LUNGevity-Funded Grants for Early 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.

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.

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.

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.

Better methods are required to accurately risk stratify patients with a solitary pulmonary nodule (SPN) who may undergo unnecessary procedures to exclude a cancer diagnosis. 18F-FDG Positron Emission Tomography (PET) is a widely available clinical test used to evaluate concerning SPNs and stage malignant lung nodules. It therefore facilitates clinical assessment but remains an imperfect tool for the diagnosis, localization, and prognostication of SPNs, be they infectious or malignant in nature. Furthermore, it performs well for staging lung cancer, but inaccurately categorizes patients in some cases who receive futile thoracotomies for disseminated disease, or conversely, are undertreated for localized disease. The applicant therefore plans on investigating whether circulating molecular biomarkers can increase the utility of 18F-FDG-PET imaging in clinical practice using statistical models that incorporate in vivo and in vitro diagnostics The concept here is “one-stop shopping,” where a patient can obtain routine molecular imaging and molecular diagnostics from routine blood work during an appointment that in combination increase the accuracy of a clinician’s diagnosis and facilitate the appropriate decision-making process. For this proposal we will develop a model that incorporates a circulating microRNA profile to discriminate infectious from malignant SPNs for patients along with clinical and FDG-PET data and, secondly, identify patients with malignant nodules and detectable circulating tumor cells to determine whether these cells upstage or augment clinical staging or prognosis post-operatively when compared to FDG-PET alone.

Evaluating suspicious pulmonary nodules in the setting of a lung cancer diagnostic work-up is a common clinical management challenge. High resolution multi-detector computed tomography visualizes many noncalcified lesions that could represent either potentially lethal cancers or benign processes. Although the vast majority of these nodules are benign, non-neoplastic lesions, a subset will be malignant and in these cases, patients could benefit from immediate treatment. A non-invasive test that maintains a high sensitivity and specificity across the spectrum of clinical presentations of pulmonary nodules would be of tremendous clinical benefit by reducing the number unnecessary invasive procedures and minimizing the time between detection and definitive treatment. The overall goal for the proposed studies is to develop a convenient and low-cost serum test that will, either alone or in combination with clinical features, accurately classify indeterminate nodules and direct proper clinical management. Our approach to develop such a test will be to profile and identify which proteins detected in the serum at the time of the detection of these nodules were immunogenic and induced the production of circulating autoantibodies. Differences in the autoantibody profile between the malignant and non-malignant groups will then be further evaluated against additional clinical specimens from both our institution and two pre-specified collaborator institutions to identify the optimal test for this urgent clinical need. Once completed, we anticipate this test will aid clinicians in deciding the optimal treatment for patients found to have suspicious nodules and improve the current standard of care.

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.

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.

Pulmonary nodules found on imaging studies are a significant diagnostic problem. Most lesions are indeterminate, but because of the concern for lung cancer all patients require further evaluation with resultant radiation risk, significant cost, and delays in diagnosis. We believe that the development of a serum test for lung cancer would have a significant impact on patient care and outcomes. We recently identified a novel panel of 25 serum autoantibodies associated with non-small cell lung cancer (NSCLC) and constructed a protein microarray containing the autoantigens. In a pilot study, we tested the microarray with human sera and developed a classification algorithm that incorporated microarray test results with nodule size. This algorithm had an overall sensitivity of 81% and specificity of 83% for the diagnosis of lung cancer. We now propose to further develop this panel and hypothesize that an autoantibody signature along with nodule size will be able to determine which patients have lung cancer.

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.

Three independent principal investigators at the Fred Hutchinson Cancer Research Center with combined expertise in thoracic oncology, cancer epidemiology and prevention, and molecular diagnostics are joining efforts to respond to the Protect Your Lungs RFA. The proposed research program is focused on developing novel blood-based tests to 1) identify never-smoker subjects at increased risk of developing lung cancer (C. Li, PI), 2) detect lung cancer before onset of symptoms (G. Goodman, PI),  and 3) distinguish between benign and malignant lesions identified by CT scans (S. Hanash, PI). The research questions address important public health issues in lung cancer and build on discoveries of candidate markers by the applicant group for which we propose validation studies in this proposal. Validation studies to be conducted will take advantage of the availability to the investigators of pertinent bio-specimens consisting of samples derived from two large cohort studies (The Women’s Health Initiative and the Beta Carotene and Retinol Efficacy Trial (CARET)) and samples derived from CT screening studies. The samples available are sufficient to meet the needs of the proposed studies. The collaborative nature of the proposed research will ensure synergism and efficiency of scale to meet study objectives and fast-track the development of clinically relevant applications.