Abstract
PurposeMore accurate prediction of patient outcome based on molecular subtype is required to identify patients who will benefit from specific treatments.MethodsWe selected novel 16 candidate prognostic genes, including 10 proliferation-related genes (p-genes) and 6 immune response-related genes (i-genes), from the gene list identified in our previous study. We then analyzed the association between their expression, measured by quantitative real-time reverse transcription-PCR in formalin-fixed, paraffin-embedded tissues, and clinical outcome in 819 breast cancer patients according to molecular subtype.ResultsThe prognostic significance of clinical and gene variables varied according to the molecular subtype. Univariate analysis showed that positive lymph node status was significantly correlated with the increased risk of distant metastasis in all subtypes except the hormone receptor-negative, HER2-positive (HR−/HER2+) subtype. Most p-genes were significantly associated with poor prognosis in patients with the HR+/HER2− subtype, whereas i-genes correlated with a favorable outcome in patients with HR−/HER2+ breast cancer. In HR−/HER2+ breast cancer, four genes (three i-genes BTN3A2, CD2, and TRBC1 and the p-gene MMP11) were significantly associated with distant metastasis-free survival (DMFS). A new prognostic model for HR−/HER2+ breast cancer based on the expression of MMP11 and CD2 was developed and the DMFS for patients in the high-risk group according to our model was significantly lower than that for those in the low-risk group. Multivariate analyses revealed that our risk score is an independent prognostic factor for DMFS. Moreover, C-index showed that our risk score has a superior prognostic performance to traditional clinicopathological factors.ConclusionsOur new prognostic model for HR−/HER2+ breast cancer provides more accurate information on the risk of distant metastasis than traditional clinical prognostic factors and may be used to identify patients with a good prognosis in this aggressive subtype of breast cancer.
Highlights
Breast cancer is a highly heterogeneous disease and is currently classified into four general molecular subtypes according to the status of hormone receptors, including estrogen receptor (ER) or progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) [1]
The HR?/HER22 subtype had the highest percent of histologic grade 1 and 2 tumors, whereas the HR2/HER2? and TNBC subtypes consisted of a higher proportion of grade 3 tumors
Our model showed the best performance in predicting the risk of distant metastasis with the highest concordance index (C-index) (0.694) among other traditional prognostic factors (Fig. 2) or prognostic models based on clinicopathological factors alone (Supplementary Fig. S3)
Summary
Breast cancer is a highly heterogeneous disease and is currently classified into four general molecular subtypes according to the status of hormone receptors, including estrogen receptor (ER) or progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) [1]. Gene expression-based approaches provide significant prognostic or predictive information, and commercial assays such as Oncotype DX [5, 6], MammaPrint [7, 8], Prosigna [9, 10], and EndoPredict [11] based on multigene expression profiling in frozen or formalin-fixed, paraffin-embedded (FFPE) samples have been developed for ER-positive (ER?) breast cancer These assays predict the risk of distant recurrence after hormone therapy and are useful to identify patients who will benefit from adjuvant chemotherapy by discriminating high- and low-risk patients with early ER? Meta-analysis using publicly available microarray data from over 2100 patients showed that the key biological processes associated with the clinical outcome of patients with
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