Abstract
Breast cancer is a complex and heterogeneous disease that affects about one out of every eight women. In the last decade, several advancements have been made that have increased our understanding of breast cancer and have allowed us to more accurately diagnose and treat this disease in a more targeted manner. For example, gene expression profiling enabled the classification of breast cancers into four main subtypes - basal-like, HER2+ (human epidermal growth factor receptor 2-positive), luminal A and luminal B - and this classification is used to direct the use of targeted therapies such as tamoxifen or trastuzumab. The luminal subtypes are generally characterized as being estrogen receptor-positive and targetable with anti-hormone therapies. However, whereas luminal A cancers have a good prognosis, luminal B cancers are associated with early relapse following endocrine therapy and a prognosis that is similar to that of the aggressive basal subtype. It is thus imperative that luminal B cancers be better characterized so that therapeutic targets and biomarkers for this disease type can be realized. In the previous issue of Breast Cancer Research, Katchman and colleagues address this need by demonstrating that quiescin sulfydryl oxidase 1 (QSOX1), a secreted enzyme involved in post-translational modifications, is associated with poor prognosis in patients with luminal B breast cancer. The authors further determined that this protein promotes breast cancer proliferation and invasion. Collectively, these studies suggest that QSOX1 is a predictive biomarker for luminal cancers and that it may be a useful target for elusive luminal B disease.
Highlights
Breast cancer is a complex and heterogeneous disease that affects about one out of every eight women
One such attempt is described in the previous issue of Breast Cancer Research, in which Katchman and colleagues [1] investigated the role of quiescin sulfydryl oxidase 1 (QSOX1) in luminal B breast cancer
The authors employed the Gene expression-based Outcome for Breast cancer Online (GOBO) algorithm, a software analysis of Affymetrix data pooled from 11 public data sets [11], to investigate QSOX1 expression in the context of breast cancer
Summary
Breast cancer is a complex and heterogeneous disease that affects about one out of every eight women. Over the past 13 years, hierarchical clustering of gene expression profiles in patient tumors has been used to divide breast cancer into four main subtypes: basallike, HER2+ (human epidermal growth factor receptor 2-positive), luminal A and luminal B [2,3,4,5]. Katchman and colleagues [1] suggest that QSOX1 may serve as both a biomarker and therapeutic target for luminal B breast cancer.
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