Mutations in lysine methyltransferase 2C and PEG3 are associated with tumor mutation burden, prognosis, and antitumor immunity in pancreatic adenocarcinoma patients

Insights into the mechanisms driven by H3K4 KMTs in pancreatic cancer

Pancreatic cancer is a malignancy arising from the endocrine or exocrine compartment of this organ. Tumors from exocrine origin comprise over 90% of all pancreatic cancers diagnosed. Of these, pancreatic ductal adenocarcinoma (PDAC) is the most common histological subtype. The five-year survival rate for PDAC ranged between 5 and 9% for over four decades, and only recently saw a modest increase to ∼12-13%, making this a severe and lethal disease. Like other cancers, PDAC initiation stems from genetic changes. However, therapeutic targeting of PDAC genetic drivers has remained relatively unsuccessful, thus the focus in recent years has expanded to the non-genetic factors underlying the disease pathogenesis. Specifically, it has been proposed that dynamic changes in the epigenetic landscape promote tumor growth and metastasis. Emphasis has been given to the re-organization of enhancers, essential regulatory elements controlling oncogenic gene expression, commonly marked my histone 3 lysine 4 monomethylation (H3K4me1). H3K4me1 is typically deposited by histone lysine methyltransferases (KMTs). While well characterized as oncogenes in other cancer types, recent work has expanded the role of KMTs as tumor suppressor in pancreatic cancer. Here, we review the role and translational significance for PDAC development and therapeutics of KMTs.

The modification role and tumor association with a methyltransferase: KMT2C

Histone methylation can affect chromosome structure and binding to other proteins, depending on the type of amino acid being modified and the number of methyl groups added, this modification may promote transcription of genes (H3K4me2, H3K4me3, and H3K79me3) or reduce transcription of genes (H3K9me2, H3K9me3, H3K27me2, H3K27me3, and H4K20me3). In addition, advances in tumor immunotherapy have shown that histone methylation as a type of protein post-translational modification is also involved in the proliferation, activation and metabolic reprogramming of immune cells in the tumor microenvironment. These post-translational modifications of proteins play a crucial role in regulating immune escape from tumors and immunotherapy. Lysine methyltransferases are important components of the post-translational histone methylation modification pathway. Lysine methyltransferase 2C (KMT2C), also known as MLL3, is a member of the lysine methyltransferase family, which mediates the methylation modification of histone 3 lysine 4 (H3K4), participates in the methylation of many histone proteins, and regulates a number of signaling pathways such as EMT, p53, Myc, DNA damage repair and other pathways. Studies of KMT2C have found that it is aberrantly expressed in many diseases, mainly tumors and hematological disorders. It can also inhibit the onset and progression of these diseases. Therefore, KMT2C may serve as a promising target for tumor immunotherapy for certain diseases. Here, we provide an overview of the structure of KMT2C, disease mechanisms, and diseases associated with KMT2C, and discuss related challenges.

The Relationship Between Gene Mutations and the Clinicopathological Features and Prognosis of Gastric Cancer

Current treatments for gastric cancer (GC) are suboptimal. Potential therapeutic targets for GC were screened using next-generation sequencing. We examined many mutation genes linked to GC, including TP53 (60%), PIK3CA (19%), LRP1B (13%), and ERBB2 (12%), ARID1A (9%), KMT2C (9%), and KRAS (7%). The KMT2C, KRAS, CDK6, and ARID1A wild-type genes were dominant in diffuse-type GC (P < .05), but mutations did not influence prognosis. Patients with APC (6%) and CDH1 (8%) wild-type GC presented with vascular invasion (P < .05). Patients with ATR (2%) wild-type GC were prone to lymph node metastasis (P < .05). Patients with ARID1A (9%) wild-type GC had reduced programmed death ligand 1 expression (<1, P < .05). We found that patients who received chemotherapy had a better prognosis than those who did not (although there was no statistical difference), with platinum-based group having better prognosis and uracil combined with paclitaxel group having worse prognosis.

A novel model incorporating chromatin regulatory factors for risk stratification, prognosis prediction, and characterization of the microenvironment in Wilms tumor

BACKGROUND

Wilms tumor, also known as nephroblastoma, a pediatric most-frequent malignant-kidney tumor, may be regulated and influenced by transcriptional and epigenetic mechanisms. Chromatin regulatory factors (CRs) play key roles in epigenetic regulation. The present study aimed to explore the involvement of CRs in the development of nephroblastoma.

METHODS

RNA-sequencing and clinical information of nephroblastoma samples were obtained by downloading data from the TARGET database. The Limma package was utilized to perform differential expression analysis of genes (DEGs) between the tumor group and the control group. A Venn map was used for intersection of differential genes and CRs and to perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of DEGs using the clusterProfiler package. LASSO and Cox analyses were used to construct CR-related risk models and were evaluated based on clinical parameters. A receiver operating characteristic curve was employed to assess the diagnostic performance of risk model. Furthermore, we used a single-sample gene set enrichment analysis algorithm for immune cell infiltration analysis. Finally, to confirm the transcriptome expression of pivotal genes in human nephroblastoma cell lines, a quantitative real-time PCR was employed.

RESULTS

Fifteen key CRs were obtained through analysis in nephroblastoma and then the risk model based on 13 important CRs was constructed using the transcriptome data of nephroblastoma. Using the risk model, pediatric nephroblastoma patients were stratified into high- and low-risk groups based on their individual risk scores. The risk score of CRs can predict adverse outcomes in pediatric nephroblastoma, and this gene cluster is closely related to various immunity characteristics of nephroblastoma. Moreover, the nephroblastoma cell line exhibited higher expression levels of prognostic genes (VRK1, ARNTL, RIT1, PRDM6, and TSPY1) compared to the HEK293 T cell line.

CONCLUSIONS

The risk characteristics derived from CRs have tremendous significance in predicting prognosis and guiding clinical classification and intervention strategies for pediatric nephroblastoma.

Comprehensive characterization of adipogenesis-related genes in colorectal cancer for clinical significance and immunogenomic landscape analyses

OBJECTIVE

Colorectal cancer (CRC) is a major global health concern, necessitating the identification of biomarkers and molecular subtypes for improved clinical management. This study aims to evaluate the clinical value of adipogenesis-related genes and molecular subtypes in CRC.

METHODS

A comprehensive analysis of adipogenesis-related genes in CRC was performed using publicly available datasets (TCGA and GEO database) and bioinformatics tools. Unsupervised cluster analysis was employed to identify the molecular subtypes of CRC, while LASSO regression analysis was utilized to develop a risk prognostic model. The immunogenomic patterns and immunotherapy analysis were used to predict patient response to immunotherapy. Furthermore, qPCR analysis was conducted to confirm the expression of the identified key genes in vitro.

RESULTS

Through the analysis of RNAseq data from normal and tumor tissues, we identified 50 differentially expressed genes. Unsupervised cluster analysis identified two subtypes (Cluster A and Cluster B) with significantly different survival outcomes. Cluster A and B displayed differential immune cell compositions and enrichment in specific biological pathways, providing insights into potential therapeutic targets. A risk-scoring model was developed using five ARGs, which successfully classified patients into high and low-risk groups, showing distinct survival outcomes. The model was validated and showed robust predictive performance. High-risk patients exhibited altered immune cell proportions and gene expression patterns compared to low-risk patients. In qPCR validation, four out of the five key genes were consistent with the results of bioinformatics analysis.

CONCLUSION

Overall, the findings of our investigation offer valuable understanding regarding the clinical relevance of ARGs and molecular subtypes in CRC, laying the groundwork for improved precision medicine applications and personalized treatment modalities.