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. 2014 Dec 1:4:7268.
doi: 10.1038/srep07268.

A large-scale cross-sectional study of ALK rearrangements and EGFR mutations in non-small-cell lung cancer in Chinese Han population

Shaodong Hong  1 , Wenfeng Fang  1 , Zhihuang Hu  1 , Ting Zhou  1 , Yue Yan  1 , Tao Qin  1 , Yanna Tang  2 , Yuxiang Ma  1 , Yuanyuan Zhao  3 , Cong Xue  1 , Yan Huang  1 , Hongyun Zhao  1 , Li Zhang  1
Affiliations

A large-scale cross-sectional study of ALK rearrangements and EGFR mutations in non-small-cell lung cancer in Chinese Han population

Shaodong Hong et al. Sci Rep. .

Abstract

The predictive power of age at diagnosis and smoking history for ALK rearrangements and EGFR mutations in non-small-cell lung cancer (NSCLC) remains not fully understood. In this cross-sectional study, 1160 NSCLC patients were prospectively enrolled and genotyped for EML4-ALK rearrangements and EGFR mutations. Multivariate logistic regression analysis was performed to explore the association between clinicopathological features and these two genetic aberrations. Receiver operating characteristic (ROC) curves methodology was applied to evaluate the predictive value. We showed that younger age at diagnosis was the only independent variable associated with EML4-ALK rearrangements (odds ratio (OR) per 5 years' increment, 0.68; p < 0.001), while lower tobacco exposure (OR per 5 pack-years' increment, 0.88; p < 0.001), adenocarcinoma (OR, 6.61; p < 0.001), and moderate to high differentiation (OR, 2.05; p < 0.001) were independently associated with EGFR mutations. Age at diagnosis was a very strong predictor of ALK rearrangements but poorly predicted EGFR mutations, while smoking pack-years may predict the presence of EGFR mutations and ALK rearrangements but with rather limited power. These findings should assist clinicians in assessing the likelihood of EML4-ALK rearrangements and EGFR mutations and understanding their biological implications in NSCLC.

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Conflict of interest statement

Yes there is potential Competing Interest. Li Zhang has received research support from Boehringer Ingelheim, Astra Zeneca, Lilly, and Roche. Other authors declare no conflicts of interest.

Figures

Figure 1
Figure 1. Flow diagram of patient selection process.
Figure 2
Figure 2. The incidence of EML4-ALK rearrangements, EGFR mutations, and WT/WT in non-small-cell lung cancer patients according to different age groups (at diagnosis).
WT/WT, wild type ALK and EGFR. There is an inverse relationship between age at diagnosis and the incidence of EML4-ALK rearrangements.
Figure 3
Figure 3. Age distribution (at diagnosis) of EML4-ALK rearrangements and EGFR mutations in non-small-cell lung cancer patients at diagnosis stratified by (A) & (B) gender and (C) & (D) smoking status.
Figure 4
Figure 4. Receiver operating characteristics (ROC) curves for age at diagnosis as predictors of (A) EML4-ALK rearrangements and (B) EGFR mutations in non-small-cell lung cancer.
The optimal cut-off value is the point closest the upper-left corner of the graph. AUC, areas under ROC curve.
Figure 5
Figure 5. The incidence of EML4-ALK rearrangements, EGFR mutations, and WT/WT in non-small-cell lung cancer patients according to total smoking pack-years before diagnosis.
WT/WT, wild type ALK and EGFR.
Figure 6
Figure 6. Receiver operating characteristics (ROC) curves for total smoking pack-years before diagnosis as predictors of (A) EML4-ALK rearrangements and (B) EGFR mutations in non-small-cell lung cancer.
AUC, areas under ROC curve.
See this image and copyright information in PMC

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