Dataset Information

More than a Bubble: Extracellular Vesicle microRNAs in Head and Neck Squamous Cell Carcinoma.

ABSTRACT: MicroRNAs (miRNAs) are a class of small non-coding RNA molecules that play a pivotal regulatory role in a broad variety of biological processes. Dysregulation of miRNAs is associated with several human diseases, particularly cancer. Extracellular vesicles (EVs) are crucial components in intercellular communication. As part of the cargo of EVs, miRNAs are involved in EV-mediated cell-to-cell interactions, including promotion or suppression of tumor development. The knowledge on the molecular mechanisms and clinical importance of EV-miRNAs in head and neck squamous cell carcinoma (HNSCC) has rapidly grown over the past years. In the present review, the current understanding regarding the effect of EV-miRNAs on HNSCC tumorigenesis is summarized, which includes effects on tumor proliferation, angiogenesis, invasion and metastasis, the tumor microenvironment, immune modulation, and treatment resistance. EV-miRNA-based biomarkers in liquid biopsies such as blood and saliva may open up new possibilities for employing EV-miRNAs for screening and early diagnostics as well as disease monitoring. Future perspectives include the promise of EV-miRNAs as a novel therapeutic target.

SUBMITTER: Panvongsa W

PROVIDER: S-EPMC8909139 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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More than a Bubble: Extracellular Vesicle microRNAs in Head and Neck Squamous Cell Carcinoma.

Panvongsa Wittaya W Pegtel D Michiel DM Voortman Jens J

Cancers 20220224 5

MicroRNAs (miRNAs) are a class of small non-coding RNA molecules that play a pivotal regulatory role in a broad variety of biological processes. Dysregulation of miRNAs is associated with several human diseases, particularly cancer. Extracellular vesicles (EVs) are crucial components in intercellular communication. As part of the cargo of EVs, miRNAs are involved in EV-mediated cell-to-cell interactions, including promotion or suppression of tumor development. The knowledge on the molecular mech ...[more]

PMID: 35267467

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Project description:BackgroundOropharyngeal squamous cell carcinoma (OPSCC) is often diagnosed at an advanced stage because the disease often causes minimal symptoms other than metastasis to neck lymph nodes. Better tools are required to assist with the early detection of OPSCC. MicroRNAs (miRNAs, miRs) are potential biomarkers for early head and neck squamous cell cancer diagnosis, prognosis, recurrence, and presence of metastatic disease. However, there is no widespread agreement on a panel of miRNAs with clinically meaningful utility for head and neck squamous cell cancers. This could be due to variations in the collection, storage, pre-processing, and isolation of RNA, but several reports have indicated that the selection and reproducibility of biomarkers has been widely affected by the methods used for data analysis. The primary analysis issues appear to be model overfitting and the incorrect application of statistical techniques. The purpose of this study was to develop a robust statistical approach to identify a miRNA signature that can distinguish controls and patients with inflammatory disease from patients with human papilloma virus positive (HPV +) OPSCC.MethodsSmall extracellular vesicles were harvested from the serum of 20 control patients, 20 patients with gastroesophageal reflux disease (GORD), and 40 patients with locally advanced HPV + OPSCC. MicroRNAs were purified, and expression profiled on OpenArray™. A novel cross validation method, using lasso regression, was developed to stabilise selection of miRNAs for inclusion in a prediction model. The method, named StaVarSel (for Stable Variable Selection), was used to derive a diagnostic biomarker signature.ResultsA standard cross validation approach was unable to produce a biomarker signature with good cross validated predictive capacity. In contrast, StaVarSel produced a regression model containing 11 miRNA ratios with potential clinical utility. Sample permutations indicated that the estimated cross validated prediction accuracy of the 11-miR-ratio model was not due to chance alone.ConclusionsWe developed a novel method, StaVarSel, that was able to identify a panel of miRNAs, present in small extracellular vesicles derived from blood serum, that robustly cross validated as a biomarker for the detection of HPV + OPSCC. This approach could be used to derive diagnostic biomarkers of other head and neck cancers.

Dataset Information

More than a Bubble: Extracellular Vesicle microRNAs in Head and Neck Squamous Cell Carcinoma.

Publications

More than a Bubble: Extracellular Vesicle microRNAs in Head and Neck Squamous Cell Carcinoma.

Similar Datasets

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