A reductionist approach using primary and metastatic cell-derived extracellular vesicles reveals hub proteins associated with oral cancer prognosis

Abstract Background: The incidence rate of lip and oral cancer is increasing in recent years, the prognosis of which is associated with a country’s socioeconomic status. The mortality-to-incidence ratio (MIR) is a reasonable indicator of disparities in cancer screening and treatment. We aim to understand the association between economic status and cancer prognosis.Methods: Data were obtained from the Global Cancer Observatory (GLOBOCAN) and the World Health Organization (WHO). The MIR was applied to evaluate the correlation to healthcare expenditures and the human development index (HDI) disparities via Spearman's rank correlation coefficient.Results: The results showed that Asia has the most cases and deaths. The association of the HDI, current health expenditure (CHE), and ratio of CHE to the percentage of gross domestic product (CHE/GDP) to the crude rate (CR) of incidence show significant results (p<0.001, p=0.005, and p<0.001, respectively). However, their association with the mortality rate (p=0.303, p=0.997, and p=0.101) is not significant. In the correlation of the MIRs, the results revealed a significant association with the HDI, CHE, and CHE/GDP with the MIR (p<0.001, p<0.001, and p<0.001, respectively).Conclusion: Countries with a higher HDI, more CHE per capita, and higher CHE/GDP tend to have a lower MIR, which indicates a favorable clinical outcome.

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DNA methylation confers clinical potential to predict the oral cancer prognosis

Clinical Research and Trials ◽

10.15761/crt.1000232 ◽

2018 ◽

Vol 4 (5) ◽

Cited By ~ 2

Author(s):

Cheng-Chieh Yang ◽

Cheng-Hsien Wu ◽

Chi-Feng Chang ◽

Chien-Ping Hung ◽

Micah Sy ◽

...

Keyword(s):

Dna Methylation ◽

Oral Cancer ◽

Cancer Prognosis ◽

Clinical Potential

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A genetic programming approach to oral cancer prognosis

PeerJ ◽

10.7717/peerj.2482 ◽

2016 ◽

Vol 4 ◽

pp. e2482 ◽

Cited By ~ 3

Author(s):

Mei Sze Tan ◽

Jing Wei Tan ◽

Siow-Wee Chang ◽

Hwa Jen Yap ◽

Sameem Abdul Kareem ◽

...

Keyword(s):

Oral Cancer ◽

Genetic Programming ◽

Small Sample ◽

Cancer Prognosis ◽

Programming Approach ◽

Support Vector ◽

Survival Prediction ◽

Feature Subset ◽

Comparison Results ◽

Bank System

BackgroundThe potential of genetic programming (GP) on various fields has been attained in recent years. In bio-medical field, many researches in GP are focused on the recognition of cancerous cells and also on gene expression profiling data. In this research, the aim is to study the performance of GP on the survival prediction of a small sample size of oral cancer prognosis dataset, which is the first study in the field of oral cancer prognosis.MethodGP is applied on an oral cancer dataset that contains 31 cases collected from the Malaysia Oral Cancer Database and Tissue Bank System (MOCDTBS). The feature subsets that is automatically selected through GP were noted and the influences of this subset on the results of GP were recorded. In addition, a comparison between the GP performance and that of the Support Vector Machine (SVM) and logistic regression (LR) are also done in order to verify the predictive capabilities of the GP.ResultThe result shows that GP performed the best (average accuracy of 83.87% and average AUROC of 0.8341) when the features selected are smoking, drinking, chewing, histological differentiation of SCC, and oncogene p63. In addition, based on the comparison results, we found that the GP outperformed the SVM and LR in oral cancer prognosis.DiscussionSome of the features in the dataset are found to be statistically co-related. This is because the accuracy of the GP prediction drops when one of the feature in the best feature subset is excluded. Thus, GP provides an automatic feature selection function, which chooses features that are highly correlated to the prognosis of oral cancer. This makes GP an ideal prediction model for cancer clinical and genomic data that can be used to aid physicians in their decision making stage of diagnosis or prognosis.

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Differential MicroRNA Expression of miR-21 and miR-155 within Oral Cancer Extracellular Vesicles in Response to Melatonin

Dentistry Journal ◽

10.3390/dj7020048 ◽

2019 ◽

Vol 7 (2) ◽

pp. 48 ◽

Cited By ~ 10

Author(s):

Matthew Hunsaker ◽

Greta Barba ◽

Karl Kingsley ◽

Katherine M. Howard

Keyword(s):

Oral Cancer ◽

Cell Lines ◽

Extracellular Vesicles ◽

Rna Isolation ◽

Extracellular Vesicle ◽

Primary Objective ◽

Microrna Expression ◽

Bioactive Molecules ◽

Melatonin Administration ◽

Mirna Content

Objective: Extracellular vesicles derived from oral cancer cells, which include Exosomes and Oncosomes, are membranous vesicles secreted into the surrounding extracellular environment. These extracellular vesicles can regulate and modulate oral squamous cell carcinoma (OSCC) progression through the horizontal transfer of bioactive molecules including proteins, lipids and microRNA (miRNA). The primary objective of this study was to examine the potential to isolate and evaluate extracellular vesicles (including exosomes) from various oral cancer cell lines and to explore potential differences in miRNA content. Methods: The OSCC cell lines SCC9, SCC25 and CAL27 were cultured in DMEM containing 10% exosome-free fetal bovine serum. Cell-culture conditioned media was collected for exosome and extracellular vesicle isolation after 72 h. Isolation was completed using the Total Exosome Isolation reagent (Invitrogen) and extracellular vesicle RNA was purified using the Total Exosome RNA isolation kit (Invitrogen). Extracellular vesicle miRNA content was evaluated using primers specific for miR-16, -21, -133a and -155. Results: Extracellular vesicles were successfully isolated from all three OSCC cell lines and total extracellular vesicle RNA was isolated. Molecular screening using primers specific for several miRNA revealed differential baseline expression among the different cell lines. The addition of melatonin significantly reduced the expression of miR-155 in all of the OSCC extracellular vesicles. However, miR-21 was significantly increased in each of the three OSCC isolates. No significant changes in miR-133a expression were observed under melatonin administration. Conclusions: Although many studies have documented changes in gene expression among various cancers under melatonin administration, few studies have evaluated these effects on microRNAs. These results may be among the first to evaluate the effects of melatonin on microRNA expression in oral cancers, which suggests the differential modulation of specific microRNAs, such as miR-21, miR-133a and miR-155, may be of significant importance when evaluating the mechanisms and pathways involved in melatonin-associated anti-tumor effects.

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