First generation prognostic gene signatures for breast cancer predict both survival and chemotherapy sensitivity and identify overlapping patient populations

Abstract

The aims of this study were to compare the performance of six different genomic prognostic markers to predict long-term survival and chemotherapy response on the same patient cohort and assess if clinicopathological variables carry independent prognostic and predictive values. We examined seven clinical variables and six previously described prognostic signatures on 228 tumors from patients who received homogeneous preoperative chemotherapy and had long-term follow-up information for survival. We used the area under the receiver operator characteristic curve (AUC) to compare predictors and also performed univariate and multivariate analyses including the genomic and clinical variables and plotted Kaplan-Meir survival curves. All genomic prognostic markers had statistically similar AUCs and sensitivity to predict 5-year progression-free survival (PFS, sensitivities ranged from 0.591 to 0.773, and AUCs: 0.599-0.673), overall survival (OS, sensitivities: 0.590-0.769, AUCs: 0.596-0.684) and pathologic complete response (pCR, sensitivities: 0.596-0.851, AUCs: 0.614-0.805). In multivariate analysis, the genomic markers were not independent from one another; however, estrogen receptor (Odds Ratio [OR] 7.63, P < 0.001) and HER2 status (OR: 0.37, P = 0.021) showed significant independent predictive values for pCR. Nodal status remained an independent prognostic, but not predictive, variable (OR for PFS: 2.77, P = 0.021, OR for OS: 3.62, P = 0.01). There was moderate to good agreement between different prediction results in pair-wise comparisons. First-generation prognostic-gene signatures predict both chemotherapy response and long-term survival. When multiple predictors are applied to the same case discordant risk prediction frequently occurs.

Immunohistochemical Ki67 labeling index has similar proliferation predictive power to various gene signatures in breast cancer

“…The other covariates, including PgR status, tumor size, nodal status, and type of surgery, may have distinct prognostic power independent of proliferative markers such as histological grade and IHC Ki67. Iwamoto et al (15) reported similar results indicating that clinical variables remained predictive of survival or chemotherapy response independent of genetic markers. As a well-established cell proliferation marker in breast cancer, IHC Ki67 is an excellent candidate biomarker for luminal B tumors in ER-positive cases.…”

“…Also, genomic markers with multiple genes were assessed by average gene expression based on data normalized using the MAS5 algorithm, and log 2-converted mRNA gene expression data, a departure from the original methods used in similar published reports. (15) For determining prognosis and predicting sensitivity to chemotherapy, gene expression profiling (by, for example, the 21-gene or 70-gene signatures) remains the gold standard. Nevertheless, we suggest that IHC Ki67 could emerge as a cost-effective alternative, defined and validated for worldwide clinical diagnostic use.…”

“…(13,14) One of our co-authors previously showed that genetic markers and Ki67 mRNA expression (mRNA Ki67) had similar predictive power for both prognosis and sensitivity to chemotherapy. (15) However, few clinical datasets provide information on correlations between genomic markers, mRNA Ki67, and IHC Ki67 in the same cohort of patients with survival data.…”

Relationship between Complete Pathologic Response to Neoadjuvant Chemotherapy and Survival in Triple-Negative Breast Cancer

“…For example, high tumor proliferation rate is associated with higher probability of pCR but also with worse prognosis (25), although high tumor infiltrating lymphocyte count is associated with higher pCR rate and better prognosis (26,27). Many similar, yet to be identified, interactions between prognostic markers and pCR may exist.…”

Agreement in Risk Prediction Between the 21-Gene Recurrence Score Assay (Oncotype DX®) and the PAM50 Breast Cancer Intrinsic Classifier™ in Early-Stage Estrogen Receptor–Positive Breast Cancer

“…However, each of the tests relies on a different set of genes, with only a modest overlap between assays, and therefore may assign a different risk category to the same patient. Although several studies examined classification overlap among various genomic prognostic tests using proxy models, such as gene expression array-based unofficial versions of Oncotype DX and modified versions of published assays [20,21], no direct comparison of any two commercially available assays in the same patient population has been reported to date. An imminent clinical challenge for practicing physicians is to understand how different assays relate to each other and what to expect when more than one assay is used for the same cancer.…”