NONINVASIVE DETECTION OF CIRCULATING RNAS FOR LUNG CANCER EARLY DETECTION AND PROGNOSIS


Year of Award:
2015
Award Type:
R33
Project Number:
CA191245
RFA Number:
RFA-CA-14-004
Technology Track:
Molecular & Cellular Analysis Technologies
PI/Project Leader:
WU, YUN
Other PI or Project Leader:
N/A
Institution:
STATE UNIVERSITY OF NEW YORK AT BUFFALO
The dismal rate of survival in lung cancer is primarily a result of late diagnosis, resistance to classical or targeted therapy, and post-treatment recurrence of disease. A patient-friendly early detection and prognosis method that detects cancer at an early stage, assesses response to treatment, and predicts risk of cancer recurrence would substantially reduce the mortality in this serious disease. Non-invasive 'liquid biopsy' relying on the detection of extracellular circulating RNAs (microRNAs and mRNAs) in patient blood samples has great potential to achieve this goal. Such biomarkers in serum/plasma can be sensitively quantified by quantitative reverse transcription (qRT)-PCR of RNA isolated from the samples. However, this RNA isolation-qRT-PCR workflow cannot distinguish circulating RNAs secreted by cancer cells from those released physiologically and ubiquitously by all other, non-tumor cells of the body, making it potentially less sensitive or incapable of detecting cancer-specific RNA biomarkers. We recently developed a novel and simple tethered cationic lipoplex nanoparticle (tCLN) biochip with pre-loaded molecular beacons in the nanoparticles as probes to capture and detect cancer-specific RNAs in human serum without requiring pre- or post-sample processing. In this technology, negatively charged RNA molecules are easily captured by and fused with positively charged lipoplex nanoparticles, allowing their detection by the molecular beacons. Since both RNA targets and molecular beacons are confined within nanometer-sized liposome particles in a detection volume that is 1012 times smaller than that of a PCR reaction, this method not only provides very high detection sensitivity but also forfends the need for target amplification that qRT-PCR requires. We have demonstrated the feasibility of the tCLN biochip in detecting and quantifying extracellular miR-21 and let-7g microRNAs and Thyroid Transcription Factor-1 (TTF-1) mRNA in serum of lung cancer patients. The tCLN biochip could thus successfully distinguish early stage lung cancer patients from normal healthy controls, whereas the serum RNA isolation-qRT-PCR workflow was found to be completely ineffective for the task. We have assembled a strong multi-disciplinary team to further develop the tCLN biochip and to validate its feasibility using serum samples from smokers at high risk for developing lung cancer and from lung cancer patients. Our primary objectives are (1) to optimize the current tCLN biochip technology and to develop a microfluidic CLN (mCLN) biochip as a point-of-care diagnostic device; (2) to evaluate the performance of tCLN and mCLN biochips as a diagnostic tool for identifying lung cancer among individuals with computed tomography (CT)-detected solitary pulmonary nodules; and, (3) to evaluate the performance of tCLN and mCLN biochips as a prognostic tool using serum samples collected from early stage lung cancer patients before and at various time-points following surgical resection of cancer. We will also compare the tCLN and mCLN biochips with the traditional serum RNA isolation-qRT-PCR workflow for serum RNA detection sensitivity and specificity.