An optimized five-gene multi-platform predictor of hormone receptor negative and triple negative breast cancer metastatic risk.

Introduction: Outcome predictors in use today are prognostic only for hormone receptor-positive (HRpos) breast cancer. Although microarray-derived multigene predictors of hormone receptor-negative (HRneg) and/or triple negative (Tneg) breast cancer recurrence risk are emerging, to date none have been transferred to clinically suitable assay platforms (for example, RT-PCR) or validated against formalin-fixed paraffin-embedded (FFPE) HRneg/Tneg samples.

Methods: Multiplexed RT-PCR was used to assay two microarray-derived HRneg/Tneg prognostic signatures IR-7 and Buck-4) in a pooled FFPE collection of 139 chemotherapy-naïve HRneg breast cancers. The prognostic value of the RTPCR measured gene signatures were evaluated as continuous and dichotomous variables, and in conditional risk models incorporating clinical parameters. An optimized five-gene index was derived by evaluating gene combinations from both signatures.

Results: RT-PCR measured IR-7 and Buck-4 signatures proved prognostic as continuous variables; and conditional risk modeling chose nodal status, the IR-7 signature, and tumor grade as significant predictors of distant recurrence (DR). From the Buck-4 and IR-7 signatures, an optimized five-gene (TNFRSF17, CLIC5, HLA-F, CXCL13, XCL2) predictor was generated, referred to as the Integrated Cytokine Score (ICS) based on its functional pathway linkage through interferon-γ and IL-10. Across all FFPE cases, the ICS was prognostic as either a continuous or dichotomous variable, and conditional risk modeling selected nodal status and ICS as DR predictors. Further dichotomization of node-negative/ICS-low FFPE cases identified a subset of low-grade HRneg tumors with <10% 5-year DR risk. The prognostic value of ICS was reaffirmed in two previously studied microarray assayed cohorts containing 274 node-negative and chemotherapy naive HRneg breast cancers, including 95 Tneg cases where it proved prognostically independent of Tneg molecular subtyping. In additional HRneg/Tneg microarray assayed cohorts, the five-gene ICS also proved prognostic irrespective of primary tumor nodal status and adjuvant chemotherapy intervention.

Conclusion: We advanced the measurement of two previously reported microarray-derived HRneg/Tneg breast cancer prognostic signatures for use in FFPE samples, and derived an optimized five-gene Integrated Cytokine Score (ICS) with multi-platform capability of predicting metastatic outcome from primary HRneg/Tneg tumors independent of nodal status, adjuvant chemotherapy use, and Tneg molecular subtype.