The cancer testis antigen TDRD1 regulates prostate cancer proliferation by associating with the snRNP biogenesis machinery

Deficiency of betaine-homocysteine methyltransferase activates glucose-6-phosphate dehydrogenase (G6PD) by decreasing arginine methylation of G6PD in hepatocellular carcinogenesis

Betaine-homocysteine methyltransferase (BHMT) regulates protein methylation and is correlated with tumorigenesis; however, the effects and regulation of BHMT in hepatocarcinogenesis remain largely unexplored. Here, we determined the clinical significance of BHMT in the occurrence and progression of hepatocellular carcinoma (HCC) using tissue samples from 198 patients. BHMT was to be frequently found (86.6%) expressed at relatively low levels in HCC tissues and was positively correlated with the overall survival of patients with HCC. Bhmt overexpression effectively suppressed several malignant phenotypes in hepatoma cells in vitro and in vivo, whereas complete knockout of Bhmt (Bhmt-/-) produced the opposite effect. We combined proteomics, metabolomics, and molecular biological strategies and detected that Bhmt-/- promoted hepatocarcinogenesis and tumor progression by enhancing the activity of glucose-6-phosphate dehydrogenase (G6PD) and PPP metabolism in DEN-induced HCC mouse and subcutaneous tumor-bearing models. In contrast, restoration of Bhmt with an AAV8-Bhmt injection or pharmacological inhibition of G6PD attenuated hepatocarcinogenesis. Additionally, coimmunoprecipitation identified monomethylated modifications of the G6PD, and BHMT regulated the methylation of G6PD. Protein sequence analysis, generation and application of specific antibodies, and site-directed mutagenesis indicated G6PD methylation at the arginine residue 246. Furthermore, we established bidirectionally regulated BHMT cellular models combined with methylation-deficient G6PD mutants to demonstrate that BHMT potentiated arginine methylation of G6PD, thereby inhibiting G6PD activity, which in turn suppressed hepatocarcinogenesis. Taken together, this study reveals a new methylation-regulatory mechanism in hepatocarcinogenesis owing to BHMT deficiency, suggesting a potential therapeutic strategy for HCC treatment.

SART3 reads methylarginine-marked glycine- and arginine-rich motifs

Glycine- and arginine-rich (GAR) motifs, commonly found in RNA-binding and -processing proteins, can be symmetrically (SDMA) or asymmetrically (ADMA) dimethylated at the arginine residue by protein arginine methyltransferases. Arginine-methylated protein motifs are usually read by Tudor domain-containing proteins. Here, using a GFP-Trap, we identify a non-Tudor domain protein, squamous cell carcinoma antigen recognized by T cells 3 (SART3), as a reader for SDMA-marked GAR motifs. Structural analysis and mutagenesis of SART3 show that aromatic residues lining a groove between two adjacent aromatic-rich half-a-tetratricopeptide (HAT) repeat domains are essential for SART3 to recognize and bind to SDMA-marked GAR motif peptides, as well as for the interaction between SART3 and the GAR-motif-containing proteins fibrillarin and coilin. Further, we show that the loss of this reader ability affects RNA splicing. Overall, our findings broaden the range of potential SDMA readers to include HAT domains.

A new high-throughput screening methodology for the discovery of cancer-testis antigen using multi-omics data

BACKGROUND

Cancer/testis antigens (CTAs), also known as tumor-specific antigens (TSAs) are specifically expressed in cancer cells and exhibit high immunogenicity, making them promising targets for immunotherapy and cancer vaccines.

METHODS

A new integrated high-throughput screening methodology for CTAs was proposed in this study through combining DNA methylation and RNA sequencing data. Briefly, the genes with increased transcript level and decreased DNA methylation were identified by multi-omics analysis. RNA sequencing studies in cell lines exposed to DNA methyltransferase (DNMT) inhibitors were performed to validate the inherent causal relationship between DNA hypomethylation and gene expression upregulation.

RESULTS

We proposed a new integrated high-throughput screening methodology for identification of CTAs using multi-omics analysis. In addition, we tested the feasibility of this method using gastric cancer (GC) as an example. In GC, we identified over 2000 primary candidate CTAs and ultimately identified 20 CTAs with significant tissue-specificity, including a testis-specific serine protease TESSP1/PRSS41. Integrated analysis confirmed that PRSS41 expression was reactivated in gastrointestinal cancers by promoter DNA hypomethylation at the CpG site (cg08104780). Additionally, DNA hypomethylation of PRSS41 predicted a poor prognosis in GC.

CONCLUSION

We propose a new high-throughput screening method for the identification of CTAs in cancer and validate its effectiveness. Our work emphasizes that serine protease PRSS41 is a novel TSA that is reactivated in GC due to promoter DNA hypomethylation.

Identification of Prognostic and Immune Characteristics of Two Lung Adenocarcinoma Subtypes Based on TRPV Channel Family Genes

Lung adenocarcinoma (LUAD) is one of the deadliest malignant tumors worldwide. Transient receptor potential vanilloid (TRPV) channels take pivotal parts in many cancers, but their impact on LUAD remains unexplored. In this study, LUAD samples were classified into two subtypes according to the expression characteristics of TRPV1-6 genes, with LUAD subtype cluster2 exhibiting significantly higher survival rates than cluster1. Subsequently, analysis of differentially expressed genes (DEGs) was performed between cluster1 and cluster2, revealing enrichment of DEGs in channel activity and Ca2+ signaling pathways. We established a protein-protein interaction network based on DEGs and constructed a LUAD prognostic model by using Cox regression analysis based on genes corresponding to 170 protein nodes. The prognostic model demonstrated good predictive ability for patient prognosis, with higher survival rates observed in the low-risk (LR) group. The risk score was validated as an independent prognostic indicator, according to Cox regression analysis. A clinically applicable nomogram was plotted. Immunological analysis indicated that the LR and high-risk (HR) groups had varied proportions of immune cell infiltration. The immunotherapy prediction indicated that LUAD patients in LR group had a greater likelihood to benefit from immune checkpoint blockade therapy. Furthermore, we hypothesized that the expression patterns of feature genes in the LUAD model were related to the sensitivity to lung cancer therapeutic drugs TAS-6417 and Erlotinib. To sum up, our LUAD prognostic model possessed clinical applicability for prognosis and immunotherapy response prediction.