New insights into polysaccharide-based nanostructured delivery systems in breast cancer: Possible application of antisense oligonucleotides in breast cancer therapy.

The lack of more effective therapies for breast cancer has enhanced mortality among breast cancer patients. Recent efforts have established efficient treatments to reduce breast cancer-related deaths. The ever-increasing attraction to employing biocompatible polysaccharide-based nanostructures as delivery systems has created interest in various disease therapies, especially breast cancer treatment. A wide range of therapeutic cargo comprising bioactive or chemical drugs, oligonucleotides, peptides, and targeted biomarkers have been considered to comprehend their anti-cancer effects against breast cancer. Some limitations of naked agents or undesired constructs, such as no or low bioavailability, enzymatic digestion, short-range stability, low-cellular uptake, poor solubility, and low surface area, have lessened their effectiveness. However, nanoscale formulations of therapeutic ingredients have provided a promising platform to address the mentioned concerns. For instance, some capable polysaccharides, including cellulose, pectin, chitosan, alginate, and dextran, were developed as breast cancer therapeutics with great nanoparticle structures. This review carefully examines the characteristics of beneficial polysaccharides that are utilized in the formation of nanoparticles (NPs). It also highlights the applications of antisense oligonucleotides (ASOs), and NPs made from polysaccharides in the treatment of breast cancer and suggests ways to enhance these particles for future research.

A new insight into the early detection of HER2 protein in breast cancer patients with a focus on electrochemical biosensors approaches: A review.

Breast cancer is one of the leading causes of death in women and is a prevalent kind of cancerous growth, representing a substantial risk to women's health. Early detection of breast cancer is essential for effective treatment and improved survival rates. Biomarkers, active substances that signal the existence and advancement of a tumor, play a significant role in the early detection of breast cancer. Hence, accurate identification of biomarkers for tumors is crucial for diagnosing and treating breast cancer. However, the primary diagnostic methods used for the detection of breast cancer require specific equipment, skilled professionals, and specialized analysis, leading to elevated detection expenses. Regarding this obstacle, recent studies emphasize electrochemical biosensors as more advanced and sensitive detection tools compared to traditional methods. Electrochemical biosensors are employed to identify biomarkers that act as unique indicators for the onset, recurrence, and monitoring of therapeutic interventions for breast cancer. This study aims to provide a summary of the electrochemical biosensors that have been employed for the detection of breast cancer at an early stage over the past decade. Initially, the text provides concise information about breast cancer and tumor biomarkers. Subsequently, an in-depth analysis is conducted to systematically review the progress of electrochemical biosensors developed for the stable, specific, and sensitive identification of biomarkers associated with breast cancer. Particular emphasis was given to crucial clinical biomarkers, specifically the human epidermal growth factor receptor-2 (HER2). The analysis then explores the limitations and challenges inherent in the design of effective biosensors for diagnosing and treating breast cancer. Ultimately, we provided an overview of future research directions and concluded by outlining the advantages of electrochemical biosensor approaches.

Cross-platform gene expression profiling of breast cancer: Exploring the relationship between breast cancer grades and gene expression pattern.

Gene expression profiling is a powerful tool that has been extensively used to investigate the underlying biology and etiology of diseases, including cancer. Microarray gene expression analysis enables simultaneous measurement of thousands of mRNA levels. Sophisticated computational approaches have evolved in parallel with the rapid progress in bioassay technologies, enabling more effective analysis of the large and complex datasets that these technologies produce. In this study, we utilized systems biology approaches to examine gene expression profiles across different grades of breast cancer progression. We conducted a meta-analysis of publicly available microarray data to elucidate the molecular mechanisms underlying breast cancer grade classification. Our results suggest that while grade index is commonly used for evaluating cancer progression status in the clinic, the complexity of molecular mechanisms, histological characteristics, and other factors related to patient outcomes raises doubts about the utility of breast cancer grades as a foundation for formulating treatment protocols. Our study underscores the importance of advancing personalized strategies for breast cancer classification and management. More research is crucial to refine diagnostic tools and treatment modalities, aiming for greater precision and tailored care in patient outcomes.