As a nontraditional T-cell subgroup, γδT cells have gained popularity in the field of immunotherapy in recent years. They have extraordinary antitumor potential and prospects for clinical application. Immune checkpoint inhibitors (ICIs), which are efficacious in tumor patients, have become pioneer drugs in the field of tumor immunotherapy since they were incorporated into clinical practice. In addition, γδT cells that have infiltrated into tumor tissues are found to be in a state of exhaustion or anergy, and there is upregulation of many immune checkpoints (ICs) on their surface, suggesting that γδT cells have a similar ability to respond to ICIs as traditional effector T cells. Studies have shown that targeting ICs can reverse the dysfunctional state of γδT cells in the tumor microenvironment (TME) and exert antitumor effects by improving γδT-cell proliferation and activation and enhancing cytotoxicity. Clarification of the functional state of γδT cells in the TME and the mechanisms underlying their interaction with ICs will solidify ICIs combined with γδT cells as a good treatment option.

Immune checkpoint inhibitors (ICIs) have changed the treatment paradigm of metastatic urothelial carcinoma (mUC), a dominant type of bladder cancer (BC). Previous studies have shown an association between gene mutations in the DNA damage response (DDR) pathway and the immunotherapy response in mUC but have neglected the effect of the activation level of the DDR pathway on the ICI response in mUC. A published immunotherapy cohort with genome, transcriptome and survival data for 348 mUC patients was used. An external cohort (The Cancer Genome Atlas Bladder Cancer) and the GSE78220 cohort were used for validation. The activation level of the DDR pathway was quantified using single-sample gene set enrichment analysis (ssGSEA). Further analysis on the genome, immunogenicity, and the immune microenvironment was conducted using the DDR ssGSEA enrichment score-high (DSSH) group and the DDR ssGSEA enrichment score-low (DSSL) group. In the mUC cohorts, the DSSH group was associated with longer overall survival times (P=0.026; Hazard ratio=0.67; 95%CI: 0.46−0.95). The DSSH group was also associated with higher tumor mutation burden, neoantigen load, immune-activated cell patterns, and immune-related gene expression levels. The GSEA results indicated an immune activation state in DSSH group, which correlated with a down-regulation in the transforming growth factor β receptor signaling pathway. Our study suggests that the activation level of the DDR pathway may be a novel predictive marker for immunotherapy efficacy in patients with mUC.

Immune checkpoint inhibitors (ICIs) combined with the anti‐angiogenesis drug bevacizumab is one of the future directions of immunotherapy. However, the potential adverse drug reactions (ADRs) caused by combination therapy remain unclear. Current research on ADRs of combination therapy in cancer patients is extremely limited. Our study aims to help determine the safety of combination therapy. We downloaded the ADR reports on combination therapy, from the first quarter of 2012 to the fourth quarter of 2021, from the FDA adverse event reporting system (FAERS) database and conducted a large‐scale retrospective study. The ADR signals were monitored by reporting odds ratio (ROR) and analyzing the risk of different ADRs in patients with Pan‐cancer. A total of 2094 cases were selected, after excluding duplicate data and the use of chemotherapy drugs. We evaluated the risk of ADR in Pan‐cancer patients. Combination therapy was an independent risk factor for adverse drug reactions associated with interstitial lung disease (OR: 8.62; 95% CI: 6.14‐12.10, P < .0001), hypertension (OR: 1.35; 95% CI: 1.11‐1.65, P < .01) and gastrointestinal bleeding (OR: 3.16; 95% CI: 2.21‐4.51, P < .0001). A subgroup analysis revealed that the risk of endocrine system‐related ADRs was elevated in patients receiving different combination therapies or with certain tumor types. We retrospectively studied the ADR of combination therapy in Pan‐cancer patients and analyzed the distribution characteristics of ADR from the perspectives of treatment strategy and cancer types to provide recommendations for the individualized management of patients receiving combination therapy.

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Multi-omics data plays an important role in cancer research, helping clinicians to better explore drug targets and biomarkers. At present, there exist several databases including TCGA (the Cancer Genome Atlas) and GDSC (Genomics of Drug Sensitivity in Cancer), which contain multi-omics data on multiple cancer species, as well as various web tools for analyzing the multi-omics data, which are widely used in oncology research. Tumor heterogeneity is a widespread phenomenon, reflected by differences in multi-omics data of cancers originating from different tissues and organs. However, there is a lack of convenient analysis and visualization tools to explore tumor heterogeneity. As a result, we developed a web tool called Multi-Omics Anatomy Heatmap in Tumors (MOAHIT) based on shiny programming. This tool enables users to analyze and visualize the heterogeneity of human tissues. In addition, MOAHIT enables users to produce a beautiful human anatomy heatmap to visualize the heterogeneity between distinct cancers in the multi-omics data.

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