Metastatic behavior of subtypes in locally advanced breast carcinoma

Aim/Background

Prognostic factors have been known to predict the incidence of metastasis in breast carcinoma but the study of subtypes classification based on molecular markers may help in providing more personalised, individualised patient care with a more focussed treatment and follow up of patients with high probability of metastasis at different sites.

Methods

Patients with breast cancer (tissue biopsy proven) diagnosed between 2011 and 2013 were included. Subtypes were defined on the basis of molecular markers (ER, PR and HER2 NEU) in five categories. (Luminal A, luminal B, luminal HER2, HER2 enriched and basal). Distant sites for metastasis were classified as brain, liver, lung, bone, distant nodal, pleural/peritoneal, and others. Association between the site of relapse and subtype was assessed in multivariate models using logistic regression.

Results

Mean age at diagnosis of patients in the study was 50.71 years (SD-11.493) with 41-50 years (31.5%) being the most common age group. Most of the patients in the study were locally advanced at the time of presentation (69.6%). Incidence of metastasis at the time of presentation was (38.7%) with bone being the most common site. Patients were divided on the basis of molecular subtypes with basal (27.3%) being the most common subtype closely followed by luminal A (25.2%). Highest incidence of metastasis was seen in basal subtype (33%) followed by luminal HER (18.4%) and HER2 enriched (18.1%). On subset analysis, bone was the most common site of recurrence in luminal A (61.5%) and luminal B (58.8%). Basal and luminal HER2 subtypes had brain as the most common site of recurrence while HER2 enriched had equal recurrence in liver and brain.

Conclusions

Breast cancer subtypes are associated with distinct patterns of metastatic spread with a high probability of metastasis at the time of presentation as well as later in the lifetime. It is important to understand the nuances of these breast cancer subtypes to predict metastatic behaviour for early imaging and adequate individualised treatment and follow up.

Clinical trial identification

Disclosure

All authors have declared no conflicts of interest.