Identification of INHBA as a Potential Biomarker for Gastric Cancer by Comprehensive Analysis

Inhibin subunit beta A (INHBA) is a member of the TGF-beta (transforming growth factor-beta) superfamily proteins, which plays a fundamental role in various cancers. However, little is known about the exact role of INHBA in patients with gastric cancer (GC). The present study aims to explore the relationship between INHBA and GC and detect the underlying mechanisms. Multiple bioinformatic approaches were first preformed basing on TIMER, GEPIA2, GEO, Oncomine and UALCAN databases, which revealed that INHBA was highly elevated in GC. This result was proved by Immunohistochemistry (IHC) and real time polymerase chain reaction (RT-PCR ) in 65 cases of GC tissues in our study. The bioinformatic analysis also revealed that high expression of INHBA was significantly related to unfavorable prognosis of GC. To detect the underlying mechanism, further analysis was performed basing on Kaplan Meier plotter database and found that poor prognosis of GC was related to infiltration of different enriched immune-cell subgroups. That was INHBA being negatively correlated with B cell while positively correlated with CD8 + T cells, macrophage, neutrophil and dendritic cell infiltration. However, there was week significant methylation level change between tumor and normal tissues. Moreover, INHBA mainly enriched on cancer-related signaling pathways, including TGF-beta signaling pathway, ECM-receptor signaling pathway, PID ALK1/2 pathway, and AGE-RAGE signaling pathway, which provide a new insight for future in-depth study. methylation levels The results showed week significant methylation level change between tumor and normal tissues, which indicates that INHBA expression might not controlled by promoter methylation. ROC analysis showed that INHBA have high diagnostic value for distinguishing GC patients from healthy individuals. The Kaplan Meier plotter was used to explore the correlation between the expression level of INHBA and the prognosis in patients with GC. The results showed that the high expression level of INHBA in GC was significantly related to the unfavorable prognosis in GC. In addition, clinicopathological subtypes analysis suggested that INHBA may serve as a potential prognostic biomarker for specific subtypes GC, including male, HER2 positive and intestinal classification. analysis and Metascape databases. showed INHBA mainly enriched cancer-related signaling pathways, TGF-beta signaling pathway, ECM-receptor pathway, PID ALK1/2 pathway, and AGE-RAGE signaling pathway. consistent with They showed that


Introduction
Owing to new techniques in diagnosis and treatment, incidence of GC has decreased, but it is still one of the most prevalent malignancies as well as the third leading cause of cancer-related mortality worldwide [1,2] . The occurrence and progress of gastric cancer involving a list of complex processes, including genes and microenvironment factors [3][4][5] . People are making great efforts to understand the behavior of GC and trying to perform treatment of all kind. Despite the progress in surgery and chemotherapy, 5-year survival rates of GC remain unsatisfying and many patients are still initially diagnosed at an advanced stage and relapse after treatment [6][7][8] . Hence, more efforts should be made to seek for beneficial biomarkers to make early diagnosis and targeted therapy to get better prognosis.
Inhibin subunit beta A (INHBA) is a member of the TGF-beta (transforming growth factor-beta) superfamily proteins which exerts a variety of biological functions, including immune response, sex determination, stem cell differentiation, developmental differentiation, and control of cellular migration and proliferation [9][10][11][12] . Nowadays, the emerging studies have shown that INHBA is aberrantly expressed in various of tumors, such as nasopharyngeal carcinoma [13] , lung adenocarcinoma [14] , ovarian cancer [15,16] , colon cancer [17,18] , esophageal squamous cell carcinoma [19] , pancreatic cancer [20] , breast cancer [21] and blander cancer [22] , and serves as a prognostic factor. Wang and Oshima et al. have shown that INHBA is highly expressed in GC tumor tissues and is a prognostic biomarker for patients with GC [23,24] . However, there is little systematical analysis on the underlying mechanisms of INHBA regarding GC. These findings shed light on the important role of INHBA in GC and illustrated the potential mechanism related to immune infiltration in GC. It also provides a certain theoretical foundation for making early diagnosis, prognosis evaluation, and specific treatment for GC.  Figure 2). And previous studies confirmed that INHBA protein was highly expressed in GC tumor tissues by using immunohistochemistry and western blotting [23,25,26] .

Immune infiltrates in correlation with INHBA in GC
Previous studies had shown that tumor infiltration was significantly related to the progression and prognosis of GC [27][28][29] . So, we utilized TIMER database to investigate whether the expression levels of

Relationship between INHBA expression and immune cell type markers in GC
We feather analyzed the correlation between the expression of INHBA and different immune cells type markers in GC based on TIMER database. The results showed that INHBA in GC was positively correlated with CD38 in B cells (Table 1)

The correlation between INHBA expression and methylation around the promoter region
Previous studies had shown that DNA promoter methylation is a meaningful pattern which affect tumorigenesis of tumors [30][31][32] . To explore the correlation between INHBA expression and DNA methylation, then the methylation levels of INHBA in GC were performed by using of MEXPRESS database. Figure 10 shows

Functional enrichment analysis of genes co-expressed with GC
In order to uncovered the potential function of the INHBA, we performed protein-protein interaction (PPI) network, GO function and KEGG pathway enrichment analysis via Metascape database. The PPI network as shown in Figure 11A and 11B. As Figure 11C-E shows that the most significant enriched GO terms were regulation transmembrane receptor protein serine/threonine kinase signaling pathway, BMP signaling pathway, SMAD protein signal transduction, nodal signaling pathway, cell proliferation and metabolic process. The most enriched KEGG pathways were TGF-beta signaling pathway and PID ALK1/2 pathway.

INHBA in GC
LinkedOmics was utilized to uncovered mRNA sequencing information from GC patients in the TCGA-STAD cohort. Spearman's test was conducted to analyze correlations between INHBA and genes differentially expressed in GC (red represents positively related genes and green represents negatively related genes) ( Figure 12A). The top 50 genes that were positively and negatively correlated with INHBA were shown in heat maps (Figure 12B-C). Significantly GO and KEGG functional enrichment analysis were conducted by gene set enrichment analysis (GSEA) suggested that these genes differentially expressed in correlation with INHBA in GC were mainly enriched collagen metabolic process, extracellular structure organization, cellular response to vascular endothelial growth factor stimulus, connective tissue development and DNA replication, and so on biological process ( Figure 12D). Essentially molecular functions and cellular component were collagen binding, extracellular matrix structural constituent, growth factor, Wnt-protein binding and SMAD binding, collagen trimer, endoplasmic reticulum lumen and so on (Figure 12E-F). KEGG pathway analysis showed that cancer-related signaling pathways were enriched, including TGF-beta signaling pathway, ECM-receptor signaling pathway, AGE-RAGE signaling pathway and so on ( Figure 12G). (G) KEGG pathway analysis.

Discussion
GC is a heterogeneous malignancy worldwide with high recurrence probability and unfavorable prognosis [8,33] . Currently, effective molecules have been identified in GC diagnosis and therapy by mechanistic analysis, such as CASC2 34  Previous studies had shown that tumor infiltration was significantly related to the progression and prognosis of GC [27][28][29] . Therefore, TIMER database was utilized to investigate the relationship between Overall, the present study implies that INHBA was elevated in GC tissues and high level of INHBA is a negative prognosis factor for GC, it theoretically affects prognosis through immune infiltration mechanism,which provides a new insight for future in-depth study. While, this study also has some limitations, we did not continue to explore the deep correlation between INHBA and immune infiltration and experiments were needed to verify the research results in vitro and in vivo. That is the next step of work in our following studies.

Tissue collection
All fresh specimens were collected from January

Oncomine database analysis
Oncomine (www.oncomine. org) database contains 715 gene expression datasets and 867,33 cancers and normal samples, is also the biggest and user-friendly oncogene chip database and integrated data mining tool [48] . The DNA copy number and mRNA expression differences of INHBA gene between GC tumor and normal tissues were determined using the Oncomine database. In the present study, we drew on a series of GC studies, including Cho GC [49] , DErrico GC [50] , Deng GC [51] , Cui GC [52] , Chen GC [53] , TCGA GC [54] and Wang GC [55] studies. The expression of INHBA was involved in evaluated in GC tissues in respect to its expression in normal tissues, and P<0.05 and foldchange of 1 as the cutoff criterion considered statistically significant. Expression projects using a standard processing pipeline [56,57] . In the present study, we used GEPIA2 to analyze the expression level of INHBA between GC tumor tissues and normal tissues.

UALCAN Database analysis
UALCAN (http://ualcan.path.uab.edu/) is a user-friendly web resource for analyzing cancer transcriptome data and in-depth analyses of gene expression ,methylation information, and survival curves [58] . In the present study, we used UALCAN to evaluate the expression of INHBA in different tumor subgroups, such as tumor stages, grade, nodal metastasis status, gender, TP53 mutation status, race, age, historical subtypes, and HPV status.

TIMER database analysis
TIMER (https://cistrome.shinyapps.io/timer/) is an a comprehensive and user-friendly online tool to systematically investigate and visualize the correlation between immune infiltrates and a wide spectrum of factors, including gene expression, clinical outcomes and somatic mutations over 10,897 tumors from 32 cancer types [59,60] .

Kaplan-Meier plotter database
Receiver operating characteristic (ROC) curve conducted by pROC [61] package in R software to explore the sensitivity and specificity for distinguishing GC patients from healthy individuals.
Kaplan-Meier plotter (http://kmplot.com/) is an online database containing microarray gene expression data and survival information extrcated from Gene Expression Omnibus (GEO) and TCGA database, which contain gene expression data and survival data of 1065 GC patients [62] . And the valid number of studies, which provides large scale cancer genomics data sets to visualize, analyze and download [63,64] .
The frequency of INHBA alterations (amplification, deep deletion, and missense mutations) in GC patients were assessed using the cBioportal for Cancer Genomics database and TCGA. What's more, we using the Kaplan-Meier analysis in cBioportal to analyze the effect of INHBA expression dysregulation on the patients' overall survival and disease-free survival.

MEXPRESS database analysis
MEXPRESS (https://mexpress.be/) is an intuitive and user-friendly online web tool for the visualization of TCGA gene expression (normalized RNASeqV2 value), DNA methylation and clinical data, as well as the correlation between them on a interested single gene level [65 66] . By defaults, the samples are sorted by the expression (from low to high) of the gene that was entered. The Pearson correlation is used to calculate the difference between expression value and methylation data. In the present study, we evaluated the correlation between INHBA expression and promoter methylation in GC.

Functional enrichment analysis
Metascape (http://metascape.org) is a new, free and user-friendly gene list analysis online tool to perform a functional enrichment analysis, which including cellular component (CC), biological process (BP), molecular function (MF), KEGG pathway analysis and protein-protein interaction analysis [67] . In the present study, Metascape was used to perform GO and KEGG pathway analysis of INHBA and neighboring genes significantly associated with INHBA. P-value < 0.05 was considered as significant.

LinkedOmics analysis
The LinkedOmics database (http://www.linkedomics.orglogin.php) is a comprehensive and unique online tool to access, analyze and compare disseminating data from large-scale cancer omics projects within and across all 32 TCGA cancer type [68] . Linkedomics three analytical modules were applied to explore attributes that are associated with entered gene, perform functional enrichment analysis, and compare integrated association results. In the present study, we used the database to explore the genes differentially expressed related to INHBA in the TCGA STAD cohort. Then GSEA was utilized to perform analyses of Ge Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

Statistical analysis
R (version 3.6.5, United States) and GraphPad Prism version 8 (GraphPad Software, La Jolla, CA, United States). was utilized for statistical analysis in this study. Continuous variables were analyzed by the Student's t test. P < 0.05 was considered as statistically significant.