ABSTRACT
BACKGROUND: Low-dose computed tomography (CT) for lung cancer screening can reduce lung cancer mortality. The National Lung Screening Trial reported a 20% reduction in lung cancer mortality in high-risk smokers. However, CT scanning is extremely sensitive and detects non-calcified nodules (NCNs) in 24-50% of subjects, suggesting an unacceptably high false-positive rate. We hypothesized that by reviewing demographic, clinical and nodule characteristics, we could identify risk factors associated with the presence of nodules on screening CT, and with the probability that a NCN was malignant. METHODS: We performed a longitudinal lung cancer biomarker discovery trial (NYU LCBC) that included low-dose CT-screening of high-risk individuals over 50 years of age, with more than 20 pack-year smoking histories, living in an urban setting, and with a potential for asbestos exposure. We used case-control studies to identify risk factors associated with the presence of nodules (n=625) versus no nodules (n=557), and lung cancer patients (n=30) versus benign nodules (n=128). RESULTS: The NYU LCBC followed 1182 study subjects prospectively over a 10-year period. We found 52% to have NCNs >4 mm on their baseline screen. Most of the nodules were stable, and 9.7% of solid and 26.2% of sub-solid nodules resolved. We diagnosed 30 lung cancers, 26 stage I. Three patients had synchronous primary lung cancers or multifocal disease. Thus, there were 33 lung cancers: 10 incident, and 23 prevalent. A sub-group of the prevalent group were stable for a prolonged period prior to diagnosis. These were all stage I at diagnosis and 12/13 were adenocarcinomas. CONCLUSIONS: NCNs are common among CT-screened high-risk subjects and can often be managed conservatively. Risk factors for malignancy included increasing age, size and number of nodules, reduced FEV1 and FVC, and increased pack-years smoking. A sub-group of screen-detected cancers are slow-growing and may contribute to over-diagnosis and lead-time biases.
Subject(s)
Adenocarcinoma, Bronchiolo-Alveolar/diagnostic imaging , Adenocarcinoma, Bronchiolo-Alveolar/mortality , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/mortality , Tomography, X-Ray Computed , Urban Population , Adult , Age Factors , Aged , Aged, 80 and over , Case-Control Studies , Female , Humans , Male , Middle Aged , Risk Factors , Smoking/adverse effects , Time FactorsABSTRACT
BACKGROUND: Sera from lung cancer patients contain autoantibodies that react with tumor associated antigens (TAAs) that reflect genetic over-expression, mutation, or other anomalies of cell cycle, growth, signaling, and metabolism pathways. METHODS: We performed immunoassays to detect autoantibodies to ten tumor associated antigens (TAAs) selected on the basis of previous studies showing that they had preferential specificity for certain cancers. Sera examined were from lung cancer patients (22); smokers with ground-glass opacities (GGOs) (46), benign solid nodules (55), or normal CTs (35); and normal non-smokers (36). Logistic regression models based on the antibody biomarker levels among the high risk and lung cancer groups were developed to identify the combinations of biomarkers that predict lung cancer in these cohorts. RESULTS: Statistically significant differences in the distributions of each of the biomarkers were identified among all five groups. Using Receiver Operating Characteristic (ROC) curves based on age, c-myc, Cyclin A, Cyclin B1, Cyclin D1, CDK2, and survivin, we obtained a sensitivity = 81% and specificity = 97% for the classification of cancer vs smokers(no nodules, solid nodules, or GGO) and correctly predicted 31/36 healthy controls as noncancer. CONCLUSION: A pattern of autoantibody reactivity to TAAs may distinguish patients with lung cancer versus smokers with normal CTs, stable solid nodules, ground glass opacities, or normal healthy never smokers.
Subject(s)
Antigens, Neoplasm/immunology , Autoantibodies/blood , Lung Neoplasms/immunology , Smoking/immunology , Aged , Early Detection of Cancer , Female , Humans , Immunoassay , Logistic Models , Lung Neoplasms/diagnostic imaging , Male , Middle Aged , Predictive Value of Tests , Proportional Hazards Models , ROC Curve , Risk Assessment , Risk Factors , Smoking/adverse effects , Tomography, X-Ray ComputedABSTRACT
BACKGROUND: S-Adenosylmethionine (AdoMet) is a major methyl donor for transmethylation reactions and propylamine donor for the biosynthesis of polyamines in biological systems, and therefore may play a role in lung cancer development. We hypothesized that AdoMet levels were elevated in patients with lung cancer and may prove useful as a biomarker for early lung cancer. METHODS: High-performance liquid chromatography was used to analyze plasma AdoMet levels in triplicate samples from 68 patients. This included 13 patients with lung cancer, 33 smokers with benign lung disease, and 22 healthy nonsmokers. The three groups of subjects were compared with respect to the distribution of demographic and disease characteristics and AdoMet levels. Distributions were examined using summary statistics and box plots, and nonparametric analysis of variance procedures. RESULTS: Serum AdoMet levels were elevated in patients with lung cancer as compared to smokers with benign lung disorders and healthy nonsmokers. There were no significant correlations between AdoMet levels and tumor cell types, nodule size, or other demographic variables. CONCLUSIONS: Our data demonstrate that plasma levels of AdoMet are significantly elevated in patients with lung cancer. Plasma AdoMet levels may prove to be a useful tool for the diagnosis of early lung cancer, in combination with chest CT. Registered at: clinicaltrials.gov (NCT00301119).
