We used enzymatic activity and immunochemical quantifications to analyse the expression and secretion of cathepsin D by human breast cancer cell lines of different invasive potentials (MCF-7/6, MCF-7/AZ, MDA-MB-231). This study does not directly prove that cathepsin D or procathepsin D is involved in human breast cancer cell invasion and metastasis but it shows that the proportion of procathepsin D (activity and antigen) secreted by the human breast cancer cell lines tested correlates with their invasive potential. In the estrogen receptor-positive MCF-7 subclones, this proportion is increased by estradiol only in the invasive MCF-7/6 variant. The cell content in procathepsin D is increased by estrogens to a greater extent in MCF-7/6 cells as compared to non-invasive MCF-7/AZ cells. Tamoxifen appears to be an estrogen agonist concerning cathepsin D regulation, whereas ICI 182,780 is a true antagonist. Our results suggest that synthesis and secretion of cathepsin D are regulated at two distinct levels and differentially affected by estrogens. Synthesis only seems to be affected in non-invasive MCF-7/AZ cells, whereas in invasive MCF-7/6 cells, both synthesis and the efficiency of secretion are increased by estrogens. Our results also confirm that the key site of regulation leading to lysosomal enzyme oversecretion is the Golgi apparatus insulin-like growth factor-II/mannose 6-phosphate receptor.
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Sci Rep
December 2024
Department of Breast Surgery, Second Affiliated Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, China.
Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model.
View Article and Find Full Text PDFMetaplastic breast cancer (MpBC) is a highly chemoresistant subtype of breast cancer with no standardized therapy options. A clinical study in anthracycline-refractory MpBC patients suggested that nitric oxide synthase (NOS) inhibitor NG-monomethyl-l-arginine (L-NMMA) may augment anti-tumor efficacy of taxane. We report that NOS blockade potentiated response of human MpBC cell lines and tumors to phosphoinositide 3-kinase (PI3K) inhibitor alpelisib and taxane.
View Article and Find Full Text PDFthe evolution of axillary management in breast cancer has witnessed significant changes in recent decades, leading to an overall reduction in surgical interventions. There have been notable shifts in practice, aiming to minimize morbidity while maintaining oncologic outcomes and accurate staging for newly diagnosed breast cancer patients. These advancements have been facilitated by the improved efficacy of adjuvant therapies.
View Article and Find Full Text PDFthe axillary reverse mapping (ARM) procedure aims to preserve the lymphatic drainage structures of the upper extremity during axillary surgery for breast cancer, thereby reducing the risk of lymphedema in the upper limb. Material and this prospective study included 57 patients with breast cancer who underwent SLNB and ARM. The sentinel lymph node (SLN) was identified using a radioactive tracer.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Medicine, Institute of Biomedicine, University of Eastern Finland, Yliopistonranta 1, PO Box 1627, 70211 Kuopio, Finland.
The selection of biomarker panels in omics data, challenged by numerous molecular features and limited samples, often requires the use of machine learning methods paired with wrapper feature selection techniques, like genetic algorithms. They test various feature sets-potential biomarker solutions-to fine-tune a machine learning model's performance for supervised tasks, such as classifying cancer subtypes. This optimization process is undertaken using validation sets to evaluate and identify the most effective feature combinations.
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