HHLA2 is a novel prognostic predictor and potential therapeutic target in malignant glioma

Abstract

Glioma is the most common and aggressive tumor type of the central nervous system and is associated with poor prognosis. To date, novel emerging immunotherapies have significantly improved outcomes for patients with various cancer types. Human endogenous retrovirus-H long terminal repeat-associating protein 2 (HHLA2), a newly discovered immune checkpoint molecule, has demonstrated its potential as a novel therapeutic target. Therefore, the present study aimed to investigate the clinical prognostic value of HHLA2 in gliomas and its mechanistic role. A systematic review of datasets from The Cancer Genome Atlas was performed. The RNA-seq data of a total of 669 cases were analyzed and the biological function of HHLA2 was predicted by Gene Ontology (GO) and pathway enrichment analysis. Immunohistochemistry labelling images for HHLA2 was obtained from the Human Protein Atlas. xCell was used to comprehensively analyze the model of tumor-infiltrating immune cell in glioma. The Cox proportional hazards regression model was used to predict outcomes for glioma patients. The results revealed that the expression levels of HHLA2 were significantly lower in high-grade glioma, as well as glioma with wild-type isocitrate dehydrogenase, no deletion of 1p/19q and telomerase reverse transcriptase promoter mutation. Receiver operating characteristic analysis revealed that HHLA2 was a predictor of the neural subtype. The tumor-infiltrating immune cell model indicated that HHLA2 was negatively associated with tumor-associated macrophages. GO analysis and pathway enrichment analysis revealed that HHLA2-associated genes were functionally involved in inhibition of neoplasia-associated processes. HHLA2 was significantly negatively correlated with certain genes, including interleukin-10, transforming growth factor-β, vascular endothelial growth factor and δ-like canonical Notch ligand 4, and other immune checkpoint molecules, including programmed cell death 1, lymphocyte activating 3 and CD276. Survival analysis indicated that high expression of HHLA2 predicted a favorable prognosis. In conclusion, the present study revealed that upregulation of HHLA2 is significantly associated with a favorable outcome for patients with glioma. Targeting HHLA2 as an immune stimulator may become a valuable approach for the treatment of glioma in clinical practice.

Immune Checkpoint Targeted Therapy in Glioma: Status and Hopes

“…For instance, recent research points out that B7-H3 positively relates to the Toll-like receptor signaling pathway and the poor survival of glioma patients, while it has also been reported to co-stimulate immunological function and be involved in anti-tumor functions (92)(93)(94)(95). Similarly, B7-H7 shows the same phenomenon in various solid tumors (96,97). Inhibiting NKmediated recognition of B7-H6 is an important mechanism of the tumor immune escape.…”

Prognostic value of HHLA2 expression in solid tumors

“…[ 3 , 4 ] Among various immunotherapy strategies, immune checkpoint blockade seems to be an effective approach. [ 5 ] Immune checkpoint proteins are surface molecules on certain immune cell populations that activate or inhibit immune function when engaged to their ligands. [ 5 ] Several checkpoint inhibitors have been extensively studied for cancer treatment, and some have been used in clinical trials in cancer patients, such as antibodies against cytotoxic T lymphocyte-associated antigen-4 (CTLA-4), programmed cell death protein 1 (PD-1), or its ligand PD-L1.…”

An Immune-associated lncRNA Signature Predicts the Survival of Patients With Head and Neck Squamous Cell Carcinoma

“…Increased tumor infiltrating lymphocyte (TLS) levels like CD4+, as well as CD8+ T-cells are linked to better laryngeal cancer prognosis and TILs along with PD-L1 expression may predict response to immune checkpoint inhibitors [44]. We employed seven common approaches to estimate immune invading cells, including XCELL [45,46], TIME [47], QUANTISEQ [48], MCPCOUNTER [48], EPIC [49], CIBERSORT [50] and CIBERSORT-ABS [51] and to examine the relationship of the risk score with the tumor invading immune cells. Our findings illustrated that tumor-invading immune cells like cancer associated fibroblasts and M0 macrophages are positively and negatively correlated with CD8 T-cells, myeloid dendritic cells, M1 macrophages, and plasmacytoid dendritic cells.…”