Significance of Serum Survivin and -31G/C Gene Polymorphism in the Early Diagnosis of Breast Cancer in Egypt

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Background:

Breast cancer (BC) is the most common neoplasm in women worldwide. Liquid biopsy (LB) is a non-invasive diagnostic technique that allows the analysis of biomarkers in different body fluids, particularly in peripheral blood and also in urine, saliva, nipple discharge, volatile respiratory fluids, nasal secretions, breast milk, and tears. The objective was to analyze the available evidence related to the use of biomarkers obtained by LB for the early diagnosis of BC.

Methods:

Articles related to the use of biomarkers for the early diagnosis of BC due to LB, published between 2010 and 2022, from the databases (WoS, EMBASE, PubMed, and SCOPUS) were included. The MInCir diagnostic scale was applied in the articles to determine their methodological quality (MQ). Descriptive statistics were used, as well as determination of weighted averages of each variable, to analyze the extracted data. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) are described.

Results:

In this systematic review (SR), 136 articles met the selection criteria, representing 17 709 patients with BC. However, 95.6% were case-control studies. In 96.3% of cases, LB was performed in peripheral blood samples. Most of the articles were based on microRNA (miRNA) analysis. The mean MQ score was 25/45 points. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) have been found.

Conclusions:

The determination of biomarkers through LB is a useful mechanism for the diagnosis of BC. The analysis of miRNA in peripheral blood is the most studied methodology. Our results indicate that LB has a high sensitivity and specificity for the diagnosis of BC, especially in early stages.

Identification of an autophagy-related gene signature predicting overall survival for hepatocellular carcinoma

The poor prognosis of hepatocellular carcinoma (HCC) calls for the development of accurate prognostic models. The growing number of studies indicating a correlation between autophagy activity and HCC indicates there is a commitment to finding solutions for the prognosis of HCC from the perspective of autophagy. We used a cohort in The Cancer Genome Atlas (TCGA) to evaluate the expression of autophagy-related genes in 371 HCC samples using univariate Cox and lasso Cox regression analysis, and the prognostic features were identified. A prognostic model was established by combining the expression of selected genes with the multivariate Cox regression coefficient of each gene. Eight autophagy-related genes were selected as prognostic features of HCC. We established the HCC prognostic risk model in TCGA dataset using these identified prognostic genes. The model's stability was confirmed in two independent verification sets (GSE14520 and GSE36376). The model had a good predictive power for the overall survival (OS) of HCC (hazard ratio = 2.32, 95% confidence interval = 1.76-3.05, P<0.001). Moreover, the risk score computed by the model did not depend on other clinical parameters. Finally, the applicability of the model was demonstrated through a nomogram (C-index = 0.701). In the present study, we established an autophagy-related risk model having a high prediction accuracy for OS in HCC. Our findings will contribute to the definition of prognosis and establishment of personalized therapy for HCC patients.

Tamoxifen and the PI3K Inhibitor: LY294002 Synergistically Induce Apoptosis and Cell Cycle Arrest in Breast Cancer MCF-7 Cells

Breast cancer is considered as one of the most aggressive types of cancer. Acquired therapeutic resistance is the major cause of chemotherapy failure in breast cancer patients. To overcome this resistance and to improve the efficacy of treatment, drug combination is employed as a promising approach for this purpose. The synergistic cytotoxic, apoptosis inducing, and cell cycle effects of the combination of LY294002 (LY), a phosphatidylinositide-3-kinase (PI3K) inhibitor, with the traditional cytotoxic anti-estrogen drug tamoxifen (TAM) in breast cancer cells (MCF-7) were investigated. LY and TAM exhibited potent cytotoxic effect on MCF-7 cells with IC50 values 0.87 µM and 1.02 µM. The combination of non-toxic concentration of LY and TAM showed highly significant synergistic interaction as observed from isobologram (IC50: 0.17 µM, combination index: 0.18, colony formation: 9.01%) compared to untreated control. The percentage of early/late apoptosis significantly increased after treatment of MCF-7 cells with LY and TAM combination: 40.3%/28.3% (p < 0.001), compared to LY single treatment (19.8%/11.4%) and TAM single treatment (32.4%/5.9%). In addition, LY and TAM combination induced the apoptotic genes Caspase-3, Caspase-7, and p53, as well as p21 as cell cycle promotor, and significantly downregulated the anti-apoptotic genes Bcl-2 and survivin. The cell cycle assay revealed that the combination induced apoptosis by increasing the pre-G1: 28.3% compared to 1.6% of control. pAKT and Cyclin D1 protein expressions were significantly more downregulated by the combination treatment compared to the single drug treatment. The results suggested that the synergistic cytotoxic effect of LY and TAM is achieved by the induction of apoptosis and cell cycle arrest through cyclin D1, pAKT, caspases, and Bcl-2 signaling pathways.

Application of magnetic nanoparticles in nucleic acid detection

Nucleic acid is the main material for storing, copying, and transmitting genetic information. Gene sequencing is of great significance in DNA damage research, gene therapy, mutation analysis, bacterial infection, drug development, and clinical diagnosis. Gene detection has a wide range of applications, such as environmental, biomedical, pharmaceutical, agriculture and forensic medicine to name a few. Compared with Sanger sequencing, high-throughput sequencing technology has the advantages of larger output, high resolution, and low cost which greatly promotes the application of sequencing technology in life science research. Magnetic nanoparticles, as an important part of nanomaterials, have been widely used in various applications because of their good dispersion, high surface area, low cost, easy separation in buffer systems and signal detection. Based on the above, the application of magnetic nanoparticles in nucleic acid detection was reviewed.