Patterns of chromosomal imbalances defines subgroups of breast cancer with distinct clinical features and prognosis. A study of 305 tumors by comparative genomic hybridization.

Chromosomal copy number aberrations (CNAs) are common in breast cancer and involve genomic regions in a frequency and combination, suggesting distinct routes of tumor development. We studied chromosomal gains (+) and losses (-) by comparative genomic hybridization from a series of 305 unselected primary invasive breast cancers. CNAs were observed in >90% of the tumors and involved all chromosomal arms in various frequencies, the most common being +1q (55%), +8q (41%), +16p (40%), +17q (28%), -13q (27%), -16q (22%), +20q (19%), -8p (18%), and +11q (16%). Eighteen pairs of CNAs were revealed as significantly associated using Fisher's exact test with Bonferroni correction, the most common pairs being -8p/+8q, +17q/+20q, and -4q/-13q. To study more complex relationships between individual CNAs, principal component analysis and distance-based tree modeling were performed independently. Three distinct patterns of CNAs were observed. Group A was defined by +1q, +16p, and -16q, group B by +11q, +20q, +17q, and -13q, and group C by -8p and +8q. Group A was correlated to positive estrogen receptor and progesterone receptor (PgR) status (P < 0.001 and P < 0.05, respectively). Groups B and C were correlated to DNA nondiploidy (P < 0.001 and P < 0.05), high histological grade and lymph node positivity (P < 0.05), and group B also to high proliferation rate, large primary tumor size (P < 0.001), and negative PgR status (P < 0.05). Patients with aberrations in group A only had a significantly higher breast cancer survival rate than all other patients. The worst survival was seen for patients with aberrations in group C only along with the patients displaying aberrations from all CNA pattern groups (ABC). The 5-year survival rates vary from 96% in group A to 56% in group C. These correlations were independent of node status, tumor size, and PgR status in a multivariate analysis. We conclude that patterns of copy number gains and losses define breast tumors with distinct clinicopathological features and patient prognosis.