Abstract
BackgroundOptimizing treatment through microarray-based molecular subtyping is a promising method to address the problem of heterogeneity in breast cancer; however, current application is restricted to prediction of distant recurrence risk. This study investigated whether breast cancer molecular subtyping according to its global intrinsic biology could be used for treatment customization.MethodsGene expression profiling was conducted on fresh frozen breast cancer tissue collected from 327 patients in conjunction with thoroughly documented clinical data. A method of molecular subtyping based on 783 probe-sets was established and validated. Statistical analysis was performed to correlate molecular subtypes with survival outcome and adjuvant chemotherapy regimens. Heterogeneity of molecular subtypes within groups sharing the same distant recurrence risk predicted by genes of the Oncotype and MammaPrint predictors was studied.ResultsWe identified six molecular subtypes of breast cancer demonstrating distinctive molecular and clinical characteristics. These six subtypes showed similarities and significant differences from the Perou-Sørlie intrinsic types. Subtype I breast cancer was in concordance with chemosensitive basal-like intrinsic type. Adjuvant chemotherapy of lower intensity with CMF yielded survival outcome similar to those of CAF in this subtype. Subtype IV breast cancer was positive for ER with a full-range expression of HER2, responding poorly to CMF; however, this subtype showed excellent survival when treated with CAF. Reduced expression of a gene associated with methotrexate sensitivity in subtype IV was the likely reason for poor response to methotrexate. All subtype V breast cancer was positive for ER and had excellent long-term survival with hormonal therapy alone following surgery and/or radiation therapy. Adjuvant chemotherapy did not provide any survival benefit in early stages of subtype V patients. Subtype V was consistent with a unique subset of luminal A intrinsic type. When molecular subtypes were correlated with recurrence risk predicted by genes of Oncotype and MammaPrint predictors, a significant degree of heterogeneity within the same risk group was noted. This heterogeneity was distributed over several subtypes, suggesting that patients in the same risk groups require different treatment approaches.ConclusionsOur results indicate that the molecular subtypes established in this study can be utilized for customization of breast cancer treatment.
Highlights
Optimizing treatment through microarray-based molecular subtyping is a promising method to address the problem of heterogeneity in breast cancer; current application is restricted to prediction of distant recurrence risk
Other studies have identified gene expression signatures applicable to the prediction of risk associated with regional recurrence, distant metastasis, and survival [6,7,8,9,10,11]. Despite these advancements related to the intrinsic types of breast cancer, the direct clinical application of molecular subtypes based on global intrinsic biology has yet to be realized
The approaches based on prediction of distant recurrence risk have not taken full advantage of gene expression profiles to customize breast cancer treatment according to molecular subtypes
Summary
In a seminal study by Perou et al [1], it was shown that breast cancer could be divided Despite these advancements related to the intrinsic types of breast cancer, the direct clinical application of molecular subtypes based on global intrinsic biology has yet to be realized. The clinical trials that have been launched recently are based on prediction of distant recurrence risk through gene expression [12,13] These approaches do not address the likely heterogeneity of breast cancer within groups sharing the same predicted risk. The approaches based on prediction of distant recurrence risk have not taken full advantage of gene expression profiles to customize breast cancer treatment according to molecular subtypes. Studies on how microarray-based molecular subtypes could be correlated with outcomes of various specific treatment regimes are sorely needed
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