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Analysis of Circulating Tumor RNA for Early Detection of Lun

Institution: Stanford University
Investigator(s): Young-Jun Jeon, Ph.D.
Award Cycle: 2017 (Cycle 26) Grant #: 26FT-0032 Award: $118,800
Subject Area: Early Diagnosis of Tobacco-Related Cancer
Award Type: Postdoctoral Fellowship Awards

Initial Award Abstract

Lung cancer is strongly associated with smoking and is the most common cause of cancer-related deaths in the world. Compared to never smokers, smokers are >20 times more likely to develop lung cancer. The reasons for the poor overall survival of lung cancer patients are multifactorial and the exact mechanisms underlying cancer progression are poorly understood. However, lung cancer patients detected at early stages can often be cured. Therefore, developing biomarkers for the detection of early stage lung cancers is an important goal. Tumor-specific dysregulation of nucleic acids can be used for unique molecular signature of cancers and represents an ideal biomarker for measuring the presence of tumors. I hypothesize that identification of tumor-specific circulating RNAs using an ultrasensitive method that we have developed will provide a sensitive and specific strategy for detecting early stage of lung cancer. My mentor’s lab has previously developed a non-invasive method called Cancer-derived Cell-free DNA Profiling by Deep Sequencing (CAPP-Seq) for detection of cell-free DNA. This approach involves capture of target regions followed by next generation sequencing. To date, this method has never been applied to cfRNA. In this proposal I will develop a novel strategy for early detection of lung cancer based on next generation sequencing of circulating RNAs. To do so I will adapt the CAPP-Seq method for detection of tumor-derived cfRNA. I propose the following two specific aims: Specific Aim 1 – Development of Lung Cancer RNA CAPP-Seq: First, I will analyze in plasma of lung cancer patients to identify the RNAs. To do this I will utilize publicly available gene expression data to identify RNAs (including mRNAs and non-coding RNAs) highly expressed in non-small cell lung cancers (NSCLC) but not in blood cells. To this list, I will add ~200 exons that are most frequently mutated in NSCLC, since in addition to detecting the presence of circulating RNAs, my approach will allow identification of somatic mutations and RNA mutations. I will then generate a CAPP-Seq selector and will test its sensitivity and specificity using spiking experiments of lung cancer cell line RNA into healthy donor plasma to detect lung cancer. Specific Aim 2 – I will apply the Lung Cancer RNA CAPP-Seq selector to plasma samples from NSCLC patients (Stages I-III) as well as to healthy controls. The samples for these patients are already present in a plasma bank in my mentor’s lab. I will analyze the sensitivity and specificity of my new approach and compare it to that of standard DNA-based CAPP-seq. If successful, current research proposal could enhance specificity and sensitivity of cancer detection applicable for lung cancer diagnosis with high impact on the field.