Citations

Abstract Background: The International Lung Cancer Consortium was established in 2004. To clarify the role of DNA repair genes in lung cancer susceptibility, we conducted a pooled analysis of genetic variants in DNA repair pathways, whose associations have been investigated by at least 3 individual studies. Methods: Data from 14 studies were pooled for 18 sequence variants in 12 DNA repair genes, including APEX1, OGG1, XRCC1, XRCC2, XRCC3, ERCC1, XPD, XPF, XPG, XPA, MGMT, and TP53. The total number of subjects included in the analysis for each variant ranged from 2,073 to 13,955 subjects. Results: Four of the variants were found to be weakly associated with lung cancer risk with borderline significance: these were XRCC3 T241M [heterozygote odds ratio (OR), 0.89; 95% confidence interval (95% CI), 0.79-0.99 and homozygote OR, 0.84; 95% CI, 0.71-1.00] based on 3,467 cases and 5,021 controls from 8 studies, XPD K751Q (heterozygote OR, 0.99; 95% CI, 0.89-1.10 and homozygote OR, 1.19; 95% CI, 1.02-1.39) based on 6,463 cases and 6,603 controls from 9 studies, and TP53 R72P (heterozygote OR, 1.14; 95% CI, 1.00-1.29 and homozygote OR, 1.20; 95% CI, 1.02-1.42) based on 3,610 cases and 5,293 controls from 6 studies. OGG1 S326C homozygote was suggested to be associated with lung cancer risk in Caucasians (homozygote OR, 1.34; 95% CI, 1.01-1.79) based on 2,569 cases and 4,178 controls from 4 studies but not in Asians. The other 14 variants did not exhibit main effects on lung cancer risk. Discussion: In addition to data pooling, future priorities of International Lung Cancer Consortium include coordinated genotyping and multistage validation for ongoing genome-wide association studies. (Cancer Epidemiol Biomarkers Prev 2008;17(11):3081–9)

Purpose Gene expression profiling for outcome prediction of non–small-cell lung cancer (NSCLC) remains clouded by heterogeneous and unvalidated results. This study applied multivariate approaches to identify and evaluate value-added gene expression signatures in two types of NSCLC. Materials and Methods Two NSCLC oligonucleotide microarray data sets of adenocarcinoma and squamous cell carcinoma were used as training sets to select prognostic genes independent of conventional predictors. The top 50 genes from each set were used to predict the outcomes of two independent validation data sets of 84 and 91 NSCLC cases. Results Adenocarcinomas with the 50-gene signature from adenocarcinoma in both validation data sets had a 2.4-fold (95% CI, 1.3 to 4.4 and 1.0 to 5.8) increased mortality after adjustment for conventional predictors. Squamous cell carcinoma with this high-risk signature had an adjusted risk of 1.1 (95% CI, 0.4 to 3.2) in one data set and 2.5 (95% CI, 1.1 to 5.8) in another consisting of stage I tumors. Adenocarcinoma with the 50-gene signature from squamous cell carcinoma had an elevated risk of 3.5 (95% CI, 1.4 to 9.0) after adjustment for conventional predictors. Squamous cell carcinoma with this high risk signature had an adjusted risk of 1.8 (95% CI, 0.7 to 4.6). Despite the little overlap in individual genes, the two gene signatures had significant functional connectedness in molecular pathways. Conclusion Two non-overlapping but functionally related gene expression signatures provide consistently improved survival prediction for NSCLC regardless of histologic cell type. Multiple sets of genes may exist for NSCLC with predictive value, but ones with independent predictive value beyond clinical predictors will be required for clinical translation.

Abstract Purpose. Previous studies have found that marriage is associated with longer survival and better quality of life among lung cancer patients. The present study used the Mayo Clinic Lung Cancer Cohort to re-examine this issue. Methods. In total, 5,898 non-small cell lung cancer (NSCLC) patients, who had available information on marital status and who had been enrolled in the Mayo Clinic Lung Cancer Cohort (MCLCC), were the focus of this study. Patients had extensive baseline and follow-up data on cancer stage, cancer treatment, and prognostic factors. All patients had been followed within the MCLCC with at least annual confirmation of vital status and patient-reported quality of life (the Lung Cancer Symptom Scale and the Linear Analogue Scales of Assessment). Results. The numbers of patients who were married, single, divorced, and widowed at the time of cancer diagnosis were 4,457 (76%), 265 (4%), 440 (7%), and 736 (12%), respectively. No statistically significant difference in survival was observed among these four groups, even after adjusting for a variety of prognostic factors, such as age, gender, and tumor stage. However, exploratory analyses suggested that widowed and divorced patients received less aggressive cancer therapy, and certain patient subgroups, such as stage IA widowed patients, had a shorter survival. Divorced patients reported greater financial concerns, and married and widowed patients reported greater spirituality and better social support. Conclusion. This study did not observe differences in survival or quality of life based on marital status at the time of diagnosis of NSCLC, but subgroup analyses appear to suggest findings worthy of further exploration.

AbstractEvidence for familial aggregation of glioma has been documented in both case-control and cohort studies and occurs apart from the well-described rare inherited genetic syndromes involving glioma: neurofibromatosis type 1 and 2, tuberous sclerosis, Turcot's syndrome, and Li-Fraumeni syndrome. Nonsyndromic glioma families have been studied but no genes have been identified in the two published linkage studies of familial glioma probably due to the small number of families. Because glioma is a rare but devastating cancer, and a family history of glioma has been observed in ∼5% of the cases, we initiated an international consortium to identify glioma families not affected by syndromes to better understand the inherited factors related to this disease. The international consortium GLIOGENE is an acronym for “glioma gene” and includes 15 research groups in North America, Europe, and Israel to study familial glioma. The overarching goal is to characterize genes in glioma families using a genome-wide single-nucleotide polymorphism approach and conducting linkage analysis to identify new genomic regions or loci that could harbor genes important for gliomagenesis. Here, we review the rationale for studying familial glioma and our proposed strategy for the GLIOGENE study. (Cancer Epidemiol Biomarkers Prev 2007;16(9):1730–4)

Abstract The use of tyrosine kinase inhibitors (TKI) has yielded great success in treatment of lung adenocarcinomas. However, patients who develop resistance to TKI treatment often acquire a somatic resistance mutation (T790M) located in the catalytic cleft of the epidermal growth factor receptor (EGFR) enzyme. Recently, a report describing EGFR-T790M as a germ-line mutation suggested that this mutation may be associated with inherited susceptibility to lung cancer. Contrary to previous reports, our analysis indicates that the T790M mutation confers increased Y992 and Y1068 phosphorylation levels. In a human bronchial epithelial cell line, overexpression of EGFR-T790M displayed a growth advantage over wild-type (WT) EGFR. We also screened 237 lung cancer family probands, in addition to 45 bronchoalveolar tumors, and found that none of them contained the EGFR-T790M mutation. Our observations show that EGFR-T790M provides a proliferative advantage with respect to WT EGFR and suggest that the enhanced kinase activity of this mutant is the basis for rare cases of inherited susceptibility to lung cancer. [Cancer Res 2007;67(10):4665–70]

Abstract In this study, we observed loss of heterozygosity (LOH) in human chromosomal fragment 6q25.1 in sporadic lung cancer patients. LOH was observed in 65% of the 26 lung tumors examined and was narrowed down to a 2.2-Mb region. Single-nucleotide polymorphism (SNP) analysis of genes located within this region identified a candidate gene, termed p34. This gene, also designated as ZC3H12D, C6orf95, FLJ46041, or dJ281H8.1, carries an A/G nonsynonymous SNP at codon 106, which alters the amino acid from lysine to arginine. Nearly 73% of heterozygous lung cancer tissues with LOH and the A/G SNP also exhibited loss of the A allele. In vitro clonogenic and in vivo nude mouse studies showed that overexpression of the A allele exerts tumor suppressor function compared with the G allele. p34 is located within a recently mapped human lung cancer susceptibility locus, and association of the p34 A/G SNP was tested among these families. No significant association between the less frequent G allele and lung cancer susceptibility was found. Our results suggest that p34 may be a novel tumor suppressor gene involved in sporadic lung cancer but it seems not to be the candidate familial lung cancer susceptibility gene linked to chromosomal region 6q23-25. [Cancer Res 2007;67(1):93–9]

Abstract DNA microarray has been widely used in cancer research to better predict clinical outcomes and potentially improve patient management. The new approach provides accurate tumor classification and outcome predictions, such as tumor stage, metastatic status, and patient survival, and offers some hope for individualized medicine. However, growing evidence suggests that gene-based prediction is not stable and little is known about the prediction power of gene expression profiles compared with well-known clinical and pathologic predictors. This review summarized up-to-date publications in microarray-based lung cancer clinical outcome prediction and conducted secondary analyses for those with sufficient sample sizes and associated clinical information. Among the most commonly used analytic approaches, unsupervised clustering mainly recaptures tumor histology and provides variable degrees of prediction for tumor stage, lymph node status, or survival. Overall, most studies lack an independent validation. Supervised learning and testing generally offer a better prediction. Noted is that when conventional predictors of age, gender, stage, cell type, and tumor grade are considered collectively, the predictive advantage of the gene expression profiles diminishes. We conclude that outcome prediction from gene expression signatures selected by current analytic approaches can be mostly explained by well-known conventional predictors, particularly histologic subtype and grade of differentiation. A strategy for establishing independent or more accurate signatures is commented. (Cancer Epidemiol Biomarkers Prev 2006;15(11):2063–8)

AbstractBackground: Laboratory testing in suspected α-1-antitrypsin (A1AT) deficiency involves analysis of A1AT concentrations and identification of specific alleles by genotyping or phenotyping. The purpose of this study was to define and evaluate a strategy that provides reliable laboratory evaluation of A1AT deficiency.Methods: Samples from 512 individuals referred for A1AT phenotype analysis were analyzed by quantification, phenotype, and genotype. A1AT concentrations were measured by nephelometry. Phenotype analysis was performed by isoelectric focusing electrophoresis. The genotype assay detected the S and Z deficiency alleles by a melting curve analysis.Results: Of the 512 samples analyzed, 2% of the phenotype and genotype results were discordant. Among these 10 discordant results, 7 were attributed to phenotyping errors. On the basis of these data we formulated an algorithm, according to which we analyzed samples by genotyping and quantification assays, with a reflex to phenotyping when the genotype and quantification results were not concordant. Retrospective analyses demonstrated that 4% of samples submitted for genotype and quantitative analysis were reflexed to phenotyping. Of the reflexed samples, phenotyping confirmed the genotype result in 85% of cases. In the remaining 15%, phenotyping provided further information, including identifying rare deficiency alleles and suggesting the presence of a null allele, and allowed for a more definitive interpretation of the genotype result.Conclusions: The combination of genotyping and quantification, with a reflex to phenotyping, is the optimal strategy for the laboratory evaluation of A1AT deficiency.

Abstract We evaluated somatic genetic alterations in the kinase domain of the EGFR gene in the tumors of 219 non–small cell lung cancer patients of primarily Caucasian and African American origins. We identified 26 patients (12%) whose tumors had a mutation in the EGFR gene, and 11 (5%) patients carried novel genomic variations consistent with germ-line polymorphisms. All but one mutation were identified in Caucasian patients affected with adenocarcinoma. EGFR mutations were more frequent in women and in nonsmokers, but a significant portion of the affected patients were men (12 of 26) and current or past smokers accounted for half of the patients affected (13 of 26). Screening subjects with EGFR mutations may identify patients whose tumors could respond to targeted therapy using tyrosine kinase inhibitors.