Early Detection of Lung Cancer Through Molecular Analyses of Single Extracellular Vesicles
Abstract
Background: Extracellular vesicles (EVs) are an emerging class of cancer markers. These are tiny membrane particles (50–200 nm in diameter) that are shed by living cells, including tumors. EVs carry with them DNA, RNA, and proteins, just like their parent cells. As such, they can function as cellular “avatars,” providing rich information on patients’ tumors. Indeed, tumor-associated EVs have been shown as effective surrogate biomarkers for lung cancer (LC), enabling non-invasive determination of tumor types and monitoring treatment responses. Challenges: Despite these encouraging results, technical challenges remain when using EV analyses for early cancer diagnostics. First of all, tumor-derived EVs comprise only a small fraction of total EVs found in blood. Conversely, normal host cell-derived vesicles account for >90% of the total vesicle population. Enriching cancer-specific EVs could thus be important to detect molecular targets specifically dysregulated in tumors. Currently available EV assays require large amount of EVs (>10,000) and produce averaged “bulk” data. These drawbacks make it hard to differentiate true tumor signal from vast biological background, and EV profiles in early cancer development are largely unknown. Goals and Innovations: We seek to overcome these challenges by advancing a new analytical platform tailor-designed to probe single EVs. Specifically, we will develop a new imaging method to probe individual EVs. The imaging method will use novel cleavable light-tagged antibodies for repeated probing on same EVs. We will next apply this platform to study EVs at very early stages of LCs using gold standard, genetically engineered mouse models of cancer that naturally arise following genetic mutation in the lung tissue, similar to what may occur in humans. We will monitor both tumor burdens and its molecular characteristics; this information will be compared with single-EV profiling results. The study will work backwards from advanced disease toward increasingly minimal disease, with concordant EV analysis and imaging to understand limits of detection. Impacts: The proposed research will significantly advance both basic science, biomedical engineering, and translational concepts of early cancer detection. Basic cancer research. The developed assay platform and approaches will be a transformative analytical tool to study nearly all types of vesicles shed by cells (e.g., EVs, lipid particles) at a single particle level. Most importantly, this bottom-up approach could uncover new biological processes that are currently masked by bulk measurements, including (1) protein/RNA composition of vesicles; their heterogeneity; different cellular origins; and molecular changes with disease progression. Clinical applications. This project will significantly expand the reach of LC preclinical and clinical research. Better understanding of EV biology would promote its innovative use, particularly as a non-invasive biomarker for early cancer diagnostics, thereby enabling prompt, rationalized clinical intervention. This information will also help clinicians devise and test new therapeutic strategies (e.g., targeted molecular therapy, immune targeted therapies) through better powered trials and improved tumor monitoring. This would have profound implications on survivorship as well as quality of life during clinical LC management. Military Relevance: Active Service members and Veterans harbor elevated risk of developing LC due to (1) higher prevalence of smoking and (2) increased chance of being exposed to carcinogenic chemicals (e.g., asbestos, agent orange, diesel exhaust). Establishing cost-effective blood test could allow physicians to detect LC at its early and most treatable stage, improving overall patient survivorship. The developed diagnostic technologies also may apply to both acute and chronic pulmonary diseases that relate to military Service members, including fro
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 16, 2019
- Source ID
- W81XWH1910194
Entities
People
- Hakho Lee
Organizations
- Massachusetts General Hospital
- United States Army