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Cancers are often associated with hypoxia and metabolic reprogramming, resulting in enhanced tumor progression. Here, we aim to study breast cancer hypoxia responses, focusing on secreted proteins from low-grade (luminal-like) and high-grade (basal-like) cell lines before and after hypoxia. We examine the overlap between proteomics data from secretome analysis and laser microdissected human breast cancer stroma, and we identify a 33-protein stromal-based hypoxia profile (33P) capturing differences between luminal-like and basal-like tumors. The 33P signature is associated with metabolic differences and other adaptations following hypoxia. We observe that mRNA values for 33P predict patient survival independently of molecular subtypes and basic prognostic factors, also among low-grade luminal-like tumors. We find a significant prognostic interaction between 33P and radiation therapy. The role of hypoxia and metabolic reprogramming in breast cancer remains to be explored. Here, the authors investigate the landscape of secreted proteins in response to hypoxia in breast cancer cell lines and identify a stromal-based hypoxia profile in breast cancer tissue.

Digital pathology enables automatic analysis of histopathological sections using artificial intelligence. Automatic evaluation could improve diagnostic efficiency and find associations between morphological features and clinical outcome. For development of such prediction models in breast cancer, identifying invasive epithelial cells, and separating these from benign epithelial cells and in situ lesions would be important. In this study, we trained an attention gated U-Net for segmentation of epithelial cells in hematoxylin and eosin stained breast cancer sections. We generated epithelial ground truths by immunohistochemistry, restaining hematoxylin and eosin sections with cytokeratin AE1/AE3, combined with pathologists’ annotations. Tissue microarrays from 839 patients, and whole slide images from two patients, were used for training and evaluation of the models. The sections were derived from four breast cancer cohorts. Tissue microarray cores from a fifth cohort of 21 patients was used as a second test set. In quantitative evaluation, mean Dice scores of 0.70, 0.79, and 0.75 were achieved for invasive epithelial cells, benign epithelial cells, and in situ lesions, respectively. In qualitative scoring (0-5) by pathologists, the best results were reached for all epithelium and invasive epithelium, with scores of 4.7 and 4.4, respectively. Scores for benign epithelium and in situ lesions were 3.7 and 2.0, respectively. The proposed model segmented epithelial cells well, but further work is needed for accurate subclassification into benign, in situ , and invasive cells.

In the growing tumor, hypoxia may lead to tumor necrosis which is associated with more aggressive tumor features and reduced patient survival. However, there are shortcomings in our understanding of biological features and clinical significance linked to tumor necrosis. We therefore analyzed transcriptome mRNA expression profiles from primary breast tumors from TCGA and METABRIC (n = 2289) including TCGA mutational data (n = 409). We employed bioinformatics analysis and independent literature-based signatures for validation to identify alterations unique to necrosis. Necrosis was associated with aggressive tumor features and strongly predicted the basal-like breast cancer phenotype. Increased tumor cell proliferation, hypoxia, stemness, and epithelial-to-mesenchymal transition (EMT) were observed in tumors with necrosis. From gene expression data, we constructed a novel Breast Cancer Necrosis Signature (BCNS) score that was a strong predictor of the basal-like phenotype but also conveyed information relevant to the luminal subtypes of breast cancer, including prognosis. Mutational profiling pointed to enrichment of TP53 and PIK3CA mutations in tumors with and without necrosis, respectively. This study confirms the association of breast cancer necrosis with aggressive tumor features and reduced survival, and points to the BCNS score as a potential biomarker that should be further explored and validated to improve breast cancer diagnosis and management.

Stromal elastosis is related to good prognosis in breast cancer and fibulin-2 helps to stabilize elastic fibers in basement membranes. Here, we examined the level of perivascular fibulin-2 expression in relation to elastosis content, vascular invasion, molecular subtypes, tumour detection mode, and patient prognosis in breast cancer. We performed a population based retrospective study of invasive breast cancers from the Norwegian Breast Screening Program (Vestfold County, 2004–2009) including 200 screen-detected and 82 interval cancers. Perivascular fibulin-2 staining was semi-quantitatively graded based on immunohistochemistry (1–3) and dichotomized as high expression (grade 2–3) and low expression (grade 1). Elastosis content was graded on a 4-tiered scale and dichotomized as high (score 3) and low (score 0–2) expression, whereas lymphatic (LVI) and blood vessel invasion (BVI) were recorded as absent or present by immunohistochemistry. High perivascular fibulin-2 expression was strongly related to stromal elastosis (p<0.001), and inversely associated with BVI and LVI (p<0.001 for both). High fibulin-2 was associated with luminal breast cancer subgroups (p<0.001) and inversely with interval cancers compared with screen-detected tumours (p<0.001). By univariate analysis, low perivascular fibulin-2 was associated with reduced recurrence-free survival (p = 0.002) and disease specific survival (p = 0.019). Low perivascular fibulin-2 expression was strongly related to vascular invasion, low stromal elastosis, non-luminal breast cancer subtypes, interval presentation, and adverse prognosis.

Background Towards discovering robust cancer biomarkers, it is imperative to unravel the cellular heterogeneity of patient samples and comprehend the interactions between cancer cells and the various cell types in the tumor microenvironment. The first generation of ‘partial’ computational deconvolution methods required prior information either on the cell/tissue type proportions or the cell/tissue type-specific expression signatures and the number of involved cell/tissue types. The second generation of ‘complete’ approaches allowed estimating both of the cell/tissue type proportions and cell/tissue type-specific expression profiles directly from the mixed gene expression data, based on known (or automatically identified) cell/tissue type-specific marker genes. Results We present Deblender, a flexible complete deconvolution tool operating in semi−/unsupervised mode based on the user’s access to known marker gene lists and information about cell/tissue composition. In case of no prior knowledge, global gene expression variability is used in clustering the mixed data to substitute marker sets with cluster sets. In addition, we integrate a model selection criterion to predict the number of constituent cell/tissue types. Moreover, we provide a tailored algorithmic scheme to estimate mixture proportions for realistic experimental cases where the number of involved cell/tissue types exceeds the number of mixed samples. We assess the performance of Deblender and a set of state-of-the-art existing tools on a comprehensive set of benchmark and patient cancer mixture expression datasets (including TCGA). Conclusion Our results corroborate that Deblender can be a valuable tool to improve understanding of gene expression datasets with implications for prediction and clinical utilization. Deblender is implemented in MATLAB and is available from ( https://github.com/kondim1983/Deblender/ ).

The incidence of breast cancer in young women (aged under 40) is on the rise and is associated with more aggressive tumor characteristics and lower survival rates. Breast cancer is most frequently diagnosed in the sixth decade, and most research presents results based on data from older patients. By using large-scale clinico-pathologic and transcriptomic data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (n = 1932), we aimed to explore age-related differences in treatment, tumor characteristics, and gene expression signatures. Young patients presented more aggressive clinico-pathologic features such as higher histological grade, more frequent lymph node metastasis involvement, and estrogen receptor negativity. Accordingly, age below 40 years was associated with lower mRNA expression of the estrogen- and progesterone receptors, encoded by ESR1 and PGR , a higher proportion of the basal-like subtype, and increased transcription patterns reflecting stemness. Young breast cancer patients showed reduced survival, also within the basal-like subtype. We observed age-related differences in treatment, with more patients receiving chemotherapy among the young. Our results confirm a more challenging disease in young patients with breast cancer despite the more abundant use of chemotherapy. This argues for increased attention to young patients in current management and future research in breast cancer.

A subset of breast cancer patients benefits from preoperative bevacizumab and chemotherapy, but validated predictive biomarkers are lacking. Here, we aimed to evaluate tissue-based angiogenesis markers for potential predictive value regarding response to neoadjuvant bevacizumab treatment in breast cancer. In this randomized 1:1 phase II clinical trial, 132 patients with large or locally advanced HER2-negative tumors received chemotherapy ± bevacizumab. Dual Factor VIII/Ki-67 immunohistochemical staining was performed on core needle biopsies at baseline and week 12. Microvessel density (MVD), proliferative microvessel density (pMVD; Factor VIII/Ki-67 co-expression), glomeruloid microvascular proliferation (GMP), and a gene expression angiogenesis signature score, were studied in relation to pathologic complete response (pCR), clinico-pathologic features and intrinsic molecular subtype. We found that high baseline MVD (by median) significantly predicted pCR in the bevacizumab-arm (odds ratio 4.9, P  = 0.012). High pMVD, presence of GMP, and the angiogenesis signature score did not predict pCR, but were associated with basal-like ( P  ≤ 0.009) and triple negative phenotypes ( P  ≤ 0.041). pMVD and GMP did also associate with high-grade tumors ( P  ≤ 0.048). To conclude, high baseline MVD significantly predicted response to bevacizumab treatment. In contrast, pMVD, GMP, and the angiogenesis signature score, did not predict response, but associated with aggressive tumor features, including basal-like and triple-negative phenotypes.

CD47 expressed on tumor cells binds to signal regulatory protein alpha on macrophages, initiating inhibition of phagocytosis. We investigated the relationships between tumor expression of CD47 and CD68 macrophage content, subsets of tumor‐infiltrating lymphocytes (TILs), and vascular invasion in breast cancer. A population‐based series of 282 cases (200 screen detected and 82 interval patients) from the Norwegian Breast Cancer Screening Program was examined. Immunohistochemical staining for CD47 and CD68 was evaluated on tissue microarray (TMA) slides. For CD47 evaluation, a staining index was used. CD68 tumor‐associated macrophages were counted and dichotomized. TIL subsets (CD45, CD3, CD4, CD8, and FOXP3) were counted and dichotomized using immunohistochemistry on TMA slides. Vascular invasion (both lymphatic and blood vessel) was determined on whole tissue slides. High CD47 tumor cell expression or high counts of CD68 macrophages were significantly associated with elevated levels of all TIL subsets (p < 0.02), CD163 macrophages (p < 0.001), blood vessel invasion (CD31 positive) (p < 0.01), and high tumor cell Ki67 (p < 0.004). High CD47 expression was associated with ER negativity (p < 0.001), HER2 positive status (p = 0.03), and interval‐detected tumors (p = 0.03). Combined high expression of CD47–CD68 was associated with a shorter recurrence‐free survival (RFS) by multivariate analysis (hazard ratio [HR]: 2.37, p = 0.018), adjusting for tumor diameter, histologic grade, lymph node status, and molecular subtype. Patients with luminal A tumors showed a shorter RFS for CD47–CD68 high cases by multivariate assessment (HR: 5.73, p = 0.004). This study demonstrates an association of concurrent high CD47 tumor cell expression and high CD68 macrophage counts with various TIL subsets, blood vessel invasion (CD31 positive), other aggressive tumor features, and interval‐presenting breast cancer. Our findings suggest a link between CD47, tumor immune response, and blood vessel invasion (CD31 positive). Combined high expression of CD47–CD68 was an independent prognostic factor associated with poor prognosis in all cases, as well as in the luminal A category.

Endometrial cancer incidence is continuing to rise in the wake of the current ageing and obesity epidemics. Much of the risk for endometrial cancer development is influenced by the environment and lifestyle. Accumulating evidence suggests that the epigenome serves as the interface between the genome and the environment and that hypermethylation of stem cell polycomb group target genes is an epigenetic hallmark of cancer. The objective of this study was to determine the functional role of epigenetic factors in endometrial cancer development. Epigenome-wide methylation analysis of >27,000 CpG sites in endometrial cancer tissue samples (n = 64) and control samples (n = 23) revealed that HAND2 (a gene encoding a transcription factor expressed in the endometrial stroma) is one of the most commonly hypermethylated and silenced genes in endometrial cancer. A novel integrative epigenome-transcriptome-interactome analysis further revealed that HAND2 is the hub of the most highly ranked differential methylation hotspot in endometrial cancer. These findings were validated using candidate gene methylation analysis in multiple clinical sample sets of tissue samples from a total of 272 additional women. Increased HAND2 methylation was a feature of premalignant endometrial lesions and was seen to parallel a decrease in RNA and protein levels. Furthermore, women with high endometrial HAND2 methylation in their premalignant lesions were less likely to respond to progesterone treatment. HAND2 methylation analysis of endometrial secretions collected using high vaginal swabs taken from women with postmenopausal bleeding specifically identified those patients with early stage endometrial cancer with both high sensitivity and high specificity (receiver operating characteristics area under the curve = 0.91 for stage 1A and 0.97 for higher than stage 1A). Finally, mice harbouring a Hand2 knock-out specifically in their endometrium were shown to develop precancerous endometrial lesions with increasing age, and these lesions also demonstrated a lack of PTEN expression. HAND2 methylation is a common and crucial molecular alteration in endometrial cancer that could potentially be employed as a biomarker for early detection of endometrial cancer and as a predictor of treatment response. The true clinical utility of HAND2 DNA methylation, however, requires further validation in prospective studies. Please see later in the article for the Editors' Summary.

Presence of lymph node (LN) metastasis is a strong prognostic factor in breast cancer, whereas the importance of extra-nodal extension and other nodal tumor features have not yet been fully recognized. Here, we examined microscopic features of lymph node metastases and their prognostic value in a population-based cohort of node positive breast cancer (n = 218), as part of the prospective Norwegian Breast Cancer Screening Program NBCSP (1996-2009). Sections were reviewed for the largest metastatic tumor diameter (TD-MET), nodal afferent and efferent vascular invasion (AVI and EVI), extra-nodal extension (ENE), number of ENE foci, as well as circumferential (CD-ENE) and perpendicular (PD-ENE) diameter of extra-nodal growth. Number of positive lymph nodes, EVI, and PD-ENE were significantly increased with larger primary tumor (PT) diameter. Univariate survival analysis showed that several features of nodal metastases were associated with disease-free (DFS) or breast cancer specific survival (BCSS). Multivariate analysis demonstrated an independent prognostic value of PD-ENE (with 3 mm as cut-off value) in predicting DFS and BCSS, along with number of positive nodes and histologic grade of the primary tumor (for DFS: P = 0.01, P = 0.02, P = 0.01, respectively; for BCSS: P = 0.02, P = 0.008, P = 0.02, respectively). To conclude, the extent of ENE by its perpendicular diameter was independently prognostic and should be considered in line with nodal tumor burden in treatment decisions of node positive breast cancer.