Abstract 2379: The importance of cell cycle biomarkers in prognostic signatures in tobacco-related cancers.

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Abstract Smokers have an increased risk of developing dozens of cancers including lung (∼90% caused from smoking), bladder (∼50%), and head and neck (∼33% from smoking alone; ∼68% from smoking and alcohol combined). We posited that disease outcome in patients with tobacco-related cancers correlates with the activity of a common biological pathway. The identification of such a pathway would aid in the selection of robust prognostic biomarkers for these patients. We collected 19 gene expression datasets (N = 1996) for patients with lung adenocarcinoma (LA, 8 cohorts, N = 770), squamous cell lung carcinoma (SCLC, 3 cohorts, N = 164), bladder transitional cell carcinoma (BL, 5 cohorts, N = 778), and head and neck squamous cell carcinoma (HNSCC, 3 cohorts, N = 188). We performed a functional analysis and identified overrepresented modules (GO terms and KEGG pathways) in lists of genes predictive of outcome (P < 0.01) for each cohort. Strikingly, the only consistently overrepresented modules were cell-cycle related, and these were histology dependent. Cell cycle related modules were overrepresented in the 3 (out of 3) BL progression cohorts and in 5 (out of 8) LA survival cohorts (FDR < 5%). No modules were consistently overrepresented in SCLC or HNSCC cohorts at FDR < 10%. The consistent association of cell cycle modules with outcome implied that a cell cycle biomarker signature would robustly predict outcome in these cohorts. We evaluated the prognostic value of a previously published cell cycle proliferation (CCP) score that was validated in prostate cancer patients. The CCP score is the average expression of 31 cell cycle-related genes, and was not optimized in any way for the current analysis. CCP score was predictive of outcome in the 5 LA cohorts enriched in cell cycle modules and of progression and survival in all BL cohorts with this information. CCP score was also significant (P < 0.05) in a multivariate analysis for overall survival in 3 (out of 4) LA cohorts and was the second most consistently predictive variable for survival in BL (behind stage). Final multivariate models were developed through forward stepwise selection of significant variables (P < 0.05). CCP score was selected for the final model in 3 (out of 4) LA cohorts and for all 3 BL cohorts when progression was the endpoint. Finally, we assessed whether the prognostic value of previously published BL and LA signatures depended on cell cycle-correlated genes. Gene expression values were adjusted for CCP score or by a constant (positive control) and 3 BL progression and 10 LA survival signatures were analyzed. Compared to the control signatures, the adjusted signatures lost their predictive ability (at P < 0.05) in 88% and 75% of BL and LA cohorts, respectively. Our results indicate that cell cycle-related genes are prognostic biomarkers in some tobacco-related cancers and may be required for robust biomarker-based outcome prediction in BL and LA patients. Citation Format: Garrett Dancik, Dan Theodorescu. The importance of cell cycle biomarkers in prognostic signatures in tobacco-related cancers. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2379. doi:10.1158/1538-7445.AM2013-2379 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.