From NPC therapeutic target identification to potential treatment strategy

Antipsychotic drug trifluoperazine as a potential therapeutic agent against nasopharyngeal carcinoma

BACKGROUND

Trifluoperazine (TFP) is a typical antipsychotic primarily used to treat schizophrenia. In this study, we aimed to evaluate whether TFP can be used as a therapeutic agent against nasopharyngeal carcinoma (NPC) and identify its underlying molecular mechanisms.

METHODS

We used NPC-TW01, TW03, TW04, and BM to assess the anticancer effects of TFP by using cytotoxicity, wound healing, colony formation, and cell invasion assays. An in vivo animal study was conducted. RNA sequencing combined with Ingenuity Pathways Analysis was performed to identify the mechanism by which TFP influences NPC cells.

RESULTS

Our data revealed that TFP decreased NPC cell viability in a dose-dependent manner. The invasion and migration of NPC tumor cells were inhibited by TFP. An in vivo study also demonstrated the anticancer effects of TFP. RNA sequencing revealed several anticancer molecular mechanisms following TFP administration.

CONCLUSIONS

The antipsychotic drug TFP could be a potential therapeutic regimen for NPC treatment.

Polyethylene Glycol-Coated Graphene Oxide Loaded with Erlotinib as an Effective Therapeutic Agent for Treating Nasopharyngeal Cancer Cells

Introduction

Nasopharyngeal carcinoma (NPC) is a common cancer in southern China and Taiwan, and radiation therapy combined with or without chemotherapy is its mainstay treatment. Although it is highly sensitive to radiotherapy, local recurrence and distant metastasis remain difficult unsolved problems. In recent years, graphene oxide (GO) has been found to be a promising novel anticancer drug carrier. Here, we present our designed functionalized GO, polyethylene glycol-coated GO (GO-PEG), as a drug carrier, which was loaded with erlotinib and showed promising anticancer effects on NPC cells.

Methods

The effects of GO-PEG-erlotinib on the proliferation, migration, and invasion of NPC cells were investigated by WST-8 assay, wound healing assay, and invasion assay, respectively. RNA sequencing was conducted and analyzed to determine the molecular mechanisms by which GO-PEG-erlotinib affects NPC cells.

Results

Our results showed that GO-PEG-erlotinib reduced NPC cell viability in a dose-dependent manner and also inhibited the migration and invasion of NPC cells. The RNA sequencing revealed several related molecular mechanisms.

Conclusion

GO-PEG-erlotinib effectively suppressed NPC cell proliferation, migration, and invasion, likely by several mechanisms. GO-PEG-erlotinib may be a potential therapeutic agent for treating NPC in the future.

MicroRNA-129-5p suppresses nasopharyngeal carcinoma lymphangiogenesis and lymph node metastasis by targeting ZIC2

PURPOSE

The etiology of nasopharyngeal carcinoma (NPC) is multifactorial, complex and not fully characterized yet. MicroRNAs (miRNAs or miRs) have been found to contribute to the development and progression of NPC. Here, we aimed to investigate the putative role of miR-129-5p in NPC lymphangiogenesis and lymph node metastasis (LNM), including the involvement of its target gene ZIC2 and the Hedgehog signaling pathway.

METHODS

The expression of miR-129-5p and ZIC2 in primary NPC tissues was assessed using RT-qPCR and Western blot analyses, followed by LNM and lymph vessel density (LVD) correlation analyses. A direct interaction between miR-129-5p and ZIC2 was verified using a dual-luciferase reporter assay. Gain- and loss-of-function experiments were conducted to investigate the effects of miR-129-5p and ZIC2 expression on NPC cell invasion, migration and proliferation in vitro, as well as on LDV and LNM in nude mice in vivo. Additionally, RT-qPCR and Western blot analyses were performed to determine the expression levels of Hedgehog signaling pathway-related factors.

RESULTS

We found that ZIC2 was highly expressed, and miR-129-5p was lowly expressed, in primary NPC tissues. In addition, we found that miR-129-5p can directly bind to and reduce ZIC2 expression. LVD was found to be negatively correlated with miR-129-5p and to be positively correlated with ZIC2 expression. Concomitantly, we found that miR-129-5p abrogated activation of the Hedgehog signaling pathway via ZIC2 targeting, leading to suppression of NPC cell invasion, migration and proliferation in vitro as well as suppression of LNM and LVD in vivo.

CONCLUSIONS

From our data we conclude that miR-129-5p, by decreasing ZIC2 expression, may inhibit NPC lymphangiogenesis and LNM through suppression of the Hedgehog signaling pathway.

Podoplanin, a Potential Therapeutic Target for Nasopharyngeal Carcinoma

Introduction

The role of podoplanin (PDPN) in nasopharyngeal carcinoma (NPC) is still unknown. The aims of this study were to investigate the expression and role of PDPN in NPC cells.

Materials and Methods

Immunofluorescence staining and functional tests were used to determine the effects of PDPN knockdown by siRNA in TW01 NPC cells. Microarray analysis was conducted to identify genes regulated by PDPN. The molecular mechanism of PDPN on NPC cells was further determined by Ingenuity Pathways Analysis (IPA).

Results

PDPN was expressed in most TW01 NPC cells. PDPN knockdown by siRNA decreased NPC cell proliferation, migration, and invasion. The microarray data showed 63 upregulated genes and 12 downregulated genes following PDPN knockdown. The top 5 most upregulated genes analyzed by IPA were IFI27, IFI44L, IFI6, OAS1, and TRIM22, and the most relevant pathway was the interferon signaling pathway.

Conclusions

To the best of our knowledge, this is the first report to show that knocking down PDPN leads to suppression of NPC cell proliferation, migration, and invasion. Our results suggest that PDPN may serve as a potential chemotherapeutic target for NPC treatment in the future.

Giving Drugs a Second Chance: Overcoming Regulatory and Financial Hurdles in Repurposing Approved Drugs As Cancer Therapeutics

The repositioning or “repurposing” of existing therapies for alternative disease indications is an attractive approach that can save significant investments of time and money during drug development. For cancer indications, the primary goal of repurposed therapies is on efficacy, with less restriction on safety due to the immediate need to treat this patient population. This report provides a high-level overview of how drug developers pursuing repurposed assets have previously navigated funding efforts, regulatory affairs, and intellectual property laws to commercialize these “new” medicines in oncology. This article provides insight into funding programs (e.g., government grants and philanthropic organizations) that academic and corporate initiatives can leverage to repurpose drugs for cancer. In addition, we highlight previous examples where secondary uses of existing, Food and Drug Administration- or European Medicines Agency-approved therapies have been predicted in silico and successfully validated in vitro and/or in vivo (i.e., animal models and human clinical trials) for certain oncology indications. Finally, we describe the strategies that the pharmaceutical industry has previously employed to navigate regulatory considerations and successfully commercialize their drug products. These factors must be carefully considered when repurposing existing drugs for cancer to best benefit patients and drug developers alike.

Drug repurposing and therapeutic anti-microRNA predictions for inhibition of oxidized low-density lipoprotein-induced vascular smooth muscle cell-associated diseases

Drug repurposing is a new method for disease treatments, which accelerates the identification of new uses for existing drugs with minimal side effects for patients. MicroRNA-based therapeutics are a class of drugs that have been used in gene therapy following the FDA's approval of the first anti-sense therapy. This study examines the effects of oxLDL on vascular smooth muscle cells (VSMCs) and identifies potential drugs and antimiRs for treating VSMC-associated diseases. The Connectivity Map (cMap) database is utilized to identify potential new uses of existing drugs. The success of the identifications was supported by MTT assay, clonogenic assay and clinical trial data. Specifically, 37 drugs, some of which are undergoing clinical trials, were identified. Three of the identified drugs exhibit IC50 activities. Among the 37 drugs' targets, three differentially expressed genes (DEGs) are identified as drug targets by using both the DrugBank and the NCBI PubChem Compound databases. Also, one DEG, DNMT1, which is regulated by 17 miRNAs, where these miRNAs are potential targets for developing antimiR-based miRNA therapy, is found.

Identify potential drugs for cardiovascular diseases caused by stress-induced genes in vascular smooth muscle cells

BACKGROUND

Abnormal proliferation of vascular smooth muscle cells (VSMC) is a major cause of cardiovascular diseases (CVDs). Many studies suggest that vascular injury triggers VSMC dedifferentiation, which results in VSMC changes from a contractile to a synthetic phenotype; however, the underlying molecular mechanisms are still unclear.

METHODS

In this study, we examined how VSMC responds under mechanical stress by using time-course microarray data. A three-phase study was proposed to investigate the stress-induced differentially expressed genes (DEGs) in VSMC. First, DEGs were identified by using the moderated t-statistics test. Second, more DEGs were inferred by using the Gaussian Graphical Model (GGM). Finally, the topological parameters-based method and cluster analysis approach were employed to predict the last batch of DEGs. To identify the potential drugs for vascular diseases involve VSMC proliferation, the drug-gene interaction database, Connectivity Map (cMap) was employed. Success of the predictions were determined using in-vitro data, i.e. MTT and clonogenic assay.

RESULTS

Based on the differential expression calculation, at least 23 DEGs were found, and the findings were qualified by previous studies on VSMC. The results of gene set enrichment analysis indicated that the most often found enriched biological processes are cell-cycle-related processes. Furthermore, more stress-induced genes, well supported by literature, were found by applying graph theory to the gene association network (GAN). Finally, we showed that by processing the cMap input queries with a cluster algorithm, we achieved a substantial increase in the number of potential drugs with experimental IC50 measurements. With this novel approach, we have not only successfully identified the DEGs, but also improved the DEGs prediction by performing the topological and cluster analysis. Moreover, the findings are remarkably validated and in line with the literature. Furthermore, the cMap and DrugBank resources were used to identify potential drugs and targeted genes for vascular diseases involve VSMC proliferation. Our findings are supported by in-vitro experimental IC50, binding activity data and clinical trials.

CONCLUSION

This study provides a systematic strategy to discover potential drugs and target genes, by which we hope to shed light on the treatments of VSMC proliferation associated diseases.

Gene Expression Profiling and Pathway Network Analysis Predicts a Novel Antitumor Function for a Botanical-Derived Drug, PG2

PG2 is a botanical drug that is mostly composed of Astragalus polysaccharides (APS). Its role in hematopoiesis and relieving cancer-related fatigue has recently been clinically investigated in cancer patients. However, systematic analyses of its functions are still limited. The aim of this study was to use microarray-based expression profiling to evaluate the quality and consistency of PG2 from three different product batches and to study biological mechanisms of PG2. An integrative molecular analysis approach has been designed to examine significant PG2-induced signatures in HL-60 leukemia cells. A quantitative analysis of gene expression signatures was conducted for PG2 by hierarchical clustering of correlation coefficients. The results showed that PG2 product batches were consistent and of high quality. These batches were also functionally equivalent to each other with regard to how they modulated the immune and hematopoietic systems. Within the PG2 signature, there were five genes associated with doxorubicin: IL-8, MDM4, BCL2, PRODH2, and BIRC5. Moreover, the combination of PG2 and doxorubicin had a synergistic effect on induced cell death in HL-60 cells. Together with the bioinformatics-based approach, gene expression profiling provided a quantitative measurement for the quality and consistency of herbal medicines and revealed new roles (e.g., immune modulation) for PG2 in cancer treatment.

Drug repositioning discovery for early- and late-stage non-small-cell lung cancer

Drug repositioning is a popular approach in the pharmaceutical industry for identifying potential new uses for existing drugs and accelerating the development time. Non-small-cell lung cancer (NSCLC) is one of the leading causes of death worldwide. To reduce the biological heterogeneity effects among different individuals, both normal and cancer tissues were taken from the same patient, hence allowing pairwise testing. By comparing early- and late-stage cancer patients, we can identify stage-specific NSCLC genes. Differentially expressed genes are clustered separately to form up- and downregulated communities that are used as queries to perform enrichment analysis. The results suggest that pathways for early- and late-stage cancers are different. Sets of up- and downregulated genes were submitted to the cMap web resource to identify potential drugs. To achieve high confidence drug prediction, multiple microarray experimental results were merged by performing meta-analysis. The results of a few drug findings are supported by MTT assay or clonogenic assay data. In conclusion, we have been able to assess the potential existing drugs to identify novel anticancer drugs, which may be helpful in drug repositioning discovery for NSCLC.

In silico identification of potential targets and drugs for non-small cell lung cancer

Lung cancer is one of the leading causes of death in both the USA and Taiwan, and it is thought that the cause of cancer could be because of the gain of function of an oncoprotein or the loss of function of a tumour suppressor protein. Consequently, these proteins are potential targets for drugs. In this study, differentially expressed genes are identified, via an expression dataset generated from lung adenocarcinoma tumour and adjacent non-tumour tissues. This study has integrated many complementary resources, that is, microarray, protein-protein interaction and protein complex. After constructing the lung cancer protein-protein interaction network (PPIN), the authors performed graph theory analysis of PPIN. Highly dense modules are identified, which are potential cancer-associated protein complexes. Up- and down-regulated communities were used as queries to perform functional enrichment analysis. Enriched biological processes and pathways are determined. These sets of up- and down-regulated genes were submitted to the Connectivity Map web resource to identify potential drugs. The authors' findings suggested that eight drugs from DrugBank and three drugs from NCBI can potentially reverse certain up- and down-regulated genes' expression. In conclusion, this study provides a systematic strategy to discover potential drugs and target genes for lung cancer.

BRCA-Monet: a breast cancer specific drug treatment mode-of-action network for treatment effective prediction using large scale microarray database

BACKGROUND

Connectivity map (cMap) is a recent developed dataset and algorithm for uncovering and understanding the treatment effect of small molecules on different cancer cell lines. It is widely used but there are still remaining challenges for accurate predictions.

METHOD

Here, we propose BRCA-MoNet, a network of drug mode of action (MoA) specific to breast cancer, which is constructed based on the cMap dataset. A drug signature selection algorithm fitting the characteristic of cMap data, a quality control scheme as well as a novel query algorithm based on BRCA-MoNet are developed for more effective prediction of drug effects.

RESULT

BRCA-MoNet was applied to three independent data sets obtained from the GEO database: Estrodial treated MCF7 cell line, BMS-754807 treated MCF7 cell line, and a breast cancer patient microarray dataset. In the first case, BRCA-MoNet could identify drug MoAs likely to share same and reverse treatment effect. In the second case, the result demonstrated the potential of BRCA-MoNet to reposition drugs and predict treatment effects for drugs not in cMap data. In the third case, a possible procedure of personalized drug selection is showcased.

CONCLUSIONS

The results clearly demonstrated that the proposed BRCA-MoNet approach can provide increased prediction power to cMap and thus will be useful for identification of new therapeutic candidates.

Using computational strategies to predict potential drugs for nasopharyngeal carcinoma

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a unique cancer. Refinement of current therapy by discovering potential drugs may be approached by several computational strategies.

METHODS

We collected NPC genes from published microarray data and the literature. The NPC disease network was constructed via a protein-protein interaction (PPI) network. The Connectivity Map (CMap) was used to predict potential chemicals, and support vector machines (SVMs) were further utilized to classify the effectiveness of tested drugs against NPC using their gene expression from CMap.

RESULTS

A highly interconnected network was obtained. Several chemically sensitive genes were identified and 87 drugs were predicted with the potential for treating NPC by SVM, in which nearly half of them have anticancer effects according to the literature. The 2 top-ranked drugs, thioridazine and vorinostat, were demonstrated to be effective in inhibiting NPC cells.

CONCLUSION

This in silico approach provides a promising strategy for screening potential therapeutic drugs for NPC treatment.

Induction of apoptosis by high-dose gold nanoparticles in nasopharyngeal carcinoma cells

OBJECTIVE

Nasopharyngeal carcinoma (NPC) is a rare malignancy in most parts of the world, but is a common cancer in southern Asia. Local recurrent disease and distant metastasis of NPC are still the unsolved problems. Recently, gold nanoparticles (AuNPs) have been developed as potential in vivo diagnostic and therapeutic agents. However, their role on nasopharyngeal cancer remains unknown. The object of this study is to investigate if AuNPs can be used as a new therapeutic agent for NPC by evaluating their anti-tumor effect in vitro.

METHODS

The AuNPs were prepared by the reduction of chloroauric acid to neutral gold. Their size distribution and microstructures were characterized by transmission electron microscopy (TEM). To evaluate their cytotoxic effect, NPC cell line TW01 and Human Nasal Epithelial Cells (HNEpC) were cultured in various concentrations of AuNPs for 3 days. Cell viability was evaluated by Trypan Blue viability assay while morphologic findings were observed via light microscopy. Terminal deoxynucleotidyltransferase-mediated dUPT nick end labeling (TUNEL) assay was used to detect apoptosis.

RESULTS

AuNPs prepared in this study had an average diameter of 20.5nm and they were observed under light microscopy as dark material aggregated in the cells after treatment. Contrary to the HNEpC, the AuNPs reduced cell viability of NPC cell in a concentration-dependant manner by Trypan Blue assay, especially at high concentration. Besides, cell apoptosis was demonstrated by positive TUNEL assay.

CONCLUSIONS

The AuNP possesses specific imaging properties and is cytotoxic to NPC cells at high concentrations.

Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.