*3.3. The Interaction Network of PUS7*

To explore the PPI and gene networks of PUS7 and its partner, an analysis using the String and GeneMANIA tools was performed. The PPI analysis results showed that a total of 10 proteins including NSUN2, NOP2, NOC3L, RBM28, BRIX1, TRUB1, WDR12, PUS1, DKC1, and NMD3 have interactions with PUS7 (Figure 5A). In the GeneMANIA analysis, a total of 20 genes named *ETFDH*, *WDR74*, *THUMPD1*, *NOC3L*, *CXXC4*, *DPYSL2*, *HSPA4L*, *RAD21*, *STAT3*, *MRPS2*, *HMBS*, *IDE*, *UBC*, *HSPH1*, *HDDC2*, *CMTR2*, *ATP6V0A1*, and *DRG1* were demonstrated to have physical interactions or genetic interactions or to share protein domains with *PUS7* or were co-expressed or co-located with *PUS7* (Figure 5B). The shared genes of the above two analyses are *PUS1* and *NOC3L* (Figure 5C), where *PUS1* was co-expressed with *PUS7* [30,31] and *NOC3L* physically interacted with *PUS7* [31–33] in GeneMANIA, both of which were known to interact with PUS7, according to the String results. In addition, GEPIA analysis showed that the expression of *PUS7* is significantly correlated with *PUS1* (R = 0.57, *p*-value = 0) and *NOC3L* (R = 0.61, *p*-value = 0) (Figure 5D).

**Figure 5.** The interaction network and correlation of *PUS7*. (**A**) The protein interaction network of PUS7. Ten proteins including NSUN2, NOP2, NOC3L, RBM28, BRIX1, TRUB1, WDR12, PUS1, DKC1, and NMD3 physically/functionally interact with PUS7. (**B**) Twenty genes named *ETFDH*, *WDR74, THUMPD1, NOC3L, CXXC4, DPYSL2, HSPA4L, RAD21, STAT3, MRPS2, HMBS, IDE, UBC, HSPH1, HDDC2, CMTR2, ATP6V0A1,* and *DRG1* have physical interactions or genetic interactions, share protein domains with *PUS7*, or co-express or co-localize with *PUS7*. (**C**) Two genes were shared by the two networks. (**D**) The correlation analysis of *PUS7* with *PUS1* and *NOC3L*. R > 0.5 plus *p* < 0.05 was regarded as a significant correlation.

## *3.4. The Pathway Enrichment Analysis of PUS7 in Ovarian Cancer*

To investigate the pathways that *PUS7* may be involved in or may regulate in ovarian cancer, a GSEA pathway analysis was performed using TCGA data, which was separated into a high (top 25%) *PUS7* group and a low (down 75%) *PUS7* group. The top eight pathways in which PUS7 participates are DNA replication, the cell cycle, mismatch repair, spliceosomes, homologous recombination, RNA polymerase, aminoacyl tRNA biosynthesis, and one carbon pool by folate in ovarian cancer (Figure 6). Among the eight pathways, the top two pathways are DNA replication and the cell cycle, both of which are linked to ovarian cancer cell proliferation. These results may imply that the overexpression of *PUS7* in ovarian cancer might promote ovarian cancer proliferation via regulation of DNA replication and the cell cycle.

**Figure 6.** The pathway enrichment analysis of PUS7 in ovarian cancer. GSEA pathway analysis using TCGA ovarian cancer data, which was separated to a high (top25%) *PUS7* group and a low (down75%) *PUS7* group. Eight top pathways in which *PUS7* participates were DNA replication, the cell cycle, mismatch repair, spliceosomes, homologous recombination, RNA polymerase, aminoacyl, tRNA biosynthesis, and one carbon pool by folate in ovarian cancer.

## *3.5. Gene Ontology (GO) Analyses of PUS7 in Ovarian Cancer*

To further clarify the GO terms of BP (biological processes), CC (cellular components) and MF (molecular functions) of *PUS7*, a total of 312 genes (Supplementary Table S4) positively related to *PUS7* (R > 0.3, *p* < 0.0001) according to the TCGA ovarian cancer data through the cBioPortal database were subjected to DAVID analysis. The results showed that biological processes in which *PUS7* mainly participates include the regulation of DNA templates and transcription, rRNA processing, tRNA export from nuclei, the regulation of glucose transport, the intracellular transport of viruses, mitotic nuclear envelope disassembly, viral processes, RNA processing, the regulation of cellular response to heat, gene silencing by RNA, and the positive regulation of gene expression (Figure 7A). The cellular components affected by *PUS7* include the nucleoplasm, nucleolus, nucleus, small subunit processomes, nuclear envelope, and nuclear membrane (Figure 7B). The molecular functions of *PUS7* include poly(A) RNA binding, nucleic acid binding, helicase activity, ATP binding, ATP-dependent RNA helicase activity, structural constituents of a nuclear pore, DNA binding, RNA binding, protein binding, single-stranded DNA binding, nucleocytoplasmic transporter activity, DNA replication origin binding, ATP-dependent helicase activity, and nucleotide binding (Figure 7C).

**Figure 7.** The GO analyses of PUS7 in ovarian cancer. The bubble diagrams were analyzed using PUS7-related genes and exhibited the biological processes (**A**), cellular components, (**B**) and molecular functions (**C**) of PUS7.

#### **4. Discussion**

It was estimated that there were 22,530 new cases and 13,980 deaths due to ovarian cancer in the United States in 2019 [34]. Ovarian cancers are often diagnosed late, when the disease has progressed to advanced stages. Hence, an efficient and reliable diagnostic marker is very necessary to facilitate clinical diagnosis and to prolong the survival time for OV. RNA modifications are reported to play vital roles in human diseases, including cancer. For example, m6A, a new star of RNA modifications, is associated with tumorigenesis, tumor proliferation and differentiation and functions as oncogenes or anti-oncogenes in malignant tumors [35]. For example, m6A plays a pivotal role in ovarian cancer progression [36]. Recent advances in human Mendelian diseases have brought focus to human PUS genes as a type of RMG in clinical medicine [37]. PUS7-mediated pseudouridylation could "activate" a class of tRNA-derived small RNAs to regulate protein synthesis and stem cell fate [20]. Additionally, PUS7 is also reported to be a potential biomarker for glioma [38].

In this study, we investigated dysregulated RMGs in ovarian cancer and identified PUS7 as a novel potential biomarker for the diagnosis of OV. ROC analysis acting as an efficient method has been commonly used to determine the accuracy and specificity of medical imaging techniques and non-imaging diagnostic tests in various settings involving disease screening, prognosis, diagnosis, staging, and treatment [39]. Herein, ROC analysis aimed at discriminating cancer from normal tissue was performed to evaluate the sensitivity and specificity of PUS7 in GEO and TCGA data. AUC is a global measure of the ability of a

test to discriminate whether a specific condition is present [40]. In this study, an AUC score over 0.9 in an ROC analysis was obtained, suggesting the potent discriminating potency of PUS7 (AUC = 0.9404, *p* < 0.0001) in ovarian cancer. In addition to PUS7 upregulation in the TCGA and GEO datasets, the Oncomine database analysis and IHC results further validated the promising diagnostic role of PUS7 in OV.

PUS7 has never been reported in ovarian cancer. To rationalize the vital role of PUS7 in OV, we explored the proteins interacting with PUS7, which may partially help explain PUS7 function in tumor diagnosis, tumorigenesis, and development. The PPI and gene network analyses identified PUS7 interacting partners, including NOC3L and PUS1, which are also not reported in ovarian cancer, although several reports have revealed that NOC3L regulates the proliferation and tumorigenesis of gastric cancer [41], and NOC3L is associated with an increased risk of gastric cancer in the Chinese Han population [42]. For PUS1, previous reports demonstrated that it is related to sideroblastic anemia [43], and no association of PUS1 with cancer was ever shown, suggesting the novelty of the protein interaction. To further explore the signaling pathway of *PUS7* in ovarian cancer, the GSEA pathways analysis demonstrated that DNA replication and the cell cycle are the top two pathways that *PUS7* regulated. These results point towards the role of *PUS7* in ovarian cancer proliferation via regulation of DNA replication and the cell cycle. However, this hypothesis needs further experiments to be validated.

#### **5. Conclusions**

In conclusion, the findings of the present study revealed PUS7 as a novel and prospective biomarker at the RNA and protein levels for ovarian cancer. Further analysis indicated that PUS7 may interact with NOC3L and PUS1 to regulate ovarian cancer proliferation via modulation of DNA replication and the cell cycle.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/10 .3390/biology10111130/s1, Table S1: The differentially expressed genes in ovarian cancer samples compared with normal tissue according to TCGA and GSE18520 data. Table S2: The baseline characteristics of ovarian cancer samples in a tissue array. Table S3: RNA modification-related genes. Table S4: The genes correlated to PUS7.

**Author Contributions:** Conceptualization, H.L., Q.W. and X.G.; Data curation, H.L., Y.H. (Yunsong Han) and F.Z.; Funding acquisition, H.L. and X.G.; Investigation, L.C., Y.H. (Yunsong Han), Y.W. (Yanyan Wang) and Y.W. (Yange Wang); Methodology, H.L., Q.W. and X.G.; Project administration, Q.W.; Software, L.C. and F.Z.; Supervision, X.G.; Validation, L.C. and Y.H.; Visualization, Y.W. (Yanyan Wang) and Q.W.; Writing—review & editing, Y.H. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by Henan Province Scientific and Technology Research Project (202102310063), Students Innovation and Entrepreneurship program (20211022008), the program for Central Plain Young Top Talents (ZYQR201912176), and the program for Innovative Talents of Science and Technology in Henan Province (18HASTIT048).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

