRNA-mRNA network could
   provide predictive significance for the prognosis of OC patients, which
   would be worthy of clinical application. Our results concluded that
   miR-142-3p and its targets gene FAM83D may be potential diagnostic and
   prognostic biomarkers for patients with OC.

   Keywords: microRNA-142-3p, ovarian cancer, GEO, FAM83D, IHC

INTRODUCTION

   Ovarian cancer (OC) is one of the main causes of female death. 70% of
   patients are in the advanced stage (clinical stage III ~ IV), and
   peritoneal metastasis is the characteristic metastasis symptom of
   patients with advanced OC. Although the incidence rate is not high, the
   mortality rate is 2.9%, which is the top ten of female malignant tumor
   mortality. For OC, the current standard treatment is not optimistic
   [[34]1]. One reason is that most patients are diagnosed only in the
   late stage of the disease. Standard treatment for OC usually includes
   surgery and platinum chemotherapy. Despite available treatments, the
   recurrence rate of OC is still high, and about 75% of advanced patients
   are incurable [[35]2, [36]3]. Genomics research shows that there is no
   regulated gene mutation, and many clinical trials have failed to bring
   lasting clinical benefits [[37]4]. Molecular typing of OC through
   molecular expression differences, exploring the microenvironment
   characteristics of different molecular subtypes of OC, and formulating
   accurate treatment may be a feasible strategy to improve the dilemma of
   OC treatment.

   Since the discovery of lin-4 and let-7, the founding members of the
   microRNA (miRNA) family, hundreds of miRNAs have been found in viruses,
   plants, and animals by molecular cloning and bioinformatics methods
   [[38]5]. There are more than 1000 known human miRNAs, which control
   more than 50% of mammalian protein-coding genes. MiRNAs can be
   overexpressed or inhibited in different diseases. It is a promising
   therapeutic research field to inhibit or replace microRNAs [[39]6].
   Although microRNA has only 20 nucleotides, it plays a key role in
   biological function by targeting plenty of mRNAs [[40]7]. For example,
   one study found that miRNA-424-5p regulated ferroptosis by targeting
   Acyl-CoA Synthetase Long-Chain Family Member 4 in OC cells and
   indicated a potential therapeutic target for OC [[41]8]. Wu et al.
   found that the downregulated microRNA-1301-3p inhabited lung carcinoma
   cell proliferation and migration and has a strong negative correlation
   with Polymerase I and transcript release factor [[42]9]. Another study
   also indicated the expression level of miR-200-b control PD-L1
   expression in lung carcinoma cells. Furthermore, it may function as a
   potential biomarker for PD-L1 expression in lung cancer patients
   [[43]10]. These studies indicated that microRNAs may be related to the
   progression of cancer, and their mechanisms may take part in the
   pathogenesis of tumors via controlling cancer-associated genes.

   In this article, DEGs and DEMs were selected by researching 1 OC mRNA
   microarray dataset and 1 miRNA dataset. We aimed to study the
   relationship between miR-142-3p, FAM83D (we identified), and the
   development of OC.

RESULTS

Identification of DEGs

   We used GEO2R to analysis the DEMs and DEGs from the [44]GSE81873 and
   [45]GSE27651. Based on the cut-off criteria, 56 DEMs such as
   hsa-microRNA-142-3p, hsa-microRNA-429, hsa-microRNA-199a-3p,
   hsa-microRNA-484, hsa-microRNA-139-5p, hsa-microRNA-483-5p,
   hsa-microRNA-423-5p, hsa-microRNA-342-3p, hsa-microRNA-885-5p, and 63
   DEGs were selected ([46]Figure 1).

Figure 1.

   [47]Figure 1
   [48]Open in a new tab

   Heat map and volcano map of differentially expressed genes of
   [49]GSE81873 and [50]GSE27651. (A). Heat map of DEGs in [51]GSE81873.
   (B). Volcano map of DEGs in [52]GSE81873. (C). Heat map of DEGs in
   [53]GSE27651. (D). Volcano map of DEGs in [54]GSE27651. Red dots
   represent up-regulated genes and blue or green dots represent
   down-regulated genes.

Gene ontology enrichment analysis

   By utilizing FunRich and R software, we performed TF enrichment
   analysis ([55]Figure 2A).

Figure 2.

   [56]Figure 2
   [57]Open in a new tab

   Gene ontology enrichment. (A). Identification of the potential
   transcription factors of DEMs by FunRich software. (B) biological
   process, (C) cellular component, and (D) molecular function enrichment
   analysis of the DEMs.

   KEGG and GO function enrichment analyses were performed here. As for GO
   function analysis, three GO were selected: molecular function (MF),
   cellular component (CC), and biological process 156 (BP). Expression
   analysis showed that DEGs had the most uniquely enriched terms for Cell
   communication, Signal transduction, Regulation of nucleobase,
   nucleotide and nucleic acid metabolism, Cytoplasm, Nucleus, Cytosol,
   Membrane, Transcription factor activity, GTPase activity, Receptor
   signaling complex scaffold activity, Receptor signaling protein
   serine/threonine kinase activity, and CAMP-mediated signaling
   ([58]Figure 2B–[59]2D). Besides, DEMs were mainly enriched in 6
   pathways: MAPK signaling pathway, PI3K-Akt signaling pathway, Wnt
   signaling pathway, TGF-beta signaling pathway, Pathways in cancer, and
   Bacterial invasion of epithelial cells ([60]Figure 3A).

Figure 3.

   [61]Figure 3
   [62]Open in a new tab

   (A). KEGG pathway enrichment analysis of potential target mRNAs. (B).
   Venn Diagram of [63]GSE81873 and [64]GSE27651. (C). Identified target
   mRNAs and miRNA-mRNA regulatory network.

miRNA-mRNA regulatory network

   According to FunRich software, 1069 potential target mRNAs were
   obtained and only 1 of them showed different expression levels in
   [65]GSE27651 (FAM83D). Based on the association between them, 1
   essential microRNA-mRNA pair (microRNA-142-3p and FAM83D) was selected
   for the next research ([66]Figure 3B, [67]3C).

genes expression and their associations with OC overall survival

   KM Plot was used to analyze the overall survival of patients with OC.
   According to uploading the miRNA and target gene we identified, we
   downloaded survival curves. The pictures showed that microRNA-124-3p
   and FAM83D were associated with the overall survival of patients with
   OC ([68]Figure 4).

Figure 4.

   [69]Figure 4
   [70]Open in a new tab

   The association between the expression level of selected genes and
   overall survival of OC patients.

Relationship between clinical characteristics and genes expression level of
OC

   Clinical and gene expression information of OC patients were downloaded
   in the TCGA database, such as patients’ age, race, FIGO stage, and
   primary therapy outcome ([71]Tables 1, [72]2). FAM83D and miR-142-3p
   expression of patients with Stage III and Stage IV was higher than that
   of patients with Stage I and Stage II (P<0.05) according to the FIGO
   stage. Furthermore, associations between clinical characteristics and
   overall survival in OC were analyzed. According to medium FAM83D and
   miR-142-3p expression, patients were divided into two groups. Our
   results indicated that FAM83D mRNA and miR-142-3p expression level
   (P<0.05), FIGO stage (P<0.05), Primary therapy outcome (P<0.05), and
   tumor stage (P<0.05) was related to the OS of patients with OC
   ([73]Tables 3, [74]4).

Table 1. Relationship between the expression level of FAM83D and clinical
characteristics in OC.

   Characteristic Low expression of FAM83D High expression of FAM83D p
   n 189 190
   FIGO stage, n (%) 0.007
   Stage I 0 (0%) 1 (0.3%)
   Stage II 53 (13.9%) 10 (2.7%)
   Stage III 100 (26.3%) 155 (41.2%)
   Stage IV 35 (9.3%) 22 (5.9%)
   Primary therapy outcome, n (%) 0.484
   PD 12 (3.9%) 15 (4.9%)
   SD 14 (4.5%) 8 (2.6%)
   PR 22 (7.1%) 21 (6.8%)
   CR 102 (33.1%) 114 (37%)
   Race, n (%) 0.840
   Asian 5 (1.4%) 7 (1.9%)
   Black or African American 13 (3.6%) 12 (3.3%)
   White 161 (44.1%) 167 (45.8%)
   Age, n (%) 0.383
   <=60 99 (26.1%) 109 (28.8%)
   >60 90 (23.7%) 81 (21.4%)
   Age, median (IQR) 60 (52, 68) 58 (50, 68) 0.390
   [75]Open in a new tab

Table 2. Relationship between the expression level of hsa-miR-142-3p and
clinical characteristics in OC.

   Characteristic Low expression of hsa-miR-142-3p High expression of
   hsa-miR-142-3p p
   n 248 248
   FIGO stage, n (%) 0.009
   Stage I 0 (0%) 1 (0.2%)
   Stage II 13 (2.6%) 76 (15.3%)
   Stage III 199 (40.4%) 123 (24.8%)
   Stage IV 35 (7.1%) 45 (9.1%)
   Primary therapy outcome, n (%) 0.210
   PD 21 (5.1%) 15 (3.7%)
   SD 16 (3.9%) 9 (2.2%)
   PR 24 (5.9%) 32 (7.8%)
   CR 139 (34.1%) 152 (37.3%)
   Race, n (%) 0.472
   Asian 10 (2.1%) 6 (1.3%)
   Black or African American 14 (2.9%) 18 (3.8%)
   White 215 (44.9%) 216 (45.1%)
   Age, n (%) 0.786
   <=60 139 (28%) 135 (27.2%)
   >60 109 (22%) 113 (22.8%)
   Age, median (IQR) 58.5 (51, 69) 59 (51.75, 68.25) 0.873
   [76]Open in a new tab

Table 3. Relationship between overall survival and the expression level of
FAM83D researched by univariate and multivariate Cox regression.

   Characteristics Total(N) Univariate analysis Multivariate analysis
   Hazard ratio (95% CI) P value Hazard ratio (95% CI) P value
   FIGO stage 374
   Stage I & Stage II 24 Reference
   Stage III 293 2.045 (0.905-4.621) 0.085 1.850 (0.670-5.108) 0.235
   Stage IV 57 2.495 (1.057-5.889) 0.037 2.563 (1.541-4.517) 0.041
   Primary therapy outcome 307
   PD 27 Reference
   SD 22 0.441 (0.217-0.895) 0.023 0.463 (0.222-0.967) 0.040
   PR 42 0.652 (0.384-1.107) 0.113 0.637 (0.360-1.126) 0.121
   CR 216 0.152 (0.093-0.247) <0.001 0.203 (0.120-0.344) <0.001
   Race 364
   Asian & Black or African American 37 Reference
   White 327 0.637 (0.405-1.004) 0.052 0.738 (0.434-1.255) 0.262
   FAM83D 377 1.645 (1.916-3.192) 0.011
   Tumor status 336
   Tumor free 72 Reference
   With tumor 264 9.576 (4.476-20.486) <0.001 9.616 (3.875-23.866) <0.001
   [77]Open in a new tab

Table 4. Relationship between overall survival and the expression level of
hsa-miR-142-3p researched by univariate and multivariate Cox regression.

   Characteristics Total(N) Univariate analysis Multivariate analysis
   Hazard ratio (95% CI) P value Hazard ratio (95% CI) P value
   FIGO stage 490
   Stage I & Stage II 30 Reference
   Stage III 380 2.179 (1.076-4.411) 0.031 1.513 (1.664-3.446) 0.004
   Stage IV 80 2.785 (1.331-5.829) 0.007 1.333 (1.563-3.155) 0.013
   Primary therapy outcome 407
   PD 36 Reference
   SD 25 0.453 (0.241-0.854) 0.014 0.452 (0.237-0.862) 0.016
   PR 55 0.668 (0.426-1.047) 0.079 0.635 (0.400-1.010) 0.055
   CR 291 0.168 (0.112-0.251) <0.001 0.211 (0.139-0.319) <0.001
   Race 478
   Asian & Black or African American 48 Reference
   White 430 0.764 (0.513-1.138) 0.186
   hsa-miR-342-3p 494 0.835 (0.738-0.946) 0.005 1.910 (1.783-2.458) 0.019
   Tumor status 442
   Tumor free 95 Reference
   With tumor 347 8.796 (4.784-16.170) <0.001 8.362 (4.057-17.236) <0.001
   [78]Open in a new tab

Validation of the expression with qRT-PCR and IHC

   To deeply evaluate the expression of miR-142-3p and FAM83D, 20 pairs of
   normal ovarian tissues (NOT) and OC tissues (OCT) were enrolled as a
   validation cohort. The qRT-PCR approach was utilized to verify the
   differential expression levels from the patient’s tissues. The same as
   the microarray data, hsa-miR-142-3p was significantly downregulated
   ([79]Figure 5A) and FAM83D was overexpressed ([80]Figure 5B) between 20
   pairs of NOTs and OCTs which indicated that hsa-miR-142-3p and FAM83D
   could be the candidate biomarkers for OC. Besides, this expression
   level of genes was detected by IHC. The staining intensity of FAM83D
   was divided into 0, 1, 2, or 3, corresponding to colorless, light
   yellow, light brown, and squid ink. In addition, the percentage score
   is defined as: 0% to 5%, 0; 6% - 25%, 1 point; 26-50%, 2 points;
   50-75%, 3 points; 76% to 100%, 4 points. The final histochemical score
   was calculated by multiplying the intensity score by the percentage
   score. The final staining scores were negative (0), low (6), and strong
   (≥ 6). Statistically, the overall expression of FAM83D was much higher
   in OC tissues than in the adjacent noncancerous tissues (P < 0.001)
   ([81]Figure 5C–[82]5F).

Figure 5.

   [83]Figure 5
   [84]Open in a new tab

   The expression level of hsa-miR-142-3p and FAM83D in normal ovarian
   tissues (NOTs) and OC tissues (OCTs). (A). Validation of hsa-miR-142-3p
   ((***, p < 0.001). (B). Validation of FAM83D (***, p < 0.001). (C, D).
   The expression level of FAM83D in human OCTs. (E, F). The expression
   level of FAM83D in human NOTs (scale bar: 200×).

Confirmation of the association between miR-142-3p and FAM83D

   The Dual-Luciferase Reporter Assay System was utilized to evaluate the
   association between FAM83D and microRNA-142-3p. The FAM83D-WT activity
   of wild-type luciferase was 36.40%, and the FAM83D-MUT activity of
   mutant luciferase was 72.80%. These outcomes indicated that
   microRNA-142-3p reduced the luciferase activity of the wild-type FAM83D
   reporter gene ([85]Figure 6).

Figure 6.

   [86]Figure 6
   [87]Open in a new tab

   FAM83D is a direct target of miR-142-3p in OC cells. (A) Putative
   binding sites in FAM83D 3’UTR for miR-142-3p were predicted by
   bioinformatics analysis (microRNA.org). (B). Validation of
   luc2/hRluc-neo between miR-142-3p and FAM83D.

DISCUSSION

   In 2020, there were 19.29 million new cancer cases worldwide, including
   10.06 million males and 9.23 million females; In 2020, there were 9.96
   million cancer deaths worldwide, including 5.53 million males and 4.43
   million females [[88]11, [89]12]. In this research, [90]GSE81873 and
   [91]GSE27651 were obtained in the GEO database. 56 DEMs and 63 DEGs
   were identified. For deeply understanding the process of the 56 DEMs in
   OC, FunRich and R software were utilized for further study. GO and KEGG
   analysis indicated that these DEMs were primarily associated with the
   Cytoplasm, Nucleus, and Transcription factor activity. Previous studies
   have shown that Lysosomes and Nucleus may function as a vital role in
   plenty of human diseases, such as tumors, obesity, and infection
   [[92]13–[93]15]. Furthermore, KEGG analysis showed that DEGs were
   mainly enriched in 6 pathways such as MAPK signaling pathway, PI3K-Akt
   signaling pathway, Wnt signaling pathway, TGF-beta signaling pathway,
   Pathways in cancer, and Bacterial invasion of epithelial cells, which
   were indicated to influence migration and proliferation [[94]16]. The
   MAPK signaling pathway is a common signaling pathway closely associated
   with carcinoma, which will not be discussed here.
   Phosphatidylinositol-4,5-diphosphate-3-kinase (PI3K) is activated by
   many genes. In PI3K / Akt signal transduction pathway, phospholipid
   dependent kinase promotes the binding of protein kinase B (Akt) to the
   cell membrane. The phosphorylation of threonine and serine promotes the
   transfer of Akt from the cytoplasm to the nucleus and further mediates
   the biological effects of enzymes, including cell proliferation,
   inhibition of apoptosis, cell migration, vesicle transport, and cell
   carcinogenesis [[95]17]. Besides, it can influence the
   epithelial-mesenchymal transition in plenty of methods to affect tumor
   aggressiveness [[96]18]. As for OC, a previous study reported that it
   took an important part in OC tumorigenesis, proliferation and
   progression, and pre-clinical and clinical experience with several
   PI3K/AKT/mTOR pathway inhibitors [[97]19]. Neurotrophins are produced
   by target tissues innervated by developing neurons, so these factors
   act on the end of axons and produce signals that must be transmitted
   back to the cell body [[98]20]. It can activate the PI3K/Akt signal
   transduction pathway and other oncogenic signaling pathways [[99]21].
   For example, it has been confirmed that in the early stage of cancer,
   the increase of nerve density is parallel to the increase of
   neurotrophin level, but it remains to be clarified which cells in TME
   are the source of neurotrophin and the nature of the stimulants that
   initiate the production of neurotrophin [[100]22]. Besides, a previous
   study reported that Neurotrophin Receptor TrkB (NTRK2) and Wnt
   β-Estradiol and MAPK signaling pathways are closely related to the
   worse prognosis of neuroblastoma [[101]23]. Besides, the changes in
   neurotrophin signals are related to neurodegenerative diseases and
   mental diseases [[102]24].

   The regulated network was performed according to Cytoscape. 56 miRNAs
   (hsa-microRNA-142-3p, hsa-microRNA-429, hsa-microRNA-199a-3p, and
   hsa-microRNA-484) were selected for further research. After that, 1069
   target genes were achieved and 1 of them showed a different expression
   level in [103]GSE27651 (FAM83D). MicroRNA-142-3p encoding human
   chromosome 17q22 is a new tumor suppressor factor, which is observed in
   many tumors including breast carcinoma, hepatocellular carcinoma,
   bladder carcinoma, and ovarian carcinoma [[104]25–[105]30]. The
   downregulation of microRNA-142-3p is related to tumorigenesis via
   regulation, cell migration, cell apoptosis, and invasion through
   various signaling pathways. Besides, microRNA-142-3p has been found as
   a carcinogenic microRNA in human T-cell acute lymphoblastic leukemia by
   acting on glucocorticoid receptors and cyclic adenosine
   monophosphate/protein kinase A pathway [[106]31]. Upregulated
   microRNA-142-3p also monitors the characteristics of breast carcinoma
   stem cells, at least in section by sensitizing the WNT signaling
   pathway and microRNA-150 expression [[107]32]. A previous study
   reported that upregulated microRNA-142-3p inhibited colorectal cancer
   cell migration and invasion, indicating that microRNA-142-3p may act as
   an oncogene during colorectal cancer tumorigenesis [[108]33]. As for
   OC, another study concluded that microRNA-142-3p suppressed the
   proliferation and chemoresistance of OC cells by targeting SIRT1. This
   indicates that microRNA-142-3p may be a therapeutic target for the cure
   of OC [[109]27].

   FAM83D (family with sequence similarity 83, member D) is a
   mitosis-related gene located on chromosome 20q11 [[110]34]. Previous
   studies have indicated that FAM83D may be amplified and upregulated in
   a variety of tumors, including hepatocellular tumors [[111]35], ovarian
   carcinoma [[112]36], colorectal carcinoma [[113]37], and lung
   adenocarcinoma [[114]38]. In addition, researches have demonstrated
   that FAM83D may act as a carcinogenic role by suppressing the invasion
   and proliferation of hepatocellular carcinoma and inhibiting the cell
   cycle of lung adenocarcinoma by suppressing FBXW7 in breast carcinoma
   [[115]39–[116]41]. These outcomes indicated that FAM83D may be widely
   taken part in process of tumors. Besides, FAM83D can advance
   epithelial-mesenchymal transition and metastasis of non-small cell lung
   carcinoma cells through the AKT/mTOR signal pathway, also improve the
   sensitivity of NSCLC cells to cisplatin [[117]42]. Furthermore, FAM83D
   is highly expressed in invasive epithelial ovarian cancer and is
   related to tumor stage and grade [[118]43]. Last but not least, FAM83D
   can also promote ovarian carcinoma cell invasion and proliferation,
   while suppressing autophagy through the PI3K/AKT/mTOR signaling pathway
   [[119]44]. Therefore, we selected and tested whether microRNA-142-3p
   and FAM83D were differently expressed between NOTs and OCT.s qPCR
   results indicated that microRNA-142-3p and FAM83D were differentially
   expressed in NOTs and OCTs. Besides, IHC results indicated that FAM83D
   had a significant difference in OCTs compared with NOTs.

   Many studies have shown that the abnormal expression of miRNAs is
   caused by gene aberrations (including genetic and epigenetic changes)
   of many cancer types, and plays a role in the occurrence and
   development of cancer through the imbalance of target gene expression.
   Therefore, many miRNAs and their target genes are closely related to
   the pathogenesis of tumors, including cell proliferation, cell
   survival, and cell invasion. Our study indicated that plenty of DEGs
   and DEMs were taken part in the process of OC by some pathways and had
   prognostic value. Therefore, suppression of FAM83D and upregulated
   miR-142-3p may have latent remedy worth in OC patients.

CONCLUSIONS

   Our study indicated some reasons for the procession of OC. Plenty of
   DEMs and DEGs were selected between OC tissues and normal ovarian
   tissues. Besides, miR-142-3p and FAM83D were selected as latent
   biomarkers of OC. qPCR and IHC results indicated that microRNA-142-3p
   and FAM83D were differentially expressed in OC tissues. Besides,
   luciferase reporter assays verified that FAM83D was a direct target of
   miR-142-3p in OC cells. However, we need more cell experiments to prove
   it.

MATERIALS AND METHODS

Microarray data

   The RNA-seq data of OC samples and corresponding normal ovarian tissues
   were retrieved from the GEO dataset
   ([120]https://www.ncbi.nlm.nih.gov/geo/). The datasets of [121]GSE81873
   and [122]GSE27651 were downloaded and divided into two groups.

Differently expressed miRNAs research

   GEO2R is software for differential analysis of expression microarray
   based on the GEO database.

   Limma R package was used to identify DEGs in the construction cohort.
   The screening standards of DEGs for functional enrichment analysis were
   |log2FC|> 1 and FDR<0.05.

Gene ontology and pathway enrichment analysis

   Transcription factors (TF), Kyoto Encyclopedia of Genes and Genomes
   (KEGG), and Gene Ontology (GO) enrichment analyses of the DEGs were
   performed by using R clusterProfiler package, including the package of
   "GOplot”, “ggplot2”, “stringi”, “colorspace” and “digest”. Then, the
   pathway and process enrichment analyses were carried out by using
   Cytoscape.

MicroRNA-mRNA regulatory network

   At present, there are two generally recognized miRNA mechanisms:
   miRNA-mediated mRNA translation inhibition and miRNA-mediated
   mRNA-specific cleavage. In addition, researchers also found that miRNA
   may have other regulatory mechanisms, such as regulating the
   localization or stability of target mRNA, or acting on target molecules
   other than mRNAs, such as complementary binding with regulatory
   non-coding RNA or even miRNA, or competing with other RNAs to bind
   proteins to achieve its regulatory function. DEMs were uploaded to the
   FunRich software to achieve target mRNAs. Furthermore, [123]GSE27651
   was researched by utilizing R software. Based on the prediction
   conclusions of target mRNAs in FunRich software and the differentially
   expressed mRNAs of [124]GSE27651, the microRNA-mRNA network was
   constructed.

The association between the expression level of identified genes and overall
survival of patients with OC

   Kaplan Meier plotter can assess the impact of 54K (mRNA, miRNA,
   protein) on the survival rate of 21 types of cancer (including breast
   cancer (n = 6234), ovarian cancer (n = 2190), lung cancer (n = 3452)
   and gastric cancer (n = 1440). The sources of the Kaplan Meier plotter
   database include GEO, EGA, and TCGA. The main purpose of the tool is
   the discovery and validation of survival biomarkers based on a
   meta-analysis. In this study, patients with OC were divided into two
   groups. By uploading the DEGs we identified, corresponding survival
   curves were obtained.

DEGs expression and clinical characteristics in the cancer genome atlas

   The associated statistics offered by The Cancer Genome Atlas. The data
   of 1037 patients with ovarian cancer were downloaded in the TCGA
   database. The expression level of mRNAs, clinicopathological
   information, and general information of patients with OC were achieved.

Immunohistochemical staining

   20 pairs of OC tissues were prepared by buffering with 10% formalin for
   24 hours. The study was approved by the Ethics Committee of the Second
   Affiliated Hospital of Soochow University and informed consent was
   obtained from all patients. 2 consecutive 5-m sections were taken from
   each formalin-fixed paraffin-embedded block and mounted on the glass
   slide treated with aminoalkyl silane, dewaxing with xylene, passing
   through graded alcohol, and then continue rinsing in deionized water
   and phosphate-buffered saline. It was blocked by 3% non-immune horse
   serum. The sections were incubated with broad-spectrum anti-cytokeratin
   AE1 / 3 (Dako, Santa Barbara, CA, USA) in 1:50 dilution overnight at
   room temperature. After washing twice in buffer, an appropriate
   biotinylated secondary antibody was applied for 30 minutes. After two
   more washes in the buffer, appropriate biotinylated secondary
   antibodies were applied for 30 minutes. The sections were developed
   under the microscope in Tris HCl buffer (pH 7.4) and 0.03% hydrogen
   peroxide for 20 minutes. Application of light Mayer hematoxylin. The
   expressions of FAM83D and β - Catenin were detected by the Chi-square
   test or Fisher exact test. GraphPad Prism 9 software was utilized for
   statistical analysis. P-value < 0.05 was considered statistically
   significant.

Real-time quantitative polymerase chain reaction

   Total RNA was extracted from OC tissues and normal tissues by utilizing
   TRIzol reagents (Invitrogen, Carlsbad, CA, USA) as per the
   manufacturer’s instructions. The total RNA was reverse-transcribed into
   cDNA by utilizing a PrimeScript™RT kit with gDNA Eraser (TaKaRa,
   China). We also constructed Quantitative Real-time PCR (qRT-PCR) by
   using SYBR Select Master Mix for CFX (Invitrogen) and the CFX Connect
   Real-Time PCR System (BioRad). The amplification conditions are 95° C
   for 15s, then 40 cycles, 95° C for 5S, 60° C for the 30s. Primer
   sequences of FAM83D were as follows: primer F, 5’-
   GCACTTCCCTTTGTTGTAGTC −3’, primer R, 5’-AGCACTTCCCTTAGGTTACTC −3’.
   Using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as endogenous
   control, the recorded data were analyzed and processed by 2−ΔΔCt.

Luciferase reporter assay

   The relationship between miR-142-3p and FAM83D was verified by
   performing a luciferase reporter assay. To construct a luciferase ratio
   vector, we amplified the wild or mutant fragment FAM83D 3 ‘- UTR
   containing the hypothetical binding site miR-142-3p and subcloned it
   into luciferase pLUC vector (Wuhan, Ruibo, China). OC cells were
   co-transfected with pLUC-FAM83D 3 ‘- UTR wild (WT) or pLUC-FAM83D 3’ -
   UTR (MU) mutants and miR-142-3p or NC analogues using Lipofectamine
   2000 according to the manufacturer’s instructions. After 48 hours of
   transfection, the relative activities of luciferase and double
   luciferase were detected by the analytical system (Promega, Madison,
   WI, USA). The luciferase activity of fireflies was normalized to
   Renilla luciferase activity.

Statistical methods

   The data were expressed as mean ± standard error. All data analyses
   were performed using R software (version 3.6.6) and GraphPad Prism 9
   software package (GraphPad Software, Inc., La Jolla, California, USA).
   The differences between the two addiction groups were compared by
   student’s t-test. All the experiments were made in triplicate.

Availability of data and materials

   The datasets used and/or analyzed during the current study are
   available from the corresponding author on reasonable request.

Ethics approval and consent to participate

   The study was conducted according to the guidelines of the Declaration
   of Helsinki, and approved by the Ethics Committee of the Soochow
   University.

Footnotes

   AUTHOR CONTRIBUTIONS: Conceptualization, Xiaofei Guo; Methodology,
   Guangyu Gao; Software, Wenyong Gu; Validation, Guangyu Gao; Formal
   Analysis, Guangyu Gao.; Investigation, Yufeng Lu; Resources, Guangyu
   Gao; Data Curation, Guangyu Gao; Writing – Original Draft Preparation,
   Guangyu Gao; Writing – Review and Editing, Guangyu Gao; Visualization,
   Guangyu Gao; Supervision, Zhigang Chen; Project Administration, Zhigang
   Chen; Funding Acquisition, Zhigang Chen.

   CONFLICTS OF INTEREST: The authors declare that they have no conflicts
   of interest.

   FUNDING: This study was approved by Pre-Research Project of the
   National Natural Science Foundation of China (SDFEYGJ2014); Suzhou
   Science and Technology Development Project (SYSD2019108); Science and
   Technology Program of Suzhou City (SLJ2021012).

REFERENCES