Risk profile

The development of non-invasive diagnostic tools to detect lung cancer at an early stage is the subject of active investigations because of its enormous potential impact on the number-one cause of cancer-related deaths. We have recently discovered by shotgun proteomics profiling 164 candidate biomarkers that are differentially expressed in stage 1 lung cancer tissue compared to non-malignant matched controls tissues and found in the circulation. Validation of these candidates by traditional methods using western blot or ELISA is a slow, low throughput, and expensive process. In this application, we propose to take advantage of the individual’s immune response to capture and detect autoantibodies directed against these 164 candidate protein targets identified by shotgun proteomics. To achieve this goal, we intend (1) to establish immune-based assays for the detection and quantitation  of lung cancer autoantibodies using an indirect ELISA; (2) to validate the diagnostic performance of our autoantibody signature in blood samples from individuals with early-stage lung cancer or matched nodule controls; and (3) to determine whether the diagnostic performance of our panel of autoantibody signatures augments the diagnostic accuracy of known predictive models for the evaluation of lung nodules. These studies may lead to the development and early validation of a new molecular diagnostic tool for lung cancer.

Recently, the National Lung Screening Trial reported a 20% reduction in lung cancer mortality and lung cancer chemoprevention trials targeting the arachidonic acid pathway have demonstrated decreases in lung cancer associate markers .These studies highlight possibilities for future reductions in lung cancer mortality through early detection and chemoprevention. Our group has previously identified smoking- and lung cancer-specific gene expression alterations in cytologically normal airway epithelial cells that can serve s a clinically relevant biomarker for the early detection of lung cancer. We propose to extend our studies of the field of injury by profiling  these cells from high-risk smokers with preinvasive lesions (dysplasia) and matched controls without lesions by RNA-Seq. We will characterize the molecular alterations (coding, noncoding, and novel RNA expression and alterative splicing) associated with the field of injury in premalignancy and identify whether these differences are similar in both current and former smokers. Next, we will develop molecular signatures that predict subsequent progression or regression of premalignant lesions as well as changes that occur as a result of progression or regression. Collectively, these signatures will aid in the stratification of high-risk smokers for chemoprevention trials, serve as intermediate markers of efficacy in these trials, and identify new targets for chemoprevention. Finally, we will explore whether these molecular signatures re associated with occult lung cancer or future lung cancer development in independent cohorts as common alterations may indicate early events in lung carcinogenesis and have additional utility as biomarkers in the early detection of lung cancer.

Small cell lung cancer (SCLC) exhibits aggressive clinical behavior and poor outcome and response to therapy. Moreover, there are no effective strategies for early detection of SCLC. Therefore, there is an urgent need to identify new strategies and markers for SCLC detection. We recently characterized the molecular airway field cancerization (FC) in non-small cell lung carcinoma (NSCLC) patients and identified airway profiles that varied spatially (n=1165) and with time (n=1395) following surgery. Moreover, we characterized the adjacent airway FC in NSCLC (n=1606 genes), a subset of which (n=299) significantly distinguished airways of smokers with lung cancer from those of healthy smokers and another (n=208) separated airways of different NSCLC subtypes. Although we previously showed that SCLCs and adjacent airways are characterized by higher level of allelic losses compared to those of NSCLC cases, the global airway FC in SCLC and its relevance to detection has not been explored. We hypothesize that the molecular airway FC in SCLC is different compared to that in NSCLC or benign lung disease and comprises biomarkers specific for early detection of SCLC. We will 1) perform global expression profiling of the airway FC and tumors or nodules in patients with SCLC, NSCLC, and benign disease for identification of airway markers specific to SCLC and 2) test identified airway mRNA markers for SCLC detection in bronchial and nasal compartments in patients with suspect lung cancer. We anticipate that our proposal, due to its unique resources and approaches, will identify novel markers for SCLC detection.

Screening smokers with CT can detect lung cancer at relatively early stages, and thus reduce mortality. However, CT screening for lung cancer has a poor specificity, often resulting in unnecessary treatments to smokers who have benign diseases. The objective of this proposal is to develop genomic- and non-coding RNA (ncRNA)-based biomarkers in sputum that can complement CT for lung cancer early detection in smokers.  Proposed aim 1 is to define sputum ncRNA signatures of early-stage lung cancer using next-generation sequencing (NGS). Proposed aim 2 is to optimize a panel of sputum ncRNA biomarkers with CT for the early detection of lung cancer. Proposed aim 3 is to integrate our previously identified genomic biomarkers and the newly optimized panel of ncRNA biomarkers with CT for the early detection of lung cancer in independent case-control series. Future use of the biomarkers in clinical practice for screening smokers for lung cancer will increase CT’s specificity, and hence reduce harmful and unnecessary treatments to many smokers who have benign diseases. Integrating the biomarkers with CT could assist making decisions for the management of abnormal findings in the lungs and enabling effective treatments to be immediately initiated for lung cancer. The study will translate the strengths of novel ncRNA profiling data developed from NGS into clinical settings by using a simple and cost-effective approach, and thus bridge the gap between basic research and patient care.