Breast cancer (BC) is a heterogeneous disease in which the tumor microenvironment (TME) seems to impact the clinical outcome. Here, we investigated whether a combination of gene expression signatures relating to both the structural and immune TME aspects can help predict prognosis in women with high‐grade BC (HGBC). Thus, we focused on a combined molecular biomarker variable that involved extracellular matrix (ECM)‐associated gene expression (ECM3 signature) and interferon (IFN)‐associated metagene (IFN metagene) expression. In 97 chemo‐naive HGBCs from the METABRIC dataset, the dichotomous ECM3/IFN (dECIF) variable identified a group of high‐risk patients (ECM3 +/IFN − vs other; hazard ratio = 3.2, 95% confidence interval: 1.5–6.7). Notably, ECM3 +/IFN − tumors showed low tumor‐infiltrating lymphocytes, high levels of CD33‐positive cells, absence of PD‐1 expression, or low expression of PD‐L1, as suggested by immune profiles and immune‐histochemical analysis on an independent cohort of 131 HGBCs. To make our results transferable to clinical use, we refined the dECIF biomarker using reduced ECM3 and IFN signatures; notably, the prognostic value of this reduced dECIF was comparable to that of the original dECIF. After validation in a new BC cohort, reduced dECIF was translated into a robust qPCR classifier for real‐world clinical use.
This study investigates the combination of two relevant molecular signatures of the tumor microenvironment (TME) in identifying aggressive high‐grade breast cancers (HGBCs). The novel molecular biomarker described here highlighted patients with worst HGBC prognosis and a peculiar TME. Finally, to improve the potential of the identified biomarker in the clinic, we reduced the two original signatures and technically validated the biomarker's expression through a qPCR‐based assay.