Stage I

Lung cancer accounts for more than 28 percent of all cancer deaths each year and is the leading cause of cancer related mortality in the United States causing more deaths than prostate, colon and breast cancers combined Despite focused research in conventional therapies, the five-year survival rate remains only 15 percent. Due to anti-tobacco initiatives the number of active smokers in the US is steadily declining, however recent studies suggest that individuals who quit smoking continue to have an elevated risk of lung cancer that may not return to baseline risk for as much as 30 years following smoking cessation. Owing to the lack of reliable early diagnostic techniques, most patients are being diagnosed with advanced stage disease that his inoperable and therefore they have a poor prognosis. Thus, 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 for lung cancer may have undetected disease for years prior to diagnosis. The clinical challenge is therefore 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 microenvironment that is comprised of many components and cell types. These complex cellular populations produce many soluble factors that could be important for tumor initiation and growth and thus potentially serve as lung cancer biomarkers. Small tumors, initiated in this environment, may remain undetected; however, the profile of soluble factors produced by the tumor mircorenvironment will be altered in the peripheral blood of cancer patients and could therefore have utility for the development of a diagnostic panel for early lung cancer detection. Because the blood vessels in the lungs comprise approximately 50% of the body’s total vasculature, the peripheral blood is expected to serve as a non-invasive biospecimen that reflects even small variations in lung cancer biomarkers.  We hypothesize that interactions between tumor cells and host cells recruited into the local tumor microenvironment will result in the production of a unique biomarker signature composed of proteins and microRNA (miRNA) important for cancer progression.

Over the past decade, our laboratory has gathered substantial data supporting the analysis of soluble mediators of lung carcinogenesis including inflammatory, growth and angiogenic factors and miRNA. Additionally, since our early investigations, 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 distinguishes smokers with and without lung cancer. Our predictive model provided 97% sensitivity.

Even with all of the targeted therapies being developed today, lung cancer is only curable when diagnosed early enough for surgical resection, or combined chemotherapy and thoracic radiation. The recent finding that screening CTs to identify early stage lung cancers can reduce mortality also refocuses our efforts on improving the definitive therapy of localized disease. In most studies, however, cure rates for stage I or II lung cancers are between 50 and 70%, and chemotherapy after surgery improves this only a few percent, and chemotherapy is toxic in almost all patients. The point of these studies is to increase the number of cures achieved in patients with early stage lung cancer and minimize the side-effects of therapy by attacking 3 goals: 1) identifying which tumors are likely to relapse and thus might benefit from additional therapy, 2) identifying which patients will benefit from the addition of chemotherapy after surgery, and 3) figuring out which signals in tumors are associated with those that will relapse to define new types of treatment targeted at these signals. We will take the novel approach of using both state-of-the-art evaluation of both proteins and genes in the same cells to define these groups.

Lung cancer is the leading cause of death for men and women in the United States. Contributing to the lethality of this disease is our inability to detect treatable early stage lung cancer resulting in the majority of lung cancer patients being diagnosed with incurable advanced disease. Computerized tomography (CT) screening has shown promising preliminary results in the detection of early stage lung cancer (with a 20% reduction in lung cancer mortality); however, it remains to be determined how it will be incorporated into standard practice. Biomarker-based screening methods that complement CT – and that are accessible to all current and former smokers – will be vital to making early lung cancer detection more attractive. Our goal at UC Davis is to combine our multidisciplinary leaders in lung cancer practice and research (Drs. Kelly, Gandara, Cooke, Yoneda and Murin) with “omics” experts (Drs. Miyamoto, Fiehn, and Lebrilla), who have developed sensitive technologies to detect and analyze sugars, lipids, and metabolites in human specimens, to identify blood biomarkers for early stage lung cancer that can be used in conjunction with CT screening. We will examine biomarker compositions of tumor tissue, non-malignant tissue, and blood in cancer patients, healthy controls and patients with benign lung nodules, to ultimately identify easily detectible blood markers that: 1) will detect early stage cancer and 2) are sensitive and specific. Such biomarkers will contribute to earlier, more informative lung cancer detection and make tailored lung cancer therapy and increased cure rates possible.

Lung cancer is the leading cause of cancer death in the world and has a dismal 16% 5 year survival rate. One reason for this discouraging statistic is that until recently, no early detection test had been validated. The National Lung Screening Trial (NLST) has recently demonstrated that CT screening results in a 20.3% decrease in lung cancer mortality compared to chest radiograph screening. It is now clear that CT scans will be increasingly used for lung cancer screening.

CT scans detect lung nodules in 20-50% of patients, while only 1-2% have lung cancer. Thus, CT scanning has low specificity (many false positive tests) for lung cancer. Patients and physicians are often put in the situation of having to decide between serial CT scans to look for nodule enlargement (which takes months) or an immediate biopsy strategy. Each approach has potential drawbacks: serial observation can result in delay in diagnosis and an immediate biopsy strategy can lead to unnecessary morbidity and expense. Biomarker based testing to determine risk for lung cancer is not currently available, but would be invaluable in aiding clinical decision making in this setting.

We propose to further refine and validate two promising risk biomarkers, abnormal chromosome numbers in sputum cells and a blood test assessing multiple bioactive proteins as guides to clinical decision making for patients and physicians confronted with indeterminate lung nodules and compare their performance to prediction models based on nodule and patient characteristics.

With the widespread availability of computed tomography (CT), an estimated 20 million chest CT-scans are now performed annually in the United States. From these studies about 4 million individuals have pulmonary nodules detected that require further evaluation. Only about 1-in-37 of these nodules will be lung cancer, even among high-risk individuals. Clinicians are charged with rapidly identifying the individuals with malignancy while minimizing the number of unnecessary testing to those without. The objective for the proposed studies is to develop a non-invasive test with excellent performance characteristics across the spectrum of clinical presentations of indeterminate pulmonary nodules would reduce the number of unnecessary invasive procedures and minimize the time from detection to diagnosis. Our hypothesis contends that, in the case of early-stage lung cancer, tumors possess a unique molecular phenotype that is discernable from highly-inflammatory, non-malignant/benign lesions commonly detected by CT-based imaging studies. A portion of these molecules are tumor-shed and provoke an immune response that can be exploited for diagnostic purposes. Our approach to address this matter is to use immunoproteomic methods to identify candidate biomarkers from clinical specimens that are useful for discerning non-neoplastic/benign nodules from malignacy. Next, we will develop and validate Luminex assays for no less than 20 candidate biomarkers and evaluate these internally to identify the optimal combination of biomarkers to form a diagnostic algorithm for this purpose. Finally, algorithm validation against external patient cohorts (in our possession) will be performed to evaluate the potential for future clinical application.