The IGF-1R [type 1 IGF (insulin-like growth factor) receptor] is activated upon binding to IGF-I and IGF-II leading to cell growth, survival and migration of both normal and cancerous cells. We have characterized the binding interaction between the IGF-1R and its ligands using two high-affinity mouse anti-IGF-1R mAbs (monoclonal antibodies), 7C2 and 9E11. These mAbs both block IGF-I binding to the IGF-1R but have no effect on IGF-II binding. Epitope mapping using chimaeras of the IGF-1R and insulin receptor revealed that the mAbs bind to the CR (cysteine-rich) domain of IGF-1R. The epitope was finely mapped using single point mutations in the IGF-1R. Mutation of Phe241, Phe251 or Phe266 completely abolished 7C2 and 9E11 binding. The three-dimensional structure showed that these residues cluster on the surface of the CR-domain. BIAcore analyses revealed that IGF-I and a chimaeric IGF-II with the IGF-I C-domain competed for the binding of both mAbs with the IGF-1R, whereas neither IGF-II nor a chimaeric IGF-I with the IGF-II C-domain affected antibody binding. We therefore conclude the IGF-I C-domain interacts with the CR (cysteine-rich) domain of the receptor at the cluster of residues Phe241, Phe251 and Phe266. These results allow precise orientation of IGF-I within the IGF-I-IGF-1R complex involving the IGF-I C-domain binding to the IGF-1R CR domain. In addition, mAbs 7C2 and 9E11 inhibited both IGF-I- and IGF-II-induced cancer cell proliferation, migration and IGF-1R down-regulation, demonstrating that targeting the IGF-1R is an effective strategy for inhibition of cancer cell growth.

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Silver nanoparticles have a wide range of research, industrial and biomedical applications that make it essential to develop a low cost and eco-friendly approach with scaling up potential. Green synthesis of nanoparticles through bio-reactions leads to a reduction of silver ions to particles could be an acceptable selection using no additional reducing chemicals. Moreover, the simplicity of scale-up processes of the method makes it more efficient than chemical and physical synthesis methods. In this study, Datura stramonium leaf extract and sodium citrate were used as biological and chemical reducing and stabilizing agents to make silver nanoparticles. The main goal is to comprise properties and evaluate antibacterial activity of nanoparticles synthesized through two approaches. Size and morphology compared between the two types of the synthesized nanoparticle by UV-Visible spectroscopy, DLS, AFM, TEM and their antibacterial effects were evaluated through growth inhibition MIC and MBC methods. The results showed narrow size range, spherical shape, high anti-oxidant, antibacterial and DNA cleavage activities of green synthesized silver nanoparticles comparing to less average size, wider range of nanoparticle size, no anti-oxidant activity and less antibacterial and DNA cleavage activities of chemically synthesized nanoparticles. The green synthesized silver nanoparticles had more desirable characteristics and biological activities compared to chemically synthesized nanoparticles. For instance, the green nanoparticles showed narrow size range, spherical shape, high anti-oxidant, antibacterial and DNA cleavage activities versus the chemically synthesized which had less average size, higher range of nanoparticles size, no anti-oxidant activity and less antibacterial and DNA cleavage activities.

Asian Pacific J Cancer Prev, 13, 3053-3059 IntroductionHuman epidermal growth factor receptor 2 (HER2), also known as ErbB2, c-erbB2 or HER2/neu, is a 185 kDa protein (p185) involved in signal transduction as well as regulating cell growth. Since the discovery of the role of HER2 in tumorigenesis, it has received great attention in cancer research and vaccine design during the past two decades (Tai et al., 2010). HER2 is a transmembrane glycoprotein contains three distinct regions: N-terminal extracellular domain (ECD), a single transmembrane α-helix (TM), and an intracellular tyrosine kinase domain. The largest part of HER2, the N-terminal ECD is composed of approximately 600 residues (90-110 kDa) which could be divided into four subdomains (I-IV). Subdomains I (residues 23-217) and III (343-510) created a binding site for the receptor's potential ligands (Lax, 1988). While the cysteine-rich subdomains II (218-342) and IV (511-582) are involved in the homodimerization and heterodimerization (Fiore, 1987;Pietras, 1995). HER2 is highly expressed in a significant proportion of breast, ovarian, gastric, colon, prostate and lung cancers. HER2 overexpression in these cancers often correlates with

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At present, the most common cause of cancer-related death in women is breast cancer. In a large proportion of breast cancers, there is the overexpression of human epidermal growth factor receptor 2 (HER2). This receptor is a 185 KDa growth factor glycoprotein, also known as the first tumor-associated antigen for different types of breast cancers. Moreover, HER2 is an appropriate cell-surface specific antigen for passive immunotherapy, which relies on the repeated application of monoclonal antibodies that are transferred to the patient. However, vaccination is preferable because it would stimulate a patient's own immune system to actively respond to a disease. In the current study, several bioinformatics tools were used for designing synthetic peptide vaccines. PEPOP was used to predict peptides from HER2 ECD subdomain III in the form of discontinuous-continuous B-cell epitopes. Then, T-cell epitope prediction web servers MHCPred, SYFPEITHI, HLA peptide motif search, Propred, and SVMHC were used to identify class-I and II MHC peptides. In this way, PEPOP selected 12 discontinuous peptides from the 3D structure of the HER2 ECD subdomain III. Furthermore, T-cell epitope prediction analyses identified four peptides containing the segments 77 (384-391) and 99 (495-503) for both B and T-cell epitopes. This work is the only study to our knowledge focusing on design of in silico potential novel cancer peptide vaccines of the HER2 ECD subdomain III that contain epitopes for both B and T-cells. These findings based on bioinformatics analyses may be used in vaccine design and cancer therapy; saving time and minimizing the number of tests needed to select the best possible epitopes.