Clinical outcome of patients with triple-negative breast cancer (TNBC) is highly variable. This study aims to identify and validate a prognostic protein signature for TNBC patients to reduce unnecessary adjuvant systemic therapy. Frozen primary tumors were collected from 126 lymph node–negative and adjuvant therapy–naive TNBC patients. These samples were used for global proteome profiling in two series: an in-house training (n = 63) and a multicenter test (n = 63) set. Patients who remained free of distant metastasis for a minimum of 5 years after surgery were defined as having good prognosis. Cox regression analysis was performed to develop a prognostic signature, which was independently validated. All statistical tests were two-sided. An 11-protein signature was developed in the training set (median follow-up for good-prognosis patients = 117 months) and subsequently validated in the test set (median follow-up for good-prognosis patients = 108 months) showing 89.5% sensitivity (95% confidence interval [CI] = 69.2% to 98.1%), 70.5% specificity (95% CI = 61.7% to 74.2%), 56.7% positive predictive value (95% CI = 43.8% to 62.1%), and 93.9% negative predictive value (95% CI = 82.3% to 98.9%) for poor-prognosis patients. The predicted poor-prognosis patients had higher risk to develop distant metastasis than the predicted good-prognosis patients in univariate (hazard ratio [HR] = 13.15; 95% CI = 3.03 to 57.07; P = .001) and multivariable (HR = 12.45; 95% CI = 2.67 to 58.11; P = .001) analysis. Furthermore, the predicted poor-prognosis group had statistically significantly more breast cancer–specific mortality. Using our signature as guidance, more than 60% of patients would have been exempted from unnecessary adjuvant chemotherapy compared with conventional prognostic guidelines. We report the first validated proteomic signature to assess the natural course of clinical TNBC.

Ferritin heavy chain (FTH1) is a 21-kDa subunit of the ferritin complex, known for its role in iron metabolism, and which has recently been identified as a favorable prognostic protein for triple negative breast cancer (TNBC) patients. Currently, it is not well understood how FTH1 contributes to an anti-tumor response. Here, we explored whether expression and cellular compartmentalization of FTH1 correlates to an effective immune response in TNBC patients. Analysis of the tumor tissue transcriptome, complemented with in silico pathway analysis, revealed that FTH1 was an integral part of an immunomodulatory network of cytokine signaling, adaptive immunity, and cell death. These findings were confirmed using mass spectrometry (MS)-derived proteomic data, and immunohistochemical staining of tissue microarrays. We observed that FTH1 is localized in both the cytoplasm and/or nucleus of cancer cells. However, high cytoplasmic (c) FTH1 was associated with favorable prognosis (Log-rank p = 0.001), whereas nuclear (n) FTH1 staining was associated with adverse prognosis (Log-rank p = 0.019). cFTH1 staining significantly correlated with total FTH1 expression in TNBC tissue samples, as measured by MS analysis (Rs = 0.473, p = 0.0007), but nFTH1 staining did not (Rs = 0.197, p = 0.1801). Notably, IFN γ-producing CD8+ effector T cells, but not CD4+ T cells, were preferentially enriched in tumors with high expression of cFTH1 (p = 0.02). Collectively, our data provide evidence toward new immune regulatory properties of FTH1 in TNBC, which may facilitate development of novel therapeutic targets.

In a previous study, we detected a significant association between phosphoserine aminotransferase 1 (PSAT1) hyper-methylation and mRNA levels to outcome to tamoxifen treatment in recurrent disease. We here aimed to study the association of PSAT1 protein levels to outcome upon tamoxifen treatment and to obtain more insight in its role in tamoxifen resistance. A cohort of ER positive, hormonal therapy naïve primary breast carcinomas was immunohistochemically (IHC) stained for PSAT1. Staining was analyzed for association with patient’s time to progression (TTP) and overall response on first-line tamoxifen for recurrent disease. PSAT1 mRNA levels were also assessed by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR; n = 161) and Affymetrix GeneChip (n = 155). Association of PSAT1 to biological pathways on tamoxifen outcome were assessed by global test. PSAT1 protein and mRNA levels were significantly associated to poor outcome to tamoxifen treatment. When comparing PSAT1 protein and mRNA levels, IHC and RT-qPCR data showed a significant association. Global test results showed that cytokine and JAK-STAT signaling were associated to PSAT1 expression. We hereby report that PSAT1 protein and mRNA levels measured in ER positive primary tumors are associated with poor clinical outcome to tamoxifen.