An Integrated Analysis of The Prognosis And Immune Cell Inltration of ITGB Superfamily Members In Gastric Cancer

in the progression of GC and that ITGBs may be potential prognostic biomarkers and therapeutic targets for GC.


Introduction
As one of the most invasive cancers, gastric cancer (GC) is the fth most common cancer and the third most common cause of cancer death worldwide, with approximately 1 million new cases diagnosed each year. The overall 5-year survival rate for gastric cancer is pessimistic as most cases are diagnosed at advanced stages [1]. Recently, immunotherapy has shown astonishing treatment effects in various cancers, including hepatocellular carcinoma and melanoma [2][3][4]. Also, immune checkpoint blockade has been applied to treat patients with chemotherapy-refractory GC [5]. Two clinical trials (ATTRACTION-2 [5] and KEYNOTE-059[6]) showed that PD-1 antibody can remarkably improve the overall survival of GC patients who progressed after two or more lines of chemotherapy. However, immunotherapy has not been shown to be superior in rst-or second-line of therapy; According to the results of KEYNOTE-061 [7] and KEYNOTE-062 trial [8], immune checkpoint blockade agent of pembrolizumab did not dispalyed a survival bene t compared to chemotherapy in second line low expressed PD-L1 patients(CPS ≥ 1), or In the rst line PD-L1 positive patients (CPS ≥ 1). Therefore, there is an urgent need to identify reliable prognostic markers and drug targets associated with tumorigenesis, chemotherapy, and immune escape in GC in order to develop more e cient therapy for GC patients.
The integrin-β superfamily( (ITGBs) is a cell surface glycoprotein containing eight different individual members in mammals. Previous study has shown ITGBs members control cell adhesion, migration, proliferation, survival and differentiation via sensing the extracellular matrix and triggering a series of cellular responses [9]. ITGB1interacts with MicroRNA-29c to control occurrence and development of GC [10] and the upregulation of ITGB1 promotes the invasion of GC cells [11]. Overexpression ITGB3 has been reported to associated with GC metastasis [12]. ITGB4 has also been found to promote the invasion and migration of GC cells [13] and TMEM268/ITGB4 signaling axis regulates the growth of GC cells and is a potential treatment target for GC [14]. However, the potential oncological pro le of ITGB2, ITGB5, ITGB6, ITGB7 and ITGB8 in GC is still unclear,and the full outline of the oncological features of the ITGB family in GC is still not depicted.
In our study, using different kinds of online databases, we are the rst to systematically compared the relationship between differences in transcript levels of ITGB family members and tumorigenesis, progression, prognosis, and immune in ltration in gastric cancer.

Oncomine Analysis
Oncomine dataset (www.oncomine.org) is an open online tumor microarray database [15]. It was employed to identify the transcriptional level difference of 20 kinds of malignancies in this study. The mRNA expression levels of ITGBs between tumor specimens and normal tissues were compared using Student's t test. Thresholds were set as the following:P value < 0.01; Fold change:2; Gene rank: top 10%.

GEPIA Dataset Analysis
GEPIA dataset (www. gepia.cancer-pku.cn) is a statistical mining tool that analyzes published annotated genomic data from the Cancer Genome Atlas (TCGA) and Genotypic Tissue Expression (GTEx) projects.
GEPIA can provide statistical analysis of expression, prognosis, and correlation [16]. In our study,GEPIA was used to analyze the correlation between ITGB superfamily subunits expression and their tumor stages in GC.

The Kaplan-Meier Plotter Analysis
Kaplan Meier plotter (http://kmplot.com) database has the ability to evaluate the correlation between gene expression information and clinical survival status from 20 different cancer types [17,18]. Using the KM plotter database, we assessed the prognostic values of mRNA expression of ITGB superfamily members in GC patients, including overall survival (OS) and recurrence-free survival (RFS). Patients sample data was divided into high expression groups and low expression groups based on the best cut off values of ITGBs mRNA expression and then Kaplan-Meier survival curve was drew. A log P-value < 0.05 was considered as statistically signi cant.

The UALCAN Analysis
UALCAN is an open online database that provides mRNA expression level of different kinds of cancers originating from TCGA database [19]. It was used to compare the relative mRNA expression of ITGBs between GC samples and their corresponding normal tissues.

GeneMANIA Analysis
GeneMANIA (www.genemania.org) is an easy-to-operate network analysis database that allows the construction of gene -gene interaction networks [20]. In this study, GeneMANIA was used to assess coexpression, co-localization, physical interactions, pathways, genetic interactions, predictions, and shared protein domains of ITGBs.

STRINGS Analysis
STRINGS (www.string-db.org) online database can build protein-protein interaction (PPI) networks based on all publicly available resources [21]. In this study, we constructed a PPI network of differentially expressed ITGBs using STRINGS to investigate the relationship between them. The basic settings are set as follows:"network type:full network""minimum required interaction score:medium con dence = 0.4"; "max number of interactors: not more than 20 interacters".

Metascape Analysis
Metascape (http://metascape.org) database allows mapping of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for enrichment analysis [22]. In this study, we used Metascape for functional enrichment Analysis of ITGBs and Their adjacent genes in GC Patients.
TIMER Analysis TIMER (www.cistrome.shinyapps.io) is a specialized online tool that can extrapolate the value of tumorin ltrating immune cells from more than 30 cancer types [23]. In present study, we used TIMER to evaluate the correlation between the expression level of ITGBs in GC and the level of immune in ltration of 6 different immune cells after tumor purity adjustment.

Cell culture
The GC cell lines (AGS, MGC803, HGC27) and stomach normal cell lines (GES-1) were given by the Immunology Laboratory of Anhui Medical University.All cell lines were cultured in RPMI-1640 medium (BI, Kibbutz Beit Haemek, Israel) supplemented with 10% fetal bovine serum (FBS, BI, Kibbutz Beit Haemek, Israel) and incubated in a 5% CO2 incubator at 37°C.

qRT-PCR analysis
The total RNA was obtained using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. cDNA was generated using Primescript RT Reagent (Takara Bio Inc., Japan). All gene transcripts were quanti ed by qRT-PCR using SYBR Green PCR Master Mix (TaKaRa, China), and the GAPDH expression was used as an internal control.Use the ΔΔCt method in Microsoft Excel to calculate the multiplicative change.The following PCR primers were used:

Transcript level differences of ITGBs in GC patients
Currently, a total of eight ITGBs are found to be widely existing in mammalian cells. However, they are differentially expressed in various tumor tissues. We compared the differences in transcript levels of ITGBs in different tumors as well as in the corresponding normal tissues using the Oncomine database ( Fig. 1). The results showed that the mRNA expression levels of ITGB1/2/3/5/8 were upregulated in GC patients while the mRNA expression level of ITGB7 was downregulated. Furthermore, for the expression levels of ITGB3 and ITGB6, there was no statistical signi cance between GC samples and their corresponding normal samples. In the dataset of Chen [24], D'Errico [25] and Cho[26], the ITGB1 transcript levels in GC samples were dramatically higher than in normal tissues, with P-values varying from 4.08E-4 to 8.56E-17. Three datasets include Chen dataset, D'Errico dataset and Wang dataset [27] showed ITGB2 expression levels were also remarkably elevated in GC patients. In the Cho dataset, ITGB4 expression was markedly increased in both subgroups of GC compared to normal samples, with fold changes of 2.105 (P = 0.001) and 2.008 (P = 4.87E-5), respectively. In the D'Errico dataset, the expression of ITGB5 was dramatically elevated in GC with a fold change of 3.241 (P = 4.89E-9). However,in two datasets (D'Errico and Cho), the expression of ITGB7 was downregulated in GC. For the expression of ITGB8, several datasets showed its high expression in tumor tissues (Table 1). NA, not available.

Association between mRNA expression levels of ITGBs and clinicopathological parameters of GC patients
With the help of the GEPIA database and UALCAN database, we compared the transcript level differences of ITGBs between GC samples and their corresponding normal samples. The results from GEPIA database showed that the transcript levels of ITGB1/2/4/8 in GC tissues were markedly higher than their corresponding normal tissues, while the transcript levels of ITGB3/5/6/7 were not signi cantly contrasted between GC tissues and their corresponding normal samples (Fig. 2). Meanwhile,the results of the UALCAN database indicated that the transcript levels of ITGB1/2/4/5/6/8 were markedly greater in GC tissues than in their corresponding normal tissues, whereas the transcript levels of ITGB3/7 were not signi cantly contrasting in GC tissues and their corresponding normal samples (Fig. 3). In addition,we used the GEPIA database to compare the differences of mRNA expression of ITGBs in GC patients at different tumor stages, the results showed that the expression levels of ITGB2 and ITGB7 are notably related to the tumor stage of GC patients, while the expression levels of ITGB1/3/4/5/6/8 are not related to the tumor stage of GC patients (Fig. 4).
To verify the above results, we examined the mRNA expression level of ITGBs in GC cell lines (AGS, MGC803, HGC27) and stomach normal cell lines (GES-1) using qRT-PCR. The results indicated that the expression level of ITGB1/2/4/5/6/7/8 was highly expressed in GC cell lines compared with normal cell lines, whereas the expression level of ITGB3 was lower in the former than in the latter (P < 0.05, Fig. 5).

The prognostic value of ITGBs in GC
We investigated the prognostic signi cance of ITGBs transcription levels in GC using Kaplan-Meier plotter. As shown in Fig. 6, GC patients with higher expression levels of ITGB2/6/7 were remarkly related to better RFS. In contrast, GC patients with low expression levels of ITGB3/4/5 were signi cantly correlation with better RFS, while expression levels of ITGB1/8 were not related to RFS in GC patients. Besides,as shown in Fig. 7, GC patients with high expression of ITGB1/6/7/8 had longer OS,while patients with high expression of ITGB3/4/5 had shorter OS, only ITGB2 transcription levels were not OS related in GC patients. In summary, the ndings suggest that high expression of ITGB1/6/7/8 may be a risk factor, while high expression of ITGB3/4/5 may be a protective factor for GC prognosis.

Gene-gene interaction network and PPI Analyses of ITGBs in GC Patients
We used the GeneMANIA database to build a gene-gene interaction network of ITGBs and then study their functions. As shown in Fig. 8a, eight ITGBs are surrounded by 20 related genes, these 20 genes stand for genes that are highly linked to ITGBs in terms of shared protein domains, physical interactions, co-localization, co-expression, prediction, genetic interactions and pathways. The ve most relevant genes for ITGBs are ITGBL1(integrin subunit beta like 1), WIF1(WNT inhibitory factor 1), EGFL7(EGF like domain multiple 7), ATRNL1(attractin like 1) and TENM4(teneurin transmembrane protein 4). Among them, ITGB3 is related to TENM4 and ITGB8 in terms of co-expression and has a physical interaction and prediction with ITGB1. ITGB6 is related to ITGB1 and ITGB4 is related to ITGB5 in terms of co-localization.
ITGBL1 and ATRNL1 share the same protein structural domain with all ITGBs family members. Meanwhile,WIF1,EGFL7 and TENM4 exhibit the same protein structural domains with the whole ITGBs members except ITGB2. In addition, functional analysis has shown that these genes are closely associated with protein complex involved in cell adhesion, receptor complex, rntegrin complex, cellsubstrate adhesion, integral component of plasma membrane, plasma membrane signaling receptor complex and gastrulation.

Functional enrichment analysis of ITGBs in GC patients
The Metascape database was adopted for functional annotation and pathway enrichment analysis of ITGBs and their neighboring genes. Among the top 20 items enriched by GO, 13 were biological processes(BP), 3 were molecular functions(MF), and 4 were cellular components(CC) (Figs. 9a, c and Table 2). The top three items are integrin-mediated signaling pathways, integrin complexes, and cell adhesion molecule binding, respectively. Among the top 11 items enriched by KEGG, as shown in Figs. 9b, d and Table 3, focal adhesion, cell adhesion molecules, proteoglycans in cancer, small cell lung cancer, rap1 signaling pathway, intestinal immune network for IgA production, and microRNAs in cancer were reported to be related to the tumorigenesis and progression of GC.  The correlation between the expression level of ITGBs and the immuno-in ltrative level in GC Immune cells have been reported to be closely associated with tumor proliferation and development. So we assessed the association between the expression levels of ITGBs and the immune in ltration degree of GC using the TIMER 2.0 database. The results demonstrated that ITGBs are participating in the body's immune response and immune cell in ltration, which in turn affect the prognosis of GC patients (Fig. 10).
The expression of ITGB1 and ITGB4 was strongly associated with the in ltration of CD4 + T cells, macrophages and dendritic cells, while the expression of ITGB2 and ITGB3 was positively linked to the in ltration of six immune cells. ITGB5 and ITGB6 expressions were positively correlated with the in ltration of B cells,CD4 + T cells and macrophages. ITGB7 expression was strongly associated with the in ltration of all six immune cells except B cells, while ITGB8 expression was only weakly correlated with the in ltration of B-cells.
Then we explored the clinical relevance of GC immune subset using Survival module in TIMER2.0, with the exibility to correct for multiple co-variables in a multi-variate Cox proportional hazards model. The output of the Cox model showed that in ltration of macrophages (P = 0.017) and ITGB4 (P = 0.026) was statistically associated with clinical outcomes in GC patients (Table 4).

Discussion
Integrins are multifunctional heterodimeric cell surface receptor molecules that can control cell adhesion, migration, proliferation, survival and differentiation [9]. The basic function of integrins in tumor metastasis has long been recognized. However, the complex role and implications of ITGBs in GC remain poorly understood. In this study,using bioinformatics analysis,the expression difference, prognostic value, immune in ltration of ITGBs in GC were investigated for the rst time.
Studies hve shown the upregulation of ITGB1 promotes the invasion of gastric cancer cells [11] and ITGB1 acts as a target of MicroRNA-29c to drive the onset and progression of GC [10]. In the present study, we found that the mRNA expression levels of ITGB1 were higher in GC than in normal tissues by multiple databases analysis, and we veri ed the results using qPCR. Meanwhile, ITGB1 expression in GC patients was not related to tumor stage and RFS, but higher ITGB1 transcript levels were associated with better OS.
Multiple studies have reported the role of ITGB2 in tumorigenesis and progression. Zhang X et al. reported High expression of ITGB2 triggered the PI3K/AKT/mTOR axis and promoted the progression of oral squamous cell carcinoma (OSCC) [29]. Liu M et al. reported that LncRNA ITGB2-AS1 could contribute to the migration and invasion of breast cancer cells through upregulation of ITGB2 [30]. However,no ITGB2 studies in gastric cancer yet. In our study,we found ITGB2 expression levels were higher in GC than in normal tissues,and ITGB2 transcript levels are associated with tumor stage in GC patients.In addition, GC patients with high ITGB2 expression had better RFS and tended to have better OS (P = 0.051).
Overexpression ITGB3 has been reported to associated with GC metastasis [12]. Wu Q et al. reported ITGB3 as a regulatory target of MiR-124-3p inhibits migration and invasion of GC [31]. However,we found there was no difference in the transcript levels of ITGB3 between gastric cancer tissues and normal tissues, and ITGB3 transcript levels are not associated with the stage of GC patients. But high ITGB3 mRNA expression levels were associated with poor OS and RFS in GC patients.
ITGB4 has also been found to promote GC cells invasion and migration [13] and TMEM268/ITGB4 signaling axis regulates the growth of GC cells and is a potential treatment target for GC [14]. Our study showed that the transcription levels of ITGB4 in GC were higher than that in normal tissues though Although there was no difference in the level of ITGB4 among different tumor stages. Survival analysis showed that high expression of ITGB4 was related to poorer OS and RFS in GC patients.
ITGB5 has been reported to have oncogenic effects in a variety of tumors [32][33][34]. But there are no studies of ITGB5 in GC.In present study, ITGB5 was found to be expressed at different levels in GC samples than in normal tissues and the survival analysis showed that high ITGB5 expression levels led to worse OS and RFS in GC patients, although its expression level did not correlate with the tumor stage of GC patients.
Cao D et al. [35] has been reported PD-L1/ITGB6/FAK/STAT3 signaling axis regulates proliferation, glucose metabolism, and chemoresistance in bladder cancer cell. In addition, by constructing a PPI network of ITGBs and its adjacent genes, we found that the protein complex involved in cell adhesion is the most closely linked to these genes. Then we performed GO enrichment analysis and KEGG pathway enrichment analysis using Metascape database, the result showed that focal adhesion, cell adhesion molecules, proteoglycans in cancer, small cell lung cancer, rap1 signaling pathway, intestinal immune network for IgA production, and microRNAs in cancer were related to the tumorigenesis and progression of GC. The ndings imply that ITGBs can be used as potential prognostic biomarkers for GC.
The tumor microenvironment (TME) is critical in tumorigenesis. [39] Different immune cells were detected in TME. [40] Immune cells within the TME generate an in ammatory response that plays a basic role in tumor growth. [39] Our study found that the expression of ITGB1 and ITGB4 was strongly associated with the in ltration of CD4 + T cells, macrophages and dendritic cells, while the expression of ITGB2 and ITGB3 was positively linked to the in ltration of six immune cells. ITGB5 and ITGB6 expressions were positively correlated with the in ltration of B cells, CD4 + T cells and macrophages. ITGB7 expression was strongly associated with the in ltration of all six immune cells except B cells, while ITGB8 expression had a weak correlation with the in ltration of B cells.These ndings suggest that ITGBs may be potential biomarkers of GC for immune checkpoint blockade therapy.
We also explored the clinical relevance of GC immune subset using Survival module in TIMER2.0. The result showed that in ltration of macrophages (P = 0.017) and ITGB4 (P = 0.026) was statistically associated with clinical outcomes in GC patients. These nds suggest that ITGBs may be potential biomarkers of GC for immune checkpoint blockade therapy.
This study has some limitations. First, the data for our study are mainly from public databases. Moreover, we did not conduct relevant functional and mechanistic studies. Further experimental studies are warranted to verify our results and thus facilitate the clinical application of ITGBs as prognostic markers or immunotherapeutic targets in GC.

Conclusion
In summary, our research described the prognostic value and immune in tration of ITGBs in GC through qRT-PCR combined with bioinformatics analysis, suggesting that abnormal expression of ITGBs plays a key role in the progression of GC and ITGBs may be potential prognostic biomarkers and therapeutic targets for GC.