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How organ-specific metastatic traits arise in primary tumors remains unknown. Here, we show a role of the breast tumor stroma in selecting cancer cells that are primed for metastasis in bone. Cancer-associated fibroblasts (CAFs) in triple-negative (TN) breast tumors skew heterogeneous cancer cell populations toward a predominance of clones that thrive on(More)
BACKGROUND Published prognostic gene signatures in breast cancer have few genes in common. Here we provide a rationale for this observation by studying the prognostic power and the underlying biological pathways of different gene signatures. METHODS Gene signatures to predict the development of metastases in estrogen receptor-positive and estrogen(More)
The tumour-suppressor gene TP53 is frequently mutated in breast tumours, and the majority of the mutations are clustered within the core domain, the region involved in DNA binding. We searched for alterations in this central domain of the TP53gene in 222 human breast cancer specimens using polymerase chain reaction-single-strand conformation analysis(More)
We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive(More)
We have analyzed the DNA copy numbers for over 100,000 single-nucleotide polymorphism loci across the human genome in genomic DNA from 313 lymph node–negative primary breast tumors for which genome-wide gene expression data were also available. Combining these two data sets allowed us to identify the genomic loci and their mapped genes, having high(More)
MOTIVATION To evaluate microarray data, clustering is widely used to group biological samples or genes. However, problems arise when comparing heterologous databases. As the clustering algorithm searches for similarities between experiments, it will most likely first separate the data sets, masking relationships that exist between samples from different(More)
MOTIVATION Retrieval of information on biological processes from large-scale expression data is still a time-consuming task. An automated analysis utilizing all expression information would greatly increase our understanding of the samples under study. RESULTS We describe here a novel method to obtain a functional analysis of complex gene expression data.(More)
Breast cancer is a genetically and phenotypically complex disease. To understand the role of miRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer cell lines to identify miRNAs associated with the most common molecular subtypes and the most frequent genetic aberrations.(More)
BACKGROUND 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. METHODS Frozen primary tumors were collected from 126 lymph node-negative and adjuvant therapy-naive TNBC patients.(More)
Epithelial ovarian cancer is a highly heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Therapeutic approaches need to account for inter-patient and intra-tumoural heterogeneity and detailed characterization of in vitro models representing the different histological and molecular ovarian cancer subtypes is(More)