Transforming growth factor-β (TGF-β) acts as a pro-metastatic factor in advanced breast cancer. RNF12, an E3 ubiquitin ligase, stimulates TGF-β signaling by binding to the inhibitory SMAD7 and inducing its proteasomal degradation. How RNF12 activity is regulated and its exact role in cancer is incompletely understood. Here we report that RNF12 was overexpressed in invasive breast cancers and its high expression correlated with poor prognosis. RNF12 promoted breast cancer cell migration, invasion, and experimental metastasis in zebrafish and murine xenograft models. RNF12 levels were positively associated with the phosphorylated AKT/protein kinase B (PKB) levels, and both displayed significant higher levels in the basal-like subtype compared with the levels in luminal-like subtype of breast cancer cells. Mechanistically, AKT-mediated phosphorylation induced the nuclear localization of RNF12, maintained its stability, and accelerated the degradation of SMAD7 mediated by RNF12. Furthermore, we demonstrated that RNF12 and AKT cooperated functionally in breast cancer cell migration. Notably, RNF12 expression strongly correlated with both phosphorylated AKT and phosphorylated SMAD2 levels in breast cancer tissues. Thus, our results uncovered RNF12 as an important determinant in the crosstalk between the TGF-β and AKT signaling pathways during breast cancer progression.

Purpose The tumor-stroma ratio (TSR) has repeatedly proven to be correlated with patient outcomes in breast cancer using large retrospective cohorts. However, studies validating the TSR often show variability in methodology, thereby hampering comparisons and uniform outcomes. Method This paper provides a detailed description of a simple and uniform TSR scoring method using Hematoxylin and Eosin (H&E)-stained core biopsies and resection tissue, specifically focused on breast cancer. Possible histological challenges that can be encountered during scoring including suggestions to overcome them are reported. Moreover, the procedure for TSR estimation in lymph nodes, scoring on digital images and the automatic assessment of the TSR using artificial intelligence are described. Conclusion Digitized scoring of tumor biopsies and resection material offers interesting future perspectives to determine patient prognosis and response to therapy. The fact that the TSR method is relatively easy, quick, and cheap, offers great potential for its implementation in routine diagnostics, but this requires high quality validation studies.

The tumor-stroma ratio (TSR) has proven to be a strong prognostic factor in breast cancer, demonstrating better survival for patients with stroma-low tumors. Since the role of the TSR as a predictive marker for neoadjuvant chemotherapy outcome is yet unknown, this association was evaluated for HER2-negative breast cancer in the prospective DIRECT and NEOZOTAC trials. The TSR was assessed on 375 hematoxylin and eosinstained sections of pre-treatment biopsies. Associations between the TSR and chemotherapy response according to the Miller-Payne (MP) grading system, and between the TSR and pathological response were examined using Pearson's chi-square, Cochran-Armitage test for trend and regression analyses. A stroma-low tumor prior to neoadjuvant chemotherapy was significantly associated with a higher MP score (P = .005). This relationship remained significant in the estrogen receptor (ER)-negative subgroup (P = .047). The univariable odds ratio (OR) of a stroma-low tumor on pathological complete response (pCR) was 2.46 (95% CI 1.34-4.51, P = .004), which attenuated to 1.90 (95% CI 0.85-4.25, P = .119) after adjustment for relevant prognostic factors. Subgroup analyses revealed an OR of 5.91 in univariable analyses for ER-negativity (95% CI 1.19-29.48, P = .030) and 1.48 for ER-positivity (95% CI 0.73-3.01, P = .281). In conclusion, a low amount of stroma on pre-treatment biopsies is associated with a higher MP score and pCR rate. Therefore, the TSR is a promising biomarker in predicting neoadjuvant treatment outcome. Incorporating this parameter in routine pathological diagnostics could be worthwhile to prevent overtreatment and undertreatment.

Women identified with an increased risk of breast cancer due to mutations in cancer susceptibility genes or a familial history of breast cancer undergo tailored screening with the goal of detecting tumors earlier, when potential curative interventions are still possible. Ideally, screening would identify signs of carcinogenesis even before a tumor is detectable by imaging. This could be achieved by timely signaling of altered biomarker levels for precancerous processes in liquid biopsies. Currently, the Nipple Aspirate Fluid (NAF) and the Trial Early Serum Test BREAST cancer (TESTBREAST), both ongoing, prospective, multicenter studies, are investigating biomarkers in liquid biopsies to improve breast cancer screening in high-risk women. The NAF study focuses on changes over time in miRNA expression levels both in blood and NAF samples, whereas the TESTBREAST study analyzes changes in protein levels in blood samples at sequential interval timepoints. These within-subject changes are studied in relation to later occurrence of breast cancer using a nested case–control design. These longitudinal studies face their own challenges in execution, such as hindrances in logistics and in sample processing that were difficult to anticipate. This article offers insight into those challenges and concurrently aims to provide useful strategies for the set-up of similar studies. See related commentary by Sauter, p. 429

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