Identification of potential CpG sites for oral squamous cell carcinoma diagnosis via integrated analysis of DNA methylation and gene expression

2α, 3α, 24-Thrihydroxyurs-12-en-24-ursolic acid enhances the cytotoxic effect of cisplatin on oral cancer cells by down-regulating autophagy

This study aimed to investigate the effect and mechanism of 2α, 3α, 24-thrihydroxyurs-12-en-24-ursolic acid (TEOA) alone or in combination with cisplatin on oral cancer. TEOA, a pentacyclic triterpenoid compound isolated from the roots of Actinidia eriantha, has demonstrated antitumor activity in preclinical experiments. However, its role in oral cancer remains poorly understood. Our findings revealed that a low concentration of TEOA did not exhibit significant cytotoxicity against oral squamous cell carcinoma cells. However, when combined with cisplatin, TEOA showed a significant therapeutic effect. The combined treatments resulted in a significant inhibition of proliferation and migration and a significant increase in apoptosis of squamous cell carcinoma cells. Cisplatin exposure increased autophagy levels, which may contribute to chemoresistance. Of note, the presence of TEOA significantly inhibited cisplatin-induced autophagy, leading to improved chemotherapy efficacy. Our findings indicate that a mild low dosage of TEOA may enhance the cytotoxic effect of cisplatin by downregulating autophagy in oral cancer cells.

A signature of immune-related gene pairs (IRGPs) for risk stratification and prognosis of oral cancer patients

Background

With low response to present immunotherapy, it is imperative to identify new immune-related biomarkers for more effective immunotherapies for oral cancer.

Methods

RNA profiles for 390 oral cancer patients and 32 normal samples were downloaded from The Cancer Genome Atlas (TCGA) database and differentially expressed genes (DEGs) were analyzed. Immune genesets from ImmPort repository were overlapped with DEGs. After implementing univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis, key immune-related gene pairs (IRGPs) among the overlapped DEGs for predicting the survival risk were obtained. Then, the cutoff of risk score was calculated by the receiver operating characteristic (ROC) curve to stratify oral cancer patients into high and low-risk groups. Multivariate Cox analysis was used to analyze independent prognostic indicators for oral cancer. Besides, infiltration of immune cells, functional annotation, and mutation analysis of IRGPs were conducted. Biological functions correlated with IRGPs were enriched by Gene Set Enrichment Analysis (GSEA) method.

Results

We identified 698 differentially expressed genes (DEGs) in response to oral cancer. 17 IRGPs among the DEGs were identified and integrated into a risk score model. Patients in the high-risk group have a significantly worse prognosis than those in the low-risk group in both training (P<0.001) and test (P=0.019) cohorts. Meanwhile, the IRGP model was identified as an independent prognostic factor for oral cancer. Different infiltration patterns of immune cells were found between the high- and low-risk groups that more types of T and B cells were enriched in the low-risk group. More immune-related signaling pathways were highly enriched in the low-risk group and Tenascin C (TNC) was the most frequently mutated gene. We have developed a novel 17-IRGPs signature for risk stratification and prognostic prediction of oral cancer.

Conclusion

Our study provides a foundation for improved immunotherapy and prognosis and is beneficial to the individualized management of oral cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02630-1.

Genome-wide analysis of cell-Free DNA methylation profiling with MeDIP-seq identified potential biomarkers for colorectal cancer

Background

Colorectal cancer is the most common malignancy and the third leading cause of cancer-related death worldwide. This study aimed to identify potential diagnostic biomarkers for colorectal cancer by genome-wide plasma cell-free DNA (cfDNA) methylation analysis.

Methods

Peripheral blood from colorectal cancer patients and healthy controls was collected for cfDNA extraction. Genome-wide cfDNA methylation profiling, especially differential methylation profiling between colorectal cancer patients and healthy controls, was performed by methylated DNA immunoprecipitation coupled with high-throughput sequencing (MeDIP-seq). Logistic regression models were established, and the accuracy of this diagnostic model for colorectal cancer was verified using tissue-sourced data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) due to the lack of cfDNA methylation data in public datasets.

Results

Compared with the control group, 939 differentially methylated regions (DMRs) located in promoter regions were found in colorectal cancer patients; 16 of these DMRs were hypermethylated, and the remaining 923 were hypomethylated. In addition, these hypermethylated genes, mainly PRDM14, RALYL, ELMOD1, and TMEM132E, were validated and confirmed in colorectal cancer by using publicly available DNA methylation data.

Conclusions

MeDIP-seq can be used as an optimal approach for analyzing cfDNA methylomes, and 12 probes of four differentially methylated genes identified by MeDIP-seq (PRDM14, RALYL, ELMOD1, and TMEM132E) could serve as potential biomarkers for clinical application in patients with colorectal cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02487-4.

Identification of latent biomarkers in connection with progression and prognosis in oral cancer by comprehensive bioinformatics analysis

BACKGROUND

Oral cancer (OC) is a common and dangerous malignant tumor with a low survival rate. However, the micro level mechanism has not been explained in detail.

METHODS

Gene and miRNA expression micro array data were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and miRNAs (DE miRNAs) were identified by R software. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of genes and genomes (KEGG) pathway analysis were used to assess the potential molecular mechanisms of DEGs. Cytoscape software was utilized to construct protein-protein interaction (PPI) network and miRNA-gene network. Central genes were screened out with the participation of gene degree, molecular complex detection (MCODE) plugin, and miRNA-gene network. Then, the identified genes were checked by The Cancer Genome Atlas (TCGA) gene expression profile, Kaplan-Meier data, Oncomine, and the Human Protein Atlas database. Receiver operating characteristic (ROC) curve was drawn to predict the diagnostic efficiency of crucial gene level in normal and tumor tissues. Univariate and multivariate Cox regression were used to analyze the effect of dominant genes and clinical characteristics on the overall survival rate of OC patients.

RESULTS

Gene expression data of gene expression profiling chip(GSE9844, GSE30784, and GSE74530) were obtained from GEO database, including 199 tumor and 63 non-tumor samples. We identified 298 gene mutations, including 200 upregulated and 98 downregulated genes. GO functional annotation analysis showed that DEGs were enriched in extracellular structure and extracellular matrix containing collagen. In addition, KEGG pathway enrichment analysis demonstrated that the DEGs were significantly enriched in IL-17 signaling pathway and PI3K-Akt signaling pathway. Then, we detected three most relevant modules in PPI network. Central genes (CXCL8, DDX60, EIF2AK2, GBP1, IFI44, IFI44L, IFIT1, IL6, MMP9,CXCL1, CCL20, RSAD2, and RTP4) were screened out with the participation of MCODE plugin, gene degree, and miRNA-gene network. TCGA gene expression profile and Kaplan-Meier analysis showed that high expression of CXCL8, DDX60, IL6, and RTP4 was associated with poor prognosis in OC patients, while patients with high expression of IFI44L and RSAD2 had a better prognosis. The elevated expression of CXCL8, DDX60, IFI44L, RSAD2, and RTP44 in OC was verified by using Oncomine database. ROC curve showed that the mRNA levels of these five genes had a helpful diagnostic effect on tumor tissue. The Human Protein Atlas database showed that the protein expressions of DDX60, IFI44L, RSAD2, and RTP44 in tumor tissues were higher than those in normal tissues. Finally, univariate and multivariate Cox regression showed that DDX60, IFI44L, RSAD2, and RTP44 were independent prognostic indicators of OC.

CONCLUSION

This study revealed the potential biomarkers and relevant pathways of OC from publicly available GEO database, and provided a theoretical basis for elucidating the diagnosis, treatment, and prognosis of OC.

Pan-cancer analysis of m5C regulator genes reveals consistent epigenetic landscape changes in multiple cancers

BACKGROUND

5-Methylcytosine (m5C) is a reversible modification to both DNA and various cellular RNAs. However, its roles in developing human cancers are poorly understood, including the effects of mutant m5C regulators and the outcomes of modified nucleobases in RNAs.

METHODS

Based on The Cancer Genome Atlas (TCGA) database, we uncovered that mutations and copy number variations (CNVs) of m5C regulatory genes were significantly correlated across many cancer types. We then assessed the correlation between the expression of individual m5C regulators and the activity of related hallmark pathways of cancers.

RESULTS

After validating m5C regulators' expression based on their contributions to cancer development and progression, we observed their upregulation within tumor-specific processes. Notably, our research connected aberrant alterations to m5C regulatory genes with poor clinical outcomes among various tumors that may drive cancer pathogenesis and/or survival.

CONCLUSION

Our results offered strong evidence and clinical implications for the involvement of m5C regulators.