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Abstract

OBJECTIVE:

LGR4 expression in serous ovarian cancer paraffin-embedded tissues and fresh tissues were investigated, and its expression associated with clinicopathological parameters and prognosis in serous ovarian cancer was explored.

METHODS:

From Dec, 2009 to Jan, 2020, 122 paraffin-embedded serous ovarian cancer patients and 41 paired paratumor tissues who were both diagnosed and operated at the memorial hospital of Sun Yat-sen University and Integrated Hospital of Traditional Chinese Medicine, Southern Medical University were selected in this research, respectively, and all of these tissues were performed by immunohistochemistry (IHC) with a polyclonal antibody for LGR4. Meanwhile, from Aug, 2013 to Mar, 2019, 15 cases of serous ovarian cancer fresh tissues and 15 cases of paratumor fresh tissues who were operated at Integrated Hospital of Traditional Chinese Medicine, Southern Medical University were performed with Quantitative Real-time PCR to detect the mRNA expression of LGR4, respectively.

RESULTS:

LGR4 expression was much higher both in paraffin-embedded and fresh cancer tissues than that in paratumor tissues, respectively, and its expression was associated with recurrence free survival and overall survival in serous ovarian cancer patients. Moreover, in a multivariate model LGR4 was an indeed independent predictor of poor survival in serous ovarian cancer patients.

CONCLUSION:

LGR4 is upregulated in serous ovarian cancer, and LGR4 is an indeed useful independent prognostic predictor in serous ovarian cancer, and it may provide important clinical value of serous ovarian cancer.

Keywords

LGR4 serous ovarian cancer prognosis

1. Introduction

Ovarian cancer (OC) is the first leading cause of mortality in female reproductive malignant cancers in China [1]. Globally, there are 239,000 new cases and 152,000 deaths annually, making ovarian cancer the seventh most common cancer, and the second most common cause of gynecologic cancer death [2]. And the main pathological type is serous ovarian cancer. The prognosis of serous ovarian cancer is very poor, and the reason is that it was found to be advanced when diagnosed [3]. However, when found early, the survival rate dramatically rises to 90% [3, 4]. Thus, detecting serous ovarian cancer in the earliest stages or discovering recurrence early after operation is critical to a cure [5]. So the effective early diagnostic methods were urgent as it may help to improve the prognosis [6, 7]. Recently several tumor biomarkers have been used to diagnose and to monitor the progression and prognosis of ovarian cancer, and also to detect the disease recurrence after operation or chemotherapy. However, these biomarkers are neither extremely sensitive nor specific. Therefore, to search new biomarkers are very important.

Leucine-rich repeat domain containing G protein-coupled receptor 4 (LGR4) also called G-protein-coupled receptor-48 (GPCR48) [8, 9]. Upregulation of LGR4 has been found to enhance cell invasion and metastasis in colon carcinoma cells [10]. Recent studies have shown that LGR4 regulates mammary gland and prostate progression and is involved in tumor stem cell functions through regulation of the Wnt, Notch and Sonic Hedgehog signaling pathways [11]. In addition, LGR4 activates multiple signalling pathways[12, 13, 14, 15, 16]. Moreover, several reports showed that the RSPOs are the endogenous ligands of GPR48/LGR4, revealing the important role of LGR proteins in epithelial stem cell homeostasis [17, 18, 19, 20]. Further studies showed that RSPOs potentiate Wnt/ $\beta$ -catenin signalling pathway through activation of LGR4 [20, 21]. RSPOs and LGR receptors activate the Frizzled receptor, leading to repression of GSK3 $\beta$ , accumulation of active $\beta$ -catenin, and its translocation to the nucleus [22]. In colorectal cancer [23], circLgr4 drives colorectal tumorigenesis and invasion through Lgr4-targeting peptide. And in gastric cancer [24], LGR4 was upregulated in cancer tissues, and was a poor prognostic factor of gastric cancer. In non-small cell lung carcinoma [25], LGR4 was targeted by miR-449b thus inhibited cell growth and invasion. However, there is no research about the role of LGR4 in serous ovarian cancer.

Therefore, in this study we aimed to investigate the exact role of LGR4 in serous ovarian cancer tissues and paratumor tissues (both paraffin-embedded and fresh tissues), and to explore its expression associated with clinicopathological parameters and prognostic value in serous ovarian cancer.

2. Materials and methods

2.1 Paraffin-embedded tissue sections

From Dec, 2009 to Jan, 2020, a total of 122 cases paraffin-embedded serous ovarian cancer tissues and 41 paraffin-embedded paratumor tissues who had been pathologically diagnosed at the memorial hospital of Sun Yat-sen University and Integrated Hospital of Traditional Chinese Medicine, Southern Medical University were all collected in this investigation. Survival duration was calculated from the operation date until Jan, 2020 (at last follow-up). This trial was both obtained approval from the memorial hospital of Sun Yat-sen University and Integrated Hospital of Traditional Chinese Medicine, Southern Medical University Ethics Committee. All of the patients signed the informed consent before operation.

2.2 Fresh tissue specimens

From Aug, 2013 to Mar, 2019, 15 cases of serous ovarian cancer fresh tissues and 15 cases of paired fresh paratumor tissues diagnosed postoperation who were collected from Integrated Hospital of Traditional Chinese Medicine, Southern Medical Universtiy. All of fresh samples were immediately preserved in liquid nitrogen. This trial was obtained approval from Integrated Hospital of Traditional Chinese Medicine, Southern Medical Universtiy Ethics Committee. All of the patients signed the informed consent before operation.

2.3 Immunohistochemistry (IHC)

The LGR4 expression in 122 cases of paraffin-embedded serous ovarian cancer and 41 cases of paired paratumor tissues were detected by immunohistochemical staining. The procedure is as follows, the samples were fixed in 4% formaldehyde for 12 h subsequently 4 $\mu$ m-thick paraffin-embedded sections (saved at $-$ 20 ${}^{\circ}$ C) were incubated at 65 ${}^{\circ}$ C for more than 2 h, deparaffinized with xylene, rehydrated and microwaved in antigen retrieval buffer. Next, high tension was used for antigen retrieval and the specimens were treated with 3% hydrogen peroxide in methanol to quench endogenous peroxidase activity, followed by incubation with 1% bovine serum albumin (OriGene Technologies, Inc.) to block non-specific binding (room temperature for 15 min), and incubation with anti-rabbit LGR4 polyclonal antibody (1:100; Proteintech, Inc. Cat: 20150-1-AP) at 4 ${}^{\circ}$ C overnight. After washing, the tissue sections were treated with secondary antibody (goat anti-mouse/rabbit IgG, cat no. K186715D; 50 uL for each section; OriGene Technologies, Inc,) for 2 h at room temperature, then incubated with streptavidin horseradish peroxidase complex (OriGene Technologies, Inc.) for 15 min at room temperature, immersed in 3-amino-9-ethyl carbazole. The sections were then counterstained with 10% Mayer’s hematoxylin (2 min at room temperature), dehydrated and mounted in Crystal Mount. Two pathologists evaluated the degree of immunostaining of each formalin-fixed, paraffin-embedded section with light microscope (Olympus). The score was due to both the proportion of positively stained cancer cells and the intensity of staining. The percentage of cancer cells was scored as follows: Sections with $<$ 10% positive cancer cells were scored as 0; 10–50% positive cancer cells were scored as 1; 50–75% positive cancer cells were scored as 2; and $>$ 75% positive cancer cells were scored as, 3. Meanwhile, the tissues were sorted into four grades based on staining intensity, as follows: 0 indicated no staining; 1 indicated weak staining (light yellow); 2 moderate staining (yellow brown); and 3 strong staining (brown). The staining index (0–9) was calculated as the product of the proportion of positive cells multiplied by the staining intensity score. The best cutoff value was defined as follows: A staining score of $\geqslant$ 6 was considered to have high LGR4 expression and a staining score of $\leqslant$ 5 indicated low LGR expression [26, 27, 28, 29, 30, 31].

2.4 Quantitative real time polymerase chain reaction (qRT-PCR)

Total RNA was extracted from the fresh serous ovarian cancer tissues and fresh paratumor tissues by Trizol (Takara Bio, Inc., Shiga, Japan). GAPDH gene were used as gene internal control. Each of paired paratumor fresh tissues’ expression levels were set as negative control group (all of the paratumor tissues’ expression level of LGR4 were 1.00 $\pm$ 0.00). Cycling conditions were 95 ${{}^{\circ}}$ C for 10 min to activate DNA polymerase, followed by 45 cycles of 95 ${{}^{\circ}}$ C for 15 s, 60 ${{}^{\circ}}$ C for 15 s and 72 ${{}^{\circ}}$ C for 10 s. Specifificity of amplifification products was confirmed by melting curve analysis [32, 33, 34, 35, 36, 37]. Independent experiments were done in triplicate. Specific sense primers for LGR4 is the following: Forward primer: 5 ${}^{\prime}$ -A C C T G G A G A C C T T A G A C T T G -3 ${}^{\prime}$ ; Reverse primer: 5 ${}^{\prime}$ -C C A C G A A T G A C T A G G G A A T G -3 ${}^{\prime}$ . GAPDH (Forward primer: 5 ${}^{\prime}$ -C C A T C T T C C A G G A G C G A G A T -3 ${}^{\prime}$ ; Reverse primer: 5 ${}^{\prime}$ -T G C T G A T G A T C T T G A G G C T G -3 ${}^{\prime}$ ).

2.5 Statistical analysis

All data were carried out with the statistical software package SPSS 21.0 and Graphpad Prism 7. The chi-square test or Fisher’s exact test were used to analyze the relationship between LGR4 and clinicopathological parameters. mRNA expression of LGR4 was presented with $\bar{x}\pm s$ . Two-tailed Student’s t-test was used for comparisons of two independent groups (The expression of LGR4 mRNA in paratumor tissues as the negative control group). Moreover, Patients’ recurrence free survival (also called RFS) and overall survival (also called OS) were analysed by a Kaplan–Meier analysis, and the differences were counted by the log-rank test. Cox’s proportional hazards regression model was used to the univariate and multivariate analysis. All of $p$ value $<$ 0.05 were considered statistically significant.

3. Results

3.1 LGR4 was upregulated in fresh serous ovarian cancer fresh tissues compared with paratumor tissues using qRT-PCR

Table 1
LGR4 was significantly upregulated in serous ovarian cancer fresh tissues compared with paratumor tissues

Group	LGR4 mRNA expression
Paratumor	1.00 $\pm$ 0.00
Patient 1	3.578 $\pm$ 1.511
Patient 2	1.583 $\pm$ 0.5615
Patient 3	1.814 $\pm$ 0.2018
Patient 4	36.54 $\pm$ 11.60
Patient 5	3.531 $\pm$ 1.406
Patient 6	0.8870 $\pm$ 0.1085
Patient 7	0.3984 $\pm$ 0.2202
Patient 8	10.20 $\pm$ 2.117
Patient 9	5.847 $\pm$ 1.260
Patient 10	22.65 $\pm$ 5.928
Patient 11	0.1212 $\pm$ 0.008875
Patient 12	0.3201 $\pm$ 0.1966
Patient 13	0.4342 $\pm$ 0.2410
Patient 14	13.39 $\pm$ 5.463
Patient 15	2.374 $\pm$ 0.9367
Expression of all patients	4.6458 $\pm$ 6.4055 ${}^{***}$
$P$	0.000

Table 2

LGR4 expression in association with standard clinicopathological parameters using the $\chi^{2}$ or fisher’s exact test

Parameters	Total	LGR4
		Low	High	$P$ -value ( $\chi$ or fisher’s exact test)
Age (years)
$\leqslant$ 50	50	23	27	0.0157
$>$ 50	72	18	54
FIGO stage
I/II	15	8	7	0.0842
III/IV	107	33	74
Lymph node metastasis
No	26	15	11	0.1056
Yes	28	10	18
Intraperitoneal metastasis
No	27	12	15	0.1767
Yes	95	29	66
Intestinal metastasis
No	42	15	27	0.7210
Yes	80	26	54
Vital status
Alive	44	25	19	0.0030
Dead	49	13	36
Intraperitoneal recurrence
No	78	29	49	0.4951
Yes	42	13	29
Distant recurrence
No	96	35	61	0.2898
Yes	24	6	18
Differentiation grade
G1/G2	37	13	24	0.8832
G3	80	27	53
Platinum resistance
No	120	50	70	0.5123
Yes	2	0	2
Ascites with tumor cells (+)
No	26	10	16	0.8008
Yes	34	12	22
CA125 (U/mL)
$\leqslant$ 35	9	3	6	0.9551
$>$ 35	108	37	71
CA72-4 (U/mL)
$\leqslant$ 7	40	14	26	0.8175
$>$ 7	58	19	39
CA153 (U/mL)
$\leqslant$ 25	12	2	10	0.1104
$>$ 25	33	14	19
AFP (U/mL)
$\leqslant$ 25	99	32	67	$>$ 0.9999
$>$ 25	0	0	0
CEA (U/mL)
$\leqslant$ 5.0	94	33	61	0.0561
$>$ 5.0	7	0	7
HE4 (pmol/L)
$\leqslant$ 140	15	4	11	0.2852
$>$ 140	55	23	32

Figure 1.

LGR4 was upregulated in fresh serous ovarian cancer fresh tissues.

Figure 2.

the mRNA expression of LGR4 in serous ovarian cancer and paratumor fresh tissues.

Figure 3.

LGR4 overexpression in paraffin-embedded serous ovarian cancer tissues with IHC: (A) LGR4 expression in serous ovarian cancer tissues and paratumor tissues ( $P<$ 0.001); (B) Comparison of LGR4 expression between serous ovarian cancer and paratumor tissues (400X); (C) The different staining of LGR4 expression in serous ovarian cancer (400X).

Figure 4.

Kaplan-meier survival of overall survival (OS) and recurrence free survival (RFS) in dead serous ovarian cancer patients.

In this study, we performed qRT-PCR to detect the expression level of LGR4 in 15 cases of serous ovarian cancer fresh tissues and 15 cases of paired paratumor fresh tissues, respectively (all of paratumor tissues were 1.00 $\pm$ 0.00) (Fig. 1 and Table 1). The results showed that the mean expression of LGR4 in 15 cases of fresh serous ovarian cancer tissues was 4.6458 $\pm$ 6.4055 (Table 1). and there was a significant difference between fresh serous ovarian cancer tissues and fresh paratumor tissues ( $P=$ 0.000) (Fig. 2 and Table 1).

3.2 LGR4 overexpression in paraffin-embedded serous ovarian cancer tissues with IHC

To further determine the expression of LGR4 in serous ovarian cancer paraffin-embedded tissues, we stained 122 cases of serous ovarian cancer and 41 cases of paratumor tissues. The results showed that 41/122 (33.61%) had low/none staining (also called low expression, LGR4-) and 81/122 (66.39%) had moderate/strong staining (also called high expression, LGR4+), while in 41 paratumor tissues stained with the LGR4 antibody, 29/41 (70.73%) had low/none staining and 12/41 (29.27%) had moderate/strongstaining, and there was significantly different between tumor and paratumor groups ( $P<$ 0.001) (Fig. 3A). Moreover, we found that LGR4 protein expression staining located at cytoplasmic (Fig. 3B and C).

Table 3
Cox regression univariate and multivariate analyses of prognostic factors in serous ovarian cancer

Variable	Univariate analysis			Multivariate analysis
	Number of patients	${p}$	Regression coefficient (SE)	${p}$	95% confidence interval
LGR4		0.003	0.406	0.014	1.379–17.970
Low expression	41
High expression	81
Intraperitoneal metastasis		0.037	0.554	0.263	–
No	27
Yes	95
CA153 (U/mL)		0.004	0.723	0.062	–
$\leqslant$ 25	12
$>$ 25	33
CEA (U/mL)		0.013	0.475	0.176	–
$\leqslant$ 5	94
$>$ 5	7

3.3 LGR4 expression was associated with the clinicopathological parameters of serous ovarian cancer

Subsequently, we explored the association between LGR4 expression and the clinicopathological parameters of serous ovarian cancer patients. The results showed in Table 2.

The results of using $\chi^{2}$ or fisher’s exact test showed that there were significant relationships between LGR4 expression and clinicopathological parameters of ser-ous ovarian cancer, such as the following factors: age, vital status (at last follow-up), and so on (Table 2).

3.4 LGR4 overexpression was associated with RFS and OS in serous ovarian cancer patients

In this study, patients with LGR4 high expression exhibited a median overall survial of only 19 months (median RFS 8.5 months), While patients with LGR4 low expression exhibited a median overall survial of 35 months (median RFS 14 months). In addition, Kaplan-Meier survival analysis demonstrated that there were statistically significant on RFS and OS between LGR4- and LGR4+ ( $P=$ 0.0036 and $P=$ 0.0015, respectively). A survival analysis showed that the cumulative OS and PFS rates of serous ovarian cancer patients increased with increasing in LGR4 high expression (Fig. 4).

3.5 LGR4 overexpression was a useful indeed independent prognostic predictor of srous ovarian cancer

In addition, using univariate analyses we found that the prognostic factors in serous ovarian cancer were as follow: LGR4 high expression, Intraperitoneal metastasis, serum CA153, serum CEA, and so on. Moreover, using multivariate analyses we found that LGR4 high expression was an indeed independent prognostic predictor of serous ovarian cancer patients. However, Intraperitoneal metastasis, serum CA153 and serum CEA were no longer significant (Table 3).

4. Discussion

Recently several reports indicate that LGR4 participates in carcinogenesis of various cancers. LGR4 high expression is significantly correlated with regional metastasis in cancer tissue, and upregulation of LGR4 promotes cell proliferation in multiple cancers by stimulating Wnt/ $\beta$ -catenin signaling [38, 39]. LGR4 is associated with poor prognosis in colorectal cancer [23, 40]. Moreover, LGR4 is also overexpressed in prostate cancer [41]. In addition, in gastric cancer [24], LGR4 was upregulated in cancer tissues, and was a poor prognostic factor of gastric cancer. And in non-small cell lung carcinoma [25], LGR4 was targeted by miR-449b thus inhibited cell growth and invasion. However, there has no research about LGR4 in serous ovarian cancer yet. In this study, we for the first time found that LGR4 was upregulated in both paraffin-embedded and fresh serous ovarian cancer tissues as compared to paratumor tissues, respectively. This study was consistent with previous reports. So this study demonstrated that LGR4 may play a candidate oncogenic role in serous ovarian cancer.

In addition, LGR4 high expression more tend to have a poor OS and RFS of serous ovarian cancer patients. And this result suggested that LGR4 was associated with prognosis of serous ovarian cancer patients. And statistical analysis showed that LGR4 high expression tend to occur in older population, which indicated that earlier screening of LGR4 is more crucial.

More importantly, in a multivariate Cox regression analysis we found that only LGR4 high expression was an indeed independent prognostic factor of serous ovarian cancer, which indicated that LGR4 high expression was very important for the prognosis of serous ovarian cancer patients, and it could be recommended as a meaningful serous ovarian cancer predict biomarker.

In conclusion, all of these results suggest that LGR4 overexpression is an indeed independent prognostic factor, and LGR4 overexpression predicts poor prognosis of serous ovarian cancer. In future, we need more in vivo and in vitro research to demonstrate its role and molecular mechanism in initiation, progression, metastasis and prognosis of serous ovarian cancer.

Footnotes

Acknowledgments

This work was supported by the Nature science fund of Guangdong Province (No. 2016A030313536), the Guangdong Provincial Medical Research Fund (No. A2019096), the President Funds of Integrated Hospital of Traditional Chinese Medicine, Southern Medical University (No. 1201902001; No. 1201901002).

Conflict of interest

The authors declare no conflict of interest.

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LGR4 overexpression is associated with clinical parameters and poor prognosis of serous ovarian cancer

Abstract

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Materials and methods

2.1 Paraffin-embedded tissue sections

2.2 Fresh tissue specimens

2.3 Immunohistochemistry (IHC)

2.4 Quantitative real time polymerase chain reaction (qRT-PCR)

2.5 Statistical analysis

3. Results

3.1 LGR4 was upregulated in fresh serous ovarian cancer fresh tissues compared with paratumor tissues using qRT-PCR

Table 1 LGR4 was significantly upregulated in serous ovarian cancer fresh tissues compared with paratumor tissues

Table 3 Cox regression univariate and multivariate analyses of prognostic factors in serous ovarian cancer

3.4 LGR4 overexpression was associated with RFS and OS in serous ovarian cancer patients

3.5 LGR4 overexpression was a useful indeed independent prognostic predictor of srous ovarian cancer

4. Discussion

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
LGR4 was significantly upregulated in serous ovarian cancer fresh tissues compared with paratumor tissues

Table 3
Cox regression univariate and multivariate analyses of prognostic factors in serous ovarian cancer