Early onset lung cancer, cigarette smoking and the SNP309 of the murine double minute-2 (MDM2) gene.

The polymorphism SNP309 (rs2279744) in the promoter region of the MDM2 gene has been shown to alter protein expression and may play a role in the susceptibility to lung cancer. The MDM2 protein is a key inhibitor of p53 and several mechanisms of MDM2/p53 interactions are presently known: modulating DNA-repair, cell-cycle control, cell growth and apoptosis.We used 635 Caucasian patients diagnosed with lung cancer before 51 years of age and 1300 healthy gender and age frequency matched population Caucasian controls to investigate the association between the MDM2 SNP309 and the risk of developing early onset lung cancer. Conditional logistic models were applied to assess the genotype-phenotype association, adjusted for smoking. Compared to the GG genotype, the adjusted ORs for the TG and TT genotype were 0.9 (95% CI: 0.7-1.5) and 1.0 (95% CI: 0.7-1.5), respectively. Also no association was found for histological subtypes of lung cancer. The strength of this study is that within young cases the genetic component to develop lung cancer may be greater. Our results indicate that the MDM2 SNP309 is not significantly associated with lung carcinogenesis but point towards gender-specific differences.

Do genetic factors protect for early onset lung cancer? A case control study before the age of 50 years.

BACKGROUND: Early onset lung cancer shows some familial aggregation, pointing to a genetic predisposition. This study was set up to investigate the role of candidate genes in the susceptibility to lung cancer patients younger than 51 years at diagnosis. METHODS: 246 patients with a primary, histologically or cytologically confirmed neoplasm, recruited from 2000 to 2003 in major lung clinics across Germany, were matched to 223 unrelated healthy controls. 11 single nucleotide polymorphisms of genes with reported associations to lung cancer have been genotyped. RESULTS: Genetic associations or gene-smoking interactions was found for GPX1(Pro200Leu) and EPHX1(His113Tyr). Carriers of the Leu-allele of GPX1(Pro200Leu) showed a significant risk reduction of OR = 0.6 (95% CI: 0.4-0.8, p = 0.002) in general and of OR = 0.3 (95% CI:0.1-0.8, p = 0.012) within heavy smokers. We could also find a risk decreasing genetic effect for His-carriers of EPHX1(His113Tyr) for moderate smokers (OR = 0.2, 95% CI:0.1-0.7, p = 0.012). Considered both variants together, a monotone decrease of the OR was found for smokers (OR of 0.20; 95% CI: 0.07-0.60) for each protective allele. CONCLUSION: Smoking is the most important risk factor for young lung cancer patients. However, this study provides some support for the T-Allel of GPX1(Pro200Leu) and the C-Allele of EPHX1(His113Tyr) to play a protective role in early onset lung cancer susceptibility.

[Therapeutic goals and outcome measurements in COPD patients]. / Therapieziele und Messungen des Therapieerfolgs bei COPD.

Due to the complex pathogenesis of chronic obstructive pulmonary disease (COPD) with systemic effects and different subjective perceptions, responses to therapy are difficult to assess. Though lung function tests correlate poorly with important features of the disease such as survival and quality of life, spirometric measures, especially forced expiratory volume (FEV(1)) and inspiratory capacity, the 6-min walk test, exacerbation indices, dyspnea scales and health status measurements remain important outcomes in clinical studies as well as in clinical practice. Markers of airway inflammation are receiving increased attention. The BODE index, combining functional and systemic outcomes, is a better predictor of mortality than FEV(1) and, therefore, particularly valuable.

Pro-gastrin-releasing peptide (ProGRP), neuron specific enolase (NSE), carcinoembryonic antigen (CEA) and cytokeratin 19-fragments (CYFRA 21-1) in patients with lung cancer in comparison to other lung diseases.

The study presents data comparing the new tumour marker, ProGRP, with the established markers, NSE, CYFRA 21-1 and CEA in the diagnosis of lung cancer. ProGRP as well as NSE have been reported to be useful markers for staging and monitoring treatment in patients with small cell lung cancer (SCLC). In order to determine the differences in the sensitivity and/or specificity particularly with regard to benign lung diseases, the present study investigated ProGRP in comparison to NSE, CEA and CYFRA 21-1 usually used in lung cancer. ProGRP was quantitatively detectable with an ELISA. So far 192 newly-diagnosed lung cancer patients including 51 SCLC have been examined. Served as controls: 124 subjects i.e. 50 patients with pneumoconiosis, 22 patients with obstructive airway diseases, 34 patients with acute inflammatory lung diseases and 18 healthy persons. Significantly elevated tumour marker concentrations were found for ProGRP and NSE in SCLC. At a specificity of 95%, ProGRP and NSE showed comparable sensitivities (68.6% and 74.5%) in SCLC. ProGRP also reached high levels in patients with limited disease status (sensitivity ProGRP: 72.2%, NSE 66.7%). Initial follow-up studies indicated that ProGRP can be used to monitor disease under chemotherapy. In non-small cell lung carcinomas, CYFRA 21-1 was the leading marker with 58.9% sensitivity where ProGRP seldom revealed positive results. ProGRP is a valuable tumour marker for the detection and monitoring of SCLC and a good tool for discriminating NSCLC versus SCLC.

Fuzzy logic-based tumor marker profiles including a new marker tumor M2-PK improved sensitivity to the detection of progression in lung cancer patients.

In lung cancer patients tumor markers are used for disease monitoring. The goal of this study was to improve diagnostic efficiency in the detection of tumor progression in lung cancer patients by using fuzzy logic modeling in combination with a tumor marker panel (Tumor M2-PK, CYFRA 21-1, CEA, NSE and SCC). Thirty-three small cell lung cancers (SCLC) and 69 consecutive inoperable patients (40 squamous and 29 adenocarcinomas) were included in a prospective study. The changes of blood levels of tumor markers as well as their analysis by fuzzy logic modelling were compared to the clinical evaluation of response vs. non-response to therapy. Clinical monitoring was evaluated according to the standard criteria of the WHO. Tumor M2-PK was measured in plasma with an ELISA (ScheBo Biotech, Germany) and all other markers in sera (Roche, Germany). At a 90% specificity, the respective best single marker found the following fraction of all patients who had tumor progression clinically detected: in SCLC with NSE 52%, in adenocarcinoma with CYFRA 21-1 89% and in squamous carcinoma with SCC 65%. A fuzzy logic rule-based system employing a tumor marker panel increased the sensitivity in small cell carcinomas to 73% with the marker combination NSE/CEA and to 63% with the marker combination NSE/Tumor M2-PK, respectively. In squamous carcinomas an improvement of sensitivity is also observed using the marker combination of SCC/Tumor M2-PK (Sensitivity: 81%) or SCC/CEA (Sensitivity: 71%). By using the fuzzy logic method and the marker combination CYFRA 21-1/CEA as well as CYFRA 21-1/Tumor M2-PK, the detection of lung cancer progression was possible in all adenocarcinomas. With the fuzzy logic method and a tumor marker panel (including the new marker Tumor M2-PK), a useful diagnostic tool for the detection of progression in lung cancer patients is available.

Tumor M2-pyruvate kinase in the follow-up of inoperable lung cancer patients: a pilot study.

Tumor markers were used for disease monitoring in lung cancer patients. The goal of this pilot study was to determine the diagnostic efficiency of a new tumor metabolic marker, Tumor M2-pyruvate kinase (Tumor M2-PK) for the detection of tumor growth in inoperable lung cancer patients.Fifty-seven consecutive and primary inoperable lung cancer patients were included in this prospective study. Changes in plasma levels of Tumor M2-PK were compared to the clinical course of the disease. Clinical monitoring was evaluated according to the standard criteria of the WHO. Of the 57 patients, 19 were in remission, 18 showed signs of stable disease and there were 20 tumor progressions under therapy. In the further follow-up after treatment, tumor relapse occurred in 30 patients. Tumor M2-PK was measured in plasma before and after treatment as well as at time of relapse. During tumor remission Tumor M2-PK levels decreased significantly under treatment (P=0.0004). As might be expected, pre- and post-treatment marker concentrations did not differ significantly in patients with stable disease. In progressive lung cancer patients a significant increase in Tumor M2-PK was detectable (P=0.0094). Overall, a decrease of Tumor M2-PK was seen in 17 (89%) of all responders, while an increase could be detected in 16 (80%) of the patients experiencing tumor progression. After treatment tumor relapse occurred in 30 patients. Tumor M2-PK increased significantly (P=0.0201) at time of relapse in 17 patients with non-small cell lung cancers and exceeded the cut-off in 11 of the 17 (65%). In conclusion, Tumor M2-PK proved useful as a diagnostic aid for therapy control in lung cancer patients. This marker can also be used to detect tumor relapse after treatment. Tumor M2-PK could be well suited to complete the present diagnostic panel for monitoring of inoperable lung cancer patients.

Fuzzy logic-based tumor-marker profiles improved sensitivity in the diagnosis of lung cancer.

BACKGROUND: The aim of this study was to improve the diagnostic efficiency of tumor markers in the diagnosis of lung cancer, by the mathematical evaluation of a tumor marker profile employing fuzzy logic modelling. METHODS: A panel of four tumor markers, i.e., carcinoembryonic antigen (CEA), cytokeratin 19 antibody (CYFRA 21-1), neuron-specific enolase (NSE), squamous cell carcinoma-related antigen (SCC) and, additionally, C-reactive protein (CRP), was measured in 175 newly diagnosed lung cancer patients with different histological types and stages. Results were compared with those in 120 control subjects, including 27 with chronic obstructive pulmonary diseases (COPD), 65 with pneumoconiosis, and 11 persons with acute inflammatory lung diseases. A classificator was developed using a fuzzy-logic rule-based system. RESULTS: Application of the fuzzy-logic rule-based system to the tumor marker values of CYFRA 21-1, NSE, and CRP yielded an increase in sensitivity of approximately 20%, i.e., 92%, compared with that of the best single marker, CYFRA 21-1(sensitivity, 72%). The corresponding specificity was 95%. The fuzzy classificator significantly improved the sensitivity of the tumor marker panel in stages I and IIIa for non-small-cell lung cancer, as well as in "limited disease" status for small-cell lung cancer. Also, the diagnosis of other stages of lung cancer was enhanced. CONCLUSION: Fuzzy-logic analysis was proven to be more powerful than the measurement of single markers alone or combinations using multiple logistic regression analysis of all markers. Therefore, fuzzy logic offers a promising diagnostic tool to improve tumor marker efficiency.