Origin of anti-tumor activity of the cysteine-containing GO peptides and further optimization of their cytotoxic properties

Effect of soybean peptides against hydrogen peroxide induced oxidative stress in HepG2 cells via Nrf2 signaling

The aim of this study was to determine the effects of soybean protein hydrolysates against intracellular antioxidant activity.

ACPred: A Computational Tool for the Prediction and Analysis of Anticancer Peptides

Anticancer peptides (ACPs) have emerged as a new class of therapeutic agent for cancer treatment due to their lower toxicity as well as greater efficacy, selectivity and specificity when compared to conventional small molecule drugs. However, the experimental identification of ACPs still remains a time-consuming and expensive endeavor. Therefore, it is desirable to develop and improve upon existing computational models for predicting and characterizing ACPs. In this study, we present a bioinformatics tool called the ACPred, which is an interpretable tool for the prediction and characterization of the anticancer activities of peptides. ACPred was developed by utilizing powerful machine learning models (support vector machine and random forest) and various classes of peptide features. It was observed by a jackknife cross-validation test that ACPred can achieve an overall accuracy of 95.61% in identifying ACPs. In addition, analysis revealed the following distinguishing characteristics that ACPs possess: (i) hydrophobic residue enhances the cationic properties of α-helical ACPs resulting in better cell penetration; (ii) the amphipathic nature of the α-helical structure plays a crucial role in its mechanism of cytotoxicity; and (iii) the formation of disulfide bridges on β-sheets is vital for structural maintenance which correlates with its ability to kill cancer cells. Finally, for the convenience of experimental scientists, the ACPred web server was established and made freely available online.

Interaction Between MUC1 and STAT1 Drives IFITM1 Overexpression in Aromatase Inhibitor-Resistant Breast Cancer Cells and Mediates Estrogen-Induced Apoptosis

The human oncoprotein, mucin 1 (MUC1), drives tumorigenesis in breast carcinomas by promoting epithelial-to-mesenchymal transition (EMT), epigenetic reprogramming, and evasion of immune response. MUC1 interacts with STAT1, through JAK/STAT signaling, and stimulates transcription of IFN-stimulated genes, specifically IFN-induced transmembrane protein 1 (IFITM1). Our laboratory has previously shown that IFITM1 overexpression in aromatase inhibitor (AI)-resistant breast cancer cells promotes aggressiveness. Here, we demonstrate that differential regulation of MUC1 in AI-sensitive (MCF-7 and T-47D) compared with AI-resistant (MCF-7:5C) cells is critical in mediating IFITM1 expression. A tumor microarray of 94 estrogen receptor-positive human breast tumors correlated coexpression of MUC1 and IFITM1 with poor recurrence-free survival, poor overall survival, and AI-resistance. In this study, we investigated the effects of MUC1/IFITM1 on cell survival and proliferation. We knocked down MUC1 levels with siRNA and pharmacologic inhibitors, which abrogated IFITM1 mRNA and protein expression and induced cell death in AI-resistant cells. In vivo, estrogen and ruxolitinib significantly reduced tumor size and decreased expression of MUC1, P-STAT1, and IFITM1. IMPLICATIONS: MUC1 and IFITM1 overexpression drives AI resistance and can be targeted with currently available therapies.Visual Overview: http://mcr.aacrjournals.org/content/molcanres/17/5/1180/F1.large.jpg.

Pro-apoptotic peptides-based cancer therapies: challenges and strategies to enhance therapeutic efficacy

Cancer is a leading cause of death worldwide. Despite many advances in the field of cancer therapy, an effective cure is yet to be found. As a more potent alternative for the conventional small molecule anti-cancer drugs, pro-apoptotic peptides have emerged as a new class of anticancer agents. By interaction with certain members in the apoptotic pathways, they could effectively kill tumor cells. However, there remain bottleneck challenges for clinical application of these pro-apoptotic peptides in cancer therapy. In this review, we will overview the developed pro-apoptotic peptides and outline the widely adopted molecular-based and nanoparticle-based strategies to enhance their anti-tumor effects.