WDR5 promotes the tumorigenesis of oral squamous cell carcinoma via CARM1/β-catenin axis

The Wdr5-H3K4me3 Epigenetic Axis Regulates Pancreatic Tumor Immunogenicity and Immune Suppression

The WDR5/MLL1-H3K4me3 epigenetic axis is often activated in both tumor cells and tumor-infiltrating immune cells to drive various cellular responses in the tumor microenvironment and has been extensively studied in hematopoietic cancer, but its respective functions in tumor cells and immune cells in the context of tumor growth regulation of solid tumor is still incompletely understood. We report here that WDR5 exhibits a higher expression level in human pancreatic tumor tissues compared with adjacent normal pancreas. Moreover, WDR5 expression is negatively correlated with patients' response to chemotherapy or immunotherapy in human colon cancer and melanoma. However, WDR5 expression is positively correlated with the HLA level in human cancer cells, and H3K4me3 enrichment is observed at the promoter region of the HLA-A, HLA-B, and HLA-C genes in pancreatic cancer cells. Using mouse tumor cell lines and in vivo tumor models, we determined that WDR5 deficiency or inhibition significantly represses MHC I expression in vitro and in vivo in pancreatic tumor cells. Mechanistically, we determine that WDR5 deficiency inhibits H3K4me3 deposition at the MHC I (H2K) promoter region to repress MHC I (H2K) transcription. On the other hand, WDR5 depletion leads to the effective downregulation of immune checkpoints and immunosuppressive cytokines, including TGFβ and IL6, in the pancreatic tumor microenvironments. Our data determine that WDR5 not only regulates tumor cell immunogenicity to suppress tumor growth but also activates immune suppressive pathways to promote tumor immune evasion. Selective activation of the WDR5-MHC I pathway and/or selective inhibition of the WDR5-immune checkpoint and WDR5-cytokine pathways should be considered in WDR5-based epigenetic cancer immunotherapy.

Unraveling the complexity of histone-arginine methyltransferase CARM1 in cancer: From underlying mechanisms to targeted therapeutics

Coactivator-associated arginine methyltransferase 1 (CARM1), a type I protein arginine methyltransferase (PRMT), has been widely reported to catalyze arginine methylation of histone and non-histone substrates, which is closely associated with the occurrence and progression of cancer. Recently, accumulating studies have demonstrated the oncogenic role of CARM1 in many types of human cancers. More importantly, CARM1 has been emerging as an attractive therapeutic target for discovery of new candidate anti-tumor drugs. Therefore, in this review, we summarize the molecular structure of CARM1 and its key regulatory pathways, as well as further discuss the rapid progress in better understanding of the oncogenic functions of CARM1. Moreover, we further demonstrate several representative targeted CARM1 inhibitors, especially focusing on demonstrating their designing strategies and potential therapeutic applications. Together, these inspiring findings would shed new light on elucidating the underlying mechanisms of CARM1 and provide a clue on discovery of more potent and selective CARM1 inhibitors for the future targeted cancer therapy.

Nine-gene signature and nomogram for predicting survival in patients with head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinomas (HNSCCs) are derived from the mucosal linings of the upper aerodigestive tract, salivary glands, thyroid, oropharynx, larynx, and hypopharynx. The present study aimed to identify the novel genes and pathways underlying HNSCC. Despite the advances in HNSCC research, diagnosis, and treatment, its incidence continues to rise, and the mortality of advanced HNSCC is expected to increase by 50%. Therefore, there is an urgent need for effective biomarkers to predict HNSCC patients’ prognosis and provide guidance to the personalized treatment.

Methods: Both HNSCC clinical and gene expression data were abstracted from The Cancer Genome Atlas (TCGA) database. Intersecting analysis was adopted between the gene expression matrix of HNSCC patients from TCGA database to extract TME-related genes. Differential gene expression analysis between HNSCC tissue samples and normal tissue samples was performed by R software. Then, HNSCC patients were categorized into clusters 1 and 2 via NMF. Next, TME-related prognosis genes (p < 0.05) were analyzed by univariate Cox regression analysis, LASSO Cox regression analysis, and multivariate Cox regression analysis. Finally, nine genes were selected to construct a prognostic risk model and a prognostic gene signature. We also established a nomogram using relevant clinical parameters and a risk score. The Kaplan–Meier curve, survival analysis, time-dependent receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and the concordance index (C-index) were carried out to assess the accuracy of the prognostic risk model and nomogram. Potential molecular mechanisms were revealed by gene set enrichment analysis (GSEA). Additionally, gene correlation analysis and immune cell correlation analysis were conducted for further enriching our results.

Results: A novel HNSCC prognostic model was established based on the nine genes (GTSE1, LRRN4CL, CRYAB, SHOX2, ASNS, KRT23, ANGPT2, HOXA9, and CARD11). The value of area under the ROC curves (AUCs) (0.769, 0.841, and 0.816) in TCGA whole set showed that the model effectively predicted the 1-, 3-, and 5-year overall survival (OS). Results of the Cox regression assessment confirmed the nine-gene signature as a reliable independent prognostic factor in HNSCC patients. The prognostic nomogram developed using multivariate Cox regression analysis showed a superior C-index over other clinical signatures. Also, the calibration curve had a high level of concordance between estimated OS and the observed OS. This showed that its clinical net can precisely estimate the one-, three-, and five-year OS in HNSCC patients. The gene set enrichment analysis (GSEA) to some extent revealed the immune- and tumor-linked cascades.

Conclusion: In conclusion, the TME-related nine-gene signature and nomogram can effectively improve the estimation of prognosis in patients with HNSCC.