title: Plasma Extracellular Vesicle MicroRNA Biomarkers for Lung Cancer Diagnosis
Creators: name: Yang, Xiaolei
Publisher: name: University of Liverpool Repository
Year: 2022

description: Plasma Extracellular Vesicle MicroRNA Biomarkers for Lung Cancer Diagnosis Background Globally, lung cancer represents the most common cause of cancer-related death. The high mortality rate of lung cancer is attributed mainly to the late stage of the disease at diagnosis. Blood-based biomarkers provide a method for early detection, but any biomarkers need to be rigorously validated at a pre-clinical and clinical level. Extracellular vesicles (EVs) are nanosized functional vacuolar structures released by cells, which play a pivotal role in intercellular communication. They are released in plasma, where they can be measured in a minimally invasive manner. It is hypothesized that a panel of EV miRNAs may provide a sensitive and specific biomarker to detect lung cancer at an early stage. Aims and objectives This thesis aims to identify panels of miRNAs in the human plasma EV fraction that may serve as biomarkers for early diagnosis of lung cancer. The specific objectives include: (a) qPCR validation of a panel of 18 pre-selected miRNAs, identified by logistic regression analysis; (b) further analysis of the EV fraction data by alternative statistical approaches; and (c) comparison of miRNA expression between whole plasma and the EV fraction. Methods The HTG EdgeSeq miRNA Whole Transcriptome Assay (WTA) was used to measure the expression of 2,083 human miRNA transcripts from (a) plasma EV fractions of 60 cases and 60 controls and (b) plasma samples of 26 cases and 24 controls. Differential expression was assessed using HTG EdgeSeq Reveal data analysis suite. For validation, the exoEasy Midi Kit (Qiagen) was used to isolate EVs from a 2ml plasma sample. In total, EVs were extracted from 188 cases and 187 age/sex matched control plasma samples. Direct-zol RNA Miniprep Kit (Zymo Research) was used for EV RNA isolation. The TaqMan Advanced miRNA cDNA Synthesis Kit (Applied Biosystems) was used to reverse transcribe miRNA. qPCR, with miRCURY LNA Probe PCR Kits (Qiagen) and TaqMan™ Advanced miRNA Assays (Applied Biosystems), was used to analyse miRNA expression. Results Validation of the 18 miRNAs previously identified by qPCR demonstrated that only a limited number of miRNAs were differentially expressed when applying an alternative EV isolation method and measurement technology. Reanalysis of the HTG EV miRNA data using updated quality control and alternative statistical methods identified batch effects for EV isolation and revealed alternative differentially expressed miRNAs. Differential expression of miRNAs in whole plasma was more robust than in EVs, with higher fold-changes and greater statistical significance (despite a smaller sample size). Comparison to whole plasma miRNA profiles identified both enrichment and depletion of miRNAs in EVs. Conclusions We have shown that some miRNAs, in both EV and whole plasma, are up- or down-regulated in lung cancer. Furthermore, we could identify miRNAs differentially expressed in relation to other characteristics, such as COPD, smoking status and sex. The results clearly demonstrate the impact of EV isolation techniques and statistical analysis methods in the selection and validation of miRNAs. Despite a clear biological relevance to EV miRNA expression and the demonstration of differential enrichment of miRNAs, there are clear technological challenges to identification and validation of EV miRNA expression patterns. Plasma and EV miRNAs show great promise as clinically useful biomarkers, but great care must be taken to overcome the practical challenges of assay reproducibility and utility.