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Metastatic breast cancers are still incurable. Characterizing the evolutionary landscape of these cancers, including the role of metastatic axillary lymph nodes (ALNs) in seeding distant organ metastasis, can provide a rational basis for effective treatments. Here, we have described the genomic analyses of the primary tumors and metastatic lesions from 99 samples obtained from 20 patients with breast cancer. Our evolutionary analyses revealed diverse spreading and seeding patterns that govern tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, in which multiple metastatic subclones originated from the primary tumor and/or other distant metastases. Synchronous ALN metastasis, a well-established prognosticator of breast cancer, was not involved in seeding the distant metastasis, suggesting a hematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably an increase in apolipoprotein B mRNA–editing enzyme, catalytic polypeptide-like–associated (APOBEC-associated) mutagenesis. Our data provide genomic evidence for a role of ALN metastasis in seeding distant organ metastasis and elucidate the evolving mutational landscape during cancer progression.

Breast cancer cells with stem cell characteristics (CSC) are a distinct cell population with phenotypic similarities to mammary stem cells. CSCs are important drivers of tumorigenesis and the metastatic process. Tamoxifen is the most widely used hormonal therapy for estrogen receptor (ER) positive cancers. In our study, tamoxifen was effective in reducing proliferation of ER + adherent cancer cells, but not their CSC population. We isolated, expanded and incubated CSC from seven breast cancers with or without tamoxifen. By genome-wide transcriptional analysis we identified tamoxifen-induced transcriptional pathways associated with ribosomal biogenesis and mRNA translation, both regulated by the mTOR-pathway. We observed induction of the key mTOR downstream targets S6K1, S6RP and 4E-BP1 in-patient derived CSCs by tamoxifen on protein level. Using the mTOR inhibitors rapamycin, everolimus and PF-04691502 (a dual PI3K/mTOR inhibitor) and in combination with tamoxifen, significant reduction in mammosphere formation was observed. Hence, we suggest that the CSC population play a significant role during endocrine resistance through activity of the mTOR pathway. In addition, tamoxifen further stimulates the mTOR-pathway but can be antagonized using mTOR-inhibitors.

Background Transcriptomic profiling of breast tumors provides opportunity for subtyping and molecular-based patient stratification. In diagnostic applications the specimen profiled should be representative of the expression profile of the whole tumor and ideally capture properties of the most aggressive part of the tumor. However, breast cancers commonly exhibit intra-tumor heterogeneity at molecular, genomic and in phenotypic level, which can arise during tumor evolution. Currently it is not established to what extent a random sampling approach may influence molecular breast cancer diagnostics. Methods In this study we applied RNA-sequencing to quantify gene expression in 43 pieces (2-5 pieces per tumor) from 12 breast tumors (Cohort 1). We determined molecular subtype and transcriptomic grade for all tumor pieces and analysed to what extent pieces originating from the same tumors are concordant or discordant with each other. Additionally, we validated our finding in an independent cohort consisting of 19 pieces (2-6 pieces per tumor) from 6 breast tumors (Cohort 2) profiled using microarray technique. Exome sequencing was also performed on this cohort, to investigate the extent of intra-tumor genomic heterogeneity versus the intra-tumor molecular subtype classifications. Results Molecular subtyping was consistent in 11 out of 12 tumors and transcriptomic grade assignments were consistent in 11 out of 12 tumors as well. Molecular subtype predictions revealed consistent subtypes in four out of six patients in this cohort 2. Interestingly, we observed extensive intra-tumor genomic heterogeneity in these tumor pieces but not in their molecular subtype classifications. Conclusions Our results suggest that macroscopic intra-tumoral transcriptomic heterogeneity is limited and unlikely to have an impact on molecular diagnostics for most patients. Electronic supplementary material The online version of this article (10.1186/s12885-017-3815-2) contains supplementary material, which is available to authorized users.

Background: The expression of oestrogen receptor (ER) α characterises a subset of breast cancers associated with good response to endocrine therapy. However, the clinical significance of the second ER, ERβ1, and its splice variant ERβcx is still unclear. Methods: We here report an assessment of ERα, ERβ1 and ERβcx by immunohistochemistry using quantitative digital image analysis of 340 primary tumours and corresponding sentinel lymph nodes. Results: No differences were seen in ER levels in primary tumours vs lymph node metastases. ERβ1 and ERβcx were equally distributed among age groups and tumour histological grades. Loss of ERβ1 in the primary tumour was strongly associated with poor survival. Its prognostic impact was particularly evident in young patients and in high-grade tumours. The worst outcome was seen in the tumours lacking both ERα and ERβ1. ERβcx expression in the primary tumour correlated with a higher risk of lymph node metastasis, and with poor survival when expressed in sentinel node lymphocytes. Conclusions: Our study reveals highly significant although antagonising roles of ERβ1 and ERβcx in breast cancer. Consequently, we suggest that the histopathological assessment of ERβ1 is of value as a prognostic and potentially predictive biomarker.

Breast cancer is a unique tumor disease in terms of the stringent requirement of predictive biomarker assessments. As recommended by current international guidelines, the established markers consist of estrogen receptor (ER), progesterone receptor, human epidermal growth factor and Ki67, and are primarily analyzed by immunohistochemistry. However, new diagnostic methods based on microarray or next-generation sequencing on DNA and mRNA level are gaining ground. These analyses require fresh-frozen tumor tissue that is generally not available from tumors