Publications by authors named "Mozania Reis"

The association between high-density lipoprotein (HDL) cholesterol and breast cancer (BC) remains controversial due to the high complexity of the HDL particle and its functionality. The HDL proteome was determined in newly diagnosed BC classified according to the molecular type [luminal A or B (LA or LB), HER2, and triple-negative (TN)] and clinical stage of the disease. Women (n = 141) aged between 18 and 80 years with BC, treatment-naïve, and healthy women [n = 103; control group (CT)], matched by age and body mass index, were included.

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The expression of inflammation-related miRs bound to high-density lipoproteins (HDLs), the anti-inflammatory activity of HDLs isolated from individuals with breast cancer, and controls were determined. Forty newly diagnosed women with breast cancer naïve of treatment and 10 control participants were included. Cholesterol-loaded bone-marrow-derived macrophages were incubated with HDL from both groups and challenged with lipopolysaccharide (LPS).

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The association between plasma lipids and breast cancer (BC) has been extensively explored although results are still conflicting especially regarding the relationship with high-density lipoprotein cholesterol (HDLc) levels. HDL mediates cholesterol and oxysterol removal from cells limiting sterols necessary for tumor growth, inflammation, and metastasis and this may not be reflected by measuring HDLc. We addressed recently diagnosed, treatment-naïve BC women (n = 163), classified according to molecular types of tumors and clinical stages of the disease, in comparison to control women (CTR; n = 150) regarding plasma lipids and lipoproteins, HDL functionality and composition in lipids, oxysterols, and apo A-I.

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Introduction: The association between high-density lipoprotein cholesterol (HDLc) with the incidence and progression of breast cancer (BC) is controversial. HDL removes excess cholesterol from cells and acts as an antioxidant and anti-inflammatory. BC is a heterogeneous disease, and its molecular classification is important in the prediction of clinical and therapeutic evolution.

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