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. 2011 Dec 21;103(24):1859-70.
doi: 10.1093/jnci/djr420. Epub 2011 Dec 8.

Prognostic and predictive value of a malignancy-risk gene signature in early-stage non-small cell lung cancer

Affiliations

Prognostic and predictive value of a malignancy-risk gene signature in early-stage non-small cell lung cancer

Dung-Tsa Chen et al. J Natl Cancer Inst. .

Abstract

Background: The malignancy-risk gene signature is composed of numerous proliferative genes and has been applied to predict breast cancer risk. We hypothesized that the malignancy-risk gene signature has prognostic and predictive value for early-stage non-small cell lung cancer (NSCLC) patients.

Methods: The ability of the malignancy-risk gene signature to predict overall survival (OS) of early-stage NSCLC patients was tested using a large NSCLC microarray dataset from the Director's Challenge Consortium (n = 442) and two independent NSCLC microarray datasets (n = 117 and 133, for the GSE13213 and GSE14814 datasets, respectively). An overall malignancy-risk score was generated by principal component analysis to determine the prognostic and predictive value of the signature. An interaction model was used to investigate a statistically significant interaction between adjuvant chemotherapy (ACT) and the gene signature. All statistical tests were two-sided.

Results: The malignancy-risk gene signature was statistically significantly associated with OS (P < .001) of NSCLC patients. Validation with the two independent datasets demonstrated that the malignancy-risk score had prognostic and predictive values: Of patients who did not receive ACT, those with a low malignancy-risk score had increased OS compared with a high malignancy-risk score (P = .007 and .01 for the GSE13212 and GSE14814 datasets, respectively), indicating a prognostic value; and in the GSE14814 dataset, patients receiving ACT survived longer in the high malignancy-risk score group (P = .03), and a statistically significant interaction between ACT and the signature was observed (P = .02).

Conclusions: The malignancy-risk gene signature was associated with OS and was a prognostic and predictive indicator. The malignancy-risk gene signature could be useful to improve prediction of OS and to identify those NSCLC patients who will benefit from ACT.

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Figures

Figure 1
Figure 1
Association of the malignancy-risk gene signature with overall survival. A malignancy-risk score was generated for each patient from the Director’s Challenge Consortium (n = 442) by principal component analysis to reflect the combined expression of the malignancy-risk genes. High and low malignancy-risk groups were determined on the basis of a median split. Kaplan–Meier curves of overall survival are shown in the two groups with corresponding 95% confidence intervals (CIs) as error bars. A statistically significant difference of the Kaplan–Meier survival curves between the high and low malignancy-risk groups was determined by the two-sided log-rank test. The number of patients at risk is listed below the survival curves. Inf = infinity; MST = median survival time.
Figure 2
Figure 2
Association of the malignancy-risk gene signature with histological grade and TNM staging system. The malignancy-risk score was calculated for patients from the Director’s Challenge Consortium for whom data on A) histological grade or B) TNM stage were available (n = 435 and 439, respectively). Box plot was used to display distribution of the malignancy-risk score within each group. The bottom and top of each box are the lower and upper quartiles, respectively. The black band near the middle of the box is the median. The extreme of the lower whisker represents the lower quartile minus 1.5 times the interquartile range, and the extreme of the higher whisker is the upper quartile plus 1.5 times the interquartile range. Any data points beyond the extremes of the whiskers are indicated by empty circles as outliers. Spearman correlation (r) was calculated to determine if an increasing trend existed between the continuous malignancy-risk score and increasing histological grade and TNM stage. All statistical tests were two-sided.
Figure 3
Figure 3
Analysis of the association between the malignancy-risk gene signature and overall survival by TNM stage. A) Kaplan–Meier curves of overall survival for patients from the Director’s Challenge Consortium for whom data on TNM stage was available (n = 439) was stratified by TNM stage (IA, IB, II, and III). A malignancy-risk score was generated for each patient by principal component analysis to reflect the combined expression of the malignancy-risk genes. High and low malignancy-risk groups were determined on the basis of a median split. A statistically significant difference in the Kaplan–Meier survival curves between the low and high malignancy-risk groups for patients with TNM stage IB and III disease (B−C, respectively) was determined by the two-sided log-rank test. Error bars indicate 95% confidence intervals (CIs). The number of patients at risk is listed below the curves. Inf = infinity; MST = median survival time.
Figure 4
Figure 4
Analysis of the association between the malignancy-risk gene signature and overall survival in stage IB patients with smoking history. Data from the Director’s Challenge Consortium (n = 100) was analyzed. A statistically significant difference in the Kaplan–Meier survival curves between the low and high malignancy-risk groups for patients with TNM stage IB and smoking history was determined by the two-sided log-rank test. 95% confidence intervals (CIs) are also presented (error bars). The number of patients at risk is listed below the curves. Inf = infinity; MST = median survival time.
Figure 5
Figure 5
Prognostic value of the malignancy-risk gene signature. A malignancy-risk score was generated using the loading coefficients of the first principal component from the Director’s Challenge Consortium dataset for each patient. High and low malignancy-risk groups were determined on the basis of a median split using the median of the malignancy-risk score from the Director’s Challenge Consortium dataset. Kaplan–Meier curves of overall survival for patients who did not receive adjuvant chemotherapy or radiation therapy from A) the Director’s Challenge Consortium (n = 190), B) the GSE13213 dataset (n = 117), and C) the GSE14814 dataset from the JBR.10 trial (n = 62) by high or low malignancy-risk group are shown. Error bars represent 95% confidence intervals (CIs). The two-sided log-rank test was done to calculate P. Inf = infinity; MST = median survival time.
Figure 6
Figure 6
Predictive value of the malignancy-risk gene signature. A malignancy-risk score was generated using the loading coefficients of the first principal component from the Director’s Challenge Consortium dataset for each patient. High and low malignancy-risk groups were determined on the basis of a median split using the median of the malignancy-risk score from the Director’s Challenge Consortium dataset. Kaplan–Meier curves of overall survival for patients in the GSE14814 dataset from A) the high malignancy-risk group and B) the low malignancy-risk group by the adjuvant chemotherapy (ACT) or the observation cohort (OBS) are shown. The two-sided log-rank test was used to calculate P. Error bars represent 95% confidence intervals (CIs). Inf = infinity; MST = median survival time.

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