Effect of Breast Milk Calcium and Fluidity on Breast Cancer Cells: An In Vitro Cell Culture Study

The role of breastfeeding in breast cancer prevention: a literature review

Breast cancer stands as the most prevalent malignancy globally. Despite the array of treatment options, its mortality rate continues to rise annually. Thus, reevaluation of factors directly linked to breast cancer emergence is imperative, alongside the development of more effective preventive measures. Estrogen levels, profoundly tied to reproduction, play a pivotal role in breast cancer development. Speculation centers on the potential of breastfeeding to mitigate cancer risk in women. However, the precise mechanism remains elusive. Breastfeeding is a modifiable reproductive factor extensively studied. Studies highlight a direct connection between lack of breastfeeding and breast cancer emergence, potentially linked to DNA methyltransferase expression alteration, aberrant methylation levels, pregnancy-associated plasma protein-A, cellular microenvironment, and oncogenes. This study reviews recent mechanisms underlying breastfeeding's role in reducing breast cancer incidence.

A Narrative Review of Breastfeeding and Its Correlation With Breast Cancer: Current Understanding and Outcomes

Breastfeeding has been extensively studied in relation to breast cancer risk. The results of the reviewed studies consistently show a decreased risk of breast cancer associated with breastfeeding, especially for 12 months or longer. This protective effect is attributed to hormonal, immunological, and physiological changes during lactation. Breastfeeding also appears to have a greater impact on reducing breast cancer risk in premenopausal women and specific breast cancer subtypes. Encouraging breastfeeding has dual benefits: benefiting infants and reducing breast cancer risk long-term. Healthcare professionals should provide evidence-based guidance on breastfeeding initiation, duration, and exclusivity, while public health policies should support breastfeeding by creating enabling environments. This review examines the existing literature and analyzes the correlation between breastfeeding and breast cancer risk.

The Impact of the Human Milk Microbiota in the Prevention of Disease and Infant Health

Background: Human milk is recognized as an ideal food for newborns and infants owing to the presence of various nutritive factors, including healthy bacteria. Aim/Objective: This review aimed to understand the effects of human milk microbiota in both the prevention of disease and the health of infants. Methods: Data were obtained from PubMed, Scopus, Web of Science, clinical trial registries, Dergipark, and Türk Atıf Dizini up to February 2023 without language restrictions. Results: It is considered that the first human milk microbiota ingested by the newborn creates the initial microbiome of the gut system, which in turn influences the development and maturation of immunity. Bacteria present in human milk modulate the anti-inflammatory response by releasing certain cytokines, protecting the newborn against certain infections. Therefore, certain bacterial strains isolated from human milk could serve as potential probiotics for various therapeutic applications. Conclusions: In this review, the origin and significance of human milk bacteria have been highlighted along with certain factors influencing the composition of human milk microbiota. In addition, it also summarizes the health benefits of human milk as a protective agent against certain diseases and ailments.

Lipocalin-1 Expression as a Prognosticator Marker of Survival in Breast Cancer Patients

Purpose

LCN1 (lipocalin-1), a gene that encodes tear lipocalin (or von Ebner's gland protein), is mainly expressed in secretory glands and tissues, such as the lachrymal and lingual gland, and nasal, mammary, and tracheobronchial mucosae. Analysis of the Cancer Genome Atlas (TCGA) Breast Carcinoma (BRCA) level 3 data revealed a relationship between LCN1 expression and survival in breast cancer patients.

Methods

The χ² test and Fisher exact test were applied to analyze the clinical data and RNA sequencing expression data, and the association between LCN1 expression and clinicopathologic features was determined. The receiver-operating characteristic (ROC) curve of LCN1 was drawn to assess its ability as a diagnostic marker, and the optimal cutoff value was obtained from the ROC curve to distinguish groups with high and low LCN1 expression. Cox regression was used to compare both groups, and a log-rank test was applied to calculate p values and compare the -Kaplan-Meier curves. Furthermore, GEO datasets were employed for external data validation.

Results

Analysis of 1,104 breast cancer patients with a primary tumor revealed that LCN1 was overexpressed in breast cancer. High LCN1 expression was associated with clinicopathologic features and poor survival. Analyzing the area under the ROC curve (AUC) of LCN1, it was found that its diagnostic ability was limited. Multivariate analysis indicated that LCN1 expression is an independent predictor of survival in breast cancer patients. Through validation in GEO datasets, LCN1 expression was higher in tumor than normal tissue of the breast. High LCN1 expression was associated with poor survival in breast cancer patients.

Conclusions

High LCN1 expression is an independent prognosticator of a poor prognosis in breast cancer.

A new prognostic factor of breast cancer: High carboxyl ester lipase expression related to poor survival

OBJECTIVE

The enzyme carboxyl ester lipase (CEL), known as bile salt-dependent lipase (BSDL) or bile salt-stimulated lipase (BSSL), is mainly expressed in pancreatic acinar cells and lactating mammary glands. To investigate the link between CEL expression of breast cancer (BC) tissues and the survival of BC patients by analyzing The Cancer Genome Atlas Breast Carcinoma (TCGA-BRCA) level 3 data.

METHODS

The clinical information and RNA-sequencing (RNA-Seq) expression data were downloaded from TCGA. Patients were divided into a high CEL expression group and a low CEL expression group using the optimal cutoff value (5.611) identified from the ROC curve. Chi-square test and Fisher exact test were used to find the correlation between the expression of CEL and clinicopathologic features. To assess the diagnostic capability, the receiver operating characteristic (ROC) curve of CEL was drawn. The survival differences between high and low CEL expression groups were compared by Cox regression analysis. Log-rank test was applied to the calculation of p values and the comparison of the Kaplan-Meier curves. Furthermore, Gene Expression Omnibus (GEO) datasets were used for external data validation.

RESULTS

Analysis of 1104 cases of tumor data showed that CEL was over-expressed in breast cancer. There were relationships between high CEL expression and clinicopathologic features. The high CEL expression group had a lower survival. By analyzing the area under the ROC curve (AUC) of CEL, it was found to have a limited diagnostic capability. CEL expression may be an independent prognostic factor for breast cancer survival through the multivariate analysis. The validation in GEO datasets also showed that CEL expression was higher in breast tumor tissues than in normal breast tissues. High CEL expression was associated with the poor overall survival of breast cancer.

CONCLUSIONS

High CEL expression may be an independent prognostic factor for the poor survival of breast cancer.