Immunotherapy for cancer is a rapidly developing treatment that modifies the immune system and enhances the antitumor immune response. B7-H3 (CD276), a member of the B7 family that plays an immunoregulatory role in the T cell response, has been highlighted as a novel potential target for cancer immunotherapy. B7-H3 has been shown to play an inhibitory role in T cell activation and proliferation, participate in tumor immune evasion and influence both the immune response and tumor behavior through different signaling pathways. B7-H3 expression has been found to be aberrantly upregulated in many different cancer types, and an association between B7-H3 expression and poor prognosis has been established. Immunotherapy targeting B7-H3 through different approaches has been developing rapidly, and many ongoing clinical trials are exploring the safety and efficacy profiles of these therapies in cancer. In this review, we summarize the emerging research on the function and underlying pathways of B7-H3, the expression and roles of B7-H3 in different cancer types, and the advances in B7-H3-targeted therapy. Considering different tumor microenvironment characteristics and results from preclinical models to clinical practice, the research indicates that B7-H3 is a promising target for future immunotherapy, which might eventually contribute to an improvement in cancer immunotherapy that will benefit patients.

Gliomas are infiltrative neoplasms with a highly invasive nature. Due to its distinct genomic, genetic and epigenetic features, the immune prognostic signature (IPS) and immune microenvironment of glioblastoma (GBM) merit further research. We aimed to explore prognosis-related immune genes and develop an IPS model for predicting prognosis in GBM. RNA-sequencing data, as well as clinical information, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) public cohorts were analyzed. To develop the IPS, least absolute shrinkage and selection operator (LASSO) Cox analysis was performed for immune-related genes that were differentially expressed between GBM and normal tissues. Then, interaction effects of the IPS on the immune microenvironment were systematically analyzed; the precise prognostic model was developed based on the IPS and clinical data and was then further validated. A total of 21 immune prognostic genes were identified based on GBM microenvironment status. An 8-gene IPS was established, and the GBM patients were effectively stratified into low-and high-risk groups in the TCGA cohort as a training set. Univariate and multivariate Cox analyses revealed that IPS was an independent prognostic factor, and the prognostic performance of individual IPS genes was systematically illustrated. In addition, a comprehensive and novel nomogram model was initially established to estimate overall survival in TCGA-GBM patients, and high-risk patients had higher levels of dendritic cell and neutrophil infiltration. Furthermore, the nomogram model was developed and validated in the CGGA validation set. The low-risk IPS was linked to a stronger response to anti-PD-L1 immunotherapy and clinical advantages in the IMvigor210 cohort. This novel IPS with promising biomarkers classifies GBM patients into subgroups with distinct clinical outcomes and immunophenotypes. Our findings and this resource may help to characterize the immune microenvironment, inform cancer immunotherapy and facilitate the development of precision immuno-oncology.

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