Biomarker or biomarker testing

There is recent evidence that metformin, a drug commonly used to treat diabetes, has anticancer effects and can significantly improve the rate of pathological response in breast cancers treated with chemotherapy. We propose to review clinical records of lung cancer patients treated over the past 25 years at Johns Hopkins to determine whether metformin treatment is associated with improved clinical response to chemotherapy for lung cancer. Because our preliminary laboratory work suggests that lung cancer cells with mutations of the LKB1 gene are particularly sensitive to metformin, we will secondarily determine whether mutations of the LKB1 gene (which is mutated in up to 40% of lung adenocarcinomas) are associated with a higher frequency of response to chemotherapy among these patients treated with metformin. In a second specific aim, we will conduct studies using xenografts of human lung cancers in the laboratory to further examine possible links between LKB1 mutations and response to metformin, with or without paclitaxel. Establishing such a link could lead to improved chemotherapy (using metformin in combination with conventional chemotherapy drugs) and to development of a biomarker that can identify patients with cancers who might have improved response to chemotherapy with metformin.

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.

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.

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.

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.

Melanoma has the highest propensity to metastasize to the brain once the disease has spread, while non-small cell lung cancer (NSCLC) has the highest incidence of brain metastases among all cancers. Approximately 50,000 patients develop brain metastases from these diseases every year. Patients with brain metastases have exceedingly limited therapeutic options since they are typically excluded from clinical trials. Recently a number of new systemic immune therapies, such as nivolumab (BMS-936558) and lambrolizumab (MK-3475), two inhibitors of PD-1 (an immune inhibitory molecule), have led to dramatic responses in metastatic melanoma (MM) and NSCLC. However, these therapies have not been studied in patients with untreated brain metastases.  Little is known about immune cells in the brain, and whether the immune system can be stimulated to reject cancer cells. Moreover, little is known about what tumor characteristics are associated with response to MK-3475 in brain metastases. This proposal includes innovative correlative biomarker studies incorporated into a clinical trial uniquely designed to study the activity of MK-3475 in patients with limited, small brain metastases in MM and NSCLC. This drug carries the hope to provide prolonged responses similar to responses seen in other metastatic sites, and might enable patients to avoid radiation therapy, and improve their outcome. As part of this clinical trial, we will collect brain and other metastatic specimens from patients enrolled and study the expression of immune inhibitory molecules utilizing a novel quantitative assay and algorithms that we have developed in preliminary work. These studies will facilitate selection of patients who are more likely to respond to this class of drugs.

Cancer-associated fibroblasts (CAFs) support the growth of lung cancer cells in vivo by secretion of soluble factors that stimulate the growth of tumor cells. One such soluble factor is CLCF1. Functional studies in our laboratory identified an important role for CLCF1–CNTFR signaling in promoting growth of NSCLCs. NSCLC cell lines as well as patient-derived xenografts were found to express CNTFR, and knock-down of CNTFR leads to decreased proliferation. To test the use of CNTFR blockade as an anti-cancer therapy, we developed a soluble version of CNTFR (i.e., a CNTFR “receptor decoy”) that can be expressed from an adenoviral vector (Ad-sCNTFR-Fc). Preliminary experiments indicate that Ad-sCNTFR-Fc can block proliferation of a NSCLC cell line in vitro. Our proposed studies build on an established translational research program that includes intensive efforts to harvest and analyze primary tumor samples and CAFs directly from patients. In Aim 1, we will test the therapeutic efficacy of Ad-sCNTFR-Fc in a panel of patient-derived xenografts (PDX) as well as established cell lines. In Aim 2, to increase therapeutic efficacy, we will use protein engineering to develop a high-affinity sCNTFR that can more effectively block CLCF1-CNTFR interactions, and will evaluate this therapeutic candidate in PDX models. In Aim 3, we will establish the utility of using plasma CLCF1 as a biomarker for CLCF1 production in CAFs isolated directly from patient tumors. Parallel analysis of CAF and plasma CLCF1 will establish if CLCF1 in plasma correlates with CLCF1 in tumors and is thus a useful biomarker.

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.

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.