Unraveling the cross-talk between N6-methyladenosine modification and non-coding RNAs in breast cancer: Mechanisms and clinical implications.

In recent years, breast cancer (BC) has surpassed lung cancer as the most common malignant tumor worldwide and remains the leading cause of cancer death in women. The etiology of BC usually involves dysregulation of epigenetic mechanisms and aberrant expression of certain non-coding RNAs (ncRNAs). N6-methyladenosine (m6A), the most prevalent RNA modification in eukaryotes, widely exists in ncRNAs to affect its biosynthesis and function, and is an important regulator of tumor-related signaling pathways. Interestingly, ncRNAs can also regulate or target m6A modification, playing a key role in cancer progression. However, the m6A-ncRNAs regulatory network in BC has not been fully elucidated, especially the regulation of m6A modification by ncRNAs. Therefore, in this review, we comprehensively summarize the interaction mechanisms and biological significance of m6A modifications and ncRNAs in BC. Meanwhile, we also focused on the clinical application value of m6A modification in BC diagnosis and prognosis, intending to explore new biomarkers and potential therapeutic targets.

Systematic analysis of cuproptosis-related genes in immunological characterization and predictive drugs in Alzheimer's disease.

Objectives: This study aimed to make a systematic analysis of cuproptosis-related genes (CRGs) in immunological characterization and predictive drugs in Alzheimer's disease (AD) through bioinformatics and biological experiments. Methods: The molecular clusters related to CRGs and associated immune cell infiltrations in AD were investigated. The diagnostic models were constructed for AD and different AD subtypes. Moreover, drug prediction and molecular docking were also performed. Subsequently, a molecular dynamics (MD) simulation was conducted to further verify the findings. Finally, RT-qPCR validation was performed. Results: The characterization of 12 AD-related CRGs was evaluated in AD, and a diagnostic model for AD showed a satisfying discrimination power based on five CRGs by LASSO regression analysis. The dysregulated CRGs and activated immune responses partially differed between patients with AD and healthy subjects. Furthermore, two molecular subtypes (clusters A and B) with different immune infiltration characteristics in AD were identified. Similarly, a diagnostic model for different AD subtypes was built with nine CRGs, which achieved a good performance. Molecular docking revealed the optimum conformation of CHEMBL261454 and its target gene CSNK1D, which was further validated by MD simulation. The RT-qPCR results were consistent with those of the comprehensive analysis. Conclusion: This study systematically elucidated the complex relationship between cuproptosis and AD, providing novel molecular targets for treatment and diagnosis biomarkers of AD.

Evaluation of Serum Fructosamine as Diagnostic Marker of Postoperative Recurrence in the Patients with Breast Cancer.

Objectives: A series of laboratory parameters were screened to identify the proper serum markers that could be used to predict breast cancer recurrence at an early stage. Methods: A case-control retrospective study on 224 patients without postoperative recurrence and 43 patients with postoperative recurrence of breast cancer was performed. The edgeR software package was used to identify the test indicators expressed differently between the two groups. Univariate analysis was used to screen for diagnostic marker that could predict postoperative recurrence of breast cancer. In addition, the differential test indicators at different time points from surgery to recurrence were collected in patients with postoperative recurrence of breast cancer as a verification database. Results: We screened out three test indicators (TBA, GSP, and URBC) for differential expression, which were all expressed downregulated in the postoperative recurrence group of breast cancer. Univariate analysis suggested that only the difference in GSP levels between the two groups was statistically significant (P = 0.001). ROC curve analysis showed that the area under the curve of GSP was 0.662, while the area under the curve of GSP+AFP+CEA+CA125+CA153+age was increased to 0.828. In addition, serum GSP levels were significantly reduced after recurrence compared with before recurrence in breast cancer patients (P < 0.01). Conclusions: In summary, GSP could be used for early diagnosis of breast cancer recurrence after surgery, and the predicted value of combining GSP, tumor markers, and age was better than that of individual indicators.