Stage I

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.

Lung cancer remains the leading cause of cancer-related death due to the limited ability to detect the disease at an early and potentially curable stage. Low-dose computerized tomography (LDCT) screening of high-risk patients improves mortality. However, the high proportion of false positive tests, the majority of which are pulmonary nodules, has limited widespread adoption of this life-saving screening modality. Since screen-detected pulmonary nodules contribute to the overall cost of screening and potential morbidity due to the need for further diagnostic testing, there is an urgent need for accurate tools to stratify patients with screen-detected nodules for routine follow-up or additional intervention. Our data suggests that, similar to the smoking-associated field effect, the lung cancer-associated airway field of injury can be measured less invasively using gene-expression profiling of the nasal epithelium. Because early-stage lung cancers detected by CT screening may have distinct biologic characteristics compared to those diagnosed in patients evaluated for clinical symptoms, we propose to develop an accurate biomarker integrating expression profiling of genes and microRNA, clinical variables, and nodule characteristics in order to distinguish early lung malignancies from benign pulmonary nodules. The immediate clinical application of this test will be in the evaluation of patients with LDCT-detected lung nodules, and will allow clinicians to more accurately stratify patients to or from further diagnostic intervention. Ultimately, this test may also have utility for further stratifying lung cancer risk in patients eligible for screening prior to undergoing LDCT.

The release of small amounts of cell-free DNA into the bloodstream from dying tumor cells has been well documented in patients with various malignancies. Driven by improvements in assay technologies, such circulating tumor DNA (ctDNA) is beginning to show excellent promise as a non-invasive cancer biomarker. Because unique somatic mutations can serve as telltale marks to distinguish tumor-derived DNA in plasma, the cancer specificity of ctDNA is expected to be very high, making it an attractive candidate as a biomarker for cancer screening. Because many somatic mutations in non-small cell lung cancer (NSCLC) are found clustered with high frequency within a small set of genes, detection of ctDNA in such patients is technically more tractable. We have created a highly multiplexed, ultrasensitive assay that uses next-generation sequencing techniques to quantify low-abundance mutant DNA fragments in plasma against a large excess of background wild-type DNA. Our assay can simultaneously evaluate mutations in 40 different hotspots in up to 96 patient samples, using novel error suppression methods to optimize detection sensitivity. We have shown that the assay is capable of measuring very small amounts of mutant ctDNA in a limited set of patients with early-stage disease or with small, localized recurrences. We now aim to test the clinical performance of the assay on a larger scale. We propose to perform a case-control study comparing patients with early-stage NSCLC to individuals with a heavy smoking history or individuals having benign pulmonary nodules.

Prognosis for non-small cell lung cancer (NSCLC) is substantially better in early-stage as opposed to late-stage disease. If high-risk individuals could be effectively identified, they could significantly benefit from intensive surveillance, early detection, and prevention strategies. While smoking is a primary risk factor, only about 15% of smokers develop the disease. Consistent with a genetic predisposition, some patients have a family history of the disease and are affected at a young age, although they have never smoked. Unfortunately, NSCLC predisposing gene mutations are poorly characterized. We aim to identify novel NSCLC germline risk gene mutations. Our team members have previously identified novel risk gene mutations for several familial cancers. We have assembled a large clinically and molecularly well-characterized NSCLC case-control cohort of never-smokers, performed whole-exome sequencing (WES) on familial and early onset NSCLC probands, identified promising candidate risk genes, and externally validated selected samples. We follow a resource-conscious approach by focusing on a founder population, Ashkenazi Jews (AJ), to decrease genetic heterogeneity and to increase the allele frequencies of candidate recurrent risk mutations. We will perform WES on additional familial and early onset NSCLC probands to identify recurrently mutated NSCLC genes and cross-validate the genes using whole-genome sequencing on matching tumors. The gene candidates identified will be validated using a targeted sequencing approach in a larger non-AJ cohort. These are anticipated to provide new biological insights, serve as future chemoprevention targets, and be used in the development of a genetic diagnostic test to identify high-risk individuals.

Background & Significance: Phase I studies with the anti-programmed death-1 antibody (anti-PD-1), nivolumab, in advanced non-small-cell lung cancer (NSCLC) have demonstrated remarkably durable responses in heavily pretreated patients that lasted a median 17 months. However, in these studies very few patients have had tumors available for immune analysis, and basic data on immune measures pre- and post-treatment are not available. This study will move the treatment paradigm forward by assessing the safety and feasibility of preoperative anti-PD-1 in NSCLC and providing detailed information on the effect of PD-1 modulation on the lung tumor immune microenvironment.

Methods: Patients with newly diagnosed stage IB-IIIA NSCLC will receive two doses of nivolumab 3mg/kg IV on day-28 and day-14 prior to planned surgery on day 0. Serial blood samples for immune markers will be obtained. The primary endpoint of this study is the safety and feasibility of preoperative nivolumab in resectable NSCLC. For the exploratory immune analyses, initial tumor biopsy, post-treatment resection specimen, and serial peripheral blood samples will be evaluated for expression of immune markers with the primary comparison being intra-patient, pre- and post-treatment.

Experimental Approach & Statistical Analysis Plan: As this is the first time that nivolumab has been administered pre-operatively in NSCLC, the study will commence with a run-in phase where six patients will be monitored continuously for adverse events through eight weeks following surgery. Overall, the study will continue without pause to a 12-patient expansion phase if none or one of the six patients experiences DLT in the run-in. Detailed statistical plans for the safety and feasibility endpoints and exploratory immune endpoints are described in the main body of this application.

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.

Approximately 30% of patients with stage 1 non-small cell lung cancer (NSCLC) will die from recurrent disease despite surgical resection . Currently, there is a lack of reliable molecular predictors being routinely used in the clinic for identifying patients at high risk for developing recurrent disease and therefore may benefit from more aggressive therapies. To date several groups have applied microarray-based methods for global gene expression profiling of frozen tumor tissues in an attempt to identify prognostic ‘signatures’ in patients with early stage NSCLC.  Building upon this, through a meta-analysis of seven independent microarray studies Govindan et al. were able to identify a 64-gene signature that is highly predictive of survival in patients with stage I NSCLC. However, recent advances in high-throughput sequencing have enabled an unbiased view of the transcriptome including novel transcriptional events such as gene fusions, splicing variants, and novel transcripts. This offers an opportunity to incorporate additional markers, which may have eluded previous technologies, but could serve for improving a predictive signature of survival in non-small cell lung cancer (NSCLC). However, despite the potential of RNA-Seq to improve existing predictive signatures, we are still faced with the challenge of translating these findings into a platform where they can be reliably applied to formalin fixed paraffin embedded (FFPE) clinical tissue specimens routinely collected in tertiary referral centers. Therefore, this proposal focuses on refining the 64-gene predictive signature using transcriptome sequencing and developing a NanoString nCounter assay to reliably predict survival of patients with resected stage I NSCLC, using RNA derived from FFPE tumor blocks. To accomplish this we have proposed the following specific aims: (1) use transcriptome sequencing to detect molecular predictors of outcome in patients with stage I NSCLC, (2) validate the technical performance of the NanoString nCounter using an RNA-Seq predictive signature across FFPE tumor blocks of resected stage I NSCLC, and (3) clinically validate the prognostic power of the predictive signature across an independent sample set. Overall, if the proposed aims are met, this research could lead to an improved assay that could be translated into future prospective studies for risk-stratifying stage I NSCLC patients.

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.

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.