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Tumor microenvironment and breast cancer survival: combined effects of breast fat, M2 macrophages and hyaluronan create a dismal prognosis.

ABSTRACT: PURPOSE:Tumor microenvironment, including inflammatory cells, adipocytes and extracellular matrix constituents such as hyaluronan (HA), impacts on cancer progression. Systemic metabolism also influences tumor growth e.g. obesity and type 2 diabetes (T2D) are risk factors for breast cancer. Here, in 262 breast cancer cases, we explored the combined impacts on survival of M2-like tumor associated macrophages (TAMs), the abundance of breast fat visualized as low density in mammograms, and tumor HA, and their associations with T2D. METHODS:Mammographic densities were assessed visually from the diagnostic images and dichotomized into very low density (VLD, density???10%, "fatty breast") and mixed density (MID, density?>?10%). The amounts of TAMs (CD163+ and CD68+) and tumor HA were determined by immunohistochemistry. The data of T2D was collected from the patient records. Statistical differences between the parameters were calculated with Chi square or Mann-Whitney test and survival analyses with Cox's model. RESULTS:A combination of fatty breasts (VLD), abundance of M2-like TAMs (CD163+) and tumor HA associated with poor survival, as survival was 88-89% in the absence of these factors but only 40-47% when all three factors were present (p?

SUBMITTER: Tiainen S

PROVIDER: S-EPMC6997252 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Tumor microenvironment and breast cancer survival: combined effects of breast fat, M2 macrophages and hyaluronan create a dismal prognosis.

Tiainen Satu S Masarwah Amro A Oikari Sanna S Rilla Kirsi K Hämäläinen Kirsi K Sudah Mazen M Sutela Anna A Vanninen Ritva R Ikonen Juho J Tammi Raija R Tammi Markku M Auvinen Päivi P

Breast cancer research and treatment 20191112 3

<h4>Purpose</h4>Tumor microenvironment, including inflammatory cells, adipocytes and extracellular matrix constituents such as hyaluronan (HA), impacts on cancer progression. Systemic metabolism also influences tumor growth e.g. obesity and type 2 diabetes (T2D) are risk factors for breast cancer. Here, in 262 breast cancer cases, we explored the combined impacts on survival of M2-like tumor associated macrophages (TAMs), the abundance of breast fat visualized as low density in mammograms, and t ...[more]

PMID: 31720917

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Project description:Breast cancer (BC), the most common cancer in women, is caused by the uncontrolled proliferation of mammary epithelial cells under the action of a variety of carcinogenic factors. Cuproptosis-related targets have been found to be closely associated with breast cancer development. TCGA obtained 1226 tumor samples, 1073 clinical data, and 37 lncRNAs during univariate Cox multivariate analysis. We used nonnegative matrix factoring (NMF) agglomeration to spot thirty-three potential molecular subsets with totally different cuproptosis-related lncRNA expression patterns. The least absolute shrinkage and selection operator (LASSO) formula and variable Cox multivariate analysis were not used to construct the best prognostic model. The variations in neoplasm mutation burden and factor gene ontology (GO) and gene set enrichment analysis (GSEA) within the high- and low-risk teams were analyzed, and therefore, the potential mechanism of the development of carcinoma was analyzed. We created a prognostic profile consisting of nineteen cuproptosis-related genes (NFE2L2, LIPT1, LIPT2, DLD, etc.) and their connected targets. The correlation between tumor mutational burden (TMB) and clinical manifestations of tumors demonstrates the importance of high- and low-expression bunch data on the incidence of clinical manifestations of tumors. The area under the curve (AUC) shows moderate prophetic power for copper mortality. GO enrichment analysis showed that immunorelated responses were enriched. Correlation analysis of immune cells showed that pathology could play an important role in the prevalence and prognosis of tumors, and there were variations in immune cells between the probable and low-risk groups. Our study suggests that the prognostic characteristic genes associated with cuproptosis can be used as new biomarkers to predict the prognosis of breast cancer patients. In addition, we found that immunotherapy may play a key role in breast cancer treatment regimens. Levels of immune-associated cells and pathways vary significantly among risk groups of breast cancer patients.

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Tumor microenvironment and breast cancer survival: combined effects of breast fat, M2 macrophages and hyaluronan create a dismal prognosis.

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Tumor microenvironment and breast cancer survival: combined effects of breast fat, M2 macrophages and hyaluronan create a dismal prognosis.

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