Whole Genome DNA Methylation and Gene Expression Profiling of Oropharyngeal Cancer Patients in North-Eastern India: Identification of Epigenetically Altered Gene Expression Reveals Potential Biomarkers

Universal penalized regression (Elastic-net) model with differentially methylated promoters for oral cancer prediction

BACKGROUND

DNA methylation showed notable potential to act as a diagnostic marker in many cancers. Many studies proposed DNA methylation biomarker in OSCC detection, while most of these studies are limited to specific cohorts or geographical location. However, the generalizability of DNA methylation as a diagnostic marker in oral cancer across different geographical locations is yet to be investigated.

METHODS

We used genome-wide methylation data from 384 oral cavity cancer and normal tissues from TCGA HNSCC and eastern India. The common differentially methylated CpGs in these two cohorts were used to develop an Elastic-net model that can be used for the diagnosis of OSCC. The model was validated using 812 HNSCC and normal samples from different anatomical sites of oral cavity from seven countries. Droplet Digital PCR of methyl-sensitive restriction enzyme digested DNA (ddMSRE) was used for quantification of methylation and validation of the model with 22 OSCC and 22 contralateral normal samples. Additionally, pyrosequencing was used to validate the model using 46 OSCC and 25 adjacent normal and 21 contralateral normal tissue samples.

RESULTS

With ddMSRE, our model showed 91% sensitivity, 100% specificity, and 95% accuracy in classifying OSCC from the contralateral normal tissues. Validation of the model with pyrosequencing also showed 96% sensitivity, 91% specificity, and 93% accuracy for classifying the OSCC from contralateral normal samples, while in case of adjacent normal samples we found similar sensitivity but with 20% specificity, suggesting the presence of early disease methylation signature at the adjacent normal samples. Methylation array data of HNSCC and normal tissues from different geographical locations and different anatomical sites showed comparable sensitivity, specificity, and accuracy in detecting oral cavity cancer with across. Similar results were also observed for different stages of oral cavity cancer.

CONCLUSIONS

Our model identified crucial genomic regions affected by DNA methylation in OSCC and showed similar accuracy in detecting oral cancer across different geographical locations. The high specificity of this model in classifying contralateral normal samples from the oral cancer compared to the adjacent normal samples suggested applicability of the model in early detection.

Role of DNA methylation-based mitotic ageing indices in oral cancer development and recurrence

OBJECTIVE

DNA methylation data can be used to derive mitotic indices from complex tissues. Here, we assessed if the DNA methylation-derived mitotic ageing indices are associated with oral squamous cell carcinoma (OSCC) development and recurrence-free survival (RFS).

METHODS

DNA methylation-based mitotic indices (MitoticAge, TNSC and hypoSC) were derived using algorithms "MitoticAge" and "epiTOC2" for the discovery [non-malignant (n = 22), premalignant (n = 22) and OSCC (n = 68) tissues] and validation datasets (GSE87053, GSE136704 and TCGA-HNSCC). Differences in mitotic indices between non-malignant, premalignant and OSCC tissues were assessed. Finally, the association between estimated mitotic indices and RFS was evaluated in OSCCs.

RESULTS

In the discovery and validation datasets, increased mitotic ageing was observed in OSCC compared to non-malignant and premalignant oral tissues. HPV-positive HNSCCs had higher mitotic index TNSC. Mitotic age index hypoSC was associated with RFS in OSCC (p = 0.011, HR 2.61, 95% CI 1.24-5.48).

CONCLUSIONS

DNA methylation-derived mitotic indices are associated with OSCC development and RFS. Thus, DNA methylation-derived mitotic indices may be a valuable research tool to reliably estimate the cumulative number of stem cell divisions in malignant and non-malignant oral tissues. Future research utilizing mitotic indices for predicting clinical outcomes in OSCC is warranted.

Genome-wide DNA methylation profiling of stomach cancer in the ethnic population of Mizoram, North East India

Stomach cancer is the fifth most common cancer in terms of prevalence and incidence and the fourth leading cause of mortality in men and women worldwide. It is well-established that aberrant DNA methylation in cells can lead to carcinogenesis. The primary objective of our study was to investigate the aberrant DNA methylation status of genes associated with stomach cancer with a particular reference to the ethnic population of Mizoram, North East India. The site-level analysis identified 2883 CpG sites differentially methylated, representing ~922 genes. Out of which 476 Differentially Methylated Positions (DMPs) were promoter-associated, 452 DMPs were hypermethylated, and 24 were hypomethylated. The region-level analysis identified 462 Differentially Methylated Regions (DMRs) corresponding to ~320 genes, of which ~281 genes were hypermethylated and ~ 40 genes were hypomethylated. TCGA analysis showed that some of the genes had been previously implicated in other cancers including stomach cancer. Five hypermethylated genes were selected as candidate genes for further investigations and they have shown to be novel and could serve as candidate hypermethylation biomarkers for stomach cancer in this particular ethnic group.

Upregulation of SPI1 during myocardial infarction aggravates cardiac tissue injury and disease progression through activation of the TLR4/NFκB axis

OBJECTIVE

Spleen focus forming virus proviral integration oncogene (SPI1) belongs to the ETS family of transcription factors participating in an array of cellular processes such as inflammation and cell apoptosis. This research focused on the role of SPI1 in the myocardial infarction (MI).

METHODS

A murine model of MI was established. HL-1 cells were exposed to hypoxic treatment to simulate an MI-like condition. Tissue injury, inflammatory infiltration, and fibrosis in the cardiac tissues, and the apoptosis and the production of inflammation-related factors in cells were examined. Expression of SPI1 was determined. The downstream targets of SPI1 were identified by bioinformatics tools and luciferase assays. Artificial up- or downregulation of SPI1 and toll like receptor 4 (TLR4) were induced to examine their involvements in MI progression.

RESULTS

SPI1 was expressed at high levels in the cardiac tissues of MI mice and in hypoxia-induced HL-1 cells. SPI1 downregulation reduced apoptosis and the production of inflammatory cytokines in the hypoxia-induced HL-1 cells. SPI1 bound to TLR4 promoter to induce transcriptional activation. TLR4 induced NFκB phosphorylation and blocked the protective role of SPI1 silencing in cells. In vivo, SPI1 inhibition restored the cardiac function and ameliorated MI-induced inflammation and fibrosis in mice. The protective role of SPI1 inhibition in mice was blocked by TLR4 activation. Aberrant upregulation of SPI1 was caused by the reduced DNA methylation during MI.

CONCLUSION

This study demonstrated that upregulation of SPI1, caused by reduced DNA methylation, augmented development of myocardial infarction by activating the TLR4/NFκB axis.