High expression of BCL-2 predicts favorable outcome in non-small cell lung cancer patients with non squamous histology

Abstract

Background: Bcl-2 promotes cell survival by inhibiting adapters needed for the activation and cleavage of caspases thus blocking the proteolytic cascade that ultimately dismantles the cell. Bcl-2 has been investigated as a prognostic factor in non small cell lung cancer (NSCLC) patients with conflicting results.

Methods: Here, we quantitatively assessed Bcl-2 expression in two large and independent cohorts to investigate the impact of Bcl-2 on survival. AQUA(R), a fluorescent-based method for analysis of in situ protein expression, was used to measure Bcl-2 protein levels and classify tumors by Bcl-2 expression in a cohort of 180 NSCLC patients. An independent cohort of 354 NSCLC patients was used to validate Bcl-2 classification and evaluate outcome.

Results: Fifty % and 52% of the cases were classified as high expressers in training and validation cohorts respectively. Squamous cell carcinomas were more likely to be high expressers compared to adenocarcinomas (63% vs. 45%, p = 0.002); Bcl-2 was not associated with other clinical or pathological characteristics. Survival analysis showed that patients with high BCL-2 expression had a longer median survival compared to low expressers (22 vs. 17.5 months, log rank p = 0.014) especially in the subset of non-squamous tumors (25 vs. 13.8 months, log rank p = 0.04). Multivariate analysis revealed an independent lower risk for all patients with Bcl-2 expressing tumors (HR = 0.53, 95% CI 0.37-0.75, p = 0.0003) and for patients with non-squamous tumors (HR = 0.5, 95% CI 0.31-0.81, p = 0.005).

Conclusions: Bcl-2 expression defines a subgroup of patients with a favorable outcome and may be useful for prognostic stratification of NSCLC patients.

Figure 1

Distribution and reproducibility of Bcl-2 AQUA scores in cell lines and training set. A. Plotting AQUA scores of the same histospots on serial cuts of the control array stained aside the 2 cohorts at different runs provided a standard curve in order to normalize for run to run variability (Pearson's R = o.96 between runs, p < 0.0001) B. Distribution of Ncl-2 AQUA scores in 19 cell line controls embedded in the control TMA C. Representative immunofluorescence staining in a high (MCF7) and low (SKBR3) Bcl-2 expressing breast cancer cell lines; AQUA scores are displayed in insets D. Linear regression between Bcl-2 AQUA scores of redundant tumor cores reveals significant correlation (Pearson's R = 0.85, p < 0.0001).

Figure 2

Automated Quantitative Analysis (AQUA) of Bcl-2 in lung cancer. (A-D) Tumor histospot corresponding to a NSCLC patient with Bcl-2 AQUA score of 400 A. Cytokeratin-Cy3 image used to identify tumor; the epithelial tumor "mask" is displayed in C B. Colocalization of subcellular compartments: the non nuclear (green) and nuclear (blue) compartment are defined by the cytokeratin and the DAPI signal respectively D. Bcl-2-Cy5 (red), cytokeratin (green) and DAPI (blue) colocalization; Bcl-2 shows a representative cytoplasmic pattern; AQUA score is inset into the bottom right corner.

Figure 3

Disease outcome by Bcl-2 expression in NSCLC. A, B. Survival curves based on cohort division by the optimal cutpoint generated from the Yale University Cohort (training set); NSCLC and non squamous patients classified as high Bcl-2 expressers (n = 90 and n = 67 respectively) show a benefit towards survival. The distribution of AQUA scores is displayed in inset. C. Kaplan-Meier graphical analysis of survival in NSCLC of the Greek Lung Cancer Cohort (validation set, n = 354). Patients with a high Bcl-2 score (n = 186) had a significant higher median survival compared to the low Bcl-2 group (log rank p = 0.014). The distribution of Bcl-2 AQUA scores is displayed in inset. D. Survival curves for non squamous tumors of the validation cohort classified as high (n = 76) versus low Bcl-2 expressers showed a significant benefit towards survival for the high expressing group (log rank p = 0.04). AQUA; automated quantitative analysis.