Imaging and Exosomal Genomics as an Early Identifier of Lung Cancer
Abstract
Lung cancer is the predominant form of cancer in the United States due to its high incidence, often escaping diagnoses at early stages. Lung cancer screening via imaging will result in inconsistent results due to the size of lung nodules, whether they are benign or malignant when routine imagining tools are utilized. Various tumor types, including lung, release exosomes into the blood that are enriched with DNA, reflecting the mutational status of the originating cancer cell, RNAs, as well as proteins, with important roles in disease onset, progression, and metastasis. Thus, exosome-derived biomarkers will provide a promising avenue for lung cancer early diagnoses and improved prognosis. Here, we propose to utilize imaging and exosomal genomic data to discriminate benign from malignant nodules. We will be addressing the emphasis area aiming to “Identify, develop, and/or build upon already existing tools for screening or early detection of lung cancer.” Screening may include, but is not limited to, imaging modalities, biomarkers, genetics / genomics / proteomics / metabolomics / transcriptomics, and assessment of risk factors. Several important studies from the Veterans Affairs have indicated that a significant number of military beneficiaries were diagnosed in recent years with lung cancer. This number is expected to increase in the next 20 years, in part because of the prevalence of smoking among active duty military personnel and Veterans. The personal suffering of (former) Service members and their family, combined with the financial burden to society, creates a great need for novel approaches to identify and monitor lung cancer disease, as well as its treatment, in particular because clinical outcomes in lung cancer remain poor. The proposed project is closely relevant to clinical needs of military personnel, Veterans, and Service members. This novel imaging agent and easy-to-operate device open new avenues to identify blood-based exosomal genomic biomarkers for early diagnosis and monitoring of disease progression. The proposed study will also help in determining the efficacy of therapeutics, and this may aid in the improvement of survival of lung cancer patients. We will analyze the imaging data in the first year, profile exosomal genomic data in the second year, and develop correlation models during the third year of the study. This proposal addresses an unmet need to weld disease specific circulatory biomarker data with imaging profiles to create integrated diagnostic models. Our focus on creating the ability to discriminate benign from malignant nodules by integrating imaging information with exosomal genomic data will have significant impact in the clinic. In the future, we envision that these integrated models can broadly impact the clinical medicine and become widely used for early diagnosis, prognosis, and therapy response monitoring in lung cancer and other cancers and diseases.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 10, 2021
- Source ID
- W81XWH2010746
Entities
People
- Utkan Demirci
Organizations
- Stanford University
- United States Army