Diagnostic and prognostic value of scavenger receptor class B type 1 in clear cell renal cell carcinoma

Abstract

Aberrant expression of scavenger receptor class B type 1 has been reported in several human cancers. Nevertheless, the roles of scavenger receptor class B type 1 in clear cell renal cell carcinoma remain unclear. The aim of this study was to evaluate the diagnostic and prognostic value of scavenger receptor class B type 1 in clear cell renal cell carcinoma. The messenger RNA level of scavenger receptor class B type 1 in clear cell renal cell carcinoma tissues was detected by quantitative reverse transcription polymerase chain reaction, while protein level was determined by western blot and immunohistochemistry. The lipid content between clear cell renal cell carcinoma tissues and normal kidney tissues was differentiated by Oil Red O and hematoxylin–eosin staining. The diagnostic value of scavenger receptor class B type 1 was determined by receiver operating characteristic curve. The prognostic significance of scavenger receptor class B type 1 was assessed by Kaplan–Meier analysis and Cox regression analysis. Our results showed that the expression of scavenger receptor class B type 1 in clear cell renal cell carcinoma tissues at both messenger RNA and protein level was much higher than that in normal kidney tissues. Receiver operating characteristic curve analysis exhibited a significant value of area under the curve (0.8486, 95% confidence interval: 0.7926–0.9045) with strong sensitivity (0.75, 95% confidence interval: 0.6535–0.8312) and specificity (0.90, 95% confidence interval: 0.8238–0.9510). Kaplan–Meier analysis revealed that patients with higher scavenger receptor class B type 1 expression had shorter progression-free survival time. Cox analysis indicated that scavenger receptor class B type 1 was an independent prognostic biomarker. In conclusion, our findings implied that scavenger receptor class B type 1 might serve as a diagnostic and independent prognostic biomarker in clear cell renal cell carcinoma.

Introduction

Renal cell carcinoma (RCC) consists of nearly 2%–3% of all malignancies in adults,¹ and clear cell renal cell carcinoma (ccRCC) is the major subtype of RCC.² In 2015, there were approximately 61,560 new cases and 14,080 deaths of RCC in the United States.³ Due to the lack of early diagnostic methods and specific symptoms, about 30% of patients present metastasis at the time of diagnosis.⁴ Besides, 25% of patients will still develop metastatic recurrence after surgical treatment.⁵ Worse more, patients with metastasis have a poor prognosis, with a 5-year survival rate less than 15%.³ Therefore, it is urgent to identify effective diagnostic and prognostic biomarkers in ccRCC.

Scavenger receptor class B type 1 (SR-B1) is a kind of membrane protein with a molecular weight of 82 kDa. It is well-known that SR-B1 is of vital importance in high-density lipoprotein (HDL)-cholesterol metabolism⁶ and hepatitis C virus entry.^7–9 It has been reported that SR-B1 also plays a critical role in cancers including breast cancer,^10–12 prostate cancer,^13,14 and nasopharyngeal cancer.¹⁵ The results showed that the expression of SR-B1 was highly up-regulated and SR-B1 functioned as an oncogene, promoting progression in these cancers. In addition, high SR-B1 expression was significantly associated with poor clinical outcome in breast cancer¹² and prostate cancer.¹⁴ However, expression and clinical value of SR-B1 in ccRCC has not been well addressed so far.

In this study, we detected the expression of SR-B1 in ccRCC cancerous tissues and paired normal kidney tissues. We further analyzed the correlation of SR-B1 expression with clinical features in ccRCC patients. In addition, we evaluated the diagnostic value of SR-B1 in discriminating ccRCC tumor tissues from normal tissues and explored its prognostic significance on clinical outcome of ccRCC patients after surgery.

Materials and methods

Patients and tissue samples

All ccRCC samples (n = 100) and matched normal kidney tissues were obtained from patients who underwent surgical treatment at the Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (Wuhan, China). Patients were diagnosed as ccRCC pathologically, and none of them received any other treatments prior to surgery. The clinicopathological features of patients including gender, age, tumor size, histological grade, and tumor, node, metastasis (TNM) status were recorded. All samples were freshly snap-frozen in liquid nitrogen and stored in a deep freezer at −80°C for RNA and protein extraction. Written informed consents were obtained from all patients, and the study was approved by the institutional review board of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.

Patients were followed up regularly after the surgery. The time duration from the primary operation to progression, or recurrence, or death was defined as progression-free survival (PFS). During the follow-up, those patients whom we could not contact were considered as censored.

Isolation of RNA and quantitative reverse transcription polymerase chain reaction analysis

The quantitative reverse transcription polymerase chain reaction (qRT-PCR) was conducted to determine the SR-B1 messenger RNA (mRNA) expression in ccRCC tissues as previously described.^16,17 Briefly, total RNA from tissues was extracted with TRIzol reagent (Invitrogen, Carlsbad, CA, USA). Reverse transcription (RT) of RNA was conducted using the RevertAid™ First Strand cDNA Synthesis Kit (Fermentas, Vilnius, Lithuania). The polymerase chain reaction (PCR) was performed with Platinum SYBR Green qPCR Supermix-UDG (Invitrogen) using synthesized primers from Genewiz (Suzhou, China). The primer set for SR-B1 was 5′-CCTATCCCCTTCTATCTCTCCG-3′ (forward) and 5′-GGATGTTGGGCATGACGATGT-3′ (reverse). The primers used for glyceraldehyde 3-phosphate dehydrogenase (GAPDH), the internal control, were 5′-GGTGAAGGTCGGAGTCAACGG-3′ (forward) and 5′-GAGGTCAATGAAGGGGTCATTG-3′ (reverse). The relative expression of SR-B1 was analyzed by normalizing to GAPDH using the 2^−ΔΔCt method.

Protein extraction and western blot analysis

Western blot assay was performed to evaluate protein expression of SR-B1 in ccRCC tissues as described before.^18,19 Total protein of paired tissues was extracted using radioimmunoprecipitation assay (RIPA) buffer (Beyotime Institute of Biotechnology, Haimen, Jiangsu, China) containing protease inhibitor cocktail (Roche Molecular Biochemicals, Mannheim, Germany) and phenylmethanesulfonyl fluoride (PMSF; Beyotime Institute of Biotechnology). Protein concentration of tissue samples was measured by bicinchoninic acid (BCA) protein assay kit (Thermo Scientific, Waltham, MA, USA). Equal amounts of protein samples (40–60 µg) were separated by 8% dodecyl sulfate, sodium salt (SDS)-polyacrylamide gel electrophoresis (PAGE) and transferred onto polyvinylidene difluoride (PVDF) membranes (Roche, Mannheim, Germany). The primary antibodies used for western blot analysis were polyclonal rabbit anti-SR-B1 (dilution at 1:1000; SAB2700477; Sigma-Aldrich, St. Louis, Missouri, USA) and mouse anti-β-actin (dilution at 1:3000; AF0003; Beyotime, Haimen, Jiangsu, China). The membranes were then incubated with goat anti-mouse or goat anti-rabbit secondary antibodies (Promega, Madison, WI, USA) conjugated with horseradish peroxidase (HRP) at a dilution of 1:2500 at room temperature for 2 h. Then, the stained proteins on bands were visualized using ChemiDoc XRS+ (Bio-Rad, Hercules, CA, USA) by enhanced chemiluminescence (ECL; Thermo Fisher Scientific Inc., Waltham, MA, USA).

Immunohistochemical staining

Protein expression of SR-B1 was also assessed by immunohistochemical (IHC) analysis by staining paraffin-embedded sections of ccRCC tissues and paired normal kidney tissues according to instructions. The primary polyclonal rabbit antibody against SR-B1 (SAB2700477; Sigma-Aldrich) was used at a dilution of 1:250. Representative images were obtained as our intention.

Oil Red O staining and hematoxylin–eosin staining

To compare the content of lipid droplets in ccRCC and non-cancerous tissues, fresh frozen sections of paired ccRCC specimens and normal kidney tissues were stained with Oil Red O (ORO) and hematoxylin–eosin (HE) according to the manufacturer’s instructions. Classical and typical images were stored.

Statistical analysis

The statistical analysis was performed by SPSS 16.0 software (SPSS, Inc., Chicago, IL, USA) or GraphPad Prism version 5.01 (GraphPad Software, Inc., La Jolla, CA, USA). The continuous data were presented as the mean ± standard deviation (SD). The paired t-test was utilized to compare SR-B1 mRNA expression in ccRCC tissues with their normal counterparts. SR-B1 mRNA expression in unpaired samples was analyzed by the Mann–Whitney test. The correlation between SR-B1 mRNA expression and clinical features of all patients was analyzed by Pearson’s chi-square test or Fisher’s exact test. Receiver operating characteristic (ROC) curve was applied to assess the diagnostic value of SR-B1 in ccRCC. PFS analysis was carried out by the Kaplan–Meier method, and the log-rank test was used to determine the difference. Univariate and multivariate analyses were conducted to predict prognosis based on the Cox proportional hazards regression model. In all statistical tests, two-sided p value less than 0.05 was considered statistically significant.

Results

Clinicopathological characteristics of ccRCC patients

Basic features of patients enrolled in this study were listed in Table 1. There were 59 males and 41 females with the median age of 55.5 years (range: 22–82 years) at diagnosis. The median size of tumors was 5.2 cm (range: 2.0–14.9 cm). Sixty-five patients had low grade (G1 + G2), whereas 35 cases had high grade (G3 + G4), accounting for 65.0% and 35.0%, respectively. Seventy-two patients, accounting for 72.0%, had local disease (pT1 + pT2), and another 28 patients, the remaining 28.0%, had locally advanced disease (pT3 + pT4). Fourteen patients (14.0%) had lymph node metastasis, and only eight (8.0%) had distant metastasis. In all, 65.0% patients were at low TNM stage and 35.0% patients were at high TNM stage (either at pT3 + pT4, or with lymph node or distant metastasis).

Table 1.

Correlations between SR-B1 mRNA expression and clinicopathological parameters of ccRCC patients.

Features	Number	SR-B1 mRNA expression		p value
		Low (n = 50)	High (n = 50)
Gender				0.155
Male	59	33	26
Female	41	17	24
Age (years)				0.529
≤60	65	31	34
>60	35	19	16
Tumor size (cm)				0.001
≤4.0	29	20	9
>4.0	71	30	41
Fuhrman grade				0.834
G1 + G2	65	33	32
G3 + G4	35	17	18
Tumor stage				0.373
T1 + T2	72	38	34
T3 + T4	28	12	16
Lymph node metastasis				0.249
N0	86	45	41
N1	14	5	9
Distant metastasis				0.006a
M0	92	50	42
M1	8	0	8
TNM stage				0.142
I + II	65	36	29
III + IV	35	14	21

SR-B1: scavenger receptor class B type 1; mRNA: messenger RNA; ccRCC: clear cell renal cell carcinoma; TNM: tumor, node, metastasis.

a

Fisher’s exact test.

Increased SR-B1 expression in ccRCC tissues

To determine the expression pattern of SR-B1 in ccRCC, we conducted qRT-PCR, western blot, and IHC. As shown in Figure 1(a) and (b), the mRNA and protein expression levels of SR-B1 were much higher in ccRCC tissues than those in paired normal kidney tissues. IHC analysis also showed that SR-B1 protein level was much higher in cancerous tissues (Figure 1(c)). Furthermore, the ccRCC tissues with high SR-B1 expression contain more abundant lipids than normal kidney tissues (Figure 1(c)).

Figure 1.

Expression of SR-B1 in ccRCC tissues. (a) Relative mRNA expression of SR-B1 in normal kidney and ccRCC tissues by qRT-PCR, (b) protein expression of SR-B1 in normal kidney and ccRCC tissues by western blot analysis, and (c) representative images of ORO staining, HE staining, and IHC analysis of SR-B1 protein in normal kidney and ccRCC tissues (original magnification ×400).

***p < 0.001.

[Figure omitted. See PDF]

Correlations of SR-B1 mRNA expression with clinicopathological parameters of ccRCC

Patients were divided into high- and low-expression groups according to the medium expression level of SR-B1 mRNA in ccRCC cancerous tissues. As shown in Table 1, high SR-B1 mRNA expression was significantly associated with tumor size (p = 0.001) and distant metastasis (p = 0.006). Nevertheless, there were no significant links between SR-B1 mRNA expression and other features. In consistent with these findings, we analyzed SR-B1 mRNA expression in subgroups according to clinical features and found that there was significant association between high SR-B1 mRNA expression and tumor size or distant metastasis (Figure 2(c) and (g)).

Figure 2.

Relative expression of SR-B1 mRNA in subgroups: (a) gender, (b) age, (c) tumor size, (d) grade, (e) T stage, (f) lymph node metastasis, (g) distant metastasis, and (h) TNM stage.

**p < 0.01.

[Figure omitted. See PDF]

Diagnostic value of SR-B1 in ccRCC

ROC curve analysis indicated that up-regulation of SR-B1 might serve as a diagnostic biomarker in discriminating ccRCC tissues from normal tissues. As shown in Figure 3, the value of area under the curve (AUC) was 0.8486 (95% confidence interval: 0.7926–0.9045), with a sensitivity of 0.75 (95% confidence interval: 0.6535–0.8312) and a specificity of 0.90 (95% confidence interval: 0.8238–0.9510) when the cutoff value was set at 0.01285 according to our detection method.

Figure 3.

ROC curve analysis for the diagnostic value of SR-B1 in ccRCC.

[Figure omitted. See PDF]

Prognostic value of SR-B1 in ccRCC

We conducted Kaplan–Meier analysis to verify the clinical significance of expression of SR-B1 mRNA in ccRCC patients. Total patients were divided into high- and low-expression groups according to the medium expression level of SR-B1 mRNA in ccRCC cancerous tissues. As shown in Figure 4(a), we found that patients with higher SR-B1 mRNA expression had shorter PFS time (p = 0.0008). Next, we further explored the link of SR-B1 mRNA expression with PFS in different subgroups. Our results indicated that high expression of SR-B1 mRNA exhibited a strong link with shorter PFS in patients who had features as follows (Figure 4(b)–(i)): male (p < 0.0001), patients younger than 60 years (p = 0.0014), tumor size >4 cm (p = 0.0055), low grade (G1 + G2; p = 0.0030), low T stage (T1 + T2; p = 0.0001), no lymph node metastasis (p = 0.0005), no distant metastasis (p = 0.0063), and low TNM stage (I + II; p = 0.0024). However, SR-B1 mRNA expression showed no significant correlation with PFS in patients who had clinical features as follows: female, patients older than 60 years, tumor size ≤4 cm, high grade (G3 + G4), high T stage (T3 + T4), lymph node metastasis, and high TNM stage (III + IV) (Supplemental Figure S1). It should be noted that although higher expression of SR-B1 generally correlated with shorter PFS in ccRCC patients, we failed to get the correlation between shorter PFS and SR-B1 expression in patients with lymph node metastasis, distant metastasis, higher grade, higher T stage, and higher TNM stage.

Figure 4.

Kaplan–Meier analysis of PFS based on the expression of SR-B1 mRNA. Kaplan–Meier analysis of PFS in (a) total patients, (b) male patients, (c) patients with age ≤60 years, (d) patients with tumor size >4 cm, (e) patients with low grade, (f) patients with low T stage, (g) patients with no lymph node metastasis, (h) patients with no distant metastasis, and (i) patients with low TNM stage.

[Figure omitted. See PDF]

Subsequently, we performed Cox regression analysis to clarify the clinical value. We summarized from Table 2 that features including tumor size (p = 0.005), lymph node metastasis (p < 0.001), distant metastasis (p < 0.001), TNM stage (p = 0.001), and SR-B1 mRNA expression (p = 0.002) were significantly related to PFS in univariate analysis, whereas only tumor size (p = 0.025) and SR-B1 mRNA expression (p = 0.040) were independent prognostic biomarkers in multivariate analysis.

Table 2.

Cox regression analysis of PFS rate in 100 ccRCC patients.

Variables	Univariate analysis			Multivariate analysis
	HR	95% CI	p value	HR	95% CI	p value
Gender	2.367	0.991–5.657	0.053
Age	1.079	0.478–2.432	0.855
Tumor size	8.225	1.904–35.536	0.005	5.433	1.243–23.749	0.025
Fuhrman grade	1.617	0.738–3.540	0.230
Tumor stage	1.486	0.615–3.587	0.379
LNM	5.526	2.280–13.395	0.000	3.001	0.783–11.499	0.109
DM	6.084	2.201–16.815	0.000	1.042	0.275–3.944	0.951
TNM stage	3.940	1.771–8.768	0.001	1.618	0.548–4.778	0.384
SR-B1 expression	4.248	1.692–10.666	0.002	2.787	1.046–7.425	0.040

PFS: progression-free survival; ccRCC: clear cell renal cell carcinoma; HR: hazard ratio; CI: confidence interval; LNM: lymph node metastasis; DM: distant metastasis; TNM: tumor, node, metastasis; SR-B1: scavenger receptor class B type 1.

Discussion

During the past decades, mushroomed researches revealed that cell metabolism especially cholesterol metabolism played vital roles in tumorigenesis. As the most important mediator in HDL-cholesterol metabolism, SR-B1 has been reported in several cancers.^10,11,13,15 Nevertheless, we knew little about the roles of SR-B1 in ccRCC.

In our study, we explored the expression of SR-B1 in ccRCC tissues and found that SR-B1 expression was much higher in cancerous tissues compared with their normal counterparts. In accordance with the expression pattern of SR-B1, tissue staining by ORO and HE revealed that ccRCC tissues showed higher lipid content than normal kidney tissues. Furthermore, we analyzed the relation between its expression status and clinical features of ccRCC patients. We found that larger tumor size and distant metastasis had strong links with higher SR-B1 expression. We also evaluated the clinical value of SR-B1 in diagnosis and prognosis of ccRCC. ROC curve proved that SR-B1 might be used as a diagnostic biomarker with strong sensitivity and specificity. We also acquired the results that PFS of ccRCC patients after surgery correlated tightly with SR-B1 expression in different subgroups. According to Cox regression analysis, we concluded that SR-B1 might serve as an independent prognostic biomarker in ccRCC.

Abnormal metabolism fuels the aggressive phenotypes of cancer cells.^20,21 As the major transporter of HDL-cholesterol located on the cell membrane, SR-B1 tended to participate in the carcinogenesis of cancer through altered cholesterol metabolism. Danilo et al.¹⁰ reported that SR-B1 regulated cholesterol metabolism and signaling transduction related to the development of breast cancer. Twiddy et al.¹³ concluded that knockdown of SR-B1 impaired the viability of prostate cancer cells. In line with these results, Schorghofer et al.¹⁴ displayed that increase of SR-B1 expression involved in castration resistance of prostate cancer.

The molecular mechanism related to SR-B1 in ccRCC remains uncertain. However, several reports have demonstrated that SR-B1 might play biological roles in different cancers and cells via various signal pathways. Cao et al.²² reported that the PI3K/Akt pathway correlated with SR-B1 in breast cancer, mutant form of SR-B1 inhibited the growth of MCF-7 cells, and the effect was induced by specific inhibition of PI3K/Akt activation. Fruhwurth et al.²³ found that inhibition of mammalian target of rapamycin (mTOR) pathway decreased SR-B1 expression and reduced nitric oxide (NO) synthesis in human umbilical vein endothelial cells (HUVECs) and human coronary artery endothelial cells (HCAECs). It has been reported that HDL binding to SR-B1 increased the synthesis of NO in pulmonary artery endothelial cells by activating the endothelial nitric oxide synthase (eNOS).²⁴ While NO correlated with lymph node metastasis by stimulating the vascular endothelial growth factor-C (VEGF-C) expression in breast cancer,²⁵ the expression of NOS also related to lymph node metastasis in breast cancer.^26–28 This study revealed that SR-B1 might be correlated with tumor size and distant metastasis in ccRCC and acted as an independent prognostic index. The relative studies on the exact mechanism of SR-B1 in ccRCC are undergoing at present in our laboratory.

We acknowledge that there are several limitations in this study, and we will perform further studies in the future. First, the study is a retrospective study from a single unit, and the sample size is small. We plan to perform a prospective study among multi-centers with larger sample size because the prognostic analysis of SR-B1 in subgroups may be confused. Second, we will validate the expression pattern of SR-B1 in ccRCC cell lines, and explore its biological roles and underlying mechanism. Third, we will test the expression of SR-B1 in patient blood samples in the future and evaluate whether it can be a good biomarker for ccRCC.

Collectively, we demonstrated that the expression of SR-B1 in ccRCC tissues was highly up-regulated. Besides, high SR-B1 expression correlated significantly with aggressive properties of ccRCC. Furthermore, up-regulation of SR-B1 might be used as a diagnostic and prognostic biomarker in ccRCC patients.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Natural Science Foundation of China (NSFC; Grant No. 81372760 & 81072095 & 81672528), the National High Technology Research and Development Program of China (863 Program; 2012AA021101) to Xiaoping Zhang, and the NSFC (Grant No. 31070142 & 81272560) to Hongmei Yang.