Expression of PSTPIP1 in kidney renal clear cell carcinoma and its prognostic value

doi:10.21203/rs.3.rs-1996482/v1

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Expression of PSTPIP1 in kidney renal clear cell carcinoma and its prognostic value

https://doi.org/10.21203/rs.3.rs-1996482/v1

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Purpose: Kidney renal clear cell carcinoma is the most common histological form of kidney cancer, but targeted therapy is still lacking. PSTPIP1 is associated with multiple immune-related pathways and has higher expression in tumor tissue. Thus, the correlation of PSTPIP1 and KIRC was studied to evaluate the effect of PSTPIP1 on KIRC progression.

Methods: The Oncomine and UALCAN databases were used to analyze PSTPIP1 mRNA expression in KIRC. Then, IHC was performed to detect PSTPIP1 protein in clinical samples. Next, the chi-square test, univariate analysis and multivariate analysis were performed to verify the relationship between PSTPIP1 and KIRC. Finally, coexpressed genes and enriched pathways were obtained from the TCGA and GSEA databases. A protein‒protein interaction network was constructed to assist in mechanism analysis.

Results: Both the bioinformatics analysis based on several databases and IHC experiment results showed an obvious upregulation of PSTPIP1 expression in cancer tissue. The high expression of PSTPIP1 significantly reduced the median survival time and was related to tumor size, Edmondson grade and TNM stage. Further analysis indicated that PSTPIP1 may promote prognosis through various immune responses, suggesting that PSTPIP1 may be a potential biomarker for KIRC diagnosis and therapy.

kidney renal clear cell carcinoma

PSTPIP1

prognosis

bioinformatics

IHC

Renal cell carcinoma (RCC) kills over 100000 people per year worldwide (Patel PH 2006), and this number continues to increase. Approximately 85% of all kidney tumors are RCC, and approximately 70% of RCC cases have clear cell histology (Moch H et al. 2000; Leibovich BC et al. 2010; Lipworth L et al.2016). Early diagnosis is limited due to the nearly nonsymptomatic course of KIRC. Almost 30% of patients with localized cancers eventually develop metastases despite early surgical treatment (Huang M et al. 2021). Favorable therapy selections depend on tumor histology and risk stratification of patients. Options for therapy include surgical and systemic therapy. As a new effective systemic therapy, targeted therapy for patients with relapsed or stage IV disease includes kinase inhibitors, mTOR inhibitors, and monoclonal antibodies against VEGF, PD-1, or PD-L1. (Motzer Robert J et al. 2021) However, long-term therapy may lead to drug resistance, which results in therapy failure. Therefore, more biomarkers are needed for early diagnosis and effective therapy.

PSTPIP1 (proline-serine-threonine phosphatase-interacting protein 1), also known as CD2BP1, HPIP, and PAPAS, is a cytoskeleton adaptor protein. PSTPIP1 regulates several cellular functions, including interleukin-1β (IL-1β) release, cytoskeletal organization, cell migration, and T-cell activation (Sood A K et al. 2019). Mutations of the PSTPIP1 gene are associated with a large group of inflammatory disorders (Borgia P et al. 2021), which is called PSTPIP1-associated myeloid-related proteinemia inflammatory syndrome (PAMI syndrome). PAMI syndrome shows features of both autoinflammatory disease and autoimmune diseases, including chronic systemic inflammation, pyogenic arthritis, hepatosplenomegaly and elevated myeloid-related protein (MRP)-8/14 complexes.

PSTPIP1 is highly expressed in the bone morrow, lymph nodes and spleen. It is also expressed in the kidney. The special role of PSTPIP1 in inflammation and immunity suggests that the expression of PSTPIP1 might be correlated with the occurrence and progression of renal cell carcinoma. In this study, a bioinformatics analysis was performed via an open database to clarify the relationship between PSTPIP1 and KIRC, and then an immunohistochemistry experiment was conducted to verify its expression in human KIRC samples.

Samples

A total of 150 KIRC samples were collected from patients with renal clear cell carcinoma between 2008 and 2010 at the Zhejiang Provincial People’s Hospital, Hangzhou, China. Patients included 43 females and 107 males, ranging from 24 years old to 83 years old (median age=57.0 years). Control samples were obtained from paracancerous tissue in 27 patients. No therapy in any form was used before the surgery. All samples were used to create tissue microarrays (TMAs) by the Shanghai Outdo Biotech Company (Shanghai, China). Patient information about age, sex, tumor size, location, Edmondson grade, the presence of metastases, survival time, and TNM stage was obtained from medical records. The study was approved by the Ethics Committee of the Zhejiang Provincial People’s Hospital (2021QT077) and was conducted in accordance with the Helsinki Declaration. Written informed consent was provided by all patients.

Analysis strategy

Several open databases were used to analyze PSTPIP1 expression differences between tumor tissues and normal tissues, including Oncomine (https://www.oncomine.org/resource/main.html), GSCA (http://bioinfo.life.hust.edu.cn/GSCA), UALCAN (http://ualcan.path.uab.edu/analysis.html), and GEPIA (http://gepia.cancer-pku.cn/index.html). The parameters searched in these databases included tumor grade, sample type, cancer stage, nodal metastasis status and patient age, sex, and race. The LinkedOmics (http://www.linkedomics.org/admin.php) online tool was used to further analyze the coexpressed genes and enriched pathways. Median survival was used for survival analysis. The GSEA database was used for GO (Gene Ontology) and KEGG pathway analysis.

Immunohistochemistry(IHC)

The distribution of PSTPIP1 expression in different tissues was confirmed by IHC. The TMA was immersed in different liquids in the following order: three times with xylene for 15 min each time and different concentrations of alcohol (100%, 85%, 75%) for 5 min each time. Then, it was washed with distilled water. To retrieve antigen, the slides were placed in a box filled with citric acid (pH 6.0) antigen retrieval buffer and heated until 120 °C for 3 minutes in a pressure cooker. After cooling, the sections were placed in 3% hydrogen peroxide and incubated at room temperature in darkness for 25 minutes to block endogenous peroxidase activity. BSA (3%) was added to seal the tissue for 30 mins. After removing the sealing solution, the tissue array was cultured with rabbit anti-PSTPIP1 polyclonal antibody (11951-1-AP, Proteintech Group, Inc. Rosemont, USA) overnight at 4 °C, washed 3 times with PBS, and cultured with secondary antibody for 50 min at room temperature. Finally, the cells were cultured with DAB color developing solution, counterstained with hematoxylin, dehydrated with ethanol, n-butanol, and xylene and mounted with SweSuper Clean Bio Mount Medium.

Two independent experimenters, blinded to the clinical data, scored the expression of PSTPIP1 according to the staining intensity, and the positive signal was brownish yellow. A consensus score standard was based on the following: ‘0’ indicated no stain at all, ‘1’ indicated a weak stain with a light yellow color, ‘2’ indicated moderate staining with a yellowish-brown color, and ‘3’ indicated strong staining with a brown color. The proportion of stained cells was described as ‘0’ for 0-5% cells stained, 1 for 6–25% cells stained, 2 for 26–50% cells stained and 3 for 50-100% cells stained. The total score was determined by multiplying two scores. The expression of PSTPIP1 was considered high if the value was ≥4.

Statistical analysis

Statistical analysis was performed with SPSS 17.0 (IBM SPSS, Chicago, IL, USA) and GraphPad Prism version 8.0 (GraphPad Software, San Diego, CA, USA). The chi-square test was used to evaluate the relationship between PSTPIP1 expression and various clinical factors. The overall survival curves were plotted using the Kaplan–Meier method. The hazard ratio was analyzed by a log rank test and univariate and multivariate Cox regression analyses. P<0.05 was the statistically significant difference standard..

PSTPIP1 has a higher expression in KIRC than in normal tissue. The Oncomine, GIAPIA, and UALCAN databases were used to evaluate the expression difference of PSTPIP1 at the mRNA level in different tissues. There was a significant increase in PSTPIP1 expression in many kinds of tumor tissue, especially in kidney renal clear cell carcinoma (KIRC) (Fig. 1A). Analysis of Oncomine databases showed that PSTPIP1 mRNA was expressed at higher levels in both gumz renal KIRC (Fig. 1B) and Lenburg renal (Fig. 1C) KIRC.

Figure 2. PSTPIP1 transcription in subgroups of KIRC patients. (A-B) Boxplot showing relative expression PSTPIP1 in KIRC and normal tissue samples (GIAPIA and UALCAN). (C–I) Association between PSTPIP1 expression and tumor grade of KIRC (C), individual cancer stage of KIRC (D), KIRC subtypes (E), nodal metastasis status (F), patient’s race (G), patient’s gender (H), patient’s age (I).

Then, the GIAPIA (Fig. 2A) and UALCAN databases were searched, and similar results were obtained. Analysis of the UALCAN database revealed that the median PSTPIP1 expression was 0.741 in normal samples (n=72) compared to 5.189 in primary tumor samples (n=533) (Fig. 2B). Based on tumor grade, the median PSTPIP1 expression was 0.741 (n=50) in normal samples compared to 6.32 (n=14) in grade 1, 4.523 (n=229) in grade 2, 5.412 (n=206) in grade 3, and 6.6 (n=76) in grade 4 (Fig. 2C). Based on individual cancer stages, it was 0.741 (n=72, normal) compared to 4.455 (n=267, stage 1), 5.8 (n=57, stage 2), 5.946 (n=123, stage 3), and 5.801 (n=84, stage 4) (Fig. 2D). These results suggested that PSTPIP1 has a significant increase of expression in tumor tissue regardless of KIRC subtypes (Fig. 2E), nodal metastasis status (Fig. 2F), tumor grade (Fig. 2C), individual cancer stages (Fig. 2D), patient’s race (Fig. 2G), patient’s gender (Fig. 2H), patient’s age (Fig. 2I).

The experimental evidence of differential PSTPIP1 protein expression between normal tissue and tumor tissue was collected by immunohistochemistry (IHC). The staining results showed obvious PSTPIP1 expression in tumor tissue (Fig. 3A-D) and low or no expression in normal tissue. In tumor tissue, high expression occurred in 65 (43.3%) samples, while low expression occurred in 85 (56.6%) samples. For normal tissue, only 5 (18.6%) samples had high expression, compared to 22 (81.4%) low expression samples. The chi-square test result was 5.893 (P<0.05), showing a significant difference.

Relationship between PSTPIP1’s expression and clinic pathological characteristics in KIRC. A chi-square test was used to analyze whether PSTPIP1 expression was correlated with clinical pathological characteristics. The results showed that the expression level was significantly related to tumor size (P=0.004), Edmonson grade (P=0.045), and TNM stage (P=0.013). Sex (P=0.769), age (P=0.629), metastasis (P=0.41), microvascular invasion (P=0.711) and PDL-1 (P=0.051) did not have statistically significant relevance to PSTPIP1 expression.

Table 1. Relationship between PSTPIP1 expression and clinical parameters of KIRC patients.

Clinical parameters		PSTPIP1 expression
		Low(%)	High(%)	χ2	p-value
Gender				0.086	0.769
	Male	62(72.9%)	46(70.8%)
	Famale	23(27.1%)	19(29.2%)
Age (yrs.)				0.234	0.629
	<55	32(37.6%)	27(41.5%)
	>=55	53(62.4%)	38(58.5%)
Size				8.193	0.004
	<5cm	54(63.5%)	26(40.0%)
	>=5cm	31(36.5%)	39(60.0%)
metastasis				0.679	0.41
	No	84((98.8%)	63(96.9%)
	Yes	1(1.2%)	2(3.1%)
Microvascular invasion				0.138	0.711
	No	77(90.6%)	60(92.3%)
	Yes	8(9.4%)	5(7.7%)
Edmondson grade				4.004	0.045
	Ⅰ~Ⅱ	64(75.3%)	39(60.0%)
	Ⅲ~Ⅳ	21(24.7%)	26(40.0%)
TNM stage				6.155	0.013
	Ⅰ	75(88.2%)	47(72.3%)
	Ⅱ~Ⅳ	10(11.8%)	18(27.7%)
PDL-1				3.824	0.051
	<10	49(57.6%)	27(41.5%)
	>=10	36(42.4%)	38(58.5%)

Clinical outcome influenced by PSTPIP1 expression. We searched the GSCA database and generated Kaplan‒Meier curves of high and low expression of PSTPIP1 in KIRC (Fig. 4A). The high expression group had a significantly shorter overall survival (P<0.01), which was also proven by our clinical sample data. Survival analysis of clinical samples showed that the average survival time of the high expression group was 74.58±3.44 months, while that of the low expression group was 80.91±2.37 months (P<0.05, Fig. 4B). Univariate analysis and multivariate analysis were performed to determine the effect of PSTPIP1 protein on KIRC prognosis (Table 2). Univariate analysis showed that tumor size (HR=4.024, 95%CI:1.709-9.471, P<0.05), metastasis (HR=23.486, 95%CI:6.286-87.755, P<0.05), microvascular invasion (HR=4.076, 95%CI:1.995-11.097, P<0.05), Edmondson grade (HR=4.911, 95%CI:2.264-10.650, P<0.05), TNM stage (HR=8.346, 95%CI:3.931-17.722, P<0.05) and PSTPIP1 expression (HR=2.159, 95%CI:1.011-4.610, P<0.05) significantly influenced survival time. Further multivariate analysis indicated that metastasis, grade and TNM stage were independent factors. Although PSTPIP1 expression was not an independent factor, its high expression negatively affected KIRC progression and contributed to poor prognosis.

Table 2 Univariate and Multivariate Cox Regression Survival Analysis of Clinicopathologica Parameters and PSTPIP1 Expression in Patients.

Parameters	Univariate Analysis			Multivariate Analysis
Parameters	HR	95%CI	P	HR	95%CI	P
Gender	0.399	0.139-1.151	0.089	NA
Age (yrs.)	2.099	0.892-4.937	0.089	NA
Size	4.024	1.709-9.471	P<0.05	1.532	0.532-4.408	0.429
metastasis	23.486	6.286-87.755	P<0.05	4.591	1.134-18.581	P<0.05
Microvascular invasion	4.706	1.995-11.097	P<0.05	1.594	0.600-0.4.234	0.35
Edmondson grade	4.911	2.264-10.650	P<0.05	2.569	1.093-6.039	P<0.05
TNM stage	8.346	3.931-17.722	P<0.05	3.296	1.180-9.209	P<0.05
PDL-1	1.932	0.892-4.187	0.095	NA
PSTPIP1	2.159	1.011-4.610	P<0.05	1.349	0.578-3.149	0.49

Co-expressed genes and pathways correlated with PSTPIP1. We analyzed 533 samples from the TCGA database through the LinkedOmics online tool. There were 8861 genes (red spots, FDR<0.05) positively related to PSTPIP1 and 4905 genes (green spots, FDR<0.05) negatively related to PSTPIP1, as shown in the volcano plot (Fig. 5 A). The heatmaps display the top 50 positively related and negatively related genes (Fig. 5 B, C). The three most positively related genes were ACAP1, CORO1A, and DEF6 (Fig. 5 D, E, F). The three most negatively related genes were SYPL1, CYP51A1, and PTPLAD1 (Fig. 5 G, H, I).

Next, GO (Gene Ontology) and KEGG pathway analyses were performed by GSEA (Gene Set Enrichment Analysis). Coexpressed genes located in the biological process, cellular component, and molecular function categories are listed in Fig. 6(ABC). PSTPIP1 has a clear preference for participating in biological processes: adaptive immune response; regulation of leukocyte activation; cellular defense response; interleukin-1 production; and leukocyte differentiation. KEGG pathway analysis results (Fig. 6D) showed that the top 6 enrichment pathways were cell adhesion molecules (CAMs) (Fig. 6E), natural killer cell-mediated cytotoxicity (Fig. 6F), cytokine‒cytokine receptor interaction (Fig. 6G), osteoclast differentiation (Fig. 6H), Epstein‒Barr virus infection (Fig. 6I), and tuberculosis (Fig. 6J). These results indicated that PSTPIP1 may promote KIRC progression through several immune response pathways.

Protein–protein interaction analysis. The STRING database were used to build up protein-protein interaction network (Fig. 7). The top 10 closest proteins were MEFV, PTPN12, WAS, PTPN18, CD2, FASLG, PTPN22, WASL, PYCARD and PTS.

More valid targets for diagnosis and therapy are needed for KIRC, which is a common kidney tumor. Inflammation and immune reactions are important factors in cancer progression, making related genes more likely to become new biomarkers. The protein encoded by PSTPIP1 binds to the cytoplasmic tail of CD2, an effector of T-cell activation and adhesion, negatively affecting CD2-triggered T-cell activation. PSTPIP1 is widely considered to be correlated with many autoinflammatory disorders (Manso José A). Taylor W. Starnes et al. (2014) proposed the mechanism by which the PSTPIP1 protein controls extracellular matrix degradation and filopodia formation in macrophages to transform into a highly invasive phenotype, which is responsible for PAPA syndrome. Janssen et al. (2018) reported that PSTPIP1 controls IS (immune synapse) formation and cell adhesion through its function as an orchestrator of the F-actin cytoskeleton.

According to the GIPEA, UALCAN and UNCOMINE databases, the transcription of PSTPIP1 is obviously upregulated in tumor tissue and negatively affects prognosis. IHC experiment results showed that the PSTPIP1 protein is expressed at higher levels in tumor samples than in normal samples, further confirming the bioinformatics analysis data. Survival analyses from both the GASE database and clinical cases indicated that high expression of PSTPIP1 reduced the median survival time. Chi-square tests showed the positive correlation of PSTPIP1 expression with tumor size, Edmondson grade, and TNM stage. Although multivariate analysis did not classify PSTPIP1 as an independent factor, PSTPIP1 may indirectly negatively influence KIRC prognosis

To learn more about the way PSTPIP1 works in vivo, GO and KEGG analyses were used to identify coexpressed genes and pathways. The top 3 coexpressed genes were ACAP1, CORO1A, and DEF6. ACAP1 is a member of the ADP-ribosylation factor (ARF) GTPase-activating protein (GAP) family (Bai M et al. 2012). ARF GAPs have been conventionally known as regulators of their cognate small GTPases (D'Souza-Schorey C and Chavrier P 2006). In particular, ACAP1 is an ARF6 GAP that has been found to function as a component of a recently defined clathrin complex for endocytic recycling (Li J et al. 2007). CORO1A, a member of the type Ⅰ coronin subfamily, participates in the regulation of actin cytoskeleton disassembly by targeting Cofilin and Arp2/3. DEF6 is highly expressed in T and B cells and regulates various immune-related processes, such as the activation of CD4+ T cells and the differentiation of T helper cells (Zhu ZP et al. 2020). More importantly, DEF6 has been identified as an independent factor involved in KIRC progression (Zhu ZP et al. 2020). All three genes are involved in cell movement, adhesion, and activation. Two of them are closely related to immune activity.

Enriched pathways included cell adhesion molecules (CAMs), natural killer cell-mediated cytotoxicity, cytokine‒cytokine receptor interaction, osteoclast differentiation, Epstein‒Barr virus infection and tuberculosis, which are mainly related to cell adhesion and immune response, concurring with coexpressed genes. Protein‒protein interaction analysis screened out ten proteins that participate in the PSTPIP1 action route. The MEFV protein is involved in the regulation of innate immunity and the inflammatory response in response to IFNG/IFN-gamma. In detail, MEFV can recognize specific autophagy targets, thus coordinating target recognition with assembly of the autophagic apparatus and initiation of autophagy. WAS controls actin protein, which is related to cell movement. PTPN12 regulates cellular signaling cascades by dephosphorylating a range of proteins. Studies have shown that lncRNA GATA2-AS1 suppresses esophageal squamous cell carcinoma progression via the miR-940/PTPN12 axis (Yunfeng Niu et al. 2022). It has been proven that miR-494-3p is abundant in Ras- and syntenin-1-dependent sEVs and mediates sEV-induced migration and invasion of cancer cells and angiogenesis by targeting PTPN12 in the TME (Kim O et al. 2022).

In conclusion, our study analyzed PSTPIP1’s effect on KIRC prognosis and determined the relevance among PSTPIP1 and clinical parameters. Since survival time is significantly different between high expression and low expression, PSTPIP1 may be a potential diagnostic and therapeutic target. Finally, we predicted possible signaling pathways and interacting proteins to explain how PSTPIP1 plays a role in KIRC progression. More in-depth studies are needed to clarify the specific mechanism by which PSTPIP1 affects KIRC.

This research was supported by Natural Science Foundation of Zhejiang Province. (LQ21H160041)

Conflict of interest

The authors declare that they have no conflicts of interest in this work.

Ethical approval

The study was approved by the Ethics Committee of the Zhejiang Provincial People’s Hospital (2021QT077) and was conducted in accordance with the Helsinki Declaration. All patients signed written informed consent.

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No competing interests reported.

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Expression of PSTPIP1 in kidney renal clear cell carcinoma and its prognostic value

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