Identifying Biomarkers of Metastasis Through Biosynthetic Tagging

Abstract

Lung cancer is the most common malignancy, with lung cancer deaths in the United States exceeding that of the next four major cancers combined. With a 5-year survival rate of less than 15% overall, lung cancer has a significant effect on both civilian and military populations, with higher rates of lung cancer incidence and mortality among the latter. To move beyond the current diagnostic and therapeutic plateaus, new strategies for diagnosis and treatment are urgently needed. Sensitive, non-invasive methods for early lung cancer detection and new approaches to treatment for specific lung cancer subtypes have the potential to prevent unnecessary suffering to both military and civilian patients and to reduce the financial burden of military and civilian patient care. Small non-coding RNAs, called microRNAs (miRNAs), are exported by tumor cells, stable in serum, and able to modify the properties and behavior of other cells. They are therefore potential biomarkers of metastasis and therapeutic targets by which metastasis may be controlled. However, there is currently no method by which to distinguish miRNAs that originate from tumor cells from those that are involved in host responses, such as a general inflammatory response, limiting our ability to exploit their value. The current proposal addresses this knowledge gap with a novel combination of chemical and genetic tools to identify the tumor-specific miRNA secretome. We leverage a murine model of the extremes of lung cancer metastatic behavior, a protozoan enzyme that can selectively incorporate a modified base into RNA, and expression profiling by next-generation sequencing to identify miRNA markers of metastasis. The proposed research addresses the LCRP Area of Emphasis: “Understanding the molecular mechanisms of progression to clinically significant lung cancer.” Completion of the proposed work will identify miRNAs that are biomarkers of lung cancer metastasis that can then be investigated as therapeutic targets in the same mouse models, extended to models based on human cell lines, evaluated in patient populations, and developed as clinical tools. The goal is to provide new biomarkers that can better stratify patients for treatment, and by doing so improve outcomes.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 16, 2019
Source ID
W81XWH1910362

Entities

People

  • Alexander Pertsemlidis

Organizations

  • United States Army
  • University of Texas Health Science Center at San Antonio

Tags

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Oncology
  • Oncology (Cancer Research).

Technology Areas

  • Biotechnology