Molecular alterations associated with breast cancer mortality

Abstract

Background: Breast cancer is a heterogeneous disease and patients with similar pathologies and treatments may have different clinical outcomes. Identification of molecular alterations associated with disease outcome may improve risk assessment and treatments for aggressive breast cancer.

Methods: Allelic imbalance (AI) data was generated for 122 invasive breast tumors with known clinical outcome. Levels and patterns of AI were compared between patients who died of disease (DOD) and those with ≥5 years disease-free survival (DFS) using Student t-test and chi-square analysis with a significance value of P<0.05.

Results: Levels of AI were significantly higher in tumors from the 31 DOD patients (28.6%) compared to the 91 DFS patients (20.1%). AI at chromosomes 7q31, 8p22, 13q14, 17p13.3, 17p13.1 and 22q12.3 was associated with DOD while AI at 16q22-q24 was associated with DFS. After multivariate analysis, AI at chromosome 8p22 remained an independent predictor of breast cancer mortality. The frequency of AI at chromosome 13q14 was significantly higher in patients who died ≥5 years compared to those who died <5 years from diagnosis.

Conclusion: Tumors from DOD compared to DFS patients are marked by increased genomic instability and AI at chromosome 8p22 is significantly associated with breast cancer morality, independent of other clinicopathological factors. AI at chromosome 13q14 was associated with late (>5-years post-diagnosis) mortality but not with death from disease within five years, suggesting that patients with short- and long-term mortality may have distinct genetic diseases.

Figure 1. Scatter plot of levels of AI by chromosomal region.

Chromosomal regions are on the x-axis, average level of AI on the y-axis. Chromosomes with significantly different frequencies between DOD and DFS groups are boxed.

Figure 2. Survival curves of six chromosomal regions associated with significant differences in survival between patients with and without AI.

Red circles = tumors demonstrating AI, blue squares = tumors without detectable AI. For chromosome 16q22–q24, those patients with AI at chromosome 16q22–q24 have significantly better survival than those with retention of chromosome 16q22–q24.

Figure 3. Extended survival curves (>60 months) for patients with AI at chromosome 13q14.

The survival curves between patients with and without AI begin to separate only after 60 months (P = 0.0159), suggesting that alteration of 13q14 is associated with long-term mortality.