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1.  Global assessment of genetic variation influencing response to retinoid chemoprevention in head and neck cancer patients 
Head and neck squamous cell carcinoma (HNSCC) patients are at an increased risk of developing a second primary tumor (SPT) or recurrence following curative treatment. 13-cis-retinoic acid (13-cRA) has been tested in chemoprevention clinical trials but the results have been inconclusive. We genotyped 9,465 SNPs in 450 patients from the Retinoid Head and Neck Second Primary Trial. SNPs were analyzed for associations with SPT/recurrence in patients receiving placebo to identify prognosis markers and further analyzed for effects of 13-cRA in patients with these prognostic loci. Thirteen loci identified a majority subgroup of patients at a high risk of SPT/recurrence and in whom 13-cRA was protective. Patients carrying the common genotype of rs3118570 in the retinoid X receptor (RXRA) were at a 3.33-fold increased risk (95% confidence interval [CI], 1.67–6.67) and represented over 70% of the study population. This locus also identified individuals who received benefit from chemoprevention with a 38% reduced risk (95% CI, 0.43–0.90). Analyses of cumulative effect and potential gene-gene interactions also implicated CDC25C:rs6596428 and JAK2:rs1887427 as two other genetic loci with major roles in prognosis and 13-cRA response. Patients with all three common genotypes had a 76% reduction in SPT/recurrence (95% CI, 0.093–0.64) following 13-cRA chemoprevention. Carriers of these common genotypes constituted a substantial percentage of the study population, indicating that a pharmacogenetics approach could help select patients for 13-cRA chemoprevention. The lack of any alternatives for reducing risk in these patients highlights the need for future clinical trials to prospectively validate our findings.
doi:10.1158/1940-6207.CAPR-10-0125
PMCID: PMC3955084  PMID: 21292633
HNSCC; SPT; single nucleotide polymorphisms; retinoids
2.  An Expanded Risk Prediction Model for Lung Cancer 
Risk prediction models are useful in clinical decision making. We have published an internally validated prediction tool for lung cancer based on easily obtainable epidemiologic and clinical data. Because the precision of the model was modest, we now estimate the improvement obtained by adding two markers of DNA repair capacity.
Assay data (host-cell reactivation and mutagen sensitivity) were available for 725 White lung cancer cases and 615 controls, all former or current smokers, a subset of cases and controls from the previous analysis. Multivariable models were constructed from the original variables with addition of the biomarkers separately and together. Pairwise comparisons of the area under the receiver operating characteristic curves (AUC) and 3-fold cross-validations were done.
For former smokers, the AUC and 95% confidence intervals were 0.67 (0.63–0.71) for the baseline model and 0.70 (0.66–0.74) for the expanded model. For current smokers, the comparable AUC values were 0.68 (0.64–0.72) and 0.73 (0.69–0.77). For both groups, the expanded models were statistically significantly better than the baseline models (P = 0.006 and P = 0.0048, respectively), although the increases in the concordance statistics were modest. We also recomputed 1-year absolute risks of lung cancer as described previously for two different risk profiles and showed that individuals who exhibited poor repair capacity or heightened mutagen sensitivity had increased absolute risks of lung cancer.
Addition of biomarker assays improved the sensitivity of the expanded models.
doi:10.1158/1940-6207.CAPR-08-0060
PMCID: PMC2854404  PMID: 19138968
3.  Genetic variants in the PI3K/PTEN/AKT/MTOR pathway predict head and neck cancer patient second primary tumor/recurrence risk and response to retinoid chemoprevention 
Clinical Cancer Research  2012;18(13):3705-3713.
Purpose
The development of second primary tumors (SPT) or recurrence alters prognosis for curatively-treated head and neck squamous cell carcinoma (HNSCC) patients. 13-cis-retnoic acid (13-cRA) has been tested as a chemoprevention agent in clinical trials with mixed results. Therefore, we investigated if genetic variants in the PI3K/PTEN/AKT/MTOR pathway could serve as biomarkers to identify which patients are at high risk of an SPT/recurrence while also predicting response to 13-cRA chemoprevention.
Experimental Design
A total of 137 pathway SNPs were genotyped in 440 patients from the Retinoid Head and Neck Second Primary Trial and assessed for SPT/recurrence risk and response to 13-cRA. Risk models were created based on epidemiology, clinical, and genetic data.
Results
Twenty-two genetic loci were associated with increased SPT/recurrence risk with six also being associated with a significant benefit following chemoprevention. Combined analysis of these high-risk/high-benefit loci identified a significant (P = 1.54×10−4) dose-response relationship for SPT/recurrence risk, with patients carrying 4–5 high-risk genotypes having a 3.76-fold (95%CI:1.87–7.57) increase in risk in the placebo group (n=215). Patients carrying 4–5 high-risk loci showed the most benefit from 13-cRA chemoprevention with a 73% reduction in SPT/recurrence (95%CI:0.13–0.58) compared to those with the same number of high-risk genotypes who were randomized to receive placebo. Incorporation of these loci into a risk model significantly improved the discriminatory ability over models with epidemiology, clinical, and previously identified genetic variables.
Conclusions
These results demonstrate that loci within this important pathway could identify individuals with a high-risk/high-benefit profile and are a step towards personalized chemoprevention for HNSCC patients.
doi:10.1158/1078-0432.CCR-11-3271
PMCID: PMC3404728  PMID: 22577058
4.  Genome-Wide Association Study of Survival in Non–Small Cell Lung Cancer Patients Receiving Platinum-Based Chemotherapy 
Background
Interindividual variation in genetic background may influence the response to chemotherapy and overall survival for patients with advanced-stage non–small cell lung cancer (NSCLC).
Methods
To identify genetic variants associated with poor overall survival in these patients, we conducted a genome-wide scan of 307 260 single-nucleotide polymorphisms (SNPs) in 327 advanced-stage NSCLC patients who received platinum-based chemotherapy with or without radiation at the University of Texas MD Anderson Cancer Center (the discovery population). A fast-track replication was performed for 315 patients from the Mayo Clinic followed by a second validation at the University of Pittsburgh in 420 patients enrolled in the Spanish Lung Cancer Group PLATAX clinical trial. A pooled analysis combining the Mayo Clinic and PLATAX populations or all three populations was also used to validate the results. We assessed the association of each SNP with overall survival by multivariable Cox proportional hazard regression analysis. All statistical tests were two-sided.
Results
SNP rs1878022 in the chemokine-like receptor 1 (CMKLR1) was statistically significantly associated with poor overall survival in the MD Anderson discovery population (hazard ratio [HR] of death = 1.59, 95% confidence interval [CI] = 1.32 to 1.92, P = 1.42 × 10−6), in the PLATAX clinical trial (HR of death = 1.23, 95% CI = 1.00 to 1.51, P = .05), in the pooled Mayo Clinic and PLATAX validation (HR of death = 1.22, 95% CI = 1.06 to 1.40, P = .005), and in pooled analysis of all three populations (HR of death = 1.33, 95% CI = 1.19 to 1.48, P = 5.13 × 10−7). Carrying a variant genotype of rs10937823 was associated with decreased overall survival (HR of death = 1.82, 95% CI = 1.42 to 2.33, P = 1.73 × 10−6) in the pooled MD Anderson and Mayo Clinic populations but not in the PLATAX trial patient population (HR of death = 0.96, 95% CI = 0.69 to 1.35).
Conclusion
These results have the potential to contribute to the future development of personalized chemotherapy treatments for individual NSCLC patients.
doi:10.1093/jnci/djr075
PMCID: PMC3096796  PMID: 21483023
5.  Reduced DNA Repair Capacity for Removing Tobacco Carcinogen-Induced DNA Adducts Contributes to Risk of Head and Neck Cancer but not Tumor Characteristics 
Purpose
Although cigarette smoking and alcohol use are known risk factors for squamous cell carcinoma of head and neck (SCCHN), only a few exposed individuals develop this disease, suggesting an individual susceptibility. In this study, we investigated the associations between genetically determined DNA repair capacity (DRC) for removing tobacco-induced DNA adducts and risk of SCCHN and tumor characteristics.
Experimental Design
We measured DRC in cultured T-lymphocytes using the host-cell reactivation assay in a hospital-based case-control study of 744 SCCHN patients and 753 age-, sex-and ethnicity-matched cancer-free controls recruited from The University of Texas M. D. Anderson Cancer Center.
Results
Patients with SCCHN had significantly lower mean DRC (8.84% ± 2.68%) than controls (9.97% ± 2.61%) (P < 0.0001), and the difference accounted for approximately 2-fold increased risk of SCCHN (adjusted odds ratio [OR], 1.91; 95% CI, 1.52–2.40) after adjustment for other covariates. Compared with the highest DRC quartile of controls, this increased risk was dose-dependent (second highest quartile: OR, 1.40; 95% CI, 0.99–1.98; third quartile: OR, 1.87; 95% CI, 1.34–2.62; and fourth quartile: OR, 2.76; 95% CI, 1.98–3.84, respectively; Ptrend < 0.0001). We also assessed the performance of DRC in risk prediction models by calculating the area of under the receiver operating characteristic curve. The addition of DRC to the model significantly improved the sensitivity of the expanded model. However, we did not find the association between DRC and tumor sites and stages.
Conclusion
DRC is an independent susceptibility biomarker for SCCHN risk but not a tumor marker.
doi:10.1158/1078-0432.CCR-09-2156
PMCID: PMC2848391  PMID: 20068090
nucleotide excision repair; genetic susceptibility; head and neck neoplasm; molecular epidemiology
6.  Genetic Variants in Inflammation-Related Genes Are Associated with Radiation-Induced Toxicity Following Treatment for Non-Small Cell Lung Cancer 
PLoS ONE  2010;5(8):e12402.
Treatment of non-small cell lung cancer (NSCLC) with radiotherapy or chemoradiotherapy is often accompanied by the development of esophagitis and pneumonitis. Identifying patients who might be at increased risk for normal tissue toxicity would help in determination of the optimal radiation dose to avoid these events. We profiled 59 single nucleotide polymorphisms (SNPs) from 37 inflammation-related genes in 173 NSCLC patients with stage IIIA/IIIB (dry) disease who were treated with definitive radiation or chemoradiation. For esophagitis risk, nine SNPs were associated with a 1.5- to 4-fold increase in risk, including three PTGS2 (COX2) variants: rs20417 (HR:1.93, 95% CI:1.10–3.39), rs5275 (HR:1.58, 95% CI:1.09–2.27), and rs689470 (HR:3.38, 95% CI:1.09–10.49). Significantly increased risk of pneumonitis was observed for patients with genetic variation in the proinflammatory genes IL1A, IL8, TNF, TNFRSF1B, and MIF. In contrast, NOS3:rs1799983 displayed a protective effect with a 45% reduction in pneumonitis risk (HR:0.55, 95% CI:0.31–0.96). Pneumonitis risk was also modulated by polymorphisms in anti-inflammatory genes, including genetic variation in IL13. rs20541 and rs180925 each resulted in increased risk (HR:2.95, 95% CI:1.14–7.63 and HR:3.23, 95% CI:1.03–10.18, respectively). The cumulative effect of these SNPs on risk was dose-dependent, as evidenced by a significantly increased risk of either toxicity with an increasing number of risk genotypes (P<0.001). These results suggest that genetic variations among inflammation pathway genes may modulate the development of radiation-induced toxicity and, ultimately, help in identifying patients who are at an increased likelihood for such events.
doi:10.1371/journal.pone.0012402
PMCID: PMC2928273  PMID: 20811626
7.  Development and Validation of a Lung Cancer Risk Prediction Model for African-Americans 
Because existing risk prediction models for lung cancer were developed in white populations, they may not be appropriate for predicting risk among African-Americans. Therefore, a need exists to construct and validate a risk prediction model for lung cancer that is specific to African-Americans. We analyzed data from 491 African-Americans with lung cancer and 497 matched African-American controls to identify specific risks and incorporate them into a multivariable risk model for lung cancer and estimate the 5-year absolute risk of lung cancer. We performed internal and external validations of the risk model using data on additional cases and controls from the same ongoing multiracial/ethnic lung cancer case-control study from which the model-building data were obtained as well as data from two different lung cancer studies in metropolitan Detroit, respectively. We also compared our African-American model with our previously developed risk prediction model for whites. The final risk model included smoking-related variables [smoking status, pack-years smoked, age at smoking cessation (former smokers), and number of years since smoking cessation (former smokers)], self- reported physician diagnoses of chronic obstructive pulmonary disease or hay fever, and exposures to asbestos or wood dusts. Our risk prediction model for African-Americans exhibited good discrimination [75% (95% confidence interval, 0.67−0.82)] for our internal data and moderate discrimination [63% (95% confidence interval, 0.57−0.69)] for the external data group, which is an improvement over the Spitz model for white subjects. Existing lung cancer prediction models may not be appropriate for predicting risk for African-Americans because (a) they were developed using white populations, (b) level of risk is different for risk factors that African-American share with whites, and (c) unique group-specific risk factors exist for African-Americans. This study developed and validated a risk prediction model for lung cancer that is specific to African-Americans and thus more precise in predicting their risks. These findings highlight the importance of conducting further ethnic-specific analyses of disease risk.
doi:10.1158/1940-6207.CAPR-08-0082
PMCID: PMC2854402  PMID: 19138969
8.  Germline Genetic variations in drug action pathways predict clinical outcomes in advanced lung cancer treated with platinum-based chemotherapy 
Pharmacogenetics and genomics  2008;18(11):955-965.
Purpose
Genetic polymorphisms contribute to interindividual variation in drug response. However, a single polymorphism is likely to exhibit a modest effect. Therefore, we applied a pathway-based approach to evaluate the cumulative effect of multiple polymorphisms on clinical outcome of patients with non-small cell lung cancer (NSCLC).
Methods
We genotyped 25 functional polymorphisms in 16 key genes involved in cisplatin metabolism and action and evaluated their associations with overall survival in 229 NSCLC patients receiving first-line cisplatin-based chemotherapy.
Results
Several biologically plausible main effects were identified in individual analysis. More importantly, when 6 polymorphisms in nucleotide excision repair genes were analyzed jointly, a significant trend of reduced risk of death with decreasing number of putative unfavorable genotypes was observed (P for trend <0.001 and log-rank p<0.001). Survival tree analysis revealed potential higher-order gene-gene interactions and categorized subgroups with dramatically different survival experiences, based on distinct genotype profiles. The median survival time was 78.5 months for terminal node 1 in the low-risk group, 15.1 months for terminal node 10 in the medium-risk group, and 6.7 months for terminal node 9 in the high-risk group (log rank P<0.001). We also constructed a prediction hazard model. The area under the curve (AUC) increased from 0.71 (using clinical variables only) to 0.84 (using clinical, epidemiological, and genetic variations from survival tree analysis).
Conclusions
Our results highlight the clinical potential of taking a pathway-based approach and using survival tree analytic approach to identify subgroups of patients with distinctly differing outcomes.
doi:10.1097/FPC.0b013e32830efdd4
PMCID: PMC2665725  PMID: 18854777

Results 1-8 (8)