Erlotinib-Induced Breast Cancer Regression

DRGCL: Drug Repositioning via Semantic-Enriched Graph Contrastive Learning

Drug repositioning greatly reduces drug development costs and time by discovering new indications for existing drugs. With the development of technology and large-scale biological databases, computational drug repositioning has increasingly attracted remarkable attention, which can narrow down repositioning candidates. Recently, graph neural networks (GNNs) have been widely used and achieved promising results in drug repositioning. However, the existing GNNs based methods usually focus on modeling the complex drug-disease association graph, but ignore the semantic information on the graph, which may lead to a lack of consistency of global topology information and local semantic information for the learned features. To alleviate the above challenge, we propose a novel drug repositioning model based on graph contrastive learning, termed DRGCL. First, we treat the known drug-disease associations as the topology graph. Second, we select the top- similar neighbor from drug/disease similarity information to construct the semantic graph rather than use the traditional data augmentation strategy, thereby maximally retaining rich semantic information. Finally, we pull closer to embedding consistency of the different embedding spaces by graph contrastive learning to enhance the topology and semantic feature on the graph. We have evaluated DRGCL on four benchmark datasets and the experiment results show that the proposed DRGCL is superior to the state-of-the-art methods. Especially, the average result of DRGCL is 11.92% higher than that of the second-best method in terms of AUPRC. The case studies further demonstrate the reliability of DRGCL.

Multi-Omic Data Interpretation to Repurpose Subtype Specific Drug Candidates for Breast Cancer

Triple-negative breast cancer (TNBC), which is largely synonymous with the basal-like molecular subtype, is the 5th leading cause of cancer deaths for women in the United States. The overall prognosis for TNBC patients remains poor given that few treatment options exist; including targeted therapies (not FDA approved), and multi-agent chemotherapy as standard-of-care treatment. TNBC like other complex diseases is governed by the perturbations of the complex interaction networks thereby elucidating the underlying molecular mechanisms of this disease in the context of network principles, which have the potential to identify targets for drug development. Here, we present an integrated "omics" approach based on the use of transcriptome and interactome data to identify dynamic/active protein-protein interaction networks (PPINs) in TNBC patients. We have identified three highly connected modules, EED, DHX9, and AURKA, which are extremely activated in TNBC tumors compared to both normal tissues and other breast cancer subtypes. Based on the functional analyses, we propose that these modules are potential drivers of proliferation and, as such, should be considered candidate molecular targets for drug development or drug repositioning in TNBC. Consistent with this argument, we repurposed steroids, anti-inflammatory agents, anti-infective agents, cardiovascular agents for patients with basal-like breast cancer. Finally, we have performed essential metabolite analysis on personalized genome-scale metabolic models and found that metabolites such as sphingosine-1-phosphate and cholesterol-sulfate have utmost importance in TNBC tumor growth.

DRUGSURV: a resource for repositioning of approved and experimental drugs in oncology based on patient survival information

The use of existing drugs for new therapeutic applications, commonly referred to as drug repositioning, is a way for fast and cost-efficient drug discovery. Drug repositioning in oncology is commonly initiated by in vitro experimental evidence that a drug exhibits anticancer cytotoxicity. Any independent verification that the observed effects in vitro may be valid in a clinical setting, and that the drug could potentially affect patient survival in vivo is of paramount importance. Despite considerable recent efforts in computational drug repositioning, none of the studies have considered patient survival information in modelling the potential of existing/new drugs in the management of cancer. Therefore, we have developed DRUGSURV; this is the first computational tool to estimate the potential effects of a drug using patient survival information derived from clinical cancer expression data sets. DRUGSURV provides statistical evidence that a drug can affect survival outcome in particular clinical conditions to justify further investigation of the drug anticancer potential and to guide clinical trial design. DRUGSURV covers both approved drugs (∼1700) as well as experimental drugs (∼5000) and is freely available at http://www.bioprofiling.de/drugsurv.

IL-24 gene transfer sensitizes melanoma cells to erlotinib through modulation of the Apaf-1 and Akt signaling pathways

Interleukin-24 (IL-24) is a novel tumor suppressor/cytokine gene expressed in normal human melanocytes but for which expression is nearly undetectable in metastatic melanoma. Overexpression of the IL-24 protein has been shown to inhibit tumor cell proliferation and induce apoptosis in many melanoma cell lines, and is now considered a tumor suppressor. Erlotinib, a small-molecule epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, has been widely studied for the treatment of human lung cancer and other solid tumors, but the erlotinib-targeted therapy has not been tested in melanoma. The objective of this study is to investigate the potency of erlotinib in suppressing the growth of human melanoma cells and whether IL-24 could enhance the antitumor activity of erlotinib. In cell viability and apoptosis assays, treatment with erlotinib dependently inhibited the growth of different melanoma cell lines and when combined with adenoviral vector-mediated IL-24 gene therapy, a significant increase in cell growth inhibition and apoptosis induction resulted (P<0.05). Immunoblot assay showed that the combination treatment of erlotinib and IL-24 considerably increased the cleavage of caspase-3 and caspase-9 and the expression of Apaf-1 protein in melanoma cells, inducing activation of the Apaf-1-dependent apoptotic pathways. Moreover, this combination treatment markedly inhibited phosphorylation of the EGFR, phosphatidylinositol-3 kinase, and Akt proteins, inactivating the Akt-dependent cell survival signaling pathway. These results show that a combination of IL-24-mediated molecular therapy and EGFR inhibitors such as erlotinib may be a promising treatment strategy for human melanoma and will serve as a basis for guiding the combination treatment designs in future preclinical and clinical trials.

Antiangiogenic strategies in breast cancer management

Angiogenesis is considered one of the key mechanisms of tumour growth and survival. Therefore it represents an ideal pharmaceutical target. Many antiangiogenic agents have been developed so far in several solid tumours and also in breast cancer. Vascular endothelial growth factor (VEFG) is the main target and both monoclonal antibodies and small molecules belonging to the tyrosine kinase inhibitors directed against VEGF(R) have been developed. Some other therapeutic approaches have shown to exert some antiangiogenic activity, such as hormonal agents, metronomic chemotherapy, bisphosphonates and others. In this paper we provide an introduction of the current data supporting the angiogenesis in breast cancer and a review of the most relevant antiagiogenic therapies which have been investigated so far.

Molecular targeted therapies for breast cancer treatment

Targeting the oestrogen receptor, HER2 (human epidermal growth factor receptor 2) and vascular endothelial growth factor has markedly improved breast cancer therapy. New targeted therapeutic approaches to induction of apoptosis or inhibition of anti-apoptosis, cell cycle progression, signal transduction and angiogenesis are described. The molecular pathways and their inhibitory or repair mechanisms are discussed in the preclinical and clinical settings.

Central nervous system metastases in HER-2-overexpressing metastatic breast cancer: a treatment challenge

With improvements in diagnostic and therapeutic options and a corresponding improvement in survival, central nervous system (CNS) metastasis is becoming a more frequent diagnosis in breast cancer patients. It can be assumed that up to 30% of metastatic breast cancer (MBC) patients may experience CNS metastasis during the course of their disease. Moreover, it has been reported that patients with human epidermal growth factor receptor (HER)-2-overexpressing MBC are at a higher risk for CNS involvement. Whereas locoregional treatment modalities such as surgery, radiosurgery, and whole-brain radiotherapy still must be considered as the treatment of first choice, the armamentarium of systemic treatment modalities has been expanded by the introduction of small molecules such as the tyrosine kinase inhibitors. Rather than analyzing the risk factors for the development of CNS metastasis and reviewing the standard diagnostic and therapeutic approaches in patients with CNS involvement, this review focuses specifically on systemic treatment modalities in patients suffering from CNS metastasis from HER-2-overexpressing MBC.

TACE: a new target in epidermal growth factor receptor dependent tumors

Soluble proteins play vital roles in mediating intercellular communication. Many of these proteins are secreted as freely soluble molecules, but an important class of signaling proteins are first synthesized and presented at the cell surface as transmembrane precursor proteins. Unlike classically secreted proteins, many of these molecules are regulated at an additional level, requiring proteolytic cleavage for activity. This review focuses on a subset of these proteins, which are cleaved by tumor necrosis factor alpha-converting enzyme (TACE)/ADAM17, and on their role in cancer.