Stage I

Despite focused research in conventional therapies, the 5-year survival rate of lung cancer patients remains only 15%. Due to the lack of reliable early diagnostic techniques, most patients are diagnosed with advanced-stage disease and therefore have a poor prognosis. There are more than 100 million current and former smokers in the US who have elevated risk for lung cancer and may benefit from a non-invasive test for early detection. Patients at risk may have subclinical disease for years prior to diagnosis. Therefore the clinical challenge is to develop lung cancer detection methods that are effective during this window of opportunity to increase the rate of early detection and thereby spur early treatment and improve lung cancer patient outcomes. During tumorigenesis, the developing tumor forms a complex cellular microenvironment that produces many soluble mediators, such as proteins and miRNAs, which are important for tumor initiation and growth and thus can serve as lung cancer biomarkers. Because the pulmonary vascular bed comprises approximately 50% of the body’s total vasculature, the peripheral blood is expected to reflect even small variations in lung cancer biomarkers.

Over the past decade, our laboratory has gathered substantial data supporting the analysis of soluble mediators of lung carcinogenesis including inflammatory cytokines, growth and angiogenic factors, and miRNA. Additionally, a considerable literature has developed describing the contribution of these factors to lung carcinogenesis. Based on these findings, in our preliminary studies we have developed a plasma protein-based biomarker panel that accurately distinguished between lung cancer patients and at-risk control subjects. Our predictive model provided 97% sensitivity, 77% specificity, and an area under the ROC of .93 for stage 1 vs. high-risk controls. Because recent studies demonstrated that circulating miRNA can serve as robust and specific diagnostic biomarkers, we developed a panel of 17 miRNAs relevant to lung carcinogenesis. In our preliminary studies utilizing this miRNA panel, we were able to detect miRNAs that are differentially expressed in the plasma of lung cancer patients as compared to high-risk controls. We hypothesize that the proteins and miRNA profiles will each contribute unique information and thus, an integrated panel of protein and miRNA markers may provide higher sensitivity for early lung cancer detection than either platform alone.

Specific aims for the current proposal include: 1) to identify protein profiles in plasma associated with early-stage lung cancer, 2) to identify plasma miRNA profiles associated with early stage lung cancer, and 3) to integrate miRNA and cytokine biomarkers established in Aims 1 and 2 to improve early-stage lung cancer detection. The first and second aims address the clinical problems of patients at risk for lung cancer who present with a suspicious pulmonary nodule of indeterminate significance that has be further evaluated.

The most effective curative modality we have for lung cancer is still surgery, but, even with optimum surgery, many patients relapse and die of their lung cancer, and this fraction is improved only slightly by adjuvant chemotherapy, which is nonetheless toxic for everybody. Thus, we need to identify prognostic biomarkers (to define which patients are likely to relapse after surgery) and predictive biomarkers (to define who will benefit from adjuvant therapy, and what specific type of adjuvant therapy should be used on each particular patient). In this proposal, collaborators from two different lung cancer SPOREs in three different universities will use two sets of high information-content analyses of protein and RNA expression already acquired on a cohort of early-stage lung cancer patients who did not receive adjuvant chemotherapy and in a panel of cell lines rigorously characterized for sensitivity to platinum doublets, and will add to that data funded by this proposal on a new cohort of patients treated with adjuvant chemotherapy to generate our classifier. This classifier will then be reduced to a small number of RNA or protein assays and tested in a larger set of resected patients with and without adjuvant chemotherapy.

Lung cancer is the leading cause of death for men and women in the United States. Screening methods for the early detection of lung cancer must be developed to circumvent the phenomenon that sees the majority of patients being diagnosed with advanced, and thus incurable, lung cancer. While computerized tomography was demonstrated to reduce mortality by 20% in a high-risk smoker patient cohort, further examination of this method, complementary screening methods, and tools to screen less at-risk populations are needed to make the detection of early-stage lung cancer most beneficial. Using the expertise of our multidisciplinary clinical lung cancer team (Drs. Kelly, Gandara, Cooke, Yoneda, and Murin) with leaders in metabolomics and lipid biology (Dr. Fiehn) and glycomics (Drs. Miyamoto and Lebrilla), we aim to identify mass spectroscopy-detectible biomarkers of early lung cancer. The advent of “omics” technologies will allow us to expand the current pool of DNA and protein biomarkers and facilitate our vision of a systems-biology screening and/or diagnostic tool based on “biomarker panels.” Our approach begins with a discovery phase that will identify biomarkers in tumor and blood with the aim of finding blood-based biomarkers that most closely reflect tumor biology. Next we will proceed to the testing phase to determine the performance of these biomarkers in four independent cohorts (two lung cancer cohorts, healthy controls, and benign nodules). Biomarkers that meet our pre-specified criteria will require further evaluation that is beyond the scope of this proposal.

The overarching concept guiding our work is that combinations of biomarkers and imaging characteristics will be most robust in predicting which patients with lung nodules should receive an aggressive diagnostic and/or therapeutic approach and which patients should be monitored for nodule stability over time. Our objectives are to improve two biomarker tests that already have shown significant promise-- sputum chromosomal aneusomy by fluorescence in situ hybridization (CA-FISH) and the analysis of multiple serum analytes by a highly multiplexed aptamer-based assay developed by SomaLogic, Inc.-- and then to compare test performance with predictive models based on nodule and patient characteristics. These objectives are based on two separate hypotheses: 1. The current CA-FISH assay panel can be further improved by the development of two sub-panels, one for detection of squamous cell carcinoma of the lung (SCC) and the second for the detection of adenocarcinoma of the lung (AC). 2. The current aptamer-based analysis can be further improved by developing separate assays specifically designed for the detection of AC, SCC, K-ras, and EGFR-mutated lung tumors. The assays will then be applied to sputum and blood specimens from the Pittsburgh SPORE Pittsburgh Lung Screening Study (PLuSS) and Colorado SPORE Lung Nodule cohorts, in concert with analysis of the CT characteristics of the corresponding lung nodules, including size, volume, density, location, or airway involvement, to compare test performances and to assess whether combining tests would be valuable.