| Literature DB >> 32600443 |
Xing Huang1,2,3, Xiaozhen Zhang4,5,6, Enliang Li4,5,6, Gang Zhang4,5,6, Xun Wang4,5,6, Tianyu Tang4,5,6, Xueli Bai7,8,9, Tingbo Liang10,11,12.
Abstract
VISTA (V-domain immunoglobulin suppressor of T cell activation) is a well-established immune regulatory receptor. However, pre-clinical investigations indicated more complicated influences of VISTA on cancer immunity than previously recognized. Here, we review the current knowledge on the therapeutic phenotypes and molecular mechanisms that underlie the contradictory roles of VISTA in checking anti-cancer immune responses. Furthermore, we highlight the potential indeterminacy of VISTA-targeted strategies in cancer immunotherapy, with in silico analyses. In fact, VISTA functions like a homeostatic regulator that actively normalizes immune responses. Thus, the regulatory role of VISTA in anti-cancer immunity remains to be fully elucidated.Entities:
Keywords: Cancer immunotherapy; Co-inhibition; Co-stimulation; Immune checkpoint; VISTA
Mesh:
Substances:
Year: 2020 PMID: 32600443 PMCID: PMC7325042 DOI: 10.1186/s13045-020-00917-y
Source DB: PubMed Journal: J Hematol Oncol ISSN: 1756-8722 Impact factor: 17.388
Fig. 1VISTA structure and its downstream signaling
Fig. 2Inhibitory immune checkpoint roles of VISTA in anti-cancer immunity. Positive expression of VISTA on tumor cells and/or immune cells induces an immunosuppressive environment in multiple cancer types
Inhibitory immune checkpoint roles of VISTA
| Cancer type | Research object | VISTA expression | Reference |
|---|---|---|---|
| Melanoma | Samples from patients with untreated metastatic melanoma | CD68+ macrophages | Blando et al. [ |
| B16-BL6 melanoma cells | Tumor-associated myeloid cells | Xu et al. [ | |
| Patient samples, melanoma cell lines | Melanoma cells | Rosenbaum et al. [ | |
| B16 OVA melanoma models | CD8+ T cells | Kondo et al. [ | |
| VISTA-KO mice, PD-1 KO mice, VISTA/PD-1 double KO mice | T cells | Liu et al. [ | |
| Patient samples with acquired anti-PD-1 resistance | Lymphocytes | Kakavand et al. [ | |
| Pancreatic ductal adenocarcinoma | Patient samples | CD68+ macrophages | Blando et al. [ |
| Patient samples | Activated T cells | Xie et al. [ | |
| Pancreatic tissue including pancreatic adenocarcinomas | Normal ductal epithelium within the pancreas | Byers et al. [ | |
| Prostate cancer | Samples from patients with or without ipilimumab treatment | Independent subsets of macrophages | Gao et al. [ |
| Renal cell carcinoma | Patient samples | Activated T cells | Ni et al. [ |
| Patient samples | Tumor tissues, CD14+HLA-DR+ macrophages | Hong et al. [ | |
| Non-small cell lung cancer | NSCLC FFPE tumor samples | NSCLC tumor and stromal cells | Villarroel-Espindola et al. [ |
| NSCLC FFPE tumor samples | NSCLC tumor and stromal cells | Hernandez-Martinez et al. [ | |
| Resected tissues and bronchoalveolar lavage samples | Lymphocytes | Brcic et al. [ | |
| Acute myeloid leukemia | Human AML donors, AML mouse model, VISTA-KO mice | Myeloid subsets and T cells | Kim et al. [ |
| Peripheral blood from AML patients | Myeloid-derived suppressor cells | Wang et al. [ | |
| Colorectal cancer | VISTA-KO mice, CT26 colon carcinoma cell line | Tumor-infiltrating leukocytes | Xie et al. [ |
| Ovarian cancer | Patient samples, ID8 mouse ovarian cancer cell line, mice | Tumor cells | Mulati et al. [ |
| Endometrial cancer | Patient samples, OV2944-HM-1 mouse ovarian cancer cell line, mice | Tumor cells, CD8+ T cells | Mulati et al. [ |
| Fibrosarcoma | MCA105 fibrosarcoma cell lines, mice | Hematopoietic cell types | Wang et al. [ |
| Glioma | Murine glioma model, VISTA-KO mice | CD4+ T cells | Flies et al. [ |
AML acute myeloid leukemia, FFPE formalin-fixed paraffin-embedded, KO knockout, NSCLC non-small cell lung cancer
Stimulatory immune checkpoint-like effects of VISTA
| Cancer type | Research object | VISTA expression | Reference |
|---|---|---|---|
| Ovarian cancer | Samples from patients with stage I–IV ovarian cancer | Tumor cells, immune cells, endothelial cells | Zong et al. [ |
| Esophageal adenocarcinoma | Patient samples | Tumor cells; CD68+ TILs, CD4+ TILs | Loeser et al. [ |
| Gastric cancer | Samples from patients with gastric cancer and corresponding liver metastases | Tumor cells, immune cells, endothelial cells | Boger et al. [ |
| Hepatocellular carcinoma | Patient samples | Tumor cells, immune cells | Zhang et al. [ |
TIL tumor-infiltrating lymphocyte
Drug candidates targeting VISTA in clinical trials
| Intervention | Condition(s) | Phase | Identifiers | Status | Location |
|---|---|---|---|---|---|
| JNJ-61610588 (CI-8993) | Advanced cancers | I | NCT02671955 | Terminated | USA |
| CA-170 | Advanced solid tumors or lymphomas | I | NCT02812875 | Active, not recruiting | USA |
Fig. 3Expression profile analyses of VISTA across multiple cancers and normal tissues. Expression pattern of VISTA in ACC, BLCA, BRCA, CESC, CHOL, COAD, DLBC, ESCA, GBM, HNSC, KICH, KIRC, KIRP, LAML, LGG, LIHC, LUAD, LUSC, OV, PAAD, PCPG, PRAD, READ, SARC, SKCM, STAD, TGCT, THCA, THYM, UCEC, and UCS. GEPIA was used to generate dot plots profiling VISTA expression patterns across multiple cancer types (TCGA tumor) and paired normal tissue samples (TCGA normal + GTEx normal). Each dot represents the individual expression of a distinct tumor or normal sample. ANOVA method was used for differential gene expression analysis, and genes with higher |log2FC| values (> 1) and lower q values (< 0.01) were considered differentially expressed genes
Fig. 4Correlation analyses between VISTA and immune regulation across multiple cancers. (a) Correlations between VISTA expression and the immune-related signatures of multiple tumor-infiltrating lymphocytes (TILs) across human cancers. (b) Correlations between VISTA expression and immunoinhibitors. (c) Correlations between VISTA expression and immunostimulators. (d) Correlations between VISTA expression and major histocompatibility complexes (MHCs). (e) Correlations between VISTA expression and chemokines. (f) Correlations between VISTA expression and chemokine receptors. TISIDB was used to generate correlations between expression of VISTA and abundance of TILs or immunomodulators across multiple cancers (TCGA tumor). For each cancer type, the relative abundances of TILs or immunomodulators were inferred by using gene set variation analysis based on gene expression profile. Each correlation between VISTA and a distinct TIL or immunomodulator in an individual cancer type was integrated into the indicated heatmap. Spearman method was used to analyze the pair-wise gene expression correlations, and p value < 0.05 was considered statistically significant
Fig. 5Association analyses between VISTA and clinical features across multiple cancers. (a) Associations between VISTA expression and overall survival across human cancers. (b) Associations between VISTA expression and stage across human cancers. (c) Associations between VISTA expression and grade across human cancers. (d) Associations between VISTA expression and molecular subtypes across human cancers. (e) Associations between VISTA expression and immune subtypes across human cancers. TISIDB was used to generate associations between expression of VISTA and prognostic impact or pathological distribution across multiple cancers (TCGA tumor). Log rank test and spearman test, as well as Kruskal-Wallis test, were individually used to calculate the associations, and p value < 0.05 was considered statistically significant