Germline genetic variations in drug action pathways predict clinical outcomes in advanced lung cancer treated with platinum-based chemotherapy

Xifeng Wu, Charles Lu, Yuanqing Ye, Joe Y. Chang, Hushan Yang, Jie Lin, Jian Gu, Waun Ki Hong, David J. Stewart, Margaret R. Spitz

Pharmacogenetics and Genomics · 2008 · 49 citations · 33 references

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Abstract

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. 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 non-small cell lung cancer patients receiving first-line cisplatin-based chemotherapy. RESULTS: Several biologically plausible main effects were identified in individual analysis. More importantly, when six 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 increased from 0.71 (using clinical variables only) to 0.84 (using clinical, epidemiological, and genetic variations from survival tree analysis). CONCLUSION: 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.

References

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