Abstract
Breast cancer is the most common cancer in women worldwide, with the highest mortality rates. While breast tumors can have heterogeneous biology, the mutational burden/genomic alterations, etc, are relatively less when compared to other malignancies like pancreatic cancer or glioblastomas, rendering breast tumors comparatively less aggressive. Despite this, adjuvant chemotherapy, which was devised as a means to reduce the risk of distant recurrence, has become the mainstay treatment choice for a majority of these patients, but is proving effective only for a subset. Therefore, efficient and effective treatment planning should involve strategies to de-escalate therapy regimens to balance the benefits and side effects of each therapy.
To circumvent the dilemma of relying solely on clinical parameters for chemotherapy treatment decisions, molecular profiling was introduced to look for signatures that better describe underlying tumor biology and act as an effective prognostic tool. This review discusses the advancements in prognostic tools for early breast cancer patients, giving a comprehensive overview of several commercially available prognostic tests. We also discuss CanAssist Breast®, a relatively newer entry into the field of prognostic tests and the only one that uses immunohistochemistry as a platform coupled with Artificial Intelligence (AI).