The aim of our retrospective study was to analyze patterns of subtype specific metastatic spread and to identify the time course of distant metastases. A consecutive series of 490 patients with breast cancer who underwent surgery and postoperative treatment at Semmelweis University, Hungary, and diagnosed between the years 2000 and 2007 was identified from the archives of the 2nd Department of Pathology, Hungary. Molecular subtypes were defined based on the 2011 St. Gallen recommendations. Statistical analysis was performed with SPSS Statistics for Windows, Version 22.0. Distant metastasis free survival (DMFS) was defined as the time elapsed between the first pathological diagnosis of the tumor and the first distant metastasis detection. Distant metastases were detected in 124 patients. Mean time to develop metastasis was 29 months (range 0-127 months). The longest DMFS was observed in the Luminal A (LUMA) subtype (mean 39 months) whereas the shortest was seen in the HER2-positive (HER2+) subtype (mean 21 months; p = 0.012). We confirmed that HER2+ tumors carry a higher risk for distant metastases (42.1%). LUMA-associated metastases were found to be solitary in 59% of cases, whereas HER2+ tumors showed multiple metastases in 79.2% of cases. LUMA tumors showed a preference for bone-only metastasis as compared with HER2+ and triple negative breast cancer (TNBC) cases, which exhibited a higher rate of brain metastasis. The most frequent second metastatic sites of hormone receptor (HR) positive tumors were the lung and liver, whereas the brain was the most affected organ in HR-negative (HR-) cases. Tumor subtypes differ in DMFS and in pattern of distant metastases. HER2+ tumors featured the most aggressive clinical course. Further identification of subtype-specific factors influencing prognosis might have an impact on clinical care and decision-making.

BackgroundStudies have partly demonstrated the clinical validity of Ki-67 as a predictive marker in the neoadjuvant setting, but the question of the best cut-off points as well as the importance of this marker as a prognostic factor in partial responder/non-responder groups remains uncertain.MethodsOne hundred twenty patients diagnosed with invasive breast cancer and treated with neoadjuvant chemotherapy (NAC) between 2002 and 2013 were retrospectively recruited to this study. The optimal cut-off value for Ki-67 labeling index (LI) to discriminate response to treatment was assessed by receiver operating characteristic (ROC) curve analysis. Kaplan-Meier curve estimation, log-rank test and cox regression analysis were carried out to reveal the association between Ki-67 categories and survival (DMFS = Distant metastases-free survival, OS = Overall survival).ResultsTwenty three out of 120 patients (19.2%) achieved pathologic complete remission (pCR), whereas partial remission (pPR) and no response (pNR) to neoadjuvant chemotherapy (NAC) was detected in 60.8% and 20.0%, respectively. The distribution of subtypes showed a significant difference in pathological response groups (p < 0.001). Most of the TNBC cases were represented in pCR group.The most relevant cut-off value for the Ki-67 distinguishing pCR from pNR cases was 20% (p = 0.002). No significant threshold for Ki-67 was found regarding DMFS (p = 0.208). Considering OS, the optimal cut-off point occurred at 15% Ki-67 (p = 0.006). The pPR group represented a significant Ki-67 threshold at 30% regarding OS (p = 0.001). Ki-67 and pPR subgroups were not significantly associated (p = 0.653). For prognosis prediction, Ki-67 at 30% cut-off value (p = 0.040) furthermore subtype (p = 0.037) as well as pathological response (p = 0.044) were suitable to separate patients into good and unfavorable prognosis cohorts regarding OS. However, in multivariate analyses, only Ki-67 at 30% threshold (p = 0.029), and subtype (p = 0.008) were independently linked to OS.ConclusionsNAC is more efficient in tumors with at least 20% Ki-67 LI. Both Ki-67 LI and subtype showed a significant association with pathological response. Ki-67 LI represented independent prognostic potential to OS in our neoadjuvant patient cohort, while pathological response did not. Additionally, our data also suggest that if a tumor is non-responder to NAC, increased Ki-67 is a poor prognostic marker.Electronic supplementary materialThe online version of this article (doi:10.1186/s13000-017-0608-5) contains supplementary material, which is available to authorized users.

Breast cancer is characterized by considerable metabolic diversity. A relatively high percentage of patients diagnosed with breast carcinoma do not respond to standard-of-care treatment, and alteration in metabolic pathways nowadays is considered one of the major mechanisms responsible for therapeutic resistance. Consequently, there is an emerging need to understand how metabolism shapes therapy response, therapy resistance and not ultimately to analyze the metabolic changes occurring after different treatment regimens. The most commonly applied neoadjuvant chemotherapy regimens in breast cancer contain an anthracycline (doxorubicin or epirubicin) in combination or sequentially administered with taxanes (paclitaxel or docetaxel). Despite several efforts, drug resistance is still frequent in many types of breast cancer, decreasing patients’ survival. Understanding how tumor cells rapidly rewire their signaling pathways to persist after neoadjuvant cancer treatment have to be analyzed in detail and in a more complex system to enable scientists to design novel treatment strategies that target different aspects of tumor cells and tumor resistance. Tumor heterogeneity, the rapidly changing environmental context, differences in nutrient use among different cell types, the cooperative or competitive relationships between cells pose additional challenges in profound analyzes of metabolic changes in different breast carcinoma subtypes and treatment protocols. Delineating the contribution of metabolic pathways to tumor differentiation, progression, and resistance to different drugs is also the focus of research. The present review discusses the changes in glucose and fatty acid pathways associated with the most frequently applied chemotherapeutic drugs in breast cancer, as well the underlying molecular mechanisms and corresponding novel therapeutic strategies.

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We hypothesized that different BC subtypes are characterized by spatially distinct tumor immune microenvironment (TIME) and that immune gene assembly of metastatic (Met) and non-metastatic (Ctrl) BCs vary across subtypes. Peritumoral, stromal and intratumoral TIL was assessed on 309 BC cases. Hot, cold and immune-excluded groups were defined, and the prognostic role of this classification was assessed. CD4+/CD8+ positivity was analyzed in 75 cases in four systematically predefined tumor regions. Immune gene expression of Met and Ctrl HER2-negative BCs was compared by using NanoString nCounter technology. The amount of TIL infiltration varied greatly within all BC subtypes. Two-third of the cases were cold tumors with no significant survival difference compared to hot tumors. A lower CD4+/CD8+ ratio at the stromal internal tumor region was significantly associated with longer distant metastasis-free survival. The differentially expressed immune genes between Met and Ctrl varied across the studied BC subtypes with TNBC showing distinct features from the luminal subtypes. The TIME is characterized by a considerable heterogeneity; however, low level of TILs does not equate to disease progression. The differences in immune gene expression observed between Met and Ctrl breast carcinomas call attention to the important role of altered immune function in BC progression.