While a majority of lung cancer patients have a history of tobacco use, the variation in lung cancer risk among smokers can be 20-fold. One well-documented host factor related to the risk of lung cancer is COPD, including emphysema and chronic bronchitis. COPD shares common etiologic factors with lung cancer, particularly cigarette smoking. Previous studies have suggested that a1-antitrypsin deficiency (A1ATD) not only can cause emphysema but is also associated with an increased risk of multiple malignancies, including lung cancer. Several mechanisms of tumorigenesis have been postulated between A1ATD and lung cancer development, as follows: excess neutrophil elastase, the counterpart of a1-antitryp-sin, may facilitate cancer development by causing tissue damage and air trapping that fosters longer carcinogen exposure; may promote cancer progression by degrading the intercellular matrix barrier; and may lead to cancer development through the tumor necrosis factor signaling pathway. To test the hypothesis that a1-antitrypsin and neutrophil elastase may be critical in the causal pathway from tobacco smoke exposure to lung cancer development, we conducted a case-control study using functionally significant polymorphic markers to assess the role of protease inhibitor-1 (PI1) and neutrophil elastase-2 (ELA2), which encode functional variations of the two proteins in lung cancer risk in concert with known environmental and host factors.
Study Participants and Data Collection
The research protocol was approved by the Mayo Clinic Institutional Review Board. Written informed consent was obtained from all subjects. As reported previously, 305 case patients were consecutively enrolled into the study from among patients who had received diagnoses and/or been treated for pathologically confirmed primary lung cancer at the Mayo Clinic between 1997 and 2001. Eligible patients were invited to participate in a baseline interview and a peripheral blood sample collection.
The 338 control subjects were frequency-matched to case patients by age, sex, and ethnic background from a pool of 2,335 Olmsted County, MN, residents who had attended the Mayo Clinic between 1998 and 2002, and who had a blood sample left over from their clinical tests. This design was chosen because Mayo Clinic is a major primary care provider for the local population, and > 90% of Olmsted County residents visit the Mayo Clinic at least once during any 3-year period. Eligible control subjects had no current or previously diagnosed malignancy (except nonmelanoma skin cancer) as of the date of phlebotomy. Control subjects received a self-administered questionnaire and a request for permission to use their leftover blood samples. Drugs should be of high quality to help to avoid the severe ramifications. Such kind of drugs you may find on Canadian Neighbor Pharmacy.
Data collected included information regarding each first-degree relative and the ancestral background of each subject’s paternal and maternal grandparents. The ethnic backgrounds of the case patients and control subjects were very similar, consisting mostly of white persons of non-Hispanic origin from the United States. Minority groups included African Americans, American Indians, Alaskan Natives, Asians and Pacific Islanders, Hispanics, and other ethnicities. Never-smokers were defined as those persons who had smoked < 100 cigarettes during their Lifetime. Data collected from ever-smokers (former and current) included age of smoking initiation, years of smoking (duration), cigarettes smoked per day (intensity), and date of smoking cessation. A detailed environmental tobacco smoke history was also obtained.
PI1 Allele Typing
To identify PI1 alleles, an isoelectric focusing (IEF) test (ie, a1-antitrypsin allele typing or phenotyping) was performed. IEF has been the standard clinical diagnostic test for A1ATD for > 20 years in the United States and Europe, and the proteins that have been separated in the electrophoresis gel are visualized with a Coomassie Blue protein stain. Over 70 variants of ar antitrypsin have been reported, each named by a letter of the alphabet, are transmitted as a codominant gene (PI1). Over 60 of these variants are rare (ie, < 0.001 of allelic frequency) and are infrequently observed in the general population. The majority of the population is MM type or some combinations of its subtypes (ie, M1, M2, or M3), all of whom have normal serum ar antitrypsin levels of 110 to 200 mg/dL. A1ATD (ie, serum a1-antitrypsin level, < 80 mg/dL) is mainly seen in individuals with ZZ, SZ, SS, II, and null types. The serum a1-antitrypsin levels are marginally normal in those who persons who are heterozygous for the Z or S allele (serum a1-antitrypsin level, 70 to 110 mg/dL). The two common variants that produce the A1ATD phenotype are Z and S, and the rare variants include I, null, and others. We included all deficient alleles in the definition of PI1 allele type or high-risk allele type.
Quality control of the test results was exercised by the following four approaches: (1) one reference control sample was placed for every four lanes on each gel; (2) rare alleles was repeated next to the reference sample; (3) a quantitative assay was repeated to verify low values of < 100 mg/dL; and (4) when the allele type did not correspond to the a1-antitrypsin levels, both assays were repeated to rule out the possibility of mismatched samples. As a systematic measure of the error rate, IEF and nephelometry were repeated on 5% of the study subjects, and the results showed a 100% agreement between the original test and the repeated test.
Polymorphic Markers for Neutrophil Elastase Gene
ELA2 is the designated name (symbol) for the neutrophil elastase gene. ELA2 maps to chromosome 19p13-3 and is approximately 50 kb. A workstation (NanoChip Molecular Biology workstation; Nanogen; San Diego, CA) was employed in determining the genotypes at two ELA2 promoter region singlenucleotide polymorphism (SNP) sites, -903 (Rep_a) and -741 (Rep_b). Patient genomic DNA samples (20 ng) were amplified in a 384-well thermocycler (model 9700; ABI) in 20-^L reactions containing 0.5 μmol/L biotinylated primers (5′ AGG ACC AGA GAA GTG CCT ATT GC 3′-FORWARD; 5′ CAA ACC TGC CAA ACC TAG ACC TG 3′-REVERSE), 2 mmol/L MgCl2, and standard amounts of the remaining reagents. Forty 30-s cycles of polymerase chain reaction were performed at an annealing temperature of 58°C. The reactions were purified using polymerase chain reaction clean-up plates (MultiScreen; Milipore; Billerica, MA) and were rehydrated in 20 μL ddH2O. The average concentrations were approximately 10 ng/μL. Ten microliters of each sample was added to 35 μL 100 mmol/L histidine, which was brought to 70 μL with the addition of water, and was loaded onto a 96-pad microarray (NanoChips; Nanogen), which were subsequently probed with allele-specific 5′ Cy dye-labeled oligos (ELA2-903 5′-cy5-GGC CCT GTG A, 5′-cy3- GGC CCT GTG C, stabilizer 5′-TAC CGG CCA CAT GCA GCT GTG TCG CC; ELA2-741 5′-cy5- CGG TAT CAC G, 5′-cy3-CGG TAT CAC G, and stabilizer 5′ GGG CCC TGG GTA AAC TGA GGC A), and were scanned. The —903 T/G SNP was discriminated at 39°C in a 50 mmol/L sodium phosphate buffer and was easily genotyped based on dye signals. The — 741G/A SNP was discriminated by a melting profile of 24 to 42°C. Quality control was exercised by the inclusion of genomic DNA control subjects in every plate. The use of a robotic workstation to aliquot DNA for each assay minimized sample switching. All data were reviewed by the laboratory director (J.M.C.) before analysis.
ELA2 Rep_a and Rep_b Haplotype Analysis
Haplotypes are specific combinations of nucleotides on the same chromosome. SNP markers within the same gene may not be independent, such as the two SNP sites in the ELA2 locus. They may be coinherited because of linkage disequilibrium (LD), and they may jointly influence the function of the resulting protein. We employed a new method to test the statistical association between haplotypes and phenotypes for case-control studies, as described by Schaid et al This method uses an expectation-maximization algorithm to infer haplotypes, and accounts for ambiguity in haplotype assignment when comparing case patients to control subjects and allows adjustment for nongenetic covariates (eg, tobacco smoking history), which are critical when analyzing genetically complex phenotypes like lung cancer. This method also provides several different global tests for association, as well as haplotype-specific tests, which give a meaningful advantage in attempting to understand the roles of many different haplotypes. We used D’ and r2 to quantify and compare LD. Values of D’ near unity and r2 of more than one third are considered to be indicative of a strong LD and of correlation between the two markers, respectively.
Our goal was to identify and quantify the elevated lung cancer risk imposed by PI1 and ELA2 genotypes (Table 1) in concert with known environmental and host factors. Standard contingency table methods were used for testing whether the high-risk genotype or haplotype frequency is different in lung cancer patients than in control subjects. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated to quantify any significant association using logistic regression models. These models used case/control status as an outcome variable, and high-risk genotype, existing chronic lung disease, history of tobacco smoke exposure, and hypothesis-driven two-way interactions of these variables, as well as other known confounding variables (eg, family history), as possible predictor variables. The magnitude of each effect was estimated by the variable-specific regression coefficient. The impact of family history on these models was adjusted by incorporating binary dummy variables into the conditional logistic regressions. Then multivariable models for genotypes and haplotypes were built to generate a lung cancer risk-predicting model system. We obtained estimates of ORs and CIs for the inferred haplotypes using weighted logistic regression analysis (HaploStats program). Separate models were built under the alternative mendelian inheritance predictions of dominance between the inferred hap-lotypes of each person (ie, autosomal-dominant, additive [codominant], or recessive). The best-fit model was judged by the information criteria of Akaike.
Table 1—Hypothetical a1-Antitrypsin and Neutrophil Elastase Imbalance and Predicted Effect on Lung Cancer Risk
|Risk Category by Both Genes||Measured PI1 Genotypes/ELA2 Rep-a/b Haplotypes||^ATLevel/Function||NE Level/Function||Predicted Effects on Lung Cancer Risk|
|0. No high-risk allele||d/G-A||Normal range||Normal range||Baseline risk|
|I. 1 high-risk allele||D/G-A or d/T-A or d/G-G||Lower or normal||Normal or higher||Increased risk|
|II. 2 high-risk alleles||D/T-A or D/G-G or d/T-G||Lower or normal||Higher||Increased risk|
|III. 3 high-risk alleles||D/T-G||Lower||Higher||Increased risk|