Anti Human Fibronectin–Gold Nanoparticle Complex, a Potential Nanobiosensor Tool for Detection of Fibronectin in ECM of Cultured Cells

Specific protein detection by means of antibody-nanoparticle conjugates is a new field in medical nanobiotechnology. Among many nanoparticles used, gold nanoparticles show strong light-absorption properties which have been exploited in designing nanobiosensors. Fibronectin (FN) plays an important role in extracellular matrix (ECM) structure and function of normal cells; however, in conditions like lung carcinoma, its expression increases, especially in non small cell lung carcinoma (NSCLC). In this study, we conjugated gold nanoparticles to human fibronectin antibody (anti-hFN) to design a colorimetric nanobiosensor for detection of FN present in ECM of cultured cells. Three different cell lines, namely A549 (target cells), AGO-1522 (control cells), and Nalm-6 (negative control cells), were used to compare changes in color resulting from aggregation of gold nanoparticles due to higher amount of FN. Our construct was able to detect increased level of FN which was distinguishable visually by change in color and could be confirmed by spectrophotometer as well. © 2014, Springer Science+Business Media New York

A meta-analysis on diagnostic accuracy of serum HLA-G level in breast cancer

Background: According to the role of human leukocyte antigen (HLA)-G in tumor progression and tumor escape from immune system as well as diagnostic role of biomarkers in breast cancer, this meta-analysis is designed to reach a pooled diagnostic accuracy for this biomarker. Methods: The present work is a meta-analysis on diagnostic accuracy studies using preferred reporting items for systematic reviews and meta-analyses guideline. All documents studying the serum level of HLA-G both in breast cancer patients and in healthy controls using receiver operating characteristics (ROC) curve with reporting area under ROC curve (AUC) were eligible for inclusion. Results: Five articles including 754 participants were eligible for quantitative synthesis. The range of AUC of the selected studies was 0.735�0.953. The pooled AUC was 0.922 (95 confidence interval CI 0.903�0.941) based on fixed effect model (P < 0.001) and 0.896 (95% CI 0.834�0.959) based on random effect model (P < 0.001). Conclusion: This meta-analysis updated the level of evidence for using serum HLA-G in diagnosis of breast cancer. However, this piece of evidence cannot be used as a diagnostic tool. This biomarker can be used for investigation of recurrence and response to treatment in future. Further studies are suggested to complete this evidence gap. © 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group