Hindawi Journal of Immunology Research Volume 2020, Article ID 7263602, 17 pages https://doi.org/10.1155/2020/7263602

Research Article STK3 Suppresses Ovarian Cancer Progression by Activating NF-κB Signaling to Recruit CD8+ T-Cells

Xiangyu Wang ,1,2 Fengmian Wang,1,2 Zhi-Gang Zhang ,3 Xiao-Mei Yang ,3 and Rong Zhang 1,2

1The Third School of Clinical Medicine, Southern Medical University, Guangzhou 510500, China 2Department of Obstetrics and Gynecology, Fengxian Central Hospital Affiliated to the Southern Medical University, Shanghai 201499, China 3State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 201109, China

Correspondence should be addressed to Xiao-Mei Yang; [email protected] and Rong Zhang; [email protected]

Received 6 July 2020; Revised 11 August 2020; Accepted 26 August 2020; Published 29 September 2020

Academic Editor: Jian Song

Copyright © 2020 Xiangyu Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Serine/threonine protein kinase-3 (STK3) is a critical molecule of the Hippo pathway but little is known about its biological functions in the ovarian cancer development. We demonstrated the roles of STK3 in ovarian cancer. Existing databases were used to study the expression profile of STK3. STK3 was significantly downregulated in OC patients, and the low STK3 expression was correlated with a poor prognosis. In vitro cell proliferation, apoptosis, and migration assays, and in vivo subcutaneous xenograft tumor models were used to determine the roles of STK3. The overexpression of STK3 significantly inhibited cell proliferation, apoptosis, and migration of ovarian cancer cells in vitro and tumor growth in vivo. Bisulfite sequencing PCR analysis was performed to validate the methylation of STK3 in ovarian cancer. RNA sequencing and gene set enrichment analysis (GSEA) were used to compare the transcriptome changes in the STK3 overexpression ovarian cancer and control cells. The signaling pathway was analyzed by western blotting. STK3 promoted the migration of CD8+ T-cells by activating nuclear transcription factor κB (NF-κB) signaling. STK3 is a potential predictor of OC. It plays an important role in suppressing tumor growth of ovarian cancer and in chemotaxis of CD8+ T-cells.

1. Introduction breast cancer by activating Hippo signaling [5–7]. STK3 also regulates the immune system in infections [8]. However, it is Ovarian cancer (OC) is the most frequent cause of death unclear whether STK3 can exert cancer-suppressing effects among gynecologic malignancies [1]. Due to its asymp- by regulating the functions of the immune system. tomatic development, the disease is frequently diagnosed CD8+ T-cells play an important role in inhibiting the at advanced and incurable stages [2]. Although there is a development of ovarian cancer [9]. The chemotaxis of high response rate to surgery and chemotherapy, the CD8+ T-cells is regulated by a variety of chemokines, of majority of patients subsequently relapse [3]. Therefore, it is which CXCL16 and CX3CL1 are the most important on important to identify effective molecular targets influencing CD8+ T-cells [10, 11]. The low expression of CXCL16 in tumor progression. breast cancer, osteosarcoma, renal clear cell carcinoma, and STK3 is a key molecule in the Hippo pathway, which con- melanoma is associated with a poor prognosis [12–14]. The trols cell development, proliferation, apoptosis, and various CX3CL1 expression is increased in the renal clear cell carci- stress responses [4]. STK3 plays a role in inhibiting the pro- noma tissues of patients receiving bevacizumab, accompa- gression of gastric cancer, hepatocellular carcinoma, and nied by infiltration of CD8+ T-cells [15]. NF-κB can affect 2 Journal of Immunology Research the infiltration of CD8+ T-cells in pancreatic ductal adeno- was carried out using the ABI 7500 fluorescence PCR ampli- carcinoma cells by regulating the generation of CXCL16 fication instrument (Applied Biosystems; Thermo Fisher and CX3CL1 and thereby promoting the apoptosis of Scientific, Inc.). RPS18 was used as an endogenous control, −ΔΔ pancreatic ductal adenocarcinoma cells [16]. However, it is and Ct values were processed using the 2 Ct method. The unclear whether STK3 can activate NF-κB signaling and sup- sequences of primers used in this experiment were shown press ovarian cancer growth. in Table 1. In this study, we demonstrated that STK3 was downreg- ulated in ovarian cancer via epigenetic methylation of its pro- 2.5. Western Blot Analysis. For western blot analysis, total moter DNA. STK3 inhibited proliferation and metastasis of protein samples were extracted from cells using RIPA lysis ovarian cancer cells. The overexpression of STK3 in ovarian buffer with a protease inhibitor (Beyotime, Jiangsu, China). cancer cells induced cell cycle arrest at G2/M and a higher An equal amount of protein (60 μg/lane) was loaded on rate of cell apoptosis. We also found that STK3 promoted 10% or 8% SDS-polyacrylamide gels and then transferred to the recruitment of CD8+ T-cells via an increase in chemo- a pure nitrocellulose blotting membrane (Pall Life Science, kine CXCL16 and CX3CL1 production in human ovarian AZ, USA). Next, the membrane was blocked in 5% nonfat cancer cells. This was possibly mediated by the regulation milk for 1 h and then probed with primary antibodies against κ STK3, β-actin, Phospho-IκBα,IκBα, Phospho p65, and p65 of the NF- B signaling pathway. Our results revealed a new ° molecular mechanism for serous ovarian cancer malignancy overnight at 4 C. Then, the membranes were incubated with mediated by STK3 through regulating NF-κB signaling and anti-rabbit secondary antibodies. Finally, immunoreactivity CD8+ T-cell recruitment. was detected using the Odyssey Infrared Imaging System (Gene Company Limited, Hong Kong, China). 2. Materials and Methods 2.6. DAC and TSA Treatment. Cells were treated with 5 or 2.1. Data Mining. The mRNA expression profiles for normal 10 μM of 5-aza-2′-deoxycytidine (DAC, Sigma-Aldrich, St. ovarian surface epithelium and ovarian cancer were down- Louis, MO, USA) or 300 nM trichostatin A (TSA, Selleck- loaded from UCSCXena (https://xena.ucsc.edu) and GEO chem, TX, USA) for 3 d, and the drug media were replaced (https://www.ncbi.nlm.nih.gov/geo/). The survival data of every 24 h. Control cells were incubated with the same patients were downloaded from TCGA (https://www.cancer volume of DMSO. In the combined treatment group, cells .gov/about-nci/organization/ccg/research/structural-genomics/ were cultured in the presence of 5 μM of DAC for 2 d and tcga) and GSE9899. were then treated for an additional 24 h with 300 nM of TSA.

2.2. Cell Culture and Clinical Samples. IOSE80, OVCAR3, 2.7. Plasmid Construction and Transfection. The human OVCAR8, CAOV3, ES-2, and HEK293T cell lines were all STK3 was subcloned into the pcDNATM3.1 vector. STK3 purchased from Cell Bank of the Chinese Academy of Sci- and the mock vector were packaged into the virus, and titers ences (Shanghai, China). All of the cells were cultured follow- were determined. Target cells were infected with 1×108 ing the instructions of the American Type Culture Collection lentivirus-transducing units and 6 μg/ml polybrene (TR-1003, (ATCC, Manassas, VA, USA). Sigma-Aldrich, Germany). After 72 h, the infected cells were screened in the presence of 3 μg/ml puromycin. The qPCR 2.3. Reagents. The antibodies used in this study were against and western blot also verified the overexpression efficacy STK3 (ab52641, Abcam, Cambridge, MA, USA), Phospho- of STK3. IκBα (#2859, Cell Signaling Technology), IκBα (#4812, Cell Signaling Technology), Phospho-NF-κB p65 (#3033, Cell 2.8. Cell Viability Assays. Cell viability was determined using Signaling Technology), β-actin (GB11001, Servicebio, Wuhan, a cell counting kit-8 (CK04, Dojindo, Japan). Briefly, water- China), and NF-κB p65 (#8242, Cell Signaling Technology) soluble formazan dye was added to the culture medium and for western blotting. Secondary antibodies were purchased incubated for 2 h in 5% CO2. The developed color was mea- from Jackson ImmunoResearch (West Grove, PA, USA). sured at 450 nm using an ELISA plate reader. Chemicals and biochemical used were DAC (A3656, 3 Sigma-Aldrich, St. Louis, MO, USA) and TSA (S1045, 2.9. Colony Formation Assay. The 1×10 cells/mL single-cell Selleck, Shanghai, China). CXCL16 and CX3CL1 concentra- suspension was made in RPMI1640 or DMEM. The colonies tions were measured in the medium of ovarian cancer cells were stained with 0.04% crystal violet and 2% ethanol in PBS ° using enzyme-linked immunosorbent assay (ELISA) kits and then incubated at 37 C for 21 days. The stained colonies (R&D Systems, Abingdon, UK) according to manufacturer’s were photographed under a light microscope (Olympus). instructions. 2.10. Transwell Migration and Invasion. Cells were seeded in 2.4. Quantitative Real-Time PCR. Total RNA was extracted the upper chamber of transwell plates (Corning, NY, NY from cells in each group using Trizol kits, and qualified total USA) with serum-free medium. 10% FBS medium was added RNA samples were subjected to reverse transcription. Total to the lower chamber of the transwell. Next, cells were RNA was taken to synthesize complementary deoxyribonu- transfected as described above for 48 h. For the invasion cleic acid (cDNA) using the PrimeScript™RT reagent Kit experiments, the upper chamber was covered with culture (RR047A, TAKARA, Japan). The specific reaction conditions medium and matrigel (BD Biosciences, San Jose, CA, USA) ° ° were 37 C for 30 min and 85 C for 30 s. Quantitative analysis mixture. Finally, cells on the top of the chamber were Journal of Immunology Research 3

Table 1: The oligonucleotide sequence of primers used in this experiment.

Genes Forward primer (5′-3′) Reverse primer (5′-3′) STK3 GCUGGAAAUAUUCUCCUUATT UAAGGAGAAUAUUUCCAGCTT CXCL16 CCCGCCATCGGTTCAGTTC CCCCGAGTAAGCATGTCCAC CX3CL1 ACTCTTGCCCACCCTCAGC TGGAGACGGGAGGCACTC RPS18 CAGCCAGGTCCTAGCCAATG CCATCTATGGGCCCGAATCT removed with cotton swabs, while cells that went through the Student’s t-test was used for paired comparisons between membrane were stained with 0.5% crystal violet and counted groups. P values <0.05 were considered to be statistically under a microscope at 100x magnification. significant.

2.11. Flow Cytometry Test of Cell Cycle. Ten ml of cell suspen- 3. Results sion (1 − 5×106 cells/mL) was spun at 500–1000 rpm for 5 min. The cell pellet was washed with PBS once and fixed 3.1. STK3 Was Downregulated in Ovarian Cancer and ° in 3.70% ice ethanol at 4 C for 2 h. After washing with PBS Correlated with Prognosis. To investigate the level of STK3 twice, the cells were suspended in PBS containing 50 mg/L in ovarian cancers, we first compared the expression of RNase A and 25 μg/mL PI and incubated in darkness at STK3 in ovarian cancer and matching normal ovarian sur- ° 25 C for 15 min. The cells at different phases were measured face epithelial tissue samples via GTEx and TCGA. Notably, using flow cytometry with an excitation wave length of STK3 was significantly downregulated in ovarian cancer 488 nm and an emission wave length greater than 560 nm based on the analysis of TCGA and GEO datasets (P value to detect PI signal. <0.05) (Figure 1(a)). We also investigated whether the STK3 expression was correlated with prognosis in ovarian 2.12. Flow Cytometry Test of Apoptosis. Ten ml of cell suspen- cancer patients. In TCGA cohorts, which included 428 sam- sion (1 – 5×106 cells/mL) was spun at 500–1000 rpm for ples of ovarian cancer, the low STK3 expression was associ- 5 min. The cell pellet was washed with PBS once and fixed ated with poorer overall survival and progression-free ° in 70% ice ethanol at 4 C for 2 h. After the fixation solution survival prognosis (P value <0.05) (Figure 1(b)). The poor was removed, the cells were suspended in 3 ml PBS for prognosis in ovarian cancer also correlated with the lower 5 min. Cells were transfected with lentivirus for 48 h and STK3 expression in GSE9899 (P value <0.05) (Figure 1(b)). serum-free starved for 24 h. This was filtered once with a These results suggest that the STK3 expression influences 400 gauge filter and centrifuged at 1000 rpm for 5 min, and the progression of ovarian cancer. then the cell pellet was stained with 50 mg/mL propidium iodide and Annexin V–fluorescein isothiocyanate (BD Phar- 3.2. The Overexpression of STK3 Inhibited the Proliferation, mingen, Franklin Lakes, NJ, USA) following manufacturer’s Migration, and Invasion of Ovarian Cancer Cells. To study instructions. Both the living and dead cells were measured the expression pattern of STK3 in ovarian cancer, we com- using flow cytometry with an exciting wave length of pared the level of STK3 in a normal human ovarian surface 488 nm and an emission wave length greater than 630 nm. epithelium cell line (IOSE80) with levels in ovarian cancer cell lines (CAOV3, OVCAR3, OVCAR8, and ES-2). The 2.13. Xenograft Transplantation. Female nude (BALB/c) STK3 expression levels detected by western blot were lower mice (4 weeks old) were purchased from the East China in most tested ovarian cancer cells compared with IOSE80 Normal University. Mice were randomly divided into two (Figure 2(a)). groups. OS cells stably expressing vector or lenti-STK3 were To further explore the role of STK3 in ovarian cancer pro- propagated, and 1×107 cells were inoculated subcutaneously gression in vitro, we established stable STK3-overexpressing into the right side of the posterior flank of the mice. Tumor cells by lentivirus-mediated transfection. Quantitative real- growth was examined at the indicated time points, and tumor time polymerase chain reaction (qPCR) and western blotting volumes were measured. After 4 weeks, the mice were killed, confirmed the efficiency of the STK3 overexpression in weighed, excised, fixed, and embedded in paraffin and sec- OVCAR3 and OVCAR8 cells (Figure 2(b)). We determined tioned for the histological examination of the PCNA and the effect of STK3 on the proliferation of ovarian cancer cells TUNEL expression. through CCK-8 and colony formation assays. The results showed that, compared with the control group, the prolifera- 2.14. Statistical Analysis. Data are presented as means ± SD. tion and clone formation ability of ovarian cancer cells Statistical analyses were done using SPSS V.16.0 for Win- OVCAR3 and OVCAR8 were significantly inhibited by over- dows (IBM) or GraphPad Prism (GraphPad Software, San expressing STK3 (P value <0.05) (Figure 2(c)). Diego, CA, USA). Cumulative survival time was calculated We used flow cytometry to detect the effect of STK3 on by the Kaplan-Meier method and analyzed by the log-rank the ovarian cancer cell cycle distribution. Cell cycle analysis test. Correlation of the STK3 expression with clinical param- showed that the proportion of OVCAR3 and OVCAR8 cells eters in patients with ovarian cancer was evaluated by χ2 test. in the G2/M phase significantly increased after exposure to Correlation was determined using the Spearman’s test. overexpressing STK3 (P value <0.05) (Figure 2(d)). 4 Journal of Immunology Research

TCGA-TARGET-GTEx GSE66957 15 15 ⁎⁎⁎⁎ ⁎⁎⁎⁎ STK3 STK3 10 10

5 5 Relative expression of of expression Relative Relative expression of of expression Relative

0 0 Normal ovary Ovarian cancer Normal ovary Ovarian tumor (n = 88) (n = 428) (n = 12) (n = 57)

GSE18520 GSE26712 12 ⁎⁎⁎⁎ 9 ⁎⁎⁎

11 8 STK3 STK3

10 7

9 6

8 5 Relative expression of of expression Relative of expression Relative

7 4 Normal ovary Ovarian tumor Normal ovary Ovarian cancer n n (n = 10) (n = 53) ( = 10) ( = 185) (a) TCGA cohort-OS TCGA cohort-PFS 100 100

50 50 Percent survival Percent survival Percent

P value = 0.0318 P value = 0.0221 0 0 0 2000 4000 6000 0 2000 4000 6000 Time (day) Time (day)

STK3-low (n = 215) STK3-high (n = 213)

GSE9899-OS GSE9899-PFS 100 100

50 50 Percent survival Percent survival

P value = 0.0351 P value = 0.0394 0 0 03691215 03691215 Time (year) Time (year) STK3-low (n = 54) STK3-high (n = 53) (b)

Figure 1: Database analysis showed that STK3 was downregulated in ovarian cancer tissues, and the overexpression of STK3 was closely related to better prognosis. (a) Analysis of the mRNA level expression of STK3 in the TCGA database and GEO database (two-tailed Student’s t-test, ∗∗∗P <0:001; ∗∗∗∗P <0:0001). (b) Analysis of the overall survival period and progression-free survival period according to the STK3 expression in the TCGA database and GEO database (log-rank test). Journal of Immunology Research 5

1.5 STK3 1.0

IOSE-8 CAOV3 OVCAR3 OVCAR8 ES-2

0.5 STK3 (normalized to IOSE80) to (normalized Relative expression of �-Actin 0.0 IOSE80 CAOV3 OVCAR3 OVCAR8 ES-2 (a) OVCAR3 OVCAR8

0.5 0.4 ct) ct) �� �� 0.4 (2- 0.3 (2-

Vector Lenti-STK3 STK3 STK3 0.3 Vector Lenti-STK3 0.2 STK3 STK3 0.2 0.1

0.1 �-Actin OVCAR8 �-Actin OVCAR3 Relative expression of

Relative expression of of expression Relative 0.0 0.0 Vector Lenti-STK3 Vector Lenti-STK3 (b)

OVCAR8 Vector OVCAR3 Vector OVCAR3 OVCAR8 80 ⁎⁎⁎⁎ 2.5 2.0 ⁎ 80 ⁎ ⁎ 60 2.0 60 1.5 ⁎ 1.5 ⁎ ⁎ 40 STK3 40 STK3 ⁎ 1.0 ⁎ Lenti- OVCAR8 Lenti- 1.0 ⁎ OVCAR3 Number of clones of Number Number of clones of Number 20 20 0.5 0.5 Absorbance (OD 450 nm) (OD Absorbance Absorbance (OD 450 nm) (OD Absorbance 0 0 0.0 0.0 STK3 Vector Lenti- STK3 0 h 24 h 48 h 72 h 96 h 0 h 24 h 48 h 72 h 96 h Vector Lenti- Time (h) Time (h)

Vector Lenti- STK3 (c)

Figure 2: Continued. 6 Journal of Immunology Research

Vector Lenti-STK3 OVCAR3 G1/G0 100 G1/G0

800 320 80

600 240 60 Number Number OVCAR3 400 160 G2/M 40

G2/M (%) Cell percentage 80 20 ⁎ 200 S S

0 0 0 0 50 100 150 200 250 0 50 100 150 200 250 G0/G1 S G2/M Channels (FL2-A) Channels (FL2-A) Vector Lenti-STK3

Vector Lenti-STK3 OVCAR8 G1/G0 G1/G0 100

320 800 80

240 600 60

Number 400 Number 160 40 OVCAR8 G2/M G2/M

S S (%) Cell percentage 80 200 20 ⁎⁎

0 0 0 0 50 100 150 200 250 0 50 100 150 200 250 G0/G1 S G2/M Channels (FL2-A) Channels (FL2-A) Vector Lenti-STK3 (d) Vector Lenti-STK3 OVCAR3 104 104 Q1 Q2 Q1 Q2 30 ⁎⁎⁎ 5.59% 7.40% 1.40% 22.0% 103 103 20 102 102 FL2-H FL2-H OVCAR3 101 101 10 Q3 Q3 Percent cell apoptosis Percent 0 3.11% 0 1.42% 10 10 0 100 101 102 103 104 100 101 102 103 104 Vector Lenti-STK3 FI 1-H Annexin IV FI 1-H Annexin IV

104 104 OVCAR8 Q1 Q2 Q1 Q2 20 ⁎⁎ 1.08% 6.64% 1.12% 11.6% 103 103 15 102 102 10 FL2-H FL2-H OVCAR8 101 101 5 Q3 Q3 Percent cell apoptosis Percent 100 0.909% 100 2.58% 0 100 101 102 103 104 100 101 102 103 104 Vector Lenti-STK3 FI 1-H Annexin IV FI 1-H Annexin IV (e)

Figure 2: Continued. Journal of Immunology Research 7

Vector Lenti-STK3 × 20 Vector TUNEL × 40 Lenti-STK3

OVCAR8 0.5 OVCAR8 15 ⁎ 0.4 × 20 0.3 10

0.2 5 PCNA Tumor weight (g) weight Tumor 0.1 × 40

0.0 0 Vector Lenti-STK3 03691215 18 21 24 Time (day) Vector Lenti-STK3 (f) Vector Lenti-STK3 Vector Lenti-STK3 3 AR OVCAR3 OVCAR3 OVC on i as Invasion Inv Migration 8 OVCAR8 OVCAR OVCAR8

OVCAR3 OVCAR8 OVCAR3 OVCAR8 ⁎⁎⁎⁎ ⁎⁎⁎⁎ 1500 1000 1000 400 ⁎⁎⁎⁎ 800 ⁎⁎⁎ 800 300 1000 600 600 200 400 400 500 100 200 200 Number of cells per feld of Number cells per feld of Number Number of cells per feld of Number cells per feld of Number 0 0 0 0 VectorLenti-STK3 Vector Lenti- STK3 Vector Lenti- STK3 Vector Lenti- STK3 (g)

Figure 2: Continued. 8 Journal of Immunology Research

Vector Lenti-STK3 OVCAR3 100 ⁎⁎⁎⁎

80 0 h

60

40 OVCAR3

20 24 h Wound healing percentage (%) percentage healing Wound 0 Vector Lenti-STK3

OVCAR8 100 ⁎⁎⁎⁎ 0 h 80

60

OVCAR8 40

24 h 20 Wound healing percentage (%) percentage healing Wound 0 Vector Lenti-STK3 (h)

Figure 2: Overexpressed STK3 can inhibit the invasion and proliferation of ovarian cancer cells in vitro and in vivo. (a) The STK3 expression in five different cell lines measured by qRT-PCR and Western blotting. (b) The STK3 overexpression was confirmed by Western blotting and qRT-PCR in OVCAR3 and OVCAR8 cell lines. (c) Effect of the STK3 overexpression on the proliferation and colony formation of OVCAR3 and OVCAR8 cells in vitro (two-tailed Student’s t-test, ∗P <0:05; ∗∗∗P <0:001). (d) The overexpression of STK3 arrested ovarian cancer cells at G2/M. The cell cycle distribution of OVCAR3 and OVCAR8 cells detected by flow cytometry (two- tailed Student’s t-test, ∗P <0:05). (e) The overexpression of STK3 promotes ovarian cancer cell apoptosis, as detected by cell apoptosis assays (two- tailed Student’s t-test, ∗∗P <0:01; ∗∗∗P <0:001). (f) Morphologic characteristics of tumors from mice inoculated with vector and lenti-STK3/OVCAR8 cells. Tumor weights and volumes of the vector and lenti-STK3 groups are shown (two- tailed Student’s t-test, ∗∗P <0:01). The overexpression of STK3 can inhibit the invasion and migration of ovarian cancer cells. (g) Effect of the STK3 overexpression on invasion and migration of OVCAR3 and OVCAR8 cells by cell migration and invasion assays (two- tailed Student’s t-test, ∗∗∗P <0:001; ∗∗∗∗P <0:0001). Scale bar: 100 μm. (h) Effect of the STK3 overexpression on the migration of OVCAR3 and OVCAR8 cells detected by wound healing assays (two- tailed Student’s t-test, ∗∗∗P <0:001; ∗∗∗∗P <0:0001). Scale bar: 100 μm.

We determined the effect of STK3 on ovarian cancer cells To determine the effect of STK3 on the migration and apoptosis by annexin V/PI staining and flow cytometry anal- invasion in ovarian cancer cells, we first examined the migra- ysis in vitro. The results showed that the apoptosis rate of the tion of OVCAR3 and OVCAR8 cells via transwell invasion lenti-STK3 group in OVCAR3 cell line was significantly and migration assays after overexpressing STK3. The results higher than that of the control group (17:72 ± 0:3358% showed that, compared with the control group, the invasive versus 9:887 ± 0:1203%, P value <0.05). Similarly, the and migratory abilities of ovarian cancer cells were signifi- apoptosis rate of the lenti-STK3 group in OVCAR8 cell line cantly decreased after exposure to overexpressed STK3 was also significantly higher than that in control group (P value <0.05) (Figure 2(g)). (P value <0.05) (Figure 2(e)). We also used a wound healing assay to determine the Finally, lentivector or lenti-STK3 OVCAR8 cells were effect of STK3 on the migration of serous ovarian cancer cells subcutaneously injected into nude mice to assess in vivo OVCAR3 and OVCAR8. The results showed that the migra- growth of tumors. The results showed that the tumor volume tion ability of serous ovarian cancer cells was significantly and tumor weight of the lentivector group were larger than decreased in the STK3 overexpression group compared with those of the lenti-STK3 group. These results indicate that the control group (P value <0.05) (Figure 2(h)). Thus, the the overexpression of STK3 significantly inhibited the growth overexpression of STK3 inhibited the invasion and migration of ovarian cancer (P value <0.05) (Figure 2(f)). of ovarian cancer cells. Journal of Immunology Research 9

TCGA cohort (total = 683)

Amplifcation (n = 105) Deep deletion (n = 1) NonAltered (n = 577) (a) CAOV3 IOSE-8 ⁎⁎ ns ⁎⁎ ns ⁎⁎ ns 4 ns 2.0 ns ns ns ns ns ⁎⁎ ns ⁎⁎ ns ⁎⁎ ns 1.5 3

1.0 2 (normalized to control) (normalized to

(normalized to control) (normalized to 0.5 1 Relative expression of STK3 of expression Relative Relative expression of STK3 of expression Relative

0.0 0 DAC ( �m) – 2 5 10 – – – 3 3 3 DAC ( �m) – 2 5 10 – – – 3 3 3 TSA (100 nM) – – – – 1.5 3 6 3 3 3 TSA (100 nM) – – – – 1.5 3 6 3 3 3 (b)

OVCAR3 OVCAR8 ⁎⁎ ⁎⁎ ⁎⁎ ⁎⁎ ⁎⁎ 4 ⁎⁎ 100 ⁎⁎ ns 4 ns ⁎⁎ ns ns ns ⁎ ⁎⁎ ⁎⁎ ns ⁎⁎ ⁎⁎ ⁎ ⁎ 80 3 3

60

2 2

40 (normalized to control) to (normalized 1 control) to (normalized Relative expression of STK3 of expression Relative 1 Total methylation rates (%) rates methylation Total 20 STK3 of expression Relative

0 0 0 IOSE-8 CAOV3 OVCAR3 OVCAR8 DAC (�m) – 2 5 10 – – – 3 3 3 DAC (�m) – 2 5 10 – – – 3 3 3 TSA (100 nM) – – – – 1.5 3 6 3 3 3 TSA (100 nM) – – – – 1.5 3 6 3 3 3 (c)

Figure 3: The STK3 expression in ovarian cancer cell lines. (a) Statistics of STK3-mutated samples derived from 683 patients in cBioportal. (b) The mRNA expression of STK3 was evaluated by real-time qPCR in cell lines (IOSE80, CAOV3, OVCAR3, and OVCAR8) treated with DMSO, DAC, TSA, or DAC plus TSA (two-tailed Student’s t-test, ∗∗P <0:01). (c) Total methylation rates of STK3 promoter in the human osteoblast cell line IOSE80 and three ovarian cancer cell lines (CAOV3, OVCAR3, and OVCAR8) are shown. (two-tailed Student’s t-test, ∗P <0:05, ∗∗P <0:01). 10 Journal of Immunology Research

Biological process Cellular component –Log10(P value) –Log10(P value) 0 5 10 15 20 0246810

Infammatory response Cytoplasm Immune response Nucleus I-kappaB kinase/NF-kappaB signaling Interleukin-23 complex Chemokine-mediated signaling pathway Extracellular space Cellular response to interleukin-1 I-kappaB/NF-kappaB complex Cellular response to tumor necrosis factor External side of plasma membrane Positive regulation of I-kappaB kinase/NF-kappaB signaling Cell surface Innate immune response Interleukin-6 receptor complex Positive regulation of interferon-gamma production Membrane raf Cytokine-mediated signaling pathway Transcription factor complex Positive regulation of interleukin-6 production Nucleoplasm Positive regulation of activated T cell proliferation Mitochondrial outer membrane Negative regulation of infammatory response Bcl3/NF-kappaB2 complex Positive regulation of B cell proliferation Cyclin-dependent protein kinase holoenzyme complex Cellular response to interferon-gamma Cytosol Positive regulation of NF-kappaB transcription factor activity

Molecular function KEGG

–Log10(P value) –Log10(P value) 0 5 10 15 0102030 Interleukin-23 receptor binding TNF signaling pathway CXCR3 chemokine receptor binding NF-kappa B signaling pathway Cytokine activity Cytokine-cytokine receptor interaction Chemokine activity Jak-STAT signaling pathway Growth factor activity Chemokine signaling pathway CCR chemokine receptor binding T cell receptor signaling pathway CXCR chemokine receptor binding Cytokine receptor activity TGF-beta signaling pathway DNA binding Insulin resistane RNA polymerase II transcription factor activity, sequence-specifc DNA binding B cell receptor signaling pathway Chromatin binding Non-alcoholic fatty liver disease (NAFLD) RNA polymerase II regulatory region, sequence-specifc DNA binding Type I diabetes mellitus Protein tyrosine phosphatase activity Signaling pathways regulating pluripotency of stem cells Transcription factor activity, sequence-specifc DNA binding Acute myeloid leukemia Sequence-specifc DNA binding ErbB signaling pathway RNA polymerase II transcription factor activity, ligand-activated sequence-specifc DNA binding Pancreatic cancer Zymogen binding Colorectal cancer p53 signaling pathway

(a)

Enrichment plot: HALLMARK_TNFA_SIGNALING_VIA_NFKB 0.7 0.6 0.5 0.4 0.3 0.2 NES = 1.63 FDR q value = 0.05 0.1 P

Enrichment score (ES) score Enrichment value = 0.008 0.0

0.6 “H” (positively correlated) 0.4 0.2 Zero cross at 37683 0.0 –0.2 “L” (negatively correlated)

Ranked list metricRanked (signal2noise) 0 10,000 20,000 30,000 40,000 50,000 Rank in ordered dataset Enrichment profle Hits Ranking metric scores

(b)

Figure 4: Continued. Journal of Immunology Research 11

CD8(+) T-cells B cells Cytotoxic cells 1.0 1.0 1.0

0.8 0.8 0.8

0.6 0.6 0.6

0.4 0.4 0.4

0.2 0.2 0.2 Correlation coefcient Correlation Correlation coefcient Correlation Correlation coefcient Correlation

0.0 0.0 0.0 SF1 PF4 BLK SPIB PRF1 ZEB1 PRR5 CD72 CD19 CD22 ABT1 CCR9 CD8B BLNK TBCC GNLY CD8A NKG7 TMC6 GNG7 RORA GLDC PNOC CTSW LIME1 FCRL2 ZNF22 ZNF91 QRSL1 KLRF1 COCH GZMK GZMA KLRB1 GZMH TCL1A APBA2 KLRK1 APOL3 ABCB4 KLRD1 HAUS3 SCN3A RBM33 GZMM MEF2C BACH2 RUNX3 VAMP2 PPP1R2 FLT3LG ZBTB16 DUSP22 BCL11A CAMLG MS4A10 DNAJB1 MICAL3 DTNBP1 SLC16A7 SLC15A2 OSBPL10 TSC22D3 GADD45A LEPROTL1 THUMPD1 CDKN2AIP

Macrophages Mast cells NK cells T1 cells 1.0 1.0 1.0 1.0

0.8 0.8 0.8 0.8

0.6 0.6 0.6 0.6

0.4 0.4 0.4 0.4

0.2

Correlation coefcient Correlation 0.2 0.2 0.2 Correlation coefcient Correlation Correlation coefcient Correlation Correlation coefcient Correlation

0.0 0.0 0.0 0.0 KIT FN1 SPN BLK PRX SPIB HDC MPO FZR1 TAL1 BCL2 XCL1 XCL2 CPA3 LDB3 SCG2 CCL7 CD68 CD84 CD33 CD72 CD19 CD22 PRG2 GPC4 CTSK ATG7 CCR9 MSR1 CYBB CTSG EMP1 NCR1 BLNK FU T5 RAI14 GNG7 GLDC TPSB2 PNOC CMA1 FGF18 MLPH GM2A HPGD FCRL2 QRSL1 CD163 COCH CHIT1 MAOB NR0B1 CALB2 CXCL5 TCL1A BCAT1 MS4A2 ABCB4 SCN3A GATA2 PTGDS CDC5L TCTN2 PSMD4 MEF2C BACH2 IGFBP5 PPM1H CHI3L1 ZNF747 ZNF205 ZNF528 TPSAB1 BCL11A NCAM1 MS4A10 PDLIM4 MICAL3 COL8A2 CLEC5A MARCO CELA2A TBXA2R MS4A4A FCGR3A DTNBP1 SIGLEC6 ADARB1 SLC15A2 SLC30A5 SLC18A2 MAPRE3 OSBPL10 KIR2DL1 SULT1C2 TINAGL1 COLEC12 MCM3AP PCOLCE2 ALDH1B1 CEACAM8 (c)

Figure 4: STK3 is correlated with CD8+ T cell infiltration and the NF-κB signaling pathway in ovarian cancer. (a) Representative GO and KEGG categories affected by the STK3 expression in OVCAR8 cells. (b) Gene set enrichment analysis (GSEA) using reactome gene sets compared the TCGA ovarian database. NES: normalized enrichment score. (c) The correlation between STK3 and specific gene signatures of different immune cells.

3.3. STK3 Is Downregulated in Ovarian Cancer via Epigenetic kinase/NF-kappa B signaling, I-kappa B kinase/NF-kappa B Promoter DNA Methylation. Genetic or epigenetic mecha- signaling complex, CXCR chemokine receptor binding, and nisms (or both) might cause dysregulation of the STK3 NF-kappa B signaling pathway, indicating a regulatory role expression in ovarian cancer. STK3 is located on chromo- of STK3 in ovarian cancer immune microenvironment some 8q22.2, and there is no deletion in this region in ovarian (Figure 4(a)). cancer (Figure 3(a)). We explored the epigenetic regulation We used GSEA to analyze the differentiated genes in the of the STK3 expression in ovarian cancer. Using 5-aza-20- high and low STK3 expression groups in the TCGA ovarian deoxycytidine (DAC), a specific methyltransferase inhibitor, cancer database. The results indicated that the STK3 expres- and Trichostatin A (TSA), a histone deacetylase inhibitor, sion was related to the NF-κB signaling pathway, which we found that the mRNA expression level of STK3 in ovarian was TNFA_SIGNALING_VIA_NFKB. STK3 may regulate cancer cells was significantly increased after DAC treatment immune microenviroment of ovarian cancer cells by affecting (P value <0.05), but not by TSA treatment. The expression NF-κB signaling (Figure 4(b)). of STK3 increased only slightly in IOSE80 treated with To characterize the potential immune components in the DAC (P value <0.05) (Figure 3(b)). To validate the tumor microenvironment affected by STK3, an immunome methylation-mediated downregulation of STK3 in ovarian compendium was built by publicly available data from puri- cancer, we performed bisulfite sequencing PCR of DNA from fied immune cell subsets. According to the previous studies, IOSE80, CAOV3, OVCAR3, and OVCAR8 cells. The STK3 we investigated both innate immune cells (mast cells, macro- promoter in ovarian cancer cells showed significantly higher phages, and natural killer cells) and adaptive immune cells (B levels of methylation compared with that in IOSE80 cell, Th1, and CD8+ T cell) as well as cytotoxic cells[17]. We (CAOV3: 43%; OVCAR3: 64%; and OVCAR8: 87%) observed that STK3 was specifically correlated with the gene (Figure 3(c) P value <0.05). These data indicated that epige- signatures of CD8+ T-cells. In contrast, no obvious correla- netic methylation suppresses the expression level of STK3 tion was found in the expression of STK3 and other in ovarian cancer. immune component-related genes. STK3 might exhibit a regulatory role on CD8+ T cell infiltration in ovarian cancer (Figure 4(c)). 3.4. STK3 Correlates with CD8+ T-Cell in Ovarian Cancer. To study the possible mechanism of STK3 in ovarian cancer, we compared the transcriptome of STK3 overexpressed ovarian 3.5. The Overexpression of STK3 Promoted the Release of cancer OVCAR8 cells with that of control cells by high- CXCL16 and CX3CL1 and Migration of CD8+ T-Cells by throughput transcriptome sequencing (RNA-seq, supple- Activating NF-κB Signaling. To study the chemokines regu- mentary Table 1). The differentially expressed genes were lated by STK3 that promote CD8+ T-cell infiltration, the che- analyzed by GO analysis and KEGG enrichment analysis. mokine profiles of conditional medium from vector and The results showed that overexpressing STK3 significantly lenti-STK3 OVCAR8 cells were analyzed using the RayBio affected multiple inflammatory responses, including I-kappaB Human Cytokine Antibody Array. Consistent with the 12 Journal of Immunology Research

Chemokines Log2(fold change) Regulation

CXCL16 0.85 Up

CX3CL1 0.18 Up

(a) OVCAR3 OVCAR8 4 2.0 ⁎ ⁎⁎⁎⁎ ⁎ 3 1.5 ⁎

2 1.0 Relative mRNA level mRNA Relative 1 level mRNA Relative 0.5

0 0.0 CXCL16 CX3CL1 CXCL16 CX3CL1 Vector Lenti-STK3 (b) CXCL16 CX3CL1 ⁎⁎ 4000 ⁎⁎ 400 ⁎⁎⁎ ⁎⁎⁎

3000 300

2000 200 CX3CL1 (pg/mL) CXCL16 (pg/mL) CXCL16 1000 100

0 0 OVCAR3 OVCAR8 OVCAR3 OVCAR8 Vector Lenti-STK3 (c)

Figure 5: Continued. Journal of Immunology Research 13

Control rCXCL16 rCXCL16+Blocker Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter ======80 cells 2.03 × 10 cells/mL 9.0 microns 266 cells 6.76 × 10 cells/mL 9.5 microns 167 cells 4.23 × 10 cells/mL 8.6 microns

Original Image Counted Image Original Image Counted Image Original Image Counted Image

Control rCX3CL1 rCX3CL16+Blocker Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter ======CD8+ T-cell 208 cells 5.29 × 10 cells/mL 9.6 microns 401 cells 1.02 × 10 cells/mL 10.5 microns 185 cells 4.71 × 10 cells/mL 9.7 microns

Original Image Counted Image Original Image Counted Image Original Image Counted Image

CD8+ T-cells CD8+ T-cells ⁎⁎⁎ ⁎⁎ 8 × 105 1.5 × 10 6

6 × 105 ⁎⁎⁎ ⁎⁎⁎⁎

1 × 106

4 × 105 (cells/mL) (cells/mL) 5 × 106 2 × 105 Concentration of lower chamber lower of Concentration Concentration of lower chamber lower of Concentration

0 0 Control Control rCXCL16 rCX3CL1 rCX3CL1+blocker rCXCL16+blocker (d)

Figure 5: Continued. 14 Journal of Immunology Research

OVCAR3 culture medium Vector Lenti- STK3 Lenti- STK3 +antiCXCL16 Lenti- STK3 +antiCX3CL1 Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter ======295 cells 7.53 × 10 cells/mL 10.5 microns 604 cells 1.55 × 10 cells/mL 12.0 microns 182 cells 4.64 × 10 cells/mL 10.4 microns 165 cells 4.21 × 10 cells/mL 10.5 microns

Original Image Counted Image Original Image Counted Image Original Image Counted Image Original Image Counted Image OVCAR8 culture medium Vector Lenti- STK3 Lenti- STK3 +antiCXCL16 Lenti- STK3 +antiCX3CL1 Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter Total Count Concentration Mean Diameter

CD8+ T-cell ======337 cells 8.64 × 10 cells/mL 11.6 microns 318 cells 1.08 × 10 cells/mL 10.6 microns 203 cells 5.18 × 10 cells/mL 10.4 microns 200 cells 5.08 × 10 cells/mL 9.4 microns

Original Image Counted Image Original Image Counted Image Original Image Counted Image Original Image Counted Image OVCAR3 OVCAR8 6 2 × 10 ⁎⁎⁎⁎ 1.5 × 106 ⁎⁎⁎⁎ ⁎⁎⁎⁎ ⁎⁎⁎⁎ ⁎⁎⁎⁎ ⁎⁎⁎⁎

1.5 × 10 6 1 × 10 6

1 × 10 6 (cells/mL) (cells/mL) 5 × 10 5 5 × 10 5 Concentration of lower chamber lower of Concentration Concentration of lower chamber lower of Concentration

0 0 STK3 STK3 Vector Vector Lenti- Lenti- antiCXCL16 antiCX3CL1 antiCXCL16 antiCX3CL1 (e) TCGA 10

5

0

NFKB1 –5

–10 r = 0.6287 –15 –15 –10 –5 0510 STK3 (f)

Figure 5: Continued. Journal of Immunology Research 15

10 TCGA 10 TCGA

5 5

0 0

–5 –5 CX3CL1 CXCL16

–10 –10 r = 0.78 r = 0.58 –15 –15 –15 –10 –5 0510–15 –10 –5 0510 NFKB1 NFKB1 (g) OVCAR3 OVCAR8 Vector Lenti-STK3 Vector Lenti-STK3

p-lkB

lkB

p-p65

p65

�-Actin

(h)

Figure 5: STK3 promoted release of CXCL16 and CX3CL1, migration of CD8+ T-cell, and activation of NF-κB signaling. (a) Chemokine array of the conditional medium (CM) from vector and lenti-STK3 OVCAR8 cells. A. Table summarizing the relative signal intensity of indicated chemokines is presented in the lower left corner. (b) Real-time qPCR analysis of the effect of STK3 overexpression on the CXCL16 and CX3CL1 mRNA level in OVCAR3 and OVCAR8 cells (two-tailed Student’s t-test, ∗P <0:05; ∗∗P <0:01). (c) ELISA analysis of the CXCL16 and CX3CL1 level in the CM from vector and lenti-STK3 OVCAR3 and OVCAR8 cells (two-tailed Student’s t-test, ∗∗P <0:01; ∗∗∗P <0:001). (d) Effects of rCXCL16 and rCX3CL1 on the migratory ability of human CD8+ T-cells. The number of cells was counted by Cellometer (two-tailed Student’s t-test, ∗∗P <0:01; ∗∗∗P <0:001; ∗∗∗∗P <0:0001). (e) Ovarian cancer cell culture supernatants were neutralized with anti-CXCL16 antibody and anti-CX3CL1 antibody and the migratory ability of CD8+ T-cells. The number of cells was counted by Cellometer (two-tailed Student’s t-test, ∗∗P <0:01; ∗∗∗P <0:001; ∗∗∗∗P <0:0001). (f) Correlation between STK3 and NFKB1 in the TCGA database. (g) Correlation between NFKB1 and CXCL16 or CX3CL1 in the TCGA database. (h) Western blot analysis of the effect of the STK3 overexpression on the NF-κB pathway activity. results of RNA-seq (Supplementary Table 1), two cytokines, both CXCL16 and CX3CL1 contribute to CD8+ T-cells CXCL16 and CX3CL1, were significantly increased in the (P value <0.05) (Figure 5(d)). Consistently, neutralization conditional medium of lenti-STK3 cells compared with of CXCL16 and CX3CL1 in the conditional medium from vector cells (Figure 5(a)). Real-time PCR showed that the OVCAR8 and OVCAR3 cells also suppressed the migratory STK3 overexpression drastically promoted the mRNA level potential of CD8+ T-cells (P value <0.05) (Figure 5(e)). of CXCL16 and CX3CL1 in both OVCAR8 and OVCAR3 To evaluate whether the NF-κB pathway is responsible cells (P value <0.05) (Figure 5(b)). An ELISA assay for the STK3-mediated CXCL16 and CX3CL1 expression, confirmed the increase of CXCL16 and CX3CL1 in the we first analyzed the correlation between the expression of conditional medium of lenti-STK3 cells (P value <0.05) STK3 and NF-κB in TCGA. The levels of the STK3 (Figure 5(c)). We then evaluated whether these two expression were significantly positively correlated with NF-κB chemokines are responsible for CD8+ T-cell infiltration (P value <0.05) (Figure 5(f)). Previous study revealed that in vitro. Stimulation of CD8+ T-cells with recombinant NF-κB is the widely reported transcription factor for CXCL16 CXCL16 (rCXCL16) and CX3CL1 (rCXCL16) showed and CX3CL1. Further analyses indicated that the level of enhanced migratory ability, and this promotive effect was NF-κB was also significantly positively correlated with largely compromised by the addition of neutralizing anti- CXCL16 and CX3CL1 (P value <0.05) (Figure 5(g)). The CXCL16 and anti-CX3CL1 antibody. This indicated that phosphorylation level of p65 and NF-κB inhibitor alpha 16 Journal of Immunology Research

(IkBα) in ovarian cancer regulated by STK3 was also firmed that STK3 may indirectly participate in suppressing investigated. The phosphorylation level of IkBα and p65 ovarian cancer by regulating the activity of LATS1/2 and YAP. was markedly increased by the overexpression of STK3 CD8+ T-cells are considered to be antitumor immune (Figure 5(h)). These data indicated that the upregulated cells [30]. We performed GO enrichment analysis and KEGG STK3 expression could promote the NF-κB signaling of pathway enrichment analysis based on RNA-seq results of ovarian cancer, which may further induce the expression ovarian cancer cells in the control group and STK3 of CXCL16 and CX3CL1. overexpression group. The results showed that STK3 and the NF-κB signaling were related to infiltration of CD8+ T- cells. There is a close connection between the pathways. We 4. Discussion also found a correlation between STK3 and CD8+ T-cells in the tumor microenvironment. The overexpression of STK3 Many studies have shown that key molecules of the Hippo can promote ovarian cancer cells to secrete CXCL16 and signal transduction pathway are important in inhibiting the CX3CL1. The overexpression of STK3 can promote the occurrence and development of malignant tumors [18]. migration of CD8+ T-cells. These results are the first correla- Serine/threonine kinases (STKs) are key molecules in the tion between the function of STK3 with CD8+ T-cells, and Hippo pathway. STKs control organ growth and reduce tumor they help explain the effect of STK3 inhibition on the growth ff progression by their e ects on the Hippo pathway [19]. and metastasis of ovarian cancer from the perspective of the In this study, bioinformatic analysis showed that STK3 tumor microenvironment. has low levels in ovarian cancer tissues, and the reduced expression of STK3 is closely related to the poor prognosis 5. Conclusions of patients suffering ovarian cancer. As an important compo- nent of the Hippo pathway, STK3 has been involved in the This study showed that upregulated serine/threonine kinase progression of many types of cancers. For instance, the STK3 inhibits ovarian cancer aggressiveness and is correlated reduced expression of STK3 was found in gastric cancer, with CD8+ T-cells chemotaxis. These results provide insight and tumors from patients with lymph node metastasis into the roles of serine/threonine kinase in immune modula- showed minimal levels of STK3 [20]. Genetic deletion of tion. We also found that STK3 modulates intracellular NF-κB STK3 in hepatocytes also led to the development of hepato- signaling. These findings strongly suggest that the STK3/NF- cellular carcinoma [21]. Additionally, STK3 inhibits the pro- κB/CXCL16-CX3CL1/CD8+ T-cell axis is a potential thera- liferation of breast cancer cells and is overexpressed in breast peutic target in ovarian cancer. cancer tissues [22]. Increasing evidences showing that the STK3 alterations may be caused by genetic or epigenetic Data Availability changes. For example, hypermethylation of the promoter region of the STK3 gene contributes to the downregulation The data used to support the findings of this study were sup- of the STK3 expression in soft tissue sarcoma [23], which is plied by Rong Zhang under license and so cannot be made consistent with our result on ovarian cancer. Therefore, we freely available. Requests for access to these data should be believe that STK3 may be a good prognostic marker for made to Rong Zhang, [email protected]. ovarian cancer. It is known that the overexpression of STK3 can reduce Conflicts of Interest the proliferation, migration, and invasion of glioblastoma fl and pancreatic cancer [24, 25]. In nonsmall cell lung cancer The authors declares that there is no con ict of interest tissues, the overexpression of STK3 can reduce the invasion regarding the publication of this paper. and metastasis ability of lung cancer cells and promote lung ’ cancer cell apoptosis [26]. Similarly, in the present study, Authors Contributions we found that the overexpression of STK3 inhibits the inva- Xiangyu Wang and Fengmian Wang contributed equally to sion, proliferation, and metastasis of ovarian cancer cells this work and should be considered co-first authors. and promotes their apoptosis. Besides STK3, other compo- nents of the Hippo pathway have roles in ovarian cancer Acknowledgments [27]. Previous study revealed that LATS1/2 downregulation by the ubiquitin system is associated with epithelial- This study was a supported by a grant from the National Nat- mesenchymal transition-like phenotypic changes in ovarian ural Science Foundation of China (No.: 81472445, 81672587). cancer cells, which trigger abnormal migration and invasion [28]. Moreover, a relationship between high levels of nuclear Supplementary Materials YAP in primary tumor tissues and inferior survival in ovarian cancer patients has also been reported [29]. In immortalized See Supplementary Table 1 in the Supplementary Material for ovarian surface epithelial cells, the overexpression of YAP comprehensive transcriptome analysis in control OVCAR8 increased cell proliferation and migration ability and promoted cells and STK3-overexpressing OVCAR8 cells. Transcriptome anchorage-independent growth as well as contributed to the analysis in vector control and STK3-overexpressing OVCAR8 resistance to cisplatin-induced apoptosis, suggesting the onco- cells. Transcriptome analysis was performed on vector control genetic role of YAP in ovarian cancer. Our study further con- and STK3-overexpressing OVCAR8 cells after extracting total Journal of Immunology Research 17

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