The Genomic and Immunologic Signature of VISTA Based on a Pan-cancer Analysis

The Genomic and Immunologic Signature of VISTA Based on a Pan-cancer Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Genomic and Immunologic Signature of VISTA Based on a Pan-cancer Analysis Xi Cao, Xingtong Zhou, Qiang Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1383203/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The V-domain immunoglobulin suppressor of T cell activation (VISTA) is thought to be a non-redundant T cell regulation checkpoint of the PD-1/PD-L1 axis. VISTA has recently emerged as an anti-tumor immunotherapy agent. To understand the genomic and immunological signatures of VISTA, we evaluated its expression levels, prognostic effects, mutation and copy number alterations, and immune infiltration signatures by pan-cancer analysis via multiple public datasets. Relative to normal tissues, tumour tissues frequently exhibit VISTA downregulation. Survival and immune infiltration signature analyses indicated that VISTA expression was differently correlated with outcome and immune infiltration level among various cancer types. Nevertheless, VISTA upregulation increased the survival and immune infiltration levels in breast, lung, and skin cancers but did not markedly improve survival and was only weakly correlated with the immune infiltration level in ovarian cancer. The VISTA pan-cancer mutation rate was almost 2%. The major mutation type was missense, followed by synonymous substitution with C>T. Functional annotation and pathway enrichment analyses revealed that VISTA-related genes and proteins participated in the T cell and Toll-like receptor signalling pathways, innate immune and inflammatory responses, and negative regulation of NF-κB transcription and interleukins. The foregoing results may help clarify the mechanism of VISTA in tumour immune response. VISTA pan-cancer prognosis immune infiltration genomic Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1 Introduction In recent years, immune checkpoint inhibitors have become important treatment options for refractory and recurring malignant tumours. As of 2011, the U.S. Food and Drug Administration successively approved the blocking agents CTLA-4 (ipilimumab), PD-1 (nivolumab, pembrolizumab, and cemiplimab), and PD-L1 (atezolizumab, avelumab, and durvalumab) for the treatment of several malignant tumours ( 1 ). Moreover, new immune checkpoint inhibitors such as LAG3, BTLA, TIM3, VTCN1, VISTA, and CD47 ( 2 – 4 ) are being investigated as therapeutic targets for human cancers. VISTA (V-domain immunoglobulin suppressor of T cell activation) is a type I transmembrane protein on chromosome 10. It has the same extracellular Ig-V domain as PD-L1 ( 5 ). VISTA is expressed in myeloid cells, monocytes, dendritic cells, and lymphocytes ( 3 ). A previous study showed that VISTA expression in myeloid cells plays an important role in antitumour immunity ( 6 ). VISTA also maintains naïve T cell quiescence and peripheral tolerance, and regulates CD4 + T cell activity ( 5 , 7 , 8 ). Previous studies demonstrated that VISTA was upregulated in prostate cancer tissues after anti-CTLA-4 antibody treatment and in metastatic melanoma tissues after PD-1 blockade or a combination of PD-1 blockade and CTLA-4 treatment ( 9 , 10 ). VISTA might be a non-redundant PD-1/PD-L1 T cell regulation checkpoint ( 11 ). Hence, clinical trials are underway to evaluate the safety and efficacy of VISTA blockade alone and combined with PD-L1 blockade. Our research group confirmed that VISTA expression in immune cells was correlated with favourable prognosis in triple-negative breast cancer patients ( 12 ). Other studies found that VISTA upregulation in immune cells was correlated with better survival in breast cancer ( 13 ), oesophageal adenocarcinoma ( 14 ), and non-small cell lung cancer (NSCLC) ( 15 ), but worse survival in cutaneous melanoma ( 16 ). However, there are relatively few studies on the associations between VISTA and various human cancers. Furthermore, no research has been reported for the relationship between VISTA and pan-cancer based on large-scale data. The aim of this study, then, was to conduct a pan-cancer analysis of VISTA based on its expression level, effect on survival status, genetic alteration, relationship with other genes, and correlations with immune infiltration and enrichment pathways. In this manner, we summarised the potential impact of VISTA on tumour immunity. 2 Materials And Methods 2.1 Gene expression analysis C10ORF54 (VISTA gene symbol) was used as the input for the “Gene_DE” module of the Tumour Immune Estimation Resource v. 2 (TIMER2) web server 1 (17). According to the Cancer Genome Atlas (TCGA) pan-cancer project, tumours and their adjacent normal tissues differed in terms of their VISTA mRNA expression levels. For tumours with few or no adjacent normal tissues such as adrenocortical carcinoma (ACC), lymphoid neoplasm diffuse large B cell lymphoma (DLBC), acute myeloid leukaemia (LAML), brain lower-grade glioma (LGG), ovarian serous cystadenocarcinoma (OV), testicular germ cell tumour (TGCT), thymoma (THYM), and uterine carcinosarcoma (UCS), the “Expression analysis-Box Plots” module of the Gene Expression Profiling Interactive Analysis v. 2 (GEPIA2) web server 2 was used (18). In the genotype-tissue expression (GTEx) database, differential VISTA expression between tumour and normal tissues was examined under the settings “log2FC (fold change) cutoff=1” and “Match TCGA normal and GTEx data”. VSIR (VISTA gene alias) was entered into the UALCAN portal 3 (19) to compare total protein or phosphoprotein levels especially at S235, S248, and S305 of VISTA (NP_071436.1) between normal tissue and breast cancer, ovarian cancer, colon cancer, kidney renal clear cell carcinoma (clear cell RCC), uterine corpus endometrial carcinoma (UCEC), and lung adenocarcinoma (LUAD) tumour tissues. 2.2 Survival prognosis analysis The “Survival Map” module of GEPIA2 was used to obtain overall survival (OS) and disease-free survival (DFS) significance map data for VISTA in all TCGA tumours with cutoff = 50%. This threshold separated the high- and low-expression groups. Correlations between VISTA expression and survival in human tumours were analysed with the PrognoScan database 4 (20) based on public cancer microarray data. The threshold was adjusted to Cox P < 0.05. Survival data were analysed using the Kaplan-Meier Plotter dataset 5 (21). Relationships between VISTA expression level and OS, relapse-free survival (RFS), first progression (FP), and progression-free survival (PFS) were investigated for breast, gastric, lung, and ovarian cancers. 2.3 Genomic alteration analysis The COSMIC datasets 6 (22) contains data for millions of genomic rearrangements, fusion genes, variations, coding and non-coding mutations, and copy number abnormalities (CNA) derived from 466 whole-genome and systemic studies including TCGA and International Cancer Genome Consortium. They were used to identify VISTA mutations in human cancers. The cBioPortal website 7 (23) was also used to analyse VISTA mutations and CNA. The “TCGA Pan Cancer Atlas Studies” database was selected. It included 10,953 patients and 10,967 samples from 32 studies and provided alteration frequencies, mutation types, and CNA for VISTA. The VISTA 3D structure was displayed in a protein structure schematic diagram. 2.4 Genomic integrative data visualisation Cancer Regulome tools 8 were used to draw circus plots displaying the correlations among the expression levels of VISTA and other genes in human tumours based on the TCGA dataset. Spearman’s correlation coefficients revealed correlations between gene pairs. Genes with “-log10 (P)≥10 (P<1E-10)” were displayed in the circus plots. 2.5 Immune gene and infiltration analysis Correlations among VISTA expression, immune genes, and immune infiltration levels in TCGA pan-cancer were exhibited through the TIMER2 and Tumour Immune Estimation Resource (TIMER) 9 (24) websites. Correlations between VISTA and the immune gene markers for CD8 + T cells ( CD8A , CD8B ), T-helper 1 (Th1) cells ( TBX21 , STAT4 , STAT1 , IFNG , and TNF ), T-helper 2 (Th2) cells ( GATA3 , STAT6 , STAT5A , and IL13 ), follicular helper T (Tfh) cells ( BCL6 and IL21 ), T-helper 17 (Th17) cells ( STAT3 and IL17A ), regulatory T (Treg) cells ( FOXP3 , CCR8 , STAT5B , and TGFB1 ), B cells ( CD19 and CD79A ), monocytes ( CD86 and CSF1R ), tumour-associated macrophages (TAM) ( CCL2 , CD68 , and IL10 ), M1 macrophages ( NOS2 , IRF5 , and PTGS2 ), M2 macrophages ( CD163 , VSIG4 , and MS4A4A ), natural killer (NK) cells ( KIR2DL1 , KIR2DL3 , KIR2DL4 , KIR2DS4 , KIR3DL1 , KIR3DL2 , and KIR3DL3 ) and dendritic cells (DC) ( HLA-DPA1 , HLA-DPB1 , HLA-DQB1 , HLA-DRA , CD1C , NRP1 , and ITGAX ) were also analysed. Relationships between VISTA expression and infiltrating B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and DCs in the tumour microenvironment were also analysed. P- and partial correlation (cor) values were obtained via a purity-adjusted Spearman’s rank correlation test. Data were visualised in heatmaps or scatterplots. 2.6 VISTA-related gene enrichment analysis The STRING website 10 was used to identify the available established VISTA-binding proteins. A single protein (“VISTA”) and a single organism (“Homo sapiens”) were queried and the parameters were set as follows: minimum required interaction score [“Low confidence (0.150)”], meaning of network edges (“Confidence”), active interaction sources (“Text mining, experiments, databases, co-expression, neighbourhood, gene fusion, and co-occurrence”), and maximum number of interactors to show (“No more than 50 interactors” in the 1 st shell and “None” in the 2 nd shell). The “Similar Gene Detection” module of GEPIA2 was used to identify the top 100 VISTA-associated genes based on the data for all TCGA tumour and normal tissues. This list was then uploaded to Database for Annotation, Visualisation, and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/) using a selected identifier (“OFFICIAL_GENE_SYMBOL”) and limiting the “Homo sapiens” annotations. Kyoto Encyclopaedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses were conducted and included the terms BP (Biological process), CC (Cellular component), and MF (Molecular function). 2.7 Statistical analysis Differential VISTA expression between tumour and normal tissue was analysed by the Wilcoxon or analysis of variance test and displayed in box plots. The results of GEPIA, the Kaplan Meier plots, and PrognoScan were displayed by hazard ratios (HR) with 95% confidence intervals (CI) and P- or Cox P values from a log-rank test. Correlations among gene expression levels were evaluated by Spearman’s correlation test. The strength of each correlation was determined using the following scale: r=0.00–0.19 “very weak,” r=0.20–0.39 “weak,” r=0.40–0.59 “moderate,” r=0.60–0.79 “strong,” and r=0.80–1.0 “very strong.” P < 0.05 was considered statistically significant. 1 http://timer.cistrome.org/ 2 http://gepia2.cancer-pku.cn/#analysis 3 http://ualcan.path.uab.edu/analysis-prot.html 4 http://www.abren.net/PrognoScan/ 5 http://kmplot.com/analysis/ 6 https://cancer.sanger.ac.uk/cosmic/ 7 https://www.cbioportal.org/ 8 http://explorer.cancerregulome.org/ 9 https://cistrome.shinyapps.io/timer/ 10 https://string-db.org/ 3 Results 3.1 VISTA mRNA and protein expression levels in pan-cancer We applied the TIMER2 approach and used RNA-Seq data for multiple malignancies in TCGA to evaluate VISTA expression status. VISTA expression was significantly (P < 0.001) higher in the cholangiocarcinoma (CHOL), kidney renal clear cell carcinoma (KIRC), and liver hepatocellular carcinoma (LIHC) tumour tissues than their corresponding normal tissues. By contrast, VISTA expression was significantly (P < 0.001) lower in the bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), kidney chromophobe (KICH), LUAD, lung squamous cell carcinoma (LUSC), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), UCEC, cervical squamous cell carcinoma, endocervical adenocarcinoma (CESC), and thyroid carcinoma (THCA) (P < 0.05) tumour tissues than their corresponding normal tissues (Fig. 1 (A)). We applied GEPIA2 containing the GTEx dataset and found that VISTA expression was significantly (P < 0.001) higher in the LAML and LGG tumour tissues than their corresponding normal tissues, but significantly (P < 0.001) lower in the DLBC, THYM, and UCS tumour tissues than their corresponding normal tissues (Fig. 1 (B)). However, there were no significant differences in relative VISTA expression between oesophageal carcinoma (ESCA), glioblastoma multiforme (GBM), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG) (Fig. 1 (A))(Supplementary Table 1), ACC, OV, and TGCT (Fig. 1 (B)) tumour tissues and their corresponding normal tissues. We used the UALCAN portal to evaluate VISTA total protein and phosphorylation expression in various cancers. The VISTA total protein levels were significantly (P < 0.001) lower in breast cancer, colon cancer, lung adenocarcinoma, ovarian cancer, and UCEC tumour tissues than their corresponding normal tissues. By contrast, the VISTA total protein level was significantly (P < 0.001) higher in clear cell RCC tumour tissue than its corresponding normal tissue (Fig. 2 (A))(Supplementary Table 2). Supplementary Fig. 1(A) shows that VISTA phosphorylation occurred out of the V-set domain, especially at the S235 site in human tumours. S235 showed significantly (P < 0.001) lower phosphorylation levels in breast cancer, colon cancer, lung adenocarcinoma, ovarian cancer, and UCEC tumour tissues and a significantly (P < 0.001) higher phosphorylation level in clear cell RCC (P < 0.001) tumour tissue than their corresponding normal tissues (Fig. 2 (B))(Supplementary Table 3). However, the VISTA phosphorylation levels at S305 in colon cancer (Supplementary Fig. 1(B)) and at S248 in UCEC (Supplementary Fig. 1(C)) did not significantly differ from those of their corresponding normal tissues. 3.2 Prognostic potential of VISTA in pan-cancer We used GEPIA2 to investigate the correlations between VISTA expression based on RNA-Seq data and survival in pan-cancer. Median VISTA mRNA expression levels were used as cutoff values and the TCGA cancer cohorts were divided into high-expression and low-expression subgroups. For DFS, high VISTA expression was associated with better prognosis for CHOL (HR = 0.37, P = 0.040), LUAD (HR = 0.69, P = 0.017), skin cutaneous melanoma (SKCM) (HR = 0.76, P = 0.027), and THCA (HR = 0.54, P = 0.043) but worse prognosis for UVM (HR = 3.3, P = 0.017) (Fig. 3 (A)). For OS, high VISTA expression was correlated with better prognosis for KIRC (HR = 0.69, P = 0.018), LUAD (HR = 0.73, P = 0.043), mesothelioma (MESO) (HR = 0.51, P = 0.007), SARC (HR = 0.53, P = 0.002), and SKCM (HR = 0.60, P < 0.001) but worse prognosis for OV (HR = 1.30, P = 0.033) and uveal melanoma (UVM) (HR = 4.40, P = 0.004) (Fig. 3 (B)). We also used PrognoScan to assess the impact of VISTA expression on survival. VISTA expression significantly influenced prognosis in breast cancer, lung cancer (NSCLC), skin cancer (melanoma), and brain cancer (astrocytoma) (Supplementary Fig. 2(A–H)(Supplementary Table 4). A cohort (GSE1456–GPL97) of 159 breast cancer samples showed relatively better RFS (HR = 0.63, Cox P = 0.030) and OS (HR = 0.33, Cox P = 0.033) in the high VISTA expression subgroups. Another cohort (GSE6532–GPL570) of 87 breast cancer samples demonstrated that the high VISTA expression subgroup had prolonged RFS (HR = 0.52, Cox P = 0.040) and distant metastasis-free survival (DMFS) (HR = 0.52, Cox P = 0.040) compared with the low VISTA expression subgroup. The survival benefits of high VISTA expression were also observed in lung, skin, and brain cancers. We used the Kaplan-Meier Plotter database to determine the prognostic value of VISTA for different cancers based on Affymetrix microarrays. We divided cancer cohorts into high-expression and low-expression subgroups according to the “auto best cutoff”. High VISTA expression was correlated with better RFS (HR = 0.660, P < 0.001) and OS (HR = 0.650, P = 0.009) in breast cancer. It was also correlated with better FP (HR = 0.600, P < 0.001) and OS (HR = 0.5, P < 0.001) in lung cancer. However, high VISTA expression was correlated with worse FP (HR = 1.290, P = 0.036) in gastric cancer and with worse PFS (HR = 1.48, P < 0.001) in ovarian cancer (Supplementary Fig. 2(I–P)). The foregoing data indicated that VISTA expression was associated with various prognoses for different cancers. Relative to low VISTA expression, high VISTA expression was associated with survival advantage in BRCA, LUAD, and SKCM and with survival disadvantage in OV. 3.3 VISTA mutation in pan-cancer We consulted the COSMIC website to explore missense, nonsense, and synonymous VISTA mutations in different cancers and plotted them in pie charts. Figure 4 (A–O)(Supplementary Table 5) show nonsense VISTA substitutions in colon cancer (6.25%), malignant melanoma (5.00%), and liver cancer (4.00%). Missense VISTA mutations were detected in kidney cancer (100.00%), thyroid cancer (100.00%), urinary tract cancer (100.00%), glioma (55.56%), ovarian cancer (50.00%), malignant melanoma (40.00%), lung cancer (39.13%), colon cancer (37.50%), stomach cancer (33.33%), liver cancer (32.00%), endometrial cancer (30.00%), prostate cancer (20.00%), breast cancer (12.50%), oesophageal cancer (11.11%), and haematopoietic and lymphoid cancers (7.14%). Synonymous VISTA substitutions were observed in oesophageal cancer (55.56%), lung cancer (27.14%), glioma (22.22%), malignant melanoma (20.00%), stomach cancer (18.52%), colon cancer (12.50%), endometrial cancer (10.00%) and breast cancer (6.25%). Supplementary Fig. 3 (Supplementary Table 6) show that C > T was the most common substitution mutation in VISTA for all fifteen cancer types including malignant melanoma (66.67%), glioma (57.14%), endometrial cancer (50.00%), stomach cancer (50.00%), urinary tract cancer (50.00%), colon cancer (44.44%), and lung cancer (23.08%). A > C and T > A mutations in VISTA were not detected in any of the foregoing cancer types. Other forms of substitution mutations varied among the cancer types. We used the cBioPortal portal to analyse VISTA mutation (Supplementary Table 7) and CNA (Supplementary Table 8) in pan-cancer. Of the 10,953 patients and 10,967 samples queried in TCGA pan-cancer, VISTA was altered in 2% (176/10953) of the patients and 2% (176/10967) of the samples. Figure 5 (A) shows that the highest VISTA alteration frequency (4.95%) occurred in melanoma with a major “mutation” type (4.28%). For UCS (3.51%) and DLBC (2.08%), “mutation” was the only type. CNA “amplification” was the only type in CHOL (2.78%). “Deep deletion” was the major CNA type in sarcoma. For the 10,071 samples with both VISTA mRNA and mutation data, “fusion” correlated with the highest VISTA mRNA level, followed by “missense”, “truncating”, and “inframe” (Fig. 5 (B), upper panel). For the 9,889 samples with both VISTA mRNA and CNA data from GISTIC of cBioPortal dataset, CNA “diploid” had the highest VISTA mRNA level, followed by “amplification”, “shallow deletion”, “gain”, and “deep deletion” (Fig. 5 (B), lower panel). Figure 5 (C) shows that “missense” mutation in VISTA was the main type of genetic alteration in the V-set domain. The most common mutation site was L286Cfs*51 located out of the V-set domain with “truncating” mutations. It was detected in 1of UCS, 2 of UCEC, 2 of COAD, and 2 of STAD but could not map onto the 3D structure of VISTA (Fig. 5 (D)). 3.4 Genome-wide association of VISTA in pan-cancer We plotted circular diagrams using Regulome Explorer to show the relationships between VISTA and other genes, somatic mutations, somatic copy numbers, DNA methylation, protein levels, and localisation in the human genome. Correlations between VISTA and other genes were detected in ACC, BLCA, BRCA, COAD + READ, ESCA + STAD, GBM, HNSC, LGG, LIHC, LUAD, LUSC, OV, PRAD, SKCM, THCA, and UCEC. VISTA was closely associated with genes on other chromosomes in BRCA, GBM, LGG, LIHC, LUAD, LUSC, OV, PRAD, SKCM, and UCEC (Fig. 6 ) (Supplementary Table 9). 3.5 Correlations between VISTA and immune infiltration level in pan-cancer We used TIMER to analyse the correlations between VISTA expression and immune infiltration level in 32 cancer types. Figure 7 (Supplementary Table 10) shows that VISTA had significant positive relationships with the CD8 + T cell and Th1 cell immune gene markers in all cancers except LGG, MESO, and OV. VISTA had significant positive relationships with the DC markers in all cancers except DLBC and MESO. VISTA had a significant positive relationship with the TAM and especially M2 macrophage in all cancers except MEOS. However, VISTA had rather weak relationships with the NK cell markers in most cancers. VISTA expression level was significantly correlated with tumour purity in 26 types of cancer, B cell infiltration level in 21 types of cancer, CD8 + T cells in 19 types of cancer, CD4 + T cells in 28 types of cancer, macrophages in 23 types of cancer, neutrophils in 28 types of cancer, and DCs in 26 types of cancer (Supplementary Table 11). VISTA expression was significantly correlated with all six immune cells in ACC, BLCA, BRCA, CHOL, COAD, GBM, HNSC, KIRC, KIRP, LIHC, LUAD, LUSC, PAAD, PRAD, SKCM, and THYM. Nevertheless, VISTA expression was not correlated with the six immune cells in MESO. Based on the VISTA expression and survival analyses, we selected BRCA, LUAD, SKCM, and OV because their prognoses were strongly correlated with VISTA expression. Figure 8 shows that VISTA expression was significantly, strongly, and positively correlated with CD4 + T cells (r = 0.640, P = 3.68E-112) and DCs (r = 0.636, P = 7.13E-109) and moderately correlated with neutrophils (r = 0.593, P = 3.14E-91) and CD8 + T cells (r = 0.462, P = 2.41E-44) in BRCA. VISTA expression was significantly, strongly, and positively correlated with neutrophils (r = 0.612, P = 4.94E-51) and moderately correlated with CD4 + T cells (r = 0.583, P = 2.07E-45), DCs (r = 0.581, P = 2.26E-45), macrophages (r = 0.483, P = 1.07E-29), and B cells (r = 0.454, P = 5.27E-26) in LUAD. VISTA expression was significantly, moderately, and positively correlated with DCs (r = 0.592, P = 1.63E-43), neutrophils (r = 0.581, P = 3.28E-42), macrophages (r = 0.479, P = 2.62E-27), CD4 + T cells (r = 0.434, P = 6.79E-22), and CD8 + T cells (r = 0.402, P = 1.92E-18) in SKCM. However, VISTA expression was only very weakly positively correlated with CD4 + T cells (r = 0.141, P = 0.002), DCs (r = 0.157, P = 0.0005), neutrophils (r = 0.176, P = 0.0001), CD8 + T cells (r = 0.195, P = 1.75E-05), and B cells (r = 0.114, P = 0.013) and non-significantly correlated with macrophages in OV. The foregoing results suggest that VISTA significantly affected the infiltrating immune cells in BRCA, LUAD, and SKCM. 3.6 Enrichment analysis of VISTA-related partners To investigate the mechanisms of VISTA in tumour occurrence and development, we screened the top 50 VISTA-binding proteins and the top 100 VISTA-associated genes (Supplementary Table 12) and conducted pathway enrichment analyses using the STRING tool, GEPIA, and the DAVID website. Figure 9 (A) shows the interaction network for VISTA and the top 50 VISTA-binding proteins. We combined both datasets to perform KEGG (Supplementary Table 13) and GO enrichment (Supplementary Tables 14–16) analyses. Figure 9 (B) shows that the VISTA-associated genes were enriched in the immune-related “T cell receptor signalling”, “Toll-like receptor signalling”, and “Cytokine-cytokine receptor” pathways. The GO enrichment analysis data indicated that most of these genes were related to the biological processes “negative regulation of NF-κB transcription factor, interleukin (IL)-6, IL-10, IL-12, tumour necrosis factor (TNF), and interferon-gamma”, “innate immune response”, “inflammatory response” (Fig. 9 (C)), and the “immunological synapse pathway” (Fig. 9 (D)). 4 Discussion VISTA is a newly discovered member of the B7 family. It is highly homologous with PD-L1. VISTA may participate in certain immune-related process and regulate antitumour immunity. In the present study, we used various online tools to analyse VISTA expression, prognosis, mutations, correlations with other genes, immune infiltrating levels, and enrichment pathways in pan-cancer. VISTA mRNA was downregulated in BLCA, BRCA, CESC, COAD, DLBC, KICH, LUAD, LUSC, PRAD, READ, STAD, THCA, THYM, UCEC, and UCS but upregulated in CHOL, KIRC, LAML, LIHC, and LGG. However, VISTA mRNA expression did not significantly differ between normal tissues and the other nine cancers. Based on the UALCAN data, the trend of the differences in VISTA protein level between the tumour and normal tissues was consistent with the pattern of the VISTA mRNA levels in breast cancer, colon cancer, lung adenocarcinoma, clear cell RCC, and UCEC but not ovarian cancer. Furthermore, we detected high VISTA phosphorylation levels at S235 located out of the V-set domain in human tumours. Moreover, the trend of the differences between the tumour and normal tissues in terms of VISTA phosphorylation at S235 was consistent with the pattern of the differences between tumour and normal tissues in terms of total VISTA protein content. In this study, we used GEPIA2, PrognoScan, and Kaplan-Meier Plotter approaches to detect the correlations between VISTA mRNA expression and tumour prognosis. We found consistent prognostic effects of VISTA in BRCA, LUAD, SKCM, and OV. For BRCA, analysis of PrognoScan data for breast cancer cases in the GSE1456–GPL97/GSE6532–GPL570 cohorts revealed that high VISTA expression levels were associated with prolonged RFS, DMFS, and OS. However, data from the Kaplan-Meier Plotter with Affymetrix HGU133A and HGU133 + 2 microarrays ( 25 ) showed that high VISTA expression levels were correlated with better RFS and OS. Analysis of the datasets for TCGA-LUAD (n = 478) and TCGA-LUSC (n = 482) revealed a correlation between high VISTA expression and better OS in LUAD. Nevertheless, there was no such correlation between VISTA expression levels and LUSC OS. PrognoScan data for NSCLC cases in the GSE3141 cohorts showed relatively better OS in the group with high VISTA expression levels. Moreover, high VISTA expression in the lung cancer dataset from the Kaplan-Meier Plotter showed better FP and OS. Analysis of TCGA-SKCM (n = 458) revealed that high VISTA expression levels were associated with prolonged DFS and OS. Data for the melanoma cases in the GSE19234 cohort demonstrated OS advantage in the group with high VISTA expression levels. However, high VISTA expression was correlated with worse OS in the TCGA-OV (n = 423) cohorts. In addition, data from the Kaplan-Meier Plotter showed worse PFS for the OV cases expressing VISTA at high levels. As VISTA was recently discovered and is an important immune regulatory checkpoint, we focused on the relationships between it, various immune cell marker genes, and immune cell infiltration in pan-cancer. VISTA was significantly positively correlated with the CD8 + T cell, Th1 cell, DC, TAM, and especially M2 macrophage gene markers in most cancer types. We also found that VISTA had significant strong or moderately positive correlations with CD4 + T cells, neutrophils, and DCs in BRCA, LUAD, and SKCM but only very weak correlations with the foregoing immune cells in OV. Based on the prognostic status and immune cell infiltration analyses, we investigated the role of VISTA as an immune checkpoint regulator in malignant tumour prognosis. The present study revealed that for BRCA, LUAD, and SKCM, high VISTA mRNA expression levels were associated with better prognosis and high immune infiltration levels, especially in CD4 + T cells and DCs. Nevertheless, the correlation between VISTA expression and immune cell infiltration was very weak, and VISTA upregulation was associated with poor OV prognosis. In an earlier study on breast cancer ( 13 ), immunohistochemical (IHC) staining showed that high VISTA expression levels in immune cells were associated with better prognosis. Our previous research on triple-negative breast cancer (TNBC) ( 12 ) revealed survival advantage for immune cells in the group with high VISTA expression. We also found that VISTA expression in immune cells was positively correlated with CD4 + tumour-infiltrating lymphocytes. A similar result was obtained for the mRNA level analysis between VISTA and CD4 in a TCGA-TNBC cohort (n = 139). A previous study on NSCLC ( 15 ) reported that high VISTA expression levels in the tumour stroma were associated with better prognosis. An earlier work on oesophageal adenocarcinoma ( 14 ) confirmed that high VISTA expression levels in immune cell were related to survival advantage. Based on the foregoing results, we speculated that VISTA expression in CD4 + T cells and especially Th1 cells may promote adaptive antitumour immune response and improve prognosis. However, VISTA may promote NK cell activation and antibody-dependent, cell-mediated cytotoxicity function in innate and adaptive antitumour immunity. A few studies demonstrated a correlation between VISTA expression and survival advantage in hepatocellular carcinoma and high-grade serous ovarian cancer ( 26 , 27 ), but survival disadvantage in primary cutaneous melanoma ( 28 ). Moreover, there was no significant relationship between VISTA expression and survival in gastric cancer or oral squamous cell carcinoma ( 29 , 30 ). VISTA has inconsistent prognostic value in pan-cancer. There may be modification and loss in the process of translating VISTA mRNA into protein. Hence, the VISTA mRNA and protein expression levels might have different effects on the prognosis for the same human tumour. According to a previous study ( 7 ), VISTA may act as both a ligand for antigen-presenting cells and a receptor for T cells. Thus, VISTA expression in immune cells might have a different impact on prognosis from VISTA expression in tumour cells. Different tumour types have different compositions in the tumour immune microenvironment. According to the “cold” and “hot” tumour theory ( 31 , 32 ), VISTA might have a relatively stronger influence on “hot” tumour immunity. Missense mutations alter encoded amino acid sequences and types, thereby changing polypeptide chains and/or causing their loss-of-function. Previous studies reported that p53 missense mutation in colorectal cancers might induce oncogenesis via ‘gain-of-function’ mechanisms. Furthermore, the rare BRIP1 missense mutation increased breast and ovarian cancer risk ( 33 , 34 ). In the present study, most of the cancers investigated had VISTA missense mutations. However, their functions and effects in major cancers are unknown. An earlier report stated that synonymous mutations could not alter the amino acids they encoded but could nonetheless modify protein levels and conformations by changing splicing sites, mRNA stability, and translation efficiency ( 35 ). Synonymous mutations accounted for 6–8% of all driver mutations in human cancers ( 36 ) and were correlated with treatment response in NSCLC and breast cancer ( 37 , 38 ). Here, we detected modest levels of synonymous substitution in oesophageal cancer, lung cancer, glioma, malignant melanoma, and others. Nevertheless, the effects of synonymous mutation on VISTA RNA transcription and protein translation efficiency and conformation remain unclear. In the present study, GO and KEGG analyses showed that the main functions and enrichment pathways of VISTA were related to immunity. These included negative NF-κB transcription factor regulation which could promote the neoplastic process ( 39 ), negative interleukin regulation, and enrichment of the T cell and Toll-like receptor signalling pathways in innate immune and inflammatory response. The foregoing functions of VISTA underscore its importance in antitumour immunity. In this study, we investigated VISTA expression patterns, prognostic effects, mutation signatures, correlations with tumour-infiltrating immune cells, and pathway enrichment. The results of this research will help elucidate the mechanisms by which VISTA affects the immune response in tumour microenvironments. 5 Conclusion VISTA plays a vital role in cancer immunity. However, the relationships between VISTA and prognosis differ among cancers because VISTA has unique expression levels, mutation patterns, associations with infiltrating immune cells, signalling pathways, and mechanisms in each cancer type. Declarations Disclosure Statement We declare that this manuscript is original and unpublished. Each author reviewed the final version of the manuscript and approved its submission. The authors have no conflicts of interest to declare. Author Contributions XC and QS conceived, designed, and supervised the entire study. XC performed data mining, collection, and analysis, and wrote, edited, and reviewed the manuscript. XC and XTZ evaluated and analysed the public database and guided the statistical methods. All authors reviewed and approved the final version of the manuscript. Funding This study was supported by the Fundamental Research Funds for the Central Universities (No. 3332020001). The funders had neither involvement nor vested interest in this study. Data availability statement The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials. Ethics statement This study was a data-based bioinformatics analysis that did not involve ethical issues. References Vaddepally RK, Kharel P, Pandey R, Garje R, Chandra AB. Review of Indications of FDA-Approved Immune Checkpoint Inhibitors per NCCN Guidelines with the Level of Evidence. Cancers (Basel). 2020 Mar 20;12(3):738. doi: 10.3390/cancers12030738. Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012 Mar 22;12(4):252-64. doi: 10.1038/nrc3239. 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Supplementary Files SupplementaryFigure1.tif Supplementary Figure1. Phosphorylation analysis of VISTA protein in human cancer based on the UALCAN. (A) The phosphoprotein sites with positive results in the schematic diagram of VISTA protein. (B) Phosphoprotein level (NP_071436.1, S305 site) of VISTA between colon cancer and normal tissue.(C) Phosphoprotein level (NP_071436.1, S248 site) of VISTA between uterine corpus endometrial carcinoma and normal tissue. SupplementaryFigure2.tif Supplementary Figure2. Kaplan-Meier survival curves comparing the high and low expression level of VISTA in different cancer in the PrognoScan with probe type “225372_at” or “225373_at” (A-H) and Kaplan-Meier plotter databases with probe type “225372_at” (I-P). (A,B) Survival curves of RFS with probe type “225372_at” and OS with probe type as “225373_at” in the breast cancer cohorts (GSE1456-GPL97, n=159). (C, D) Survival curves of DMFS and RFS in the breast cancer cohorts (GSE6532-GPL570, n = 87) with probe type “225373_at”. (E) Survival curves of OS in the lung cancer cohort (GSE3141, n=111) with probe type “225372_at”. (F) Survival curves of OS in the skin cancer cohort (GSE19234, n=38) with probe type “225372_at”. (G,H) Survival curves of OS in the brain cancer cohort (GSE4271-GPL97, n=77) with probe type as “225372_at” and “225373_at”, respectively. (I,J) OS and RFS survival curves of breast cancer (n = 626, n = 1764). (K,L) OS and FP survival curves of lung cancer (n = 1144, n = 596). (M,N) OS and FP survival curves of gastric cancer (n=631, n=522). (O,P) OS and PFS survival curves of ovarian cancer (n = 655, n = 614). RFS: relapse-free survival; OS: overall survival; DMFS: distant metastasis-free survival; FP: first progression; PFS: progression-free survival. SupplementaryFigure3.tif Supplementary Figure3. The percentage of different type of substitution mutations of VISTA in human cancers analyzed by COSMIC and showed as pie chart Supplementarytable1.xlsx Supplementary Table 1. Data from “TIMER2”(Tumor immune estimation resource, version 2) web (http://timer.cistrome.org/) to compare the mRNA level of VISTA.BLCA: bladder urothelial carcinoma; BRCA: breast invasive carcinoma; CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL: cholangio carcinoma; COAD: colon adenocarcinoma; ESCA: esophageal carcinoma; GBM: glioblastoma multiforme; HNSC: head and neck squamous cell carcinoma; KICH: kidney chromophobe; KIRC: kidney renal clear cell carcinoma; KIRP: kidney renal papillary cell carcinoma; LIHC: liver hepatocellular carcinoma; LUAD: lung adenocarcinoma; LUSC: lung squamous cell carcinoma; PAAD: pancreatic adenocarcinoma; PCPG: pheochromocytoma and paraganglioma; PARD: prostate adenocarcinoma; READ: rectum adenocarcinoma; SKCM: skin cutaneous melanoma; STAD: stomach adenocarcinoma; THCA: thyroid carcinoma; UCEC: uterine corpus endometrial carcinoma. Supplementarytable2.xlsx Supplementary Table 2. Data from UALCAN portal (http://ualcan.path.uab.edu/analysis-prot. html) to compare the total protein level of VISTA. Supplementarytable3.xlsx Supplementary Table 3. Data from UALCAN portal (http://ualcan.path.uab.edu/analysis-prot. html) to compare the phosphoprotein level of VISTA at the S235 sites (NP_071436.1:S235). Supplementarytable4.xlsx Supplementary Table 4. Relation between VISTA expression and patient prognosis of different cancer in Prognoscan database.* P＜0.05，HR: hazard ratio, CI: confidence interval, DSS: disease-specific survival，OS: overall survival，RFS: relapse-free survival，DMFS: distant metastasis free survival, DFS: disease-free survival，PFS: progression-free survival. Supplementarytable5.xlsx Supplementary Table 5. The percentage of the missense, nonsense and synonymous mutations of VISTA in human cancers analyzed by COSMIC. Supplementarytable6.xlsx Supplementary Table 6. The percentage of the different type of substitution mutations of VISTA in human cancers analyzed by COSMIC. Supplementarytable7.xlsx Supplementary Table 7. The mutation of VISTA in TCGA pan-cancer through cBioPortal portal with queried 10953 patients and 10967 samples. Supplementarytable8.xlsx Supplementary Table 8. The copy number alteration (CNA) of VISTA in TCGA pan-cancer through cBioPortal portal with queried 10953 patients and 10967 samples. Supplementarytable9.xlsx Supplementary Table 9. The list of load filters name of the TCGA database from the Regulome program.ACC: adrenocortical carcinoma; BLCA: bladder urothelial carcinoma; BRCA: breast invasive carcinoma; COAD: colon adenocarcinoma; READ: rectum adenocarcinoma; ESCA: esophageal carcinoma; STAD: stomach adenocarcinoma; GBM: glioblastoma multiforme; HNSC: head and neck squamous cell carcinoma; LGG: brain lower grade glioma; LIHC: liver hepatocellular carcinoma; LUAD: lung adenocarcinoma; LUSC: lung squamous cell carcinoma; OV: ovarian cancer; PRAD: prostate adenocarcinoma; SKCM: skin cutaneous melanoma; THCA: thyroid carcinoma; UCEC: uterine corpus endometrial carcinoma. Supplementarytable10.xlsx Supplementary Table 10. Correlation analysis by Spearman's rho between VISTA and kinds of immune gene markers in pan-cancer from TIMER approach. ACC: adrenocortical carcinoma, BLCA: bladder urothelial carcinoma, BRCA: breast invasive carcinoma, CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma, CHOL: cholangio carcinoma, COAD: colon adenocarcinoma, DLBC: lymphoid neoplasm diffuse large B-cell lymphoma, ESCA: esophageal carcinoma, GBM: glioblastoma multiforme, HNSC: head and neck squamous cell carcinoma, KICH: kidney chromophobe, KIRC: kidney renal clear cell carcinoma, KIRP: kidney renal papillary cell carcinoma, LAML: acute myeloid leukemia, LGG: brain lower grade glioma, LIHC: liver hepatocellular carcinoma, LUAD: lung adenocarcinoma, LUSC: lung squamous cell carcinoma, MESO: mesothelioma, OV: ovarian serous cystadenocarcinoma, PAAD: pancreatic adenocarcinoma, PCPG: pheochromocytoma and paraganglioma, PARD: prostate adenocarcinoma, READ: rectum adenocarcinoma, SARC: sarcoma, SKCM: skin cutaneous melanoma, STAD: stomach adenocarcinoma, TGCT: testicular germ cell tumors, THCA: thyroid carcinoma, THYM: thymoma, UCEC: uterine corpus endometrial carcinoma, UCS: uterine carcinosarcoma, UVM: uveal melanoma. Supplementarytable11.xlsx Supplementary Table 11. Correlation analysis between VISTA and kinds of infiltrating immune cells in pan-cancer from TIMER approach. Cor*: partial correlation.ACC: adrenocortical carcinoma, BLCA: bladder urothelial carcinoma, BRCA: breast invasive carcinoma, CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma, CHOL: cholangio carcinoma, COAD: colon adenocarcinoma, DLBC: lymphoid neoplasm diffuse large B-cell lymphoma, ESCA: esophageal carcinoma, GBM: glioblastoma multiforme, HNSC: head and neck squamous cell carcinoma, KICH: kidney chromophobe, KIRC: kidney renal clear cell carcinoma, KIRP: kidney renal papillary cell carcinoma, LAML: acute myeloid leukemia, LGG: brain lower grade glioma, LIHC: liver hepatocellular carcinoma, LUAD: lung adenocarcinoma, LUSC: lung squamous cell carcinoma, MESO: mesothelioma, OV: ovarian serous cystadenocarcinoma, PAAD: pancreatic adenocarcinoma, PCPG: pheochromocytoma and paraganglioma, PARD: prostate adenocarcinoma, READ: rectum adenocarcinoma, SARC: sarcoma, SKCM: skin cutaneous melanoma, STAD: stomach adenocarcinoma, TGCT: testicular germ cell tumors, THCA: thyroid carcinoma, THYM: thymoma, UCEC: uterine corpus endometrial carcinoma, UCS: uterine carcinosarcoma, UVM: uveal melanoma. Supplementarytable12.xlsx Supplementary Table 12. The list of top 50 targeting VISTA-binding proteins and top 100 VISTA correlated genes.  Supplementarytable13.xlsx Supplementary Table 13. The pathway list of VISTA-related genes enrichment in KEGG analysis based on the combination of top 50 VISTA-binding genes obtained by the STRING tool and top 100 VISTA-correlated genes in the TCGA and obtained by GEPIA2 approach KEGG: kyoto encyclopedia of genes and genomes; FDR: false discovery rate. Supplementarytable14.xlsx Supplementary Table 14. The biologic process date of VISTA-related genes in GO analysis based on the combination of top 50 VISTA-binding genes obtained by the STRING tool and top 100 VISTA-correlated genes in the TCGA and obtained by GEPIA2 approach.GO: gene ontology; FDR: false discovery rate. Supplementarytable15.xlsx Supplementary Table 15. The cellular component date of VISTA-related genes in GO analysis based on the combination of top 50 VISTA-binding genes obtained by the STRING tool and top 100 VISTA-correlated genes in the TCGA and obtained by GEPIA2 approach.GO: gene ontology; FDR: false discovery rate. Supplementarytable16.xlsx Supplementary Table 16. The molecular function date of VISTA-related genes in GO analysis based on the combination of top 50 VISTA-binding genes obtained by the STRING tool and top 100 VISTA-correlated genes in the TCGA and obtained by GEPIA2 approach.GO: gene ontology; FDR: false discovery rate. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1383203","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":87909909,"identity":"d0b70bfb-c160-4137-aced-f5ff6ddd85bc","order_by":0,"name":"Xi Cao","email":"","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xi","middleName":"","lastName":"Cao","suffix":""},{"id":87909910,"identity":"b056d9e8-159c-449c-a4f2-713585b60d62","order_by":1,"name":"Xingtong Zhou","email":"","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xingtong","middleName":"","lastName":"Zhou","suffix":""},{"id":87909911,"identity":"80c9aedf-ff3a-4950-8648-4c632760e22b","order_by":2,"name":"Qiang Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYLCCBDjDwIaHn7+BFC0fCtJkJGccIME2xhkfDtsYNCTgVyU/I/fgjQc1d+y2S2QnfuYxOM9jwHCA8cPHHNxaDG7kJVskHHuWvHNG7mZpHoPbPObMDcySM7fh0SKRYyaRwHY42eBG7jZmkBbLhgNszLx4tMjPAGn5B9dyjsfgQAJ+LQw3gFoS2w7bgbQwzjA4QFiLwZk3xhaJfYcTLHvebpb4YJDMIznjYDNev8i35xje/PHtsL05e+7GDwl/7Oz5+ZsPfviIz2FAIAHEiRsQfMYG/OqhWuwNCCobBaNgFIyCEQsA999VhK/rQT8AAAAASUVORK5CYII=","orcid":"","institution":"Peking Union Medical College Hospital, Chinese Academy of Medical Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2022-02-22 03:29:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1383203/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1383203/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19345050,"identity":"823f0fbe-26fc-4ddb-9648-31d600964253","added_by":"auto","created_at":"2022-03-17 18:48:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3290715,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVISTA gene expression level in pan-cancer\u003c/strong\u003e. (\u003cstrong\u003eA\u003c/strong\u003e) VISTA gene expression in various cancers and adjacent normal tissues analysed by TIMER2. (\u003cstrong\u003eB\u003c/strong\u003e) VISTA gene expression in ACC, DLBC, LAML, LGG, OV, TGCT, THYM, and UCS from the TCGA project. GTEx data were analysed by GEPIA2. ACC: adrenocortical carcinoma; DLBC: lymphoid neoplasm diffuse large B-cell lymphoma; LAML: acute myeloid leukaemia; LGG: brain lower-grade glioma; OV: ovarian serous cystadenocarcinoma; TGCT: testicular germ cell tumour; THYM: thymoma; UCS: uterine carcinosarcoma.*P \u0026lt; 0.05; **P \u0026lt; 0.01; ***P \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/e0e7acad39503be74ab63313.jpg"},{"id":19344882,"identity":"2295b81b-4787-430f-b0c1-d0c8bfb9bf02","added_by":"auto","created_at":"2022-03-17 18:45:11","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1038114,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVISTA protein and phosphorylation expression levels in various cancers\u003c/strong\u003e. (\u003cstrong\u003eA\u003c/strong\u003e) Total VISTA protein level and (\u003cstrong\u003eB\u003c/strong\u003e) total VISTA phosphoprotein level (NP_071436.1, S235 site) in normal tissue and primary tissues of selected tumours including breast cancer, clear cell RCC, colon cancer, lung adenocarcinoma, ovarian cancer, uterine corpus endometrial carcinoma, determined via the UALCAN portal. Clear cell RCC: kidney renal clear cell carcinoma.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/823fcd591a7c02e30df6a159.jpg"},{"id":19344884,"identity":"d85676a5-5a19-449d-bab4-67a26b8c03fc","added_by":"auto","created_at":"2022-03-17 18:45:11","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2755321,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrognostic effect of VISTA gene expression levels in TCGA pan-cancer analysed by GEPIA2\u003c/strong\u003e. Survival map and Kaplan-Meier curves show (\u003cstrong\u003eA\u003c/strong\u003e) disease-free survival and (\u003cstrong\u003eB\u003c/strong\u003e) overall survival.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/2946db0685191ae4286f9645.jpg"},{"id":19345051,"identity":"9a49cc2d-6d34-4fc4-b454-eddb37dff1ec","added_by":"auto","created_at":"2022-03-17 18:48:11","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4707978,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePercentages of various VISTA mutation types in human cancers analysed by COSMIC and depicted as pie chart\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/d7ed547269d711abf4970b7d.jpg"},{"id":19345295,"identity":"2c1103b3-d581-44e0-9719-1b9917521095","added_by":"auto","created_at":"2022-03-17 18:51:11","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2146383,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVISTA mutation and CNA in TCGA pan-cancer analysed by cBioPortal web\u003c/strong\u003e. (A) Alteration frequency with mutation CNA type. (\u003cstrong\u003eB\u003c/strong\u003e) VISTA mRNA expression (RSEM: batch normalised from Illumina HiSeq_RNASeqV2) in different mutation types (upper panel) and putative CNA types from GISTIC (lower panel). (\u003cstrong\u003eC\u003c/strong\u003e) Mutation site with highest alteration frequency in L286Cfs*51. (\u003cstrong\u003eD\u003c/strong\u003e) 3D structure of VISTA. CNA: copy number alteration; 3D: three-dimensional.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/b1a50036e7f1e9c99851d793.jpg"},{"id":19345064,"identity":"2316681e-56d9-4d7e-8945-05f70d33e8d4","added_by":"auto","created_at":"2022-03-17 18:48:12","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3933701,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelations between VISTA and other genes from TCGA database (Regulome programme)\u003c/strong\u003e. Circular diagrams show correlations between VISTA (central connecting site at the edges) and other genes (with genomic coordinates) located at other sites of circle. Outer ring shows cytogenetic features whilst inner ring shows relationships among features lacking genomic coordinates.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/763d0e0e80e1089ff382a4c4.jpg"},{"id":19344886,"identity":"08897715-6530-4a40-b9c0-878b51434345","added_by":"auto","created_at":"2022-03-17 18:45:11","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":5212020,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation analysis of VISTA expression and 46 immune cells markers in pan-cancer\u003c/strong\u003e.*P \u0026lt; 0.05; **P \u0026lt; 0.01; ***P \u0026lt; 0.001; ns, no statistical significance.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/9c5706c318b473fdee6b2e57.jpg"},{"id":19345362,"identity":"0a055bfe-4a49-46cc-85c8-19ba78a39318","added_by":"auto","created_at":"2022-03-17 18:54:11","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":4587315,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between VISTA expression, tumour purity, and infiltration levels of B cells, CD8\u003csup\u003e+\u003c/sup\u003e T cells, CD4\u003csup\u003e+\u003c/sup\u003e T cells, macrophages, neutrophils, and dendritic cells in (\u003cstrong\u003eA\u003c/strong\u003e) BRCA, (\u003cstrong\u003eB\u003c/strong\u003e) LUAD, (\u003cstrong\u003eC\u003c/strong\u003e) SKCM, and (\u003cstrong\u003eD\u003c/strong\u003e) OV. BRCA: breast cancer; LUAD: lung adenocarcinoma; SKCM: skin cutaneous melanoma; OV: ovarian cancer. P \u0026lt; 0.05 was considered significant.\u003c/p\u003e","description":"","filename":"Figure8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/e0ed41f3b05285e424a51ab8.jpg"},{"id":19344894,"identity":"9364d86a-2be9-4c3d-9103-fdd9ac500837","added_by":"auto","created_at":"2022-03-17 18:45:12","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":2471272,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVISTA-related gene enrichment analysis\u003c/strong\u003e. (\u003cstrong\u003eA\u003c/strong\u003e) Top 50 VISTA-binding proteins obtained using STRING tool. Based on top 50 VISTA-binding genes and top 100 VISTA-correlated genes in TCGA, (\u003cstrong\u003eB\u003c/strong\u003e) KEGG pathway, (\u003cstrong\u003eC\u003c/strong\u003e) BP data in GO, (\u003cstrong\u003eD\u003c/strong\u003e) and MF and CC data in GO were analysed and depicted as bubble chart. KEGG: Kyoto Encyclopaedia of Genes and Genomes; BP: biological process; MF: molecular function; CC: cellular component; GO: gene ontology.\u003c/p\u003e","description":"","filename":"Figure9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/335838dc949fd0eb9ec9f771.jpg"},{"id":23851166,"identity":"637b8fb5-ec6d-4de6-8795-2512e9869b86","added_by":"auto","created_at":"2022-07-14 09:59:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2226005,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/85b5b02e-b1b2-4e1a-83de-2c025fbc00c0.pdf"},{"id":19345530,"identity":"eacff56a-7e9e-4870-a07b-9d44ff910b2f","added_by":"auto","created_at":"2022-03-17 18:57:11","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1601748,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure1. \u003c/strong\u003ePhosphorylation analysis of VISTA protein in human cancer based on the UALCAN. (\u003cstrong\u003eA\u003c/strong\u003e) The phosphoprotein sites with positive results in the schematic diagram of VISTA protein. (\u003cstrong\u003eB\u003c/strong\u003e) Phosphoprotein level (NP_071436.1, S305 site) of VISTA between colon cancer and normal tissue.(\u003cstrong\u003eC\u003c/strong\u003e) Phosphoprotein level (NP_071436.1, S248 site) of VISTA between uterine corpus endometrial carcinoma and normal tissue.\u003c/p\u003e","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/03dc2fc67faee12ac5bcda0d.tif"},{"id":19344893,"identity":"3cdac4ad-a960-4509-bdee-d76e912481af","added_by":"auto","created_at":"2022-03-17 18:45:12","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":5493500,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure2. \u003c/strong\u003eKaplan-Meier survival curves comparing the high and low expression level of VISTA in different cancer in the PrognoScan with probe type “225372_at” or “225373_at” (A-H) and Kaplan-Meier plotter databases with probe type “225372_at” (I-P). (\u003cstrong\u003eA,B\u003c/strong\u003e) Survival curves of RFS with probe type “225372_at” and OS with probe type as “225373_at” in the breast cancer cohorts (GSE1456-GPL97, n=159). (\u003cstrong\u003eC, D\u003c/strong\u003e) Survival curves of DMFS and RFS in the breast cancer cohorts (GSE6532-GPL570, n = 87) with probe type “225373_at”. (\u003cstrong\u003eE\u003c/strong\u003e) Survival curves of OS in the lung cancer cohort (GSE3141, n=111) with probe type “225372_at”. (\u003cstrong\u003eF\u003c/strong\u003e) Survival curves of OS in the skin cancer cohort (GSE19234, n=38) with probe type “225372_at”. (\u003cstrong\u003eG,H\u003c/strong\u003e) Survival curves of OS in the brain cancer cohort (GSE4271-GPL97, n=77) with probe type as “225372_at” and “225373_at”, respectively. (\u003cstrong\u003eI,J\u003c/strong\u003e) OS and RFS survival curves of breast cancer (n = 626, n = 1764). (\u003cstrong\u003eK,L\u003c/strong\u003e) OS and FP survival curves of lung cancer (n = 1144, n = 596). (\u003cstrong\u003eM,N\u003c/strong\u003e) OS and FP survival curves of gastric cancer (n=631, n=522). (\u003cstrong\u003eO,P\u003c/strong\u003e) OS and PFS survival curves of ovarian cancer (n = 655, n = 614). RFS: relapse-free survival; OS: overall survival; DMFS: distant metastasis-free survival; FP: first progression; PFS: progression-free survival.\u003c/p\u003e","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/b1d2e475d65a8001c23b453a.tif"},{"id":19345062,"identity":"370242ac-75d8-47fa-83f6-50831a27387e","added_by":"auto","created_at":"2022-03-17 18:48:12","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":16368700,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure3. \u003c/strong\u003eThe percentage of different type of substitution mutations of VISTA in human cancers analyzed by COSMIC and showed as pie chart\u003c/p\u003e","description":"","filename":"SupplementaryFigure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/d1be1b07176aa88b9ffbae73.tif"},{"id":19345292,"identity":"74f5f734-cd92-4a98-a021-1ce1eee22d81","added_by":"auto","created_at":"2022-03-17 18:51:11","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":12410,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 1. \u003c/strong\u003eData from “TIMER2”(Tumor immune estimation resource, version 2) web (http://timer.cistrome.org/) to compare the mRNA level of VISTA.\u003c/p\u003e\u003cp\u003eBLCA: bladder urothelial carcinoma; BRCA: breast invasive carcinoma; CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL: cholangio carcinoma; COAD: colon adenocarcinoma; ESCA: esophageal carcinoma; GBM: glioblastoma multiforme; HNSC: head and neck squamous cell carcinoma; KICH: kidney chromophobe; KIRC: kidney renal clear cell carcinoma; KIRP: kidney renal papillary cell carcinoma; LIHC: liver hepatocellular carcinoma; LUAD: lung adenocarcinoma; LUSC: lung squamous cell carcinoma; PAAD: pancreatic adenocarcinoma; PCPG: pheochromocytoma and paraganglioma; PARD: prostate adenocarcinoma; READ: rectum adenocarcinoma; SKCM: skin cutaneous melanoma; STAD: stomach adenocarcinoma; THCA: thyroid carcinoma; UCEC: uterine corpus endometrial carcinoma.\u003c/p\u003e","description":"","filename":"Supplementarytable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/739cf0cfe67ea5da96513623.xlsx"},{"id":19344902,"identity":"379648bb-9d02-46b9-aa39-bcff44e1cd5c","added_by":"auto","created_at":"2022-03-17 18:45:12","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":11302,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 2. \u003c/strong\u003eData from UALCAN portal (http://ualcan.path.uab.edu/\u003c/p\u003e\u003cp\u003eanalysis-prot. html) to compare the total protein level of VISTA.\u003c/p\u003e","description":"","filename":"Supplementarytable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/97740478635e3ff59c8864a0.xlsx"},{"id":19345059,"identity":"bac930a8-c121-4af0-a2fb-f35c5296e94c","added_by":"auto","created_at":"2022-03-17 18:48:12","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":11343,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 3. \u003c/strong\u003eData from UALCAN portal (http://ualcan.path.uab.edu/\u003c/p\u003e\u003cp\u003eanalysis-prot. html) to compare the phosphoprotein level of VISTA at the S235 sites (NP_071436.1:S235).\u003c/p\u003e","description":"","filename":"Supplementarytable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/33c87802679257a13a0c020e.xlsx"},{"id":19345057,"identity":"feb7c5ff-f9c5-4a79-8797-372a629d4ac7","added_by":"auto","created_at":"2022-03-17 18:48:12","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":15123,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 4. \u003c/strong\u003eRelation between VISTA expression and patient prognosis of different cancer in Prognoscan database.\u003c/p\u003e\u003cp\u003e* P＜0.05，HR: hazard ratio, CI: confidence interval, DSS: disease-specific survival，OS: overall survival，RFS: relapse-free survival，DMFS: distant metastasis free survival, DFS: disease-free survival，PFS: progression-free survival.\u003c/p\u003e","description":"","filename":"Supplementarytable4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/a7baef143c3f09baf5371207.xlsx"},{"id":19344887,"identity":"8a048f00-073b-4b05-8c71-4cb6cf7c33c8","added_by":"auto","created_at":"2022-03-17 18:45:11","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":11002,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 5. \u003c/strong\u003eThe percentage of the missense, nonsense and synonymous mutations of VISTA in human cancers analyzed by COSMIC.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Supplementarytable5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/c6b74fd178d2e5fdc5bb036c.xlsx"},{"id":19345052,"identity":"8891aba5-690a-45c1-b912-355f91c7b884","added_by":"auto","created_at":"2022-03-17 18:48:11","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":11769,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 6. \u003c/strong\u003eThe percentage of the different type of substitution mutations of VISTA in human cancers analyzed by COSMIC.\u003c/p\u003e","description":"","filename":"Supplementarytable6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/0af479e2eb07f2aa54327184.xlsx"},{"id":19345060,"identity":"7d3272ce-7f67-463f-8633-500da4cae3e7","added_by":"auto","created_at":"2022-03-17 18:48:12","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":227945,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 7. \u003c/strong\u003eThe mutation of VISTA in TCGA pan-cancer through cBioPortal portal with queried 10953 patients and 10967 samples.\u003c/p\u003e","description":"","filename":"Supplementarytable7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/c79d4a9aa23551e532dd3511.xlsx"},{"id":19345063,"identity":"c585d5ac-f862-452b-9f82-16fdb39bf2af","added_by":"auto","created_at":"2022-03-17 18:48:12","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":247423,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 8. \u003c/strong\u003eThe copy number alteration (CNA) of VISTA in TCGA pan-cancer through cBioPortal portal with queried 10953 patients and 10967 samples.\u003c/p\u003e","description":"","filename":"Supplementarytable8.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/72853484de002470bff4fa2c.xlsx"},{"id":19344899,"identity":"575731d2-fc6c-4b55-999c-8ef0b2b6dc66","added_by":"auto","created_at":"2022-03-17 18:45:12","extension":"xlsx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":10803,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 9\u003c/strong\u003e. The list of load filters name of the TCGA database from the Regulome program.\u003c/p\u003e\u003cp\u003eACC: adrenocortical carcinoma; BLCA: bladder urothelial carcinoma; BRCA: breast invasive carcinoma; COAD: colon adenocarcinoma; READ: rectum adenocarcinoma; ESCA: esophageal carcinoma; STAD: stomach adenocarcinoma; GBM: glioblastoma multiforme; HNSC: head and neck squamous cell carcinoma; LGG: brain lower grade glioma; LIHC: liver hepatocellular carcinoma; LUAD: lung adenocarcinoma; LUSC: lung squamous cell carcinoma; OV: ovarian cancer; PRAD: prostate adenocarcinoma; SKCM: skin cutaneous melanoma; THCA: thyroid carcinoma; UCEC: uterine corpus endometrial carcinoma.\u003c/p\u003e","description":"","filename":"Supplementarytable9.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/fbefbd05682259bea0d2cd4a.xlsx"},{"id":19345297,"identity":"1f16e4e5-b82f-4c86-9542-24769a767daf","added_by":"auto","created_at":"2022-03-17 18:51:12","extension":"xlsx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":76999,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 10. \u003c/strong\u003eCorrelation analysis by Spearman's rho between VISTA and kinds of immune gene markers in pan-cancer from TIMER approach. \u003c/p\u003e\u003cp\u003eACC: adrenocortical carcinoma, BLCA: bladder urothelial carcinoma, BRCA: breast invasive carcinoma, CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma, CHOL: cholangio carcinoma, COAD: colon adenocarcinoma, DLBC: lymphoid neoplasm diffuse large B-cell lymphoma, ESCA: esophageal carcinoma, GBM: glioblastoma multiforme, HNSC: head and neck squamous cell carcinoma, KICH: kidney chromophobe, KIRC: kidney renal clear cell carcinoma, KIRP: kidney renal papillary cell carcinoma, LAML: acute myeloid leukemia, LGG: brain lower grade glioma, LIHC: liver hepatocellular carcinoma, LUAD: lung adenocarcinoma, LUSC: lung squamous cell carcinoma, MESO: mesothelioma, OV: ovarian serous cystadenocarcinoma, PAAD: pancreatic adenocarcinoma, PCPG: pheochromocytoma and paraganglioma, PARD: prostate adenocarcinoma, READ: rectum adenocarcinoma, SARC: sarcoma, SKCM: skin cutaneous melanoma, STAD: stomach adenocarcinoma, TGCT: testicular germ cell tumors, THCA: thyroid carcinoma, THYM: thymoma, UCEC: uterine corpus endometrial carcinoma, UCS: uterine carcinosarcoma, UVM: uveal melanoma.\u003c/p\u003e","description":"","filename":"Supplementarytable10.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/ede991ffa3e07b4befda23fc.xlsx"},{"id":19344907,"identity":"c9923d23-8d29-4c33-8587-a3d4003318d0","added_by":"auto","created_at":"2022-03-17 18:45:12","extension":"xlsx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":13554,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 11. \u003c/strong\u003eCorrelation analysis between VISTA and kinds of infiltrating immune cells in pan-cancer from TIMER approach. \u003c/p\u003e\u003cp\u003eCor*: partial correlation.\u003c/p\u003e\u003cp\u003eACC: adrenocortical carcinoma, BLCA: bladder urothelial carcinoma, BRCA: breast invasive carcinoma, CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma, CHOL: cholangio carcinoma, COAD: colon adenocarcinoma, DLBC: lymphoid neoplasm diffuse large B-cell lymphoma, ESCA: esophageal carcinoma, GBM: glioblastoma multiforme, HNSC: head and neck squamous cell carcinoma, KICH: kidney chromophobe, KIRC: kidney renal clear cell carcinoma, KIRP: kidney renal papillary cell carcinoma, LAML: acute myeloid leukemia, LGG: brain lower grade glioma, LIHC: liver hepatocellular carcinoma, LUAD: lung adenocarcinoma, LUSC: lung squamous cell carcinoma, MESO: mesothelioma, OV: ovarian serous cystadenocarcinoma, PAAD: pancreatic adenocarcinoma, PCPG: pheochromocytoma and paraganglioma, PARD: prostate adenocarcinoma, READ: rectum adenocarcinoma, SARC: sarcoma, SKCM: skin cutaneous melanoma, STAD: stomach adenocarcinoma, TGCT: testicular germ cell tumors, THCA: thyroid carcinoma, THYM: thymoma, UCEC: uterine corpus endometrial carcinoma, UCS: uterine carcinosarcoma, UVM: uveal melanoma.\u003c/p\u003e","description":"","filename":"Supplementarytable11.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/a69e70ccd436a8d1f11415dc.xlsx"},{"id":19344904,"identity":"8726222d-fb8c-4864-9a35-d96529aaca8b","added_by":"auto","created_at":"2022-03-17 18:45:12","extension":"xlsx","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":12537,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 12. \u003c/strong\u003eThe list of top 50 targeting VISTA-binding proteins and top 100 VISTA correlated genes.\u003cstrong\u003e\u0026nbsp;\u003cspan class=\"ql-cursor\"\u003e\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Supplementarytable12.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/4a411af1cd55dd20b2d3c936.xlsx"},{"id":19345296,"identity":"07bde6b5-9030-46b3-810a-31477db51c6f","added_by":"auto","created_at":"2022-03-17 18:51:12","extension":"xlsx","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":11759,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 13. \u003c/strong\u003eThe pathway list of VISTA-related genes enrichment in KEGG analysis based on the combination of top 50 VISTA-binding genes obtained by the STRING tool and top 100 VISTA-correlated genes in the TCGA and obtained by GEPIA2 approach \u003c/p\u003e\u003cp\u003eKEGG: kyoto encyclopedia of genes and genomes; FDR: false discovery rate.\u003c/p\u003e","description":"","filename":"Supplementarytable13.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/8dcb89ef25ef8ae891452e4e.xlsx"},{"id":19344909,"identity":"969b56d2-852a-4d1b-bc6e-cc54ea3907ce","added_by":"auto","created_at":"2022-03-17 18:45:13","extension":"xlsx","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":16489,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 14. \u003c/strong\u003eThe biologic process date of VISTA-related genes in GO analysis based on the combination of top 50 VISTA-binding genes obtained by the STRING tool and top 100 VISTA-correlated genes in the TCGA and obtained by GEPIA2 approach.\u003c/p\u003e\u003cp\u003eGO: gene ontology; FDR: false discovery rate.\u003c/p\u003e","description":"","filename":"Supplementarytable14.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/346e25f4cf9cb08063175b92.xlsx"},{"id":19344906,"identity":"b2b38708-e181-4e08-a54f-e1ac766b9693","added_by":"auto","created_at":"2022-03-17 18:45:12","extension":"xlsx","order_by":18,"title":"","display":"","copyAsset":false,"role":"supplement","size":11345,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 15. \u003c/strong\u003eThe cellular component date of VISTA-related genes in GO analysis based on the combination of top 50 VISTA-binding genes obtained by the STRING tool and top 100 VISTA-correlated genes in the TCGA and obtained by GEPIA2 approach.\u003c/p\u003e\u003cp\u003eGO: gene ontology; FDR: false discovery rate.\u003c/p\u003e","description":"","filename":"Supplementarytable15.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/ee118a2f02871ed56aafd517.xlsx"},{"id":19344897,"identity":"ef991635-a927-4c52-9671-4b12eeb07c7d","added_by":"auto","created_at":"2022-03-17 18:45:12","extension":"xlsx","order_by":19,"title":"","display":"","copyAsset":false,"role":"supplement","size":11534,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 16. \u003c/strong\u003eThe molecular function date of VISTA-related genes in GO analysis based on the combination of top 50 VISTA-binding genes obtained by the STRING tool and top 100 VISTA-correlated genes in the TCGA and obtained by GEPIA2 approach.\u003c/p\u003e\u003cp\u003eGO: gene ontology; FDR: false discovery rate.\u003c/p\u003e","description":"","filename":"Supplementarytable16.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1383203/v1/2685aa76d04e6f17cc9fedea.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe Genomic and Immunologic Signature of VISTA Based on a Pan-cancer Analysis\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eIn recent years, immune checkpoint inhibitors have become important treatment options for refractory and recurring malignant tumours. As of 2011, the U.S. Food and Drug Administration successively approved the blocking agents CTLA-4 (ipilimumab), PD-1 (nivolumab, pembrolizumab, and cemiplimab), and PD-L1 (atezolizumab, avelumab, and durvalumab) for the treatment of several malignant tumours (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Moreover, new immune checkpoint inhibitors such as LAG3, BTLA, TIM3, VTCN1, VISTA, and CD47 (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) are being investigated as therapeutic targets for human cancers.\u003c/p\u003e \u003cp\u003eVISTA (V-domain immunoglobulin suppressor of T cell activation) is a type I transmembrane protein on chromosome 10. It has the same extracellular Ig-V domain as PD-L1 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). VISTA is expressed in myeloid cells, monocytes, dendritic cells, and lymphocytes (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). A previous study showed that VISTA expression in myeloid cells plays an important role in antitumour immunity (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). VISTA also maintains na\u0026iuml;ve T cell quiescence and peripheral tolerance, and regulates CD4\u003csup\u003e+\u003c/sup\u003e T cell activity (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Previous studies demonstrated that VISTA was upregulated in prostate cancer tissues after anti-CTLA-4 antibody treatment and in metastatic melanoma tissues after PD-1 blockade or a combination of PD-1 blockade and CTLA-4 treatment (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). VISTA might be a non-redundant PD-1/PD-L1 T cell regulation checkpoint (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Hence, clinical trials are underway to evaluate the safety and efficacy of VISTA blockade alone and combined with PD-L1 blockade.\u003c/p\u003e \u003cp\u003eOur research group confirmed that VISTA expression in immune cells was correlated with favourable prognosis in triple-negative breast cancer patients (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Other studies found that VISTA upregulation in immune cells was correlated with better survival in breast cancer (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), oesophageal adenocarcinoma (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), and non-small cell lung cancer (NSCLC) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), but worse survival in cutaneous melanoma (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, there are relatively few studies on the associations between VISTA and various human cancers. Furthermore, no research has been reported for the relationship between VISTA and pan-cancer based on large-scale data. The aim of this study, then, was to conduct a pan-cancer analysis of VISTA based on its expression level, effect on survival status, genetic alteration, relationship with other genes, and correlations with immune infiltration and enrichment pathways. In this manner, we summarised the potential impact of VISTA on tumour immunity.\u003c/p\u003e"},{"header":"2 Materials And Methods","content":"\u003ch2\u003e2.1 Gene expression analysis\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003eC10ORF54\u003c/em\u003e (VISTA gene symbol) was used as the input for the \u0026ldquo;Gene_DE\u0026rdquo; module of the Tumour Immune Estimation Resource v. 2 (TIMER2) web server\u003csup\u003e1\u003c/sup\u003e (17). According to the Cancer Genome Atlas (TCGA) pan-cancer project, tumours and their adjacent normal tissues differed in terms of their VISTA mRNA expression levels. For tumours with few or no adjacent normal tissues such as adrenocortical carcinoma (ACC), lymphoid neoplasm diffuse large B cell lymphoma (DLBC), acute myeloid leukaemia (LAML), brain lower-grade glioma (LGG), ovarian serous cystadenocarcinoma (OV), testicular germ cell tumour (TGCT), thymoma (THYM), and uterine carcinosarcoma (UCS), the \u0026ldquo;Expression analysis-Box Plots\u0026rdquo; module of the Gene Expression Profiling Interactive Analysis v. 2 (GEPIA2) web server\u003csup\u003e2\u003c/sup\u003e was used (18). In the genotype-tissue expression (GTEx) database, differential VISTA expression between tumour and normal tissues was examined under the settings \u0026ldquo;log2FC (fold change) cutoff=1\u0026rdquo; and \u0026ldquo;Match TCGA normal and GTEx data\u0026rdquo;. \u003cem\u003eVSIR\u003c/em\u003e (VISTA gene alias) was entered into the UALCAN portal\u003csup\u003e3\u003c/sup\u003e (19) to compare total protein or phosphoprotein levels especially at S235, S248, and S305 of VISTA (NP_071436.1) between normal tissue and breast cancer, ovarian cancer, colon cancer, kidney renal clear cell carcinoma (clear cell RCC), uterine corpus endometrial carcinoma (UCEC), and lung adenocarcinoma (LUAD) tumour tissues.\u003c/p\u003e\n\u003ch2\u003e2.2 Survival prognosis analysis\u003c/h2\u003e\n\u003cp\u003eThe \u0026ldquo;Survival Map\u0026rdquo; module of GEPIA2 was used to obtain overall survival (OS) and disease-free survival (DFS) significance map data for VISTA in all TCGA tumours with cutoff = 50%. This threshold separated the high- and low-expression groups. Correlations between VISTA expression and survival in human tumours were analysed with the PrognoScan database\u003csup\u003e4\u003c/sup\u003e (20) based on public cancer microarray data. The threshold was adjusted to Cox P \u0026lt; 0.05. Survival data were analysed using the Kaplan-Meier Plotter dataset\u003csup\u003e5\u003c/sup\u003e (21). Relationships between VISTA expression level and OS, relapse-free survival (RFS), first progression (FP), and progression-free survival (PFS) were investigated for breast, gastric, lung, and ovarian cancers.\u003c/p\u003e\n\u003ch2\u003e2.3 Genomic alteration analysis\u003c/h2\u003e\n\u003cp\u003eThe COSMIC datasets\u003csup\u003e6\u003c/sup\u003e (22) contains data for millions of genomic rearrangements, fusion genes, variations, coding and non-coding mutations, and copy number abnormalities (CNA) derived from 466 whole-genome and systemic studies including TCGA and International Cancer Genome Consortium. They were used to identify VISTA mutations in human cancers. The cBioPortal website\u003csup\u003e7\u003c/sup\u003e (23) was also used to analyse VISTA mutations and CNA. The \u0026ldquo;TCGA Pan Cancer Atlas Studies\u0026rdquo; database was selected. It included 10,953 patients and 10,967 samples from 32 studies and provided alteration frequencies, mutation types, and CNA for VISTA. The VISTA 3D structure was displayed in a protein structure schematic diagram.\u003c/p\u003e\n\u003ch2\u003e2.4 Genomic integrative data visualisation\u003c/h2\u003e\n\u003cp\u003eCancer Regulome tools\u003csup\u003e8\u003c/sup\u003e were used to draw circus plots displaying the correlations among the expression levels of VISTA and other genes in human tumours based on the TCGA dataset. Spearman\u0026rsquo;s correlation coefficients revealed correlations between gene pairs. Genes with \u0026ldquo;-log10 (P)\u0026ge;10 (P\u0026lt;1E-10)\u0026rdquo; were displayed in the circus plots.\u003c/p\u003e\n\u003ch2\u003e2.5 Immune gene and infiltration analysis\u003c/h2\u003e\n\u003cp\u003eCorrelations among VISTA expression, immune genes, and immune infiltration levels in TCGA pan-cancer were exhibited through the TIMER2 and Tumour Immune Estimation Resource (TIMER)\u003csup\u003e9\u003c/sup\u003e (24) websites. Correlations between VISTA and the immune gene markers for CD8\u003csup\u003e+\u003c/sup\u003e T cells (\u003cem\u003eCD8A\u003c/em\u003e, \u003cem\u003eCD8B\u003c/em\u003e), T-helper 1 (Th1) cells (\u003cem\u003eTBX21\u003c/em\u003e, \u003cem\u003eSTAT4\u003c/em\u003e, \u003cem\u003eSTAT1\u003c/em\u003e, \u003cem\u003eIFNG\u003c/em\u003e, and \u003cem\u003eTNF\u003c/em\u003e), T-helper 2 (Th2) cells (\u003cem\u003eGATA3\u003c/em\u003e, \u003cem\u003eSTAT6\u003c/em\u003e, \u003cem\u003eSTAT5A\u003c/em\u003e, and \u003cem\u003eIL13\u003c/em\u003e), follicular helper T (Tfh) cells (\u003cem\u003eBCL6\u003c/em\u003e and \u003cem\u003eIL21\u003c/em\u003e), T-helper 17 (Th17) cells (\u003cem\u003eSTAT3\u003c/em\u003e and \u003cem\u003eIL17A\u003c/em\u003e), regulatory T (Treg) cells (\u003cem\u003eFOXP3\u003c/em\u003e, \u003cem\u003eCCR8\u003c/em\u003e, \u003cem\u003eSTAT5B\u003c/em\u003e, and \u003cem\u003eTGFB1\u003c/em\u003e), B cells (\u003cem\u003eCD19\u003c/em\u003e and \u003cem\u003eCD79A\u003c/em\u003e), monocytes (\u003cem\u003eCD86\u003c/em\u003e and \u003cem\u003eCSF1R\u003c/em\u003e), tumour-associated macrophages (TAM) (\u003cem\u003eCCL2\u003c/em\u003e, \u003cem\u003eCD68\u003c/em\u003e, and \u003cem\u003eIL10\u003c/em\u003e), M1 macrophages (\u003cem\u003eNOS2\u003c/em\u003e, \u003cem\u003eIRF5\u003c/em\u003e, and \u003cem\u003ePTGS2\u003c/em\u003e), M2 macrophages (\u003cem\u003eCD163\u003c/em\u003e, \u003cem\u003eVSIG4\u003c/em\u003e, and \u003cem\u003eMS4A4A\u003c/em\u003e), natural killer (NK) cells (\u003cem\u003eKIR2DL1\u003c/em\u003e, \u003cem\u003eKIR2DL3\u003c/em\u003e, \u003cem\u003eKIR2DL4\u003c/em\u003e, \u003cem\u003eKIR2DS4\u003c/em\u003e, \u003cem\u003eKIR3DL1\u003c/em\u003e, \u003cem\u003eKIR3DL2\u003c/em\u003e, and \u003cem\u003eKIR3DL3\u003c/em\u003e) and dendritic cells (DC) (\u003cem\u003eHLA-DPA1\u003c/em\u003e, \u003cem\u003eHLA-DPB1\u003c/em\u003e, \u003cem\u003eHLA-DQB1\u003c/em\u003e, \u003cem\u003eHLA-DRA\u003c/em\u003e, \u003cem\u003eCD1C\u003c/em\u003e, \u003cem\u003eNRP1\u003c/em\u003e, and \u003cem\u003eITGAX\u003c/em\u003e) were also analysed. Relationships between VISTA expression and infiltrating B cells, CD4\u003csup\u003e+\u003c/sup\u003e T cells, CD8\u003csup\u003e+\u003c/sup\u003e T cells, neutrophils, macrophages, and DCs in the tumour microenvironment were also analysed. P- and partial correlation (cor) values were obtained via a purity-adjusted Spearman\u0026rsquo;s rank correlation test. Data were visualised in heatmaps or scatterplots.\u003c/p\u003e\n\u003ch2\u003e2.6 VISTA-related gene enrichment analysis\u003c/h2\u003e\n\u003cp\u003eThe STRING website\u003csup\u003e10\u003c/sup\u003e was used to identify the available established VISTA-binding proteins. A single protein (\u0026ldquo;VISTA\u0026rdquo;) and a single organism (\u0026ldquo;Homo sapiens\u0026rdquo;) were queried and the parameters were set as follows: minimum required interaction score [\u0026ldquo;Low confidence (0.150)\u0026rdquo;], meaning of network edges (\u0026ldquo;Confidence\u0026rdquo;), active interaction sources (\u0026ldquo;Text mining, experiments, databases, co-expression, neighbourhood, gene fusion, and co-occurrence\u0026rdquo;), and maximum number of interactors to show (\u0026ldquo;No more than 50 interactors\u0026rdquo; in the 1\u003csup\u003est\u003c/sup\u003e shell and \u0026ldquo;None\u0026rdquo; in the 2\u003csup\u003end\u003c/sup\u003e shell). The \u0026ldquo;Similar Gene Detection\u0026rdquo; module of GEPIA2 was used to identify the top 100 VISTA-associated genes based on the data for all TCGA tumour and normal tissues. This list was then uploaded to Database for Annotation, Visualisation, and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/) using a selected identifier (\u0026ldquo;OFFICIAL_GENE_SYMBOL\u0026rdquo;) and limiting the \u0026ldquo;Homo sapiens\u0026rdquo; annotations. Kyoto Encyclopaedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses were conducted and included the terms BP (Biological process), CC (Cellular component), and MF (Molecular function).\u003c/p\u003e\n\u003ch2\u003e2.7 Statistical analysis\u003c/h2\u003e\n\u003cp\u003eDifferential VISTA expression between tumour and normal tissue was analysed by the Wilcoxon or analysis of variance test and displayed in box plots. The results of GEPIA, the Kaplan Meier plots, and PrognoScan were displayed by hazard ratios (HR) with 95% confidence intervals (CI) and P- or Cox P values from a log-rank test. Correlations among gene expression levels were evaluated by Spearman\u0026rsquo;s correlation test. The strength of each correlation was determined using the following scale: r=0.00\u0026ndash;0.19 \u0026ldquo;very weak,\u0026rdquo; r=0.20\u0026ndash;0.39 \u0026ldquo;weak,\u0026rdquo; r=0.40\u0026ndash;0.59 \u0026ldquo;moderate,\u0026rdquo; r=0.60\u0026ndash;0.79 \u0026ldquo;strong,\u0026rdquo; and r=0.80\u0026ndash;1.0 \u0026ldquo;very strong.\u0026rdquo; P \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e http://timer.cistrome.org/\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e http://gepia2.cancer-pku.cn/#analysis\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e http://ualcan.path.uab.edu/analysis-prot.html\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003e http://www.abren.net/PrognoScan/\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u003c/sup\u003e http://kmplot.com/analysis/\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e6\u003c/sup\u003e https://cancer.sanger.ac.uk/cosmic/\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e7\u003c/sup\u003e https://www.cbioportal.org/\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e8\u003c/sup\u003e http://explorer.cancerregulome.org/\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e9\u003c/sup\u003e https://cistrome.shinyapps.io/timer/\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e10\u003c/sup\u003e https://string-db.org/\u003c/p\u003e"},{"header":"3 Results","content":"\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003e3.1 VISTA mRNA and protein expression levels in pan-cancer\u003c/h2\u003e\n \u003cp\u003eWe applied the TIMER2 approach and used RNA-Seq data for multiple malignancies in TCGA to evaluate VISTA expression status. VISTA expression was significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) higher in the cholangiocarcinoma (CHOL), kidney renal clear cell carcinoma (KIRC), and liver hepatocellular carcinoma (LIHC) tumour tissues than their corresponding normal tissues. By contrast, VISTA expression was significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) lower in the bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), kidney chromophobe (KICH), LUAD, lung squamous cell carcinoma (LUSC), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), UCEC, cervical squamous cell carcinoma, endocervical adenocarcinoma (CESC), and thyroid carcinoma (THCA) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) tumour tissues than their corresponding normal tissues (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e(A)).\u003c/p\u003e\n \u003cp\u003eWe applied GEPIA2 containing the GTEx dataset and found that VISTA expression was significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) higher in the LAML and LGG tumour tissues than their corresponding normal tissues, but significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) lower in the DLBC, THYM, and UCS tumour tissues than their corresponding normal tissues (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e(B)). However, there were no significant differences in relative VISTA expression between oesophageal carcinoma (ESCA), glioblastoma multiforme (GBM), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e(A))(Supplementary Table\u0026nbsp;1), ACC, OV, and TGCT (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e(B)) tumour tissues and their corresponding normal tissues.\u003c/p\u003e\n \u003cp\u003eWe used the UALCAN portal to evaluate VISTA total protein and phosphorylation expression in various cancers. The VISTA total protein levels were significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) lower in breast cancer, colon cancer, lung adenocarcinoma, ovarian cancer, and UCEC tumour tissues than their corresponding normal tissues. By contrast, the VISTA total protein level was significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) higher in clear cell RCC tumour tissue than its corresponding normal tissue (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e(A))(Supplementary Table\u0026nbsp;2). Supplementary Fig.\u0026nbsp;1(A) shows that VISTA phosphorylation occurred out of the V-set domain, especially at the S235 site in human tumours. S235 showed significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) lower phosphorylation levels in breast cancer, colon cancer, lung adenocarcinoma, ovarian cancer, and UCEC tumour tissues and a significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) higher phosphorylation level in clear cell RCC (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) tumour tissue than their corresponding normal tissues (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e(B))(Supplementary Table\u0026nbsp;3). However, the VISTA phosphorylation levels at S305 in colon cancer (Supplementary Fig.\u0026nbsp;1(B)) and at S248 in UCEC (Supplementary Fig.\u0026nbsp;1(C)) did not significantly differ from those of their corresponding normal tissues.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003e3.2 Prognostic potential of VISTA in pan-cancer\u003c/h2\u003e\n \u003cp\u003eWe used GEPIA2 to investigate the correlations between VISTA expression based on RNA-Seq data and survival in pan-cancer. Median VISTA mRNA expression levels were used as cutoff values and the TCGA cancer cohorts were divided into high-expression and low-expression subgroups. For DFS, high VISTA expression was associated with better prognosis for CHOL (HR\u0026thinsp;=\u0026thinsp;0.37, P\u0026thinsp;=\u0026thinsp;0.040), LUAD (HR\u0026thinsp;=\u0026thinsp;0.69, P\u0026thinsp;=\u0026thinsp;0.017), skin cutaneous melanoma (SKCM) (HR\u0026thinsp;=\u0026thinsp;0.76, P\u0026thinsp;=\u0026thinsp;0.027), and THCA (HR\u0026thinsp;=\u0026thinsp;0.54, P\u0026thinsp;=\u0026thinsp;0.043) but worse prognosis for UVM (HR\u0026thinsp;=\u0026thinsp;3.3, P\u0026thinsp;=\u0026thinsp;0.017) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e(A)). For OS, high VISTA expression was correlated with better prognosis for KIRC (HR\u0026thinsp;=\u0026thinsp;0.69, P\u0026thinsp;=\u0026thinsp;0.018), LUAD (HR\u0026thinsp;=\u0026thinsp;0.73, P\u0026thinsp;=\u0026thinsp;0.043), mesothelioma (MESO) (HR\u0026thinsp;=\u0026thinsp;0.51, P\u0026thinsp;=\u0026thinsp;0.007), SARC (HR\u0026thinsp;=\u0026thinsp;0.53, P\u0026thinsp;=\u0026thinsp;0.002), and SKCM (HR\u0026thinsp;=\u0026thinsp;0.60, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but worse prognosis for OV (HR\u0026thinsp;=\u0026thinsp;1.30, P\u0026thinsp;=\u0026thinsp;0.033) and uveal melanoma (UVM) (HR\u0026thinsp;=\u0026thinsp;4.40, P\u0026thinsp;=\u0026thinsp;0.004) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e(B)).\u003c/p\u003e\n \u003cp\u003eWe also used PrognoScan to assess the impact of VISTA expression on survival. VISTA expression significantly influenced prognosis in breast cancer, lung cancer (NSCLC), skin cancer (melanoma), and brain cancer (astrocytoma) (Supplementary Fig.\u0026nbsp;2(A\u0026ndash;H)(Supplementary Table\u0026nbsp;4). A cohort (GSE1456\u0026ndash;GPL97) of 159 breast cancer samples showed relatively better RFS (HR\u0026thinsp;=\u0026thinsp;0.63, Cox P\u0026thinsp;=\u0026thinsp;0.030) and OS (HR\u0026thinsp;=\u0026thinsp;0.33, Cox P\u0026thinsp;=\u0026thinsp;0.033) in the high VISTA expression subgroups. Another cohort (GSE6532\u0026ndash;GPL570) of 87 breast cancer samples demonstrated that the high VISTA expression subgroup had prolonged RFS (HR\u0026thinsp;=\u0026thinsp;0.52, Cox P\u0026thinsp;=\u0026thinsp;0.040) and distant metastasis-free survival (DMFS) (HR\u0026thinsp;=\u0026thinsp;0.52, Cox P\u0026thinsp;=\u0026thinsp;0.040) compared with the low VISTA expression subgroup. The survival benefits of high VISTA expression were also observed in lung, skin, and brain cancers.\u003c/p\u003e\n \u003cp\u003eWe used the Kaplan-Meier Plotter database to determine the prognostic value of VISTA for different cancers based on Affymetrix microarrays. We divided cancer cohorts into high-expression and low-expression subgroups according to the \u0026ldquo;auto best cutoff\u0026rdquo;. High VISTA expression was correlated with better RFS (HR\u0026thinsp;=\u0026thinsp;0.660, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and OS (HR\u0026thinsp;=\u0026thinsp;0.650, P\u0026thinsp;=\u0026thinsp;0.009) in breast cancer. It was also correlated with better FP (HR\u0026thinsp;=\u0026thinsp;0.600, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and OS (HR\u0026thinsp;=\u0026thinsp;0.5, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in lung cancer. However, high VISTA expression was correlated with worse FP (HR\u0026thinsp;=\u0026thinsp;1.290, P\u0026thinsp;=\u0026thinsp;0.036) in gastric cancer and with worse PFS (HR\u0026thinsp;=\u0026thinsp;1.48, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in ovarian cancer (Supplementary Fig.\u0026nbsp;2(I\u0026ndash;P)).\u003c/p\u003e\n \u003cp\u003eThe foregoing data indicated that VISTA expression was associated with various prognoses for different cancers. Relative to low VISTA expression, high VISTA expression was associated with survival advantage in BRCA, LUAD, and SKCM and with survival disadvantage in OV.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003ch2\u003e3.3 VISTA mutation in pan-cancer\u003c/h2\u003e\n \u003cp\u003eWe consulted the COSMIC website to explore missense, nonsense, and synonymous VISTA mutations in different cancers and plotted them in pie charts. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e(A\u0026ndash;O)(Supplementary Table\u0026nbsp;5) show nonsense VISTA substitutions in colon cancer (6.25%), malignant melanoma (5.00%), and liver cancer (4.00%). Missense VISTA mutations were detected in kidney cancer (100.00%), thyroid cancer (100.00%), urinary tract cancer (100.00%), glioma (55.56%), ovarian cancer (50.00%), malignant melanoma (40.00%), lung cancer (39.13%), colon cancer (37.50%), stomach cancer (33.33%), liver cancer (32.00%), endometrial cancer (30.00%), prostate cancer (20.00%), breast cancer (12.50%), oesophageal cancer (11.11%), and haematopoietic and lymphoid cancers (7.14%). Synonymous VISTA substitutions were observed in oesophageal cancer (55.56%), lung cancer (27.14%), glioma (22.22%), malignant melanoma (20.00%), stomach cancer (18.52%), colon cancer (12.50%), endometrial cancer (10.00%) and breast cancer (6.25%). Supplementary Fig.\u0026nbsp;3 (Supplementary Table\u0026nbsp;6) show that C\u0026thinsp;\u0026gt;\u0026thinsp;T was the most common substitution mutation in VISTA for all fifteen cancer types including malignant melanoma (66.67%), glioma (57.14%), endometrial cancer (50.00%), stomach cancer (50.00%), urinary tract cancer (50.00%), colon cancer (44.44%), and lung cancer (23.08%). A\u0026thinsp;\u0026gt;\u0026thinsp;C and T\u0026thinsp;\u0026gt;\u0026thinsp;A mutations in VISTA were not detected in any of the foregoing cancer types. Other forms of substitution mutations varied among the cancer types.\u003c/p\u003e\n \u003cp\u003eWe used the cBioPortal portal to analyse VISTA mutation (Supplementary Table\u0026nbsp;7) and CNA (Supplementary Table\u0026nbsp;8) in pan-cancer. Of the 10,953 patients and 10,967 samples queried in TCGA pan-cancer, VISTA was altered in 2% (176/10953) of the patients and 2% (176/10967) of the samples. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e(A) shows that the highest VISTA alteration frequency (4.95%) occurred in melanoma with a major \u0026ldquo;mutation\u0026rdquo; type (4.28%). For UCS (3.51%) and DLBC (2.08%), \u0026ldquo;mutation\u0026rdquo; was the only type. CNA \u0026ldquo;amplification\u0026rdquo; was the only type in CHOL (2.78%). \u0026ldquo;Deep deletion\u0026rdquo; was the major CNA type in sarcoma. For the 10,071 samples with both VISTA mRNA and mutation data, \u0026ldquo;fusion\u0026rdquo; correlated with the highest VISTA mRNA level, followed by \u0026ldquo;missense\u0026rdquo;, \u0026ldquo;truncating\u0026rdquo;, and \u0026ldquo;inframe\u0026rdquo; (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e(B), upper panel). For the 9,889 samples with both VISTA mRNA and CNA data from GISTIC of cBioPortal dataset, CNA \u0026ldquo;diploid\u0026rdquo; had the highest VISTA mRNA level, followed by \u0026ldquo;amplification\u0026rdquo;, \u0026ldquo;shallow deletion\u0026rdquo;, \u0026ldquo;gain\u0026rdquo;, and \u0026ldquo;deep deletion\u0026rdquo; (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e(B), lower panel). Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e(C) shows that \u0026ldquo;missense\u0026rdquo; mutation in VISTA was the main type of genetic alteration in the V-set domain. The most common mutation site was L286Cfs*51 located out of the V-set domain with \u0026ldquo;truncating\u0026rdquo; mutations. It was detected in 1of UCS, 2 of UCEC, 2 of COAD, and 2 of STAD but could not map onto the 3D structure of VISTA (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e(D)).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec14\"\u003e\n \u003ch2\u003e3.4 Genome-wide association of VISTA in pan-cancer\u003c/h2\u003e\n \u003cp\u003eWe plotted circular diagrams using Regulome Explorer to show the relationships between VISTA and other genes, somatic mutations, somatic copy numbers, DNA methylation, protein levels, and localisation in the human genome. Correlations between VISTA and other genes were detected in ACC, BLCA, BRCA, COAD\u0026thinsp;+\u0026thinsp;READ, ESCA\u0026thinsp;+\u0026thinsp;STAD, GBM, HNSC, LGG, LIHC, LUAD, LUSC, OV, PRAD, SKCM, THCA, and UCEC. VISTA was closely associated with genes on other chromosomes in BRCA, GBM, LGG, LIHC, LUAD, LUSC, OV, PRAD, SKCM, and UCEC (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e) (Supplementary Table\u0026nbsp;9).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec15\"\u003e\n \u003ch2\u003e3.5 Correlations between VISTA and immune infiltration level in pan-cancer\u003c/h2\u003e\n \u003cp\u003eWe used TIMER to analyse the correlations between VISTA expression and immune infiltration level in 32 cancer types. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e (Supplementary Table\u0026nbsp;10) shows that VISTA had significant positive relationships with the CD8\u003csup\u003e+\u003c/sup\u003e T cell and Th1 cell immune gene markers in all cancers except LGG, MESO, and OV. VISTA had significant positive relationships with the DC markers in all cancers except DLBC and MESO. VISTA had a significant positive relationship with the TAM and especially M2 macrophage in all cancers except MEOS. However, VISTA had rather weak relationships with the NK cell markers in most cancers.\u003c/p\u003e\n \u003cp\u003eVISTA expression level was significantly correlated with tumour purity in 26 types of cancer, B cell infiltration level in 21 types of cancer, CD8\u003csup\u003e+\u003c/sup\u003e T cells in 19 types of cancer, CD4\u003csup\u003e+\u003c/sup\u003e T cells in 28 types of cancer, macrophages in 23 types of cancer, neutrophils in 28 types of cancer, and DCs in 26 types of cancer (Supplementary Table\u0026nbsp;11). VISTA expression was significantly correlated with all six immune cells in ACC, BLCA, BRCA, CHOL, COAD, GBM, HNSC, KIRC, KIRP, LIHC, LUAD, LUSC, PAAD, PRAD, SKCM, and THYM. Nevertheless, VISTA expression was not correlated with the six immune cells in MESO. Based on the VISTA expression and survival analyses, we selected BRCA, LUAD, SKCM, and OV because their prognoses were strongly correlated with VISTA expression. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e shows that VISTA expression was significantly, strongly, and positively correlated with CD4\u003csup\u003e+\u003c/sup\u003e T cells (r\u0026thinsp;=\u0026thinsp;0.640, P\u0026thinsp;=\u0026thinsp;3.68E-112) and DCs (r\u0026thinsp;=\u0026thinsp;0.636, P\u0026thinsp;=\u0026thinsp;7.13E-109) and moderately correlated with neutrophils (r\u0026thinsp;=\u0026thinsp;0.593, P\u0026thinsp;=\u0026thinsp;3.14E-91) and CD8\u003csup\u003e+\u003c/sup\u003e T cells (r\u0026thinsp;=\u0026thinsp;0.462, P\u0026thinsp;=\u0026thinsp;2.41E-44) in BRCA. VISTA expression was significantly, strongly, and positively correlated with neutrophils (r\u0026thinsp;=\u0026thinsp;0.612, P\u0026thinsp;=\u0026thinsp;4.94E-51) and moderately correlated with CD4\u003csup\u003e+\u003c/sup\u003e T cells (r\u0026thinsp;=\u0026thinsp;0.583, P\u0026thinsp;=\u0026thinsp;2.07E-45), DCs (r\u0026thinsp;=\u0026thinsp;0.581, P\u0026thinsp;=\u0026thinsp;2.26E-45), macrophages (r\u0026thinsp;=\u0026thinsp;0.483, P\u0026thinsp;=\u0026thinsp;1.07E-29), and B cells (r\u0026thinsp;=\u0026thinsp;0.454, P\u0026thinsp;=\u0026thinsp;5.27E-26) in LUAD. VISTA expression was significantly, moderately, and positively correlated with DCs (r\u0026thinsp;=\u0026thinsp;0.592, P\u0026thinsp;=\u0026thinsp;1.63E-43), neutrophils (r\u0026thinsp;=\u0026thinsp;0.581, P\u0026thinsp;=\u0026thinsp;3.28E-42), macrophages (r\u0026thinsp;=\u0026thinsp;0.479, P\u0026thinsp;=\u0026thinsp;2.62E-27), CD4\u003csup\u003e+\u003c/sup\u003e T cells (r\u0026thinsp;=\u0026thinsp;0.434, P\u0026thinsp;=\u0026thinsp;6.79E-22), and CD8\u003csup\u003e+\u003c/sup\u003e T cells (r\u0026thinsp;=\u0026thinsp;0.402, P\u0026thinsp;=\u0026thinsp;1.92E-18) in SKCM. However, VISTA expression was only very weakly positively correlated with CD4\u003csup\u003e+\u003c/sup\u003e T cells (r\u0026thinsp;=\u0026thinsp;0.141, P\u0026thinsp;=\u0026thinsp;0.002), DCs (r\u0026thinsp;=\u0026thinsp;0.157, P\u0026thinsp;=\u0026thinsp;0.0005), neutrophils (r\u0026thinsp;=\u0026thinsp;0.176, P\u0026thinsp;=\u0026thinsp;0.0001), CD8\u003csup\u003e+\u003c/sup\u003e T cells (r\u0026thinsp;=\u0026thinsp;0.195, P\u0026thinsp;=\u0026thinsp;1.75E-05), and B cells (r\u0026thinsp;=\u0026thinsp;0.114, P\u0026thinsp;=\u0026thinsp;0.013) and non-significantly correlated with macrophages in OV. The foregoing results suggest that VISTA significantly affected the infiltrating immune cells in BRCA, LUAD, and SKCM.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec16\"\u003e\n \u003ch2\u003e3.6 Enrichment analysis of VISTA-related partners\u003c/h2\u003e\n \u003cp\u003eTo investigate the mechanisms of VISTA in tumour occurrence and development, we screened the top 50 VISTA-binding proteins and the top 100 VISTA-associated genes (Supplementary Table\u0026nbsp;12) and conducted pathway enrichment analyses using the STRING tool, GEPIA, and the DAVID website. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e(A) shows the interaction network for VISTA and the top 50 VISTA-binding proteins. We combined both datasets to perform KEGG (Supplementary Table\u0026nbsp;13) and GO enrichment (Supplementary Tables\u0026nbsp;14\u0026ndash;16) analyses. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e(B) shows that the VISTA-associated genes were enriched in the immune-related \u0026ldquo;T cell receptor signalling\u0026rdquo;, \u0026ldquo;Toll-like receptor signalling\u0026rdquo;, and \u0026ldquo;Cytokine-cytokine receptor\u0026rdquo; pathways. The GO enrichment analysis data indicated that most of these genes were related to the biological processes \u0026ldquo;negative regulation of NF-\u0026kappa;B transcription factor, interleukin (IL)-6, IL-10, IL-12, tumour necrosis factor (TNF), and interferon-gamma\u0026rdquo;, \u0026ldquo;innate immune response\u0026rdquo;, \u0026ldquo;inflammatory response\u0026rdquo; (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e(C)), and the \u0026ldquo;immunological synapse pathway\u0026rdquo; (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e(D)).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eVISTA is a newly discovered member of the B7 family. It is highly homologous with PD-L1. VISTA may participate in certain immune-related process and regulate antitumour immunity. In the present study, we used various online tools to analyse VISTA expression, prognosis, mutations, correlations with other genes, immune infiltrating levels, and enrichment pathways in pan-cancer.\u003c/p\u003e \u003cp\u003eVISTA mRNA was downregulated in BLCA, BRCA, CESC, COAD, DLBC, KICH, LUAD, LUSC, PRAD, READ, STAD, THCA, THYM, UCEC, and UCS but upregulated in CHOL, KIRC, LAML, LIHC, and LGG. However, VISTA mRNA expression did not significantly differ between normal tissues and the other nine cancers. Based on the UALCAN data, the trend of the differences in VISTA protein level between the tumour and normal tissues was consistent with the pattern of the VISTA mRNA levels in breast cancer, colon cancer, lung adenocarcinoma, clear cell RCC, and UCEC but not ovarian cancer. Furthermore, we detected high VISTA phosphorylation levels at S235 located out of the V-set domain in human tumours. Moreover, the trend of the differences between the tumour and normal tissues in terms of VISTA phosphorylation at S235 was consistent with the pattern of the differences between tumour and normal tissues in terms of total VISTA protein content.\u003c/p\u003e \u003cp\u003eIn this study, we used GEPIA2, PrognoScan, and Kaplan-Meier Plotter approaches to detect the correlations between VISTA mRNA expression and tumour prognosis. We found consistent prognostic effects of VISTA in BRCA, LUAD, SKCM, and OV. For BRCA, analysis of PrognoScan data for breast cancer cases in the GSE1456\u0026ndash;GPL97/GSE6532\u0026ndash;GPL570 cohorts revealed that high VISTA expression levels were associated with prolonged RFS, DMFS, and OS. However, data from the Kaplan-Meier Plotter with Affymetrix HGU133A and HGU133\u0026thinsp;+\u0026thinsp;2 microarrays (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) showed that high VISTA expression levels were correlated with better RFS and OS. Analysis of the datasets for TCGA-LUAD (n\u0026thinsp;=\u0026thinsp;478) and TCGA-LUSC (n\u0026thinsp;=\u0026thinsp;482) revealed a correlation between high VISTA expression and better OS in LUAD. Nevertheless, there was no such correlation between VISTA expression levels and LUSC OS. PrognoScan data for NSCLC cases in the GSE3141 cohorts showed relatively better OS in the group with high VISTA expression levels. Moreover, high VISTA expression in the lung cancer dataset from the Kaplan-Meier Plotter showed better FP and OS. Analysis of TCGA-SKCM (n\u0026thinsp;=\u0026thinsp;458) revealed that high VISTA expression levels were associated with prolonged DFS and OS. Data for the melanoma cases in the GSE19234 cohort demonstrated OS advantage in the group with high VISTA expression levels. However, high VISTA expression was correlated with worse OS in the TCGA-OV (n\u0026thinsp;=\u0026thinsp;423) cohorts. In addition, data from the Kaplan-Meier Plotter showed worse PFS for the OV cases expressing VISTA at high levels.\u003c/p\u003e \u003cp\u003eAs VISTA was recently discovered and is an important immune regulatory checkpoint, we focused on the relationships between it, various immune cell marker genes, and immune cell infiltration in pan-cancer. VISTA was significantly positively correlated with the CD8\u003csup\u003e+\u003c/sup\u003e T cell, Th1 cell, DC, TAM, and especially M2 macrophage gene markers in most cancer types. We also found that VISTA had significant strong or moderately positive correlations with CD4\u003csup\u003e+\u003c/sup\u003e T cells, neutrophils, and DCs in BRCA, LUAD, and SKCM but only very weak correlations with the foregoing immune cells in OV.\u003c/p\u003e \u003cp\u003eBased on the prognostic status and immune cell infiltration analyses, we investigated the role of VISTA as an immune checkpoint regulator in malignant tumour prognosis. The present study revealed that for BRCA, LUAD, and SKCM, high VISTA mRNA expression levels were associated with better prognosis and high immune infiltration levels, especially in CD4\u003csup\u003e+\u003c/sup\u003e T cells and DCs. Nevertheless, the correlation between VISTA expression and immune cell infiltration was very weak, and VISTA upregulation was associated with poor OV prognosis. In an earlier study on breast cancer (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), immunohistochemical (IHC) staining showed that high VISTA expression levels in immune cells were associated with better prognosis. Our previous research on triple-negative breast cancer (TNBC) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) revealed survival advantage for immune cells in the group with high VISTA expression. We also found that VISTA expression in immune cells was positively correlated with CD4\u003csup\u003e+\u003c/sup\u003e tumour-infiltrating lymphocytes. A similar result was obtained for the mRNA level analysis between VISTA and CD4 in a TCGA-TNBC cohort (n\u0026thinsp;=\u0026thinsp;139). A previous study on NSCLC (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) reported that high VISTA expression levels in the tumour stroma were associated with better prognosis. An earlier work on oesophageal adenocarcinoma (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) confirmed that high VISTA expression levels in immune cell were related to survival advantage. Based on the foregoing results, we speculated that VISTA expression in CD4\u003csup\u003e+\u003c/sup\u003e T cells and especially Th1 cells may promote adaptive antitumour immune response and improve prognosis. However, VISTA may promote NK cell activation and antibody-dependent, cell-mediated cytotoxicity function in innate and adaptive antitumour immunity. A few studies demonstrated a correlation between VISTA expression and survival advantage in hepatocellular carcinoma and high-grade serous ovarian cancer (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), but survival disadvantage in primary cutaneous melanoma (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Moreover, there was no significant relationship between VISTA expression and survival in gastric cancer or oral squamous cell carcinoma (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). VISTA has inconsistent prognostic value in pan-cancer. There may be modification and loss in the process of translating VISTA mRNA into protein. Hence, the VISTA mRNA and protein expression levels might have different effects on the prognosis for the same human tumour. According to a previous study (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), VISTA may act as both a ligand for antigen-presenting cells and a receptor for T cells. Thus, VISTA expression in immune cells might have a different impact on prognosis from VISTA expression in tumour cells. Different tumour types have different compositions in the tumour immune microenvironment. According to the \u0026ldquo;cold\u0026rdquo; and \u0026ldquo;hot\u0026rdquo; tumour theory (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), VISTA might have a relatively stronger influence on \u0026ldquo;hot\u0026rdquo; tumour immunity.\u003c/p\u003e \u003cp\u003eMissense mutations alter encoded amino acid sequences and types, thereby changing polypeptide chains and/or causing their loss-of-function. Previous studies reported that p53 missense mutation in colorectal cancers might induce oncogenesis via \u0026lsquo;gain-of-function\u0026rsquo; mechanisms. Furthermore, the rare \u003cem\u003eBRIP1\u003c/em\u003e missense mutation increased breast and ovarian cancer risk (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In the present study, most of the cancers investigated had VISTA missense mutations. However, their functions and effects in major cancers are unknown. An earlier report stated that synonymous mutations could not alter the amino acids they encoded but could nonetheless modify protein levels and conformations by changing splicing sites, mRNA stability, and translation efficiency (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Synonymous mutations accounted for 6\u0026ndash;8% of all driver mutations in human cancers (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) and were correlated with treatment response in NSCLC and breast cancer (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Here, we detected modest levels of synonymous substitution in oesophageal cancer, lung cancer, glioma, malignant melanoma, and others. Nevertheless, the effects of synonymous mutation on VISTA RNA transcription and protein translation efficiency and conformation remain unclear.\u003c/p\u003e \u003cp\u003eIn the present study, GO and KEGG analyses showed that the main functions and enrichment pathways of VISTA were related to immunity. These included negative NF-κB transcription factor regulation which could promote the neoplastic process (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), negative interleukin regulation, and enrichment of the T cell and Toll-like receptor signalling pathways in innate immune and inflammatory response. The foregoing functions of VISTA underscore its importance in antitumour immunity.\u003c/p\u003e \u003cp\u003eIn this study, we investigated VISTA expression patterns, prognostic effects, mutation signatures, correlations with tumour-infiltrating immune cells, and pathway enrichment. The results of this research will help elucidate the mechanisms by which VISTA affects the immune response in tumour microenvironments.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eVISTA plays a vital role in cancer immunity. However, the relationships between VISTA and prognosis differ among cancers because VISTA has unique expression levels, mutation patterns, associations with infiltrating immune cells, signalling pathways, and mechanisms in each cancer type.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare that this manuscript is original and unpublished. Each author reviewed the final version of the manuscript and approved its submission. The authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXC and QS conceived, designed, and supervised the entire study. XC performed data mining, collection, and analysis, and wrote, edited, and reviewed the manuscript. XC and XTZ evaluated and analysed the public database and guided the statistical methods. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Fundamental Research Funds for the Central Universities (No. 3332020001). The funders had neither involvement nor vested interest in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was a data-based bioinformatics analysis that did not involve ethical issues.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eVaddepally RK, Kharel P, Pandey R, Garje R, Chandra AB. Review of Indications of FDA-Approved Immune Checkpoint Inhibitors per NCCN Guidelines with the Level of Evidence. Cancers (Basel). 2020 Mar 20;12(3):738. doi: 10.3390/cancers12030738.\u003c/li\u003e\n \u003cli\u003ePardoll DM. The blockade of immune checkpoints in cancer immunotherapy. 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Genes (Basel). 2018 Jan 9;9(1):24. doi: 10.3390/genes9010024.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"VISTA, pan-cancer, prognosis, immune infiltration, genomic","lastPublishedDoi":"10.21203/rs.3.rs-1383203/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1383203/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe V-domain immunoglobulin suppressor of T cell activation (VISTA) is thought to be a non-redundant T cell regulation checkpoint of the PD-1/PD-L1 axis. VISTA has recently emerged as an anti-tumor immunotherapy agent. To understand the genomic and immunological signatures of VISTA, we evaluated its expression levels, prognostic effects, mutation and copy number alterations, and immune infiltration signatures by pan-cancer analysis via multiple public datasets. Relative to normal tissues, tumour tissues frequently exhibit VISTA downregulation. Survival and immune infiltration signature analyses indicated that VISTA expression was differently correlated with outcome and immune infiltration level among various cancer types. Nevertheless, VISTA upregulation increased the survival and immune infiltration levels in breast, lung, and skin cancers but did not markedly improve survival and was only weakly correlated with the immune infiltration level in ovarian cancer. The VISTA pan-cancer mutation rate was almost 2%. The major mutation type was missense, followed by synonymous substitution with C\u0026gt;T. Functional annotation and pathway enrichment analyses revealed that VISTA-related genes and proteins participated in the T cell and Toll-like receptor signalling pathways, innate immune and inflammatory responses, and negative regulation of NF-κB transcription and interleukins. The foregoing results may help clarify the mechanism of VISTA in tumour immune response.\u003c/p\u003e","manuscriptTitle":"The Genomic and Immunologic Signature of VISTA Based on a Pan-cancer Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-03-17 18:45:09","doi":"10.21203/rs.3.rs-1383203/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f956d859-1a90-4835-b42d-e72ab23e6a5b","owner":[],"postedDate":"March 17th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-07-14T09:59:05+00:00","versionOfRecord":[],"versionCreatedAt":"2022-03-17 18:45:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1383203","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1383203","identity":"rs-1383203","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}