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

Synthesis and Structure of Novel Phenothiazine Derivatives, and Compound Prioritization via In Silico Target Search and Screening for Cytotoxic and Cholinesterase Modulatory Activities in Liver Cancer Cells and In Vivo in Zebrafish

Phenothiazines (PTZ) are antipsychotics known to modulate a variety of neurotransmitter activities that include dopaminergic and cholinergic signaling and have been identified as potential anticancer agents in vitro. However, it is important to also test whether a highly cytotoxic, repurposed, or novel PTZ has low toxicity and neuromodulatory activity in vivo using vertebrate model organisms, such as zebrafish. In this study, we synthesized novel phenothiazines and screened them in vitro in liver cancer and in vivo in zebrafish embryos/larvae. The syntheses of several intermediate PTZ 10-yl acyl chlorides were followed by elemental analysis and determination of 1H NMR and 13C NMR mass (ESI+) spectra of a large number of novel PTZ 10-carboxamides. Cytotoxicities of 28 PTZ derivatives (1-28) screened against Hep3B and SkHep1 liver cancer cell lines revealed five intermediate and five novel leads along with trifluoperazine (TFP), prochlorperazine (PCP), and perphenazine, which are relatively more cytotoxic than the basic PTZ core. Overall, the derivatives were more cytotoxic to Hep3B than SkHep1 cells. Moreover, in silico target screening identified cholinesterases as some of the commonest targets of the screened phenothiazines. Interestingly, molecular docking studies with acetylcholinesterase (AChE) and butyrylcholinesterase proteins showed that the most cytotoxic compounds 1, 3, PCP, and TFP behaved similar to Huprin W in their amino acid interactions with the AChE protein. The highly cytotoxic intermediate PTZ derivative 1 exhibited a relatively lower toxicity profile than those of 2 and 3 during the zebrafish development. It also modulated in vivo the cholinesterase activity in a dose-dependent manner while significantly increasing the total cholinesterase activity and/or ACHE mRNA levels, independent of the liver cancer cell type. Our screen also identified novel phenothiazines, i.e., 8 and 10, with significant cytotoxic and cholinesterase modulatory effects in liver cancer cells; yet both compounds had low levels of toxicity in zebrafish. Moreover, they modulated the cholinesterase activity or expression of ACHE in a cancer cell line-specific manner, and compound 10 significantly inhibited the cholinesterase activity in zebrafish. Accordingly, using a successful combination of in silico, in vitro, and in vivo approaches, we identified several lead anticancer and cholinesterase modulatory PTZ derivatives for future research.

Cytotoxicity and Multi-Enzyme Inhibition of Nepenthes miranda Stem Extract on H838 Human Non-Small Cell Lung Cancer Cells and RPA32, Elastase, Tyrosinase, and Hyaluronidase Proteins

The carnivorous pitcher plants of the genus Nepenthes have long been known for their ethnobotanical applications. In this study, we prepared various extracts from the pitcher, stem, and leaf of Nepenthes miranda using 100% ethanol and assessed their inhibitory effects on key enzymes related to skin aging, including elastase, tyrosinase, and hyaluronidase. The cytotoxicity of the stem extract of N. miranda on H838 human lung carcinoma cells were also characterized by effects on cell survival, migration, proliferation, apoptosis induction, and DNA damage. The cytotoxic efficacy of the extract was enhanced when combined with the chemotherapeutic agent 5-fluorouracil (5-FU), indicating a synergistic effect. Flow cytometry analysis suggested that the stem extract might suppress H838 cell proliferation by inducing G2 cell cycle arrest, thereby inhibiting carcinoma cell proliferation. Gas chromatography-mass spectrometry (GC-MS) enabled the tentative identification of the 15 most abundant compounds in the stem extract of N. miranda. Notably, the extract showed a potent inhibition of the human RPA32 protein (huRPA32), critical for DNA replication, suggesting a novel mechanism for its anticancer action. Molecular docking studies further substantiated the interaction between the extract and huRPA32, highlighting bioactive compounds, especially the two most abundant constituents, stigmast-5-en-3-ol and plumbagin, as potential inhibitors of huRPA32's DNA-binding activity, offering promising avenues for cancer therapy. Overall, our findings position the stem extract of N. miranda as a promising source of natural compounds for anticancer therapeutics and anti-skin-aging treatments, warranting further investigation into its molecular mechanisms and potential clinical applications.

Overcoming Chemotherapy Resistance in Metastatic Cancer: A Comprehensive Review

The management of metastatic cancer is complicated by chemotherapy resistance. This manuscript provides a comprehensive academic review of strategies to overcome chemotherapy resistance in metastatic cancer. The manuscript presents background information on chemotherapy resistance in metastatic cancer cells, highlighting its clinical significance and the current challenges associated with using chemotherapy to treat metastatic cancer. The manuscript delves into the molecular mechanisms underlying chemotherapy resistance in subsequent sections. It discusses the genetic alterations, mutations, and epigenetic modifications that contribute to the development of resistance. Additionally, the role of altered drug metabolism and efflux mechanisms, as well as the activation of survival pathways and evasion of cell death, are explored in detail. The strategies to overcome chemotherapy resistance are thoroughly examined, covering various approaches that have shown promise. These include combination therapy approaches, targeted therapies, immunotherapeutic strategies, and the repurposing of existing drugs. Each strategy is discussed in terms of its rationale and potential effectiveness. Strategies for early detection and monitoring of chemotherapy drug resistance, rational drug design vis-a-vis personalized medicine approaches, the role of predictive biomarkers in guiding treatment decisions, and the importance of lifestyle modifications and supportive therapies in improving treatment outcomes are discussed. Lastly, the manuscript outlines the clinical implications of the discussed strategies. It provides insights into ongoing clinical trials and emerging therapies that address chemotherapy resistance in metastatic cancer cells. The manuscript also explores the challenges and opportunities in translating laboratory findings into clinical practice and identifies potential future directions and novel therapeutic avenues. This comprehensive review provides a detailed analysis of strategies to overcome chemotherapy resistance in metastatic cancer. It emphasizes the importance of understanding the molecular mechanisms underlying resistance and presents a range of approaches for addressing this critical issue in treating metastatic cancer.

A novel approach for predicting upstream regulators (PURE) that affect gene expression

External factors such as exposure to a chemical, drug, or toxicant (CDT), or conversely, the lack of certain chemicals can cause many diseases. The ability to identify such causal CDTs based on changes in the gene expression profile is extremely important in many studies. Furthermore, the ability to correctly infer CDTs that can revert the gene expression changes induced by a given disease phenotype is a crucial step in drug repurposing. We present an approach for Predicting Upstream REgulators (PURE) designed to tackle this challenge. PURE can correctly infer a CDT from the measured expression changes in a given phenotype, as well as correctly identify drugs that could revert disease-induced gene expression changes. We compared the proposed approach with four classical approaches as well as with the causal analysis used in Ingenuity Pathway Analysis (IPA) on 16 data sets (1 rat, 5 mouse, and 10 human data sets), involving 8 chemicals or drugs. We assessed the results based on the ability to correctly identify the CDT as indicated by its rank. We also considered the number of false positives, i.e. CDTs other than the correct CDT that were reported to be significant by each method. The proposed approach performed best in 11 out of the 16 experiments, reporting the correct CDT at the very top 7 times. IPA was the second best, reporting the correct CDT at the top 5 times, but was unable to identify the correct CDT at all in 5 out of the 16 experiments. The validation results showed that our approach, PURE, outperformed some of the most popular methods in the field. PURE could effectively infer the true CDTs responsible for the observed gene expression changes and could also be useful in drug repurposing applications.

Neurodevelopmental deficits and cell-type-specific transcriptomic perturbations in a mouse model of HNRNPU haploinsufficiency

Heterozygous de novo loss-of-function mutations in the gene expression regulator HNRNPU cause an early-onset developmental and epileptic encephalopathy. To gain insight into pathological mechanisms and lay the potential groundwork for developing targeted therapies, we characterized the neurophysiologic and cell-type-specific transcriptomic consequences of a mouse model of HNRNPU haploinsufficiency. Heterozygous mutants demonstrated global developmental delay, impaired ultrasonic vocalizations, cognitive dysfunction and increased seizure susceptibility, thus modeling aspects of the human disease. Single-cell RNA-sequencing of hippocampal and neocortical cells revealed widespread, yet modest, dysregulation of gene expression across mutant neuronal subtypes. We observed an increased burden of differentially-expressed genes in mutant excitatory neurons of the subiculum-a region of the hippocampus implicated in temporal lobe epilepsy. Evaluation of transcriptomic signature reversal as a therapeutic strategy highlights the potential importance of generating cell-type-specific signatures. Overall, this work provides insight into HNRNPU-mediated disease mechanisms and provides a framework for using single-cell RNA-sequencing to study transcriptional regulators implicated in disease.

The Inhibitory Effects and Cytotoxic Activities of the Stem Extract of Nepenthes miranda against Single-Stranded DNA-Binding Protein and Oral Carcinoma Cells

The carnivorous pitcher plants of the genus Nepenthes exhibit many ethnobotanical uses, including treatments of stomachache and fever. In this study, we prepared different extracts from the pitcher, stem, and leaf extracts of Nepenthes miranda obtained using 100% methanol and analyzed their inhibitory effects on recombinant single-stranded DNA-binding protein (SSB) from Klebsiella pneumoniae (KpSSB). SSB is essential for DNA replication and cell survival and thus an attractive target for potential antipathogen chemotherapy. Different extracts prepared from Sinningia bullata, a tuberous member of the flowering plant family Gesneriaceae, were also used to investigate anti-KpSSB properties. Among these extracts, the stem extract of N. miranda exhibited the highest anti-KpSSB activity with an IC₅₀ value of 15.0 ± 1.8 μg/mL. The cytotoxic effects of the stem extract of N. miranda on the survival and apoptosis of the cancer cell lines Ca9-22 gingival carcinoma, CAL27 oral adenosquamous carcinoma, PC-9 pulmonary adenocarcinoma, B16F10 melanoma, and 4T1 mammary carcinoma cells were also demonstrated and compared. Based on collective data, the cytotoxic activities of the stem extract at a concentration of 20 μg/mL followed the order Ca9-22 > CAL27 > PC9 > 4T1 > B16F10 cells. The stem extract of N. miranda at a concentration of 40 μg/mL completely inhibited Ca9-22 cell migration and proliferation. In addition, incubation with this extract at a concentration of 20 μg/mL boosted the distribution of the G2 phase from 7.9% to 29.2% in the Ca9-22 cells; in other words, the stem extract might suppress Ca9-22 cell proliferation by inducing G2 cell cycle arrest. Through gas chromatography-mass spectrometry, the 16 most abundant compounds in the stem extract of N. miranda were tentatively identified. The 10 most abundant compounds in the stem extract of N. miranda were used for docking analysis, and their docking scores were compared. The binding capacity of these compounds was in the order sitosterol > hexadecanoic acid > oleic acid > plumbagin > 2-ethyl-3-methylnaphtho[2,3-b]thiophene-4,9-dione > methyl α-d-galactopyranoside > 3-methoxycatechol > catechol > pyrogallol > hydroxyhydroquinone; thus, sitosterol might exhibit the greatest inhibitory capacity against KpSSB among the selected compounds. Overall, these results may indicate the pharmacological potential of N. miranda for further therapeutic applications.

An Innovative Drug Repurposing Approach to Restrain Endometrial Cancer Metastatization

BACKGROUND

Endometrial cancer (EC) is the most common gynecologic tumor and the world's fourth most common cancer in women. Most patients respond to first-line treatments and have a low risk of recurrence, but refractory patients, and those with metastatic cancer at diagnosis, remain with no treatment options. Drug repurposing aims to discover new clinical indications for existing drugs with known safety profiles. It provides ready-to-use new therapeutic options for highly aggressive tumors for which standard protocols are ineffective, such as high-risk EC.

METHODS

Here, we aimed at defining new therapeutic opportunities for high-risk EC using an innovative and integrated computational drug repurposing approach.

RESULTS

We compared gene-expression profiles, from publicly available databases, of metastatic and non-metastatic EC patients being metastatization the most severe feature of EC aggressiveness. A comprehensive analysis of transcriptomic data through a two-arm approach was applied to obtain a robust prediction of drug candidates.

CONCLUSIONS

Some of the identified therapeutic agents are already successfully used in clinical practice to treat other types of tumors. This highlights the potential to repurpose them for EC and, therefore, the reliability of the proposed approach.

Cytotoxic, Antibacterial, and Antioxidant Activities of the Leaf Extract of Sinningia bullata

Sinningia bullata is a tuberous member of the flowering plant family Gesneriaceae. Prior to this work, the antibacterial, antioxidant, and cytotoxic properties of S. bullata were undetermined. Here, we prepared different extracts from the leaf, stem, and tuber of S. bullata and investigated their pharmacological activities. The leaf extract of S. bullata, obtained by 100% acetone (Sb-L-A), had the highest total flavonoid content, antioxidation capacity, and cytotoxic and antibacterial activities. Sb-L-A displayed a broad range of antibacterial activities against Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. The inhibition zones of Sb-L-A ranged from 8 to 30 mm and were in the following order: S. aureus > E. coli > P. aeruginosa. Incubation of B16F10 melanoma cells with Sb-L-A at a concentration of 80 μg/mL caused deaths at the rate of 96%, reduced migration by 100%, suppressed proliferation and colony formation by 99%, and induced apoptosis, which was observed in 96% of the B16F10 cells. In addition, the cytotoxic activities of Sb-L-A were synergistically enhanced when coacting with the antitumor drug epothilone B. Sb-L-A was also used to determine the cytotoxic effects against 4T1 mammary carcinoma cells. Sb-L-A of 60 μg/mL boosted the distribution of the G2 phase from 1.4% to 24.4% in the B16F10 cells. Accordingly, Sb-L-A might suppress melanoma cell proliferation by inducing G2 cell-cycle arrest. The most abundant compounds in Sb-L-A were identified using gas chromatography-mass spectrometry. Overall, the collective data in this study may indicate the pharmacological potentials of Sb-L-A for possible medical applications.

Generation of multicellular tumor spheroids with micro-well array for anticancer drug combination screening based on a valuable biomarker of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly malignant tumor with a poor prognosis. More than 30% of patients with diagnosed HCC have abnormally high expression of fibroblast growth factor receptor 4 (FGFR4). Currently, clinical trials for a variety of FGFR4-specific inhibitors have started. However, the effect of these inhibitors is not ideal, and it is necessary to find a drug combination to synergistically exert anti-tumor effects. We found strong correlations between FGFR4 and HCC clinicopathological characteristics in the present study. After grouping patients according to FGFR4 expression, the key gene signatures were inputted the drug-gene related databases, which predicted several potential drug candidates. More importantly, to achieve the reliable and high throughput drug cytotoxicity assessment, we developed an efficient and reproducible agarose hydrogel microwells to generate uniform-sized multicellular tumor spheroids, which provide better mimicry of conventional solid tumors that can precisely represent anticancer drug candidates' effects. Using high content screening, we quickly evaluated the enhanced anti-tumor effects of these combinations. Finally, we demonstrated that Parthenolide is a potential drug that can significantly enhance the clinical efficacy of FGFR4 receptor inhibitors. In general, we offered a new therapeutic way for FGFR4 positive HCC patients.

The Inhibitory Effects and Cytotoxic Activities of the Stem Extract of Sarracenia purpurea against Melanoma Cells and the SsbA Protein

The Staphylococcus aureus SsbA protein (SaSsbA) is a single-stranded DNA-binding protein (SSB) that is categorically required for DNA replication and cell survival, and it is thus an attractive target for potential antipathogen chemotherapy. In this study, we prepared the stem extract of Sarracenia purpurea obtained from 100% acetone to investigate its inhibitory effect against SaSsbA. In addition, the cytotoxic effects of this extract on the survival, apoptosis, proliferation, and migration of B16F10 melanoma cells were also examined. Initially, myricetin, quercetin, kaempferol, dihydroquercetin, dihydrokaempferol, rutin, catechin, β-amyrin, oridonin, thioflavin T, primuline, and thioflavin S were used as possible inhibitors against SaSsbA. Of these compounds, dihydrokaempferol and oridonin were capable of inhibiting the ssDNA-binding activity of SaSsbA with respective IC50 values of 750 ± 62 and 2607 ± 242 μM. Given the poor inhibition abilities of dihydrokaempferol and oridonin, we screened the extracts of S. purpurea, Nepenthes miranda, and Plinia cauliflora for SaSsbA inhibitors. The stem extract of S. purpurea exhibited high anti-SaSsbA activity, with an IC50 value of 4.0 ± 0.3 μg/mL. The most abundant compounds in the stem extract of S. purpurea were identified using gas chromatography−mass spectrometry. The top five most abundant contents in this extract were driman-8,11-diol, deoxysericealactone, stigmast-5-en-3-ol, apocynin, and α-amyrin. Using the MOE-Dock tool, the binding modes of these compounds, as well as dihydrokaempferol and oridonin, to SaSsbA were elucidated, and their binding energies were also calculated. Based on the S scores, the binding capacity of these compounds was in the following order: deoxysericealactone > dihydrokaempferol > apocynin > driman-8,11-diol > stigmast-5-en-3-ol > oridonin > α-amyrin. Incubation of B16F10 cells with the stem extract of S. purpurea at a concentration of 100 μg/mL caused deaths at the rate of 76%, reduced migration by 95%, suppressed proliferation and colony formation by 99%, and induced apoptosis, which was observed in 96% of the B16F10 cells. Overall, the collective data in this study indicate the pharmacological potential of the stem extract of S. purpurea for further medical applications.

Anticancer and Antioxidant Activities of the Root Extract of the Carnivorous Pitcher Plant Sarracenia purpurea

The carnivorous pitcher plant Sarracenia purpurea exhibits many ethnobotanical uses, including the treatments of type 2 diabetes and tuberculosis-like symptoms. In this study, we prepared different extracts from the leaves (pitchers), stems, and roots of S. purpurea and investigated their antioxidant and anticancer properties. To evaluate the extraction efficiency, we individually used different solvents, namely methanol, ethanol, acetone, and distilled water, for S. purpurea extract preparations. The root extract of S. purpurea, obtained by 100% acetone (S. purpurea-root-acetone), had the highest anticancer activities, antioxidation capacity (the DPPH activity with IC₅₀ of 89.3 ± 2.2 μg/mL), antibacterial activities, total phenolic content (33.4 ± 0.7 mg GAE/g), and total flavonoid content (107.9 ± 2.2 mg QUE/g). The most abundant compounds in S. purpurea-root-acetone were identified using gas chromatography-mass spectrometry; 7,8-Dihydro-α-ionone was the major compound present in S. purpurea-root-acetone. In addition, the co-cytotoxicity of S. purpurea-root-acetone (combined with the clinical anticancer drug 5-fluorouracil (5-FU) on the survival, apoptosis, proliferation, and migration of the 4T1 mammary carcinoma) was examined. The combination of 5-FU with S. purpurea-root-acetone could be highly efficient for anti-4T1 cells. We also found that S. purpurea-root-acetone could inhibit the enzymatic activity of human dihydroorotase (huDHOase), an attractive target for potential anticancer chemotherapy. The sic most abundant compounds in S. purpurea-root-acetone were tested using an in silico analysis via MOE-Dock software for their binding affinities. The top-ranked docking conformations were observed for 7,8-dihydro-α-ionone and stigmast-5-en-3-ol, suggesting the inhibition potential against huDHOase. Overall, the collective data in this study may indicate the pharmacological potentials of S. purpurea-root-acetone for possible medical applications.

RNA adenosine modifications related to prognosis and immune infiltration in osteosarcoma

Background

RNA adenosine modifications, which are primarily mediated by “writer” enzymes (RMWs), play a key role in epigenetic regulation in various biological processes, including tumorigenesis. However, the expression and prognostic role of these genes in osteosarcoma (OS) remain unclear.

Methods

Univariate and multivariate Cox analyses were used to construct the RMW signature for OS using Target datasets. RMW expression in OS tissue was detected by qPCR analysis. Xcell and GSVA were used to determine the relationship between RMWs and immune infiltration. The DGIdb and CMap databases were used for drug prediction. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS.

Results

A 3-RMW (CSTF2, ADAR and WTAP) prognostic signature in OS was constructed using the Target dataset and verified using GEO datasets and 63 independent OS tissues via qPCR analysis. High-risk OS patients had poor overall survival, and the prognostic signature was an independent prognostic factor for OS. Functional studies showed that tumour-, metabolism-, cell cycle- and immune-related pathways were related to high risk. Next, we found that RMW-derived high-risk patients exhibited increased infiltration of M2 macrophages and cDCs. Furthermore, we predicted the potential drugs for OS using the DGIdb and CMap databases. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS by repressing cell growth and inducing cell cycle arrest at the G1 phase.

Conclusion

The 3-RWM-based prognostic signature established in this study is a novel gene signature associated with immune infiltration, and strophanthidin was identified as a candidate therapy for OS by repressing OS cell growth and the cell cycle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03415-6.

Trifluoperazine and Its Analog Suppressed the Tumorigenicity of Non-Small Cell Lung Cancer Cell; Applicability of Antipsychotic Drugs to Lung Cancer Treatment

Despite significant advances in diagnostic and therapeutic technologies, lung cancer remains the leading cause of cancer-related mortality worldwide. Non-small cell lung cancer (NSCLC) accounts for approximately 85% of lung cancer cases. Recently, some antipsychotics have been shown to possess anticancer activity. However, the effects of antipsychotics on NSCLC need to be further explored. We examined the effects of trifluoperazine (TFP), a commonly used antipsychotic drug, and its synthetic analogs on A549 human lung cancer cells. In addition, cell proliferation analysis, colony formation assay, flow cytometry, western blot analysis, and in vivo xenograft experiments were performed. Key genes and mechanisms possibly affected by TFP are significantly related to better survival outcomes in lung cancer patients. Treatment with TFP and a selected TFP analog 3dc significantly inhibited the proliferation, anchorage-dependent/independent colony formation, and migration of A549 cells. Treatment with 3dc affected the expression of genes related to the apoptosis and survival of A549 cells. Treatment with 3dc promoted apoptosis and DNA fragmentation. In all experiments, including in vivo studies of metastatic lung cancer development, 3dc had more substantial anticancer effects than TFP. According to our analysis of publicly available clinical data and in vitro and in vivo experiments, we suggest that some kinds of antipsychotics prevent the progression of NSCLC. Furthermore, this study indicates a synthetic TFP analog that could be a potential therapeutic for lung cancer.

Plumbagin, a Natural Product with Potent Anticancer Activities, Binds to and Inhibits Dihydroorotase, a Key Enzyme in Pyrimidine Biosynthesis

Dihydroorotase (DHOase) is the third enzyme in the de novo biosynthesis pathway for pyrimidine nucleotides, and an attractive target for potential anticancer chemotherapy. By screening plant extracts and performing GC-MS analysis, we identified and characterized that the potent anticancer drug plumbagin (PLU), isolated from the carnivorous plant Nepenthes miranda, was a competitive inhibitor of DHOase. We also solved the complexed crystal structure of yeast DHOase with PLU (PDB entry 7CA1), to determine the binding interactions and investigate the binding modes. Mutational and structural analyses indicated the binding of PLU to DHOase through loop-in mode, and this dynamic loop may serve as a drug target. PLU exhibited cytotoxicity on the survival, migration, and proliferation of 4T1 cells and induced apoptosis. These results provide structural insights that may facilitate the development of new inhibitors targeting DHOase, for further clinical anticancer chemotherapies.

Antidepressants and Antipsychotic Agents as Repurposable Oncological Drug Candidates

Drug repurposing, also known as drug repositioning/reprofiling, is a relatively new strategy for the identification of alternative uses of well-known therapeutics that are outside the scope of their original medical indications. Such an approach might entail a number of advantages compared to standard de novo drug development, including less time needed to introduce the drug to the market, and lower costs. The group of compounds that could be considered as promising candidates for repurposing in oncology include the central nervous system drugs, especially selected antidepressant and antipsychotic agents. In this article, we provide an overview of some antidepressants (citalopram, fluoxetine, paroxetine, sertraline) and antipsychotics (chlorpromazine, pimozide, thioridazine, trifluoperazine) that have the potential to be repurposed as novel chemotherapeutics in cancer treatment, as they have been found to exhibit preventive and/or therapeutic action in cancer patients. Nevertheless, although drug repurposing seems to be an attractive strategy to search for oncological drugs, we would like to clearly indicate that it should not replace the search for new lead structures, but only complement de novo drug development.

SEC62 and SEC63 Expression in Hepatocellular Carcinoma and Tumor-Surrounding Liver Tissue

Introduction

The endoplasmic reticulum transmembrane proteins Sec61, Sec62, and Sec63 are responsible for the intracellular trafficking of precursor proteins and affect intracellular signaling. SEC62 overexpression has been linked to various human cancers. Our aim was to investigate SEC62 and SEC63 expression in hepatocellular carcinoma (HCC) and surrounding liver tissue.

Patients and Methods

Primary liver tissue was collected from 11 consecutive patients (70 ± 9 years; 10 men) who underwent HCC resection. In the HCC and the tumor-surrounding liver tissue we investigated SEC62 und SEC63 mRNA expression using quantitative real-time PCR. For Sec62, immunohistochemistry was performed.

Results

SEC62and SEC63 total mRNA contents were significantly (p = 0.001) higher in HCCs (C_T 22.5 ± 0.4 and 22.6 ± 0.3) when compared to the surrounding tissue (C_T 24.6 ± 0.6 and 25.1 ± 0.9). Using the comparative C_Tmethod, SEC62 and SEC63 expression in HCC was increased 5- and 8.1-fold, respectively, in comparison to surrounding tissue. For Sec62 immunohistochemistry, the mean immunoreactive scores (IRS) were 7.9 ± 2.9 for HCC and 4.8 ± 1.2 for non-tumorous liver (p = 0.027). The mean IRS in HCC were 5.7 ± 3.5 and 8.9 ± 2.3 for patients without (n = 3) and with tumor recurrence (n = 8), respectively.

Conclusions

Overexpression of SEC62 and SEC63 is a common feature of HCC. The role of Sec62 as a prognostic marker for tumor recurrence after surgery and its potential role in treatment stratification must be addressed in future studies.

Dopamine Receptors in Cancer: Are They Valid Therapeutic Targets?

The dopamine receptors (DRs) family includes 5 members with differences in signal transduction and ligand affinity. Abnormal DRs expression has been correlated multiple tumors with their clinical outcome. Thus, it has been proposed that DRs-targeting drugs-developed for other diseases as schizophrenia or Parkinson's disease-could be helpful in managing neoplastic diseases. In this review, we discuss the role of DRs and the effects of DRs-targeting in tumor progression and cancer cell biology using multiple high-prevalence neoplasms as examples. The evidence shows that DRs are valid therapeutic targets for certain receptor/disease combinations, but the data are inconclusive or contradictory for others. In either case, further studies are required to define the precise role of DRs in tumor progression and propose better therapeutic strategies for their targeting.

Transcriptomics-Based Drug Repurposing Approach Identifies Novel Drugs against Sorafenib-Resistant Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma (HCC), a type of liver cancer, remains a treatment challenge due to late detection and resistance to currently approved drugs. It takes 15–20 years for a single new drug to become FDA approved. The purpose of this study was to expedite identification of novel drugs against drug-resistant HCC. For this, we matched gene expression alterations in resistant HCC with gene expression changes caused by treatment of cancer cells with drugs already FDA approved for other diseases to find the drug that can reverse the resistance-related changes. Among the identified drugs, we validated the growth inhibitory effect of two drugs, identified their mechanism in HCC and, thus, provided proof of concept evidence for validity of this drug repurposing approach with potential for use in personalized medicine.

Abstract

Objective: Hepatocellular carcinoma (HCC) is frequently diagnosed in patients with late-stage disease who are ineligible for curative surgical therapies. The majority of patients become resistant to sorafenib, the only approved first-line therapy for advanced cancer, underscoring the need for newer, more effective drugs. The purpose of this study is to expedite identification of novel drugs against sorafenib resistant (SR)-HCC. Methods: We employed a transcriptomics-based drug repurposing method termed connectivity mapping using gene signatures from in vitro-derived SR Huh7 HCC cells. For proof of concept validation, we focused on drugs that were FDA-approved or under clinical investigation and prioritized two anti-neoplastic agents (dasatinib and fostamatinib) with targets associated with HCC. We also prospectively validated predicted gene expression changes in drug-treated SR Huh7 cells as well as identified and validated the targets of Fostamatinib in HCC. Results: Dasatinib specifically reduced the viability of SR-HCC cells that correlated with up-regulated activity of SRC family kinases, its targets, in our SR-HCC model. However, fostamatinib was able to inhibit both parental and SR HCC cells in vitro and in xenograft models. Ingenuity pathway analysis of fostamatinib gene expression signature from LINCS predicted JAK/STAT, PI3K/AKT, ERK/MAPK pathways as potential targets of fostamatinib that were validated by Western blot analysis. Fostamatinib treatment reversed the expression of genes that were deregulated in SR HCC. Conclusion: We provide proof of concept evidence for the validity of this drug repurposing approach for SR-HCC with implications for personalized medicine.

Gene-signature-derived IC50s/EC50s reflect the potency of causative upstream targets and downstream phenotypes

Multiplexed gene-signature-based phenotypic assays are increasingly used for the identification and profiling of small molecule-tool compounds and drugs. Here we introduce a method (provided as R-package) for the quantification of the dose-response potency of a gene-signature as EC₅₀ and IC₅₀ values. Two signaling pathways were used as models to validate our methods: beta-adrenergic agonistic activity on cAMP generation (dedicated dataset generated for this study) and EGFR inhibitory effect on cancer cell viability. In both cases, potencies derived from multi-gene expression data were highly correlated with orthogonal potencies derived from cAMP and cell growth readouts, and superior to potencies derived from single individual genes. Based on our results we propose gene-signature potencies as a novel valid alternative for the quantitative prioritization, optimization and development of novel drugs.

ERα-related chromothripsis enhances concordant gene transcription on chromosome 17q11.1-q24.1 in luminal breast cancer

BACKGROUND

Chromothripsis is an event of genomic instability leading to complex chromosomal alterations in cancer. Frequent long-range chromatin interactions between transcription factors (TFs) and targets may promote extensive translocations and copy-number alterations in proximal contact regions through inappropriate DNA stitching. Although studies have proposed models to explain the initiation of chromothripsis, few discussed how TFs influence this process for tumor progression.

METHODS

This study focused on genomic alterations in amplification associated regions within chromosome 17. Inter-/intra-chromosomal rearrangements were analyzed using whole genome sequencing data of breast tumors in the Cancer Genome Atlas (TCGA) cohort. Common ERα binding sites were defined based on MCF-7, T47D, and MDA-MB-134 breast cancer cell lines using univariate K-means clustering methods. Nanopore sequencing technology was applied to validate frequent rearrangements detected between ATC loci on 17q23 and an ERα hub on 20q13. The efficacy of pharmacological inhibition of a potentially druggable target gene on 17q23 was evaluated using breast cancer cell lines and patient-derived circulating breast tumor cells.

RESULTS

There are five adjoining regions from 17q11.1 to 17q24.1 being hotspots of chromothripsis. Inter-/intra-chromosomal rearrangements of these regions occurred more frequently in ERα-positive tumors than in ERα-negative tumors. In addition, the locations of the rearrangements were often mapped within or close to dense ERα binding sites localized on these five 17q regions or other chromosomes. This chromothriptic event was linked to concordant upregulation of 96 loci that predominantly regulate cell-cycle machineries in advanced luminal tumors. Genome-editing analysis confirmed that an ERα hub localized on 20q13 coordinately regulates a subset of these loci localized on 17q23 through long-range chromosome interactions. One of these loci, Tousled Like Kinase 2 (TLK2) known to participate in DNA damage checkpoint control, is an actionable target using phenothiazine antipsychotics (PTZs). The antiproliferative effect of PTZs was prominent in high TLK2-expressing cells, compared to low expressing cells.

CONCLUSION

This study demonstrates a new approach for identifying tumorigenic drivers from genomic regions highly susceptible to ERα-related chromothripsis. We found a group of luminal breast tumors displaying 17q-related chromothripsis for which antipsychotics can be repurposed as treatment adjuncts.

Drug rechanneling: A novel paradigm for cancer treatment

Cancer continues to be one of the leading contributors towards global disease burden. According to NIH, cancer incidence rate per year will increase to 23.6 million by 2030. Even though cancer continues to be a major proportion of the disease burden worldwide, it has the lowest clinical trial success rate amongst other diseases. Hence, there is an unmet need for novel, affordable and effective anti-neoplastic medications. As a result, a growing interest has sparkled amongst researchers towards drug repurposing. Drug repurposing follows the principle of polypharmacology, which states, "any drug with multiple targets or off targets can present several modes of action". Drug repurposing also known as drug rechanneling, or drug repositioning is an economic and reliable approach that identifies new disease treatment of already approved drugs. Repurposing guarantees expedited access of drugs to the patients as these drugs are already FDA approved and their safety and toxicity profile is completely established. Epidemiological studies have identified the decreased occurrence of oncological or non-oncological conditions in patients undergoing treatment with FDA approved drugs. Data from multiple experimental studies and clinical observations have depicted that several non-neoplastic drugs have potential anticancer activity. In this review, we have summarized the potential anti-cancer effects of anti-psychotic, anti-malarial, anti-viral and anti-emetic drugs with a brief overview on their mechanism and pathways in different cancer types. This review highlights promising evidences for the repurposing of drugs in oncology.

New drugs are not enough‑drug repositioning in oncology: An update

Drug repositioning refers to the concept of discovering novel clinical benefits of drugs that are already known for use treating other diseases. The advantages of this are that several important drug characteristics are already established (including efficacy, pharmacokinetics, pharmacodynamics and toxicity), making the process of research for a putative drug quicker and less costly. Drug repositioning in oncology has received extensive focus. The present review summarizes the most prominent examples of drug repositioning for the treatment of cancer, taking into consideration their primary use, proposed anticancer mechanisms and current development status.

Dissecting the Anticancer Mechanism of Trifluoperazine on Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers with almost no curative chemotherapeutic treatment. Besides the development of new compounds, repurposing of approved drugs to treat cancer, alone or in combination, has become an attractive strategy, showing many therapeutic and economic advantages. However, it is necessary to improve our knowledge about the mechanism of cell death elicited by approved drugs itself, but also to rationally develop more powerful multidrug treatments. In this work, we focus our attention on determining the mechanism promoting cell death following trifluoperazine (TFP) treatment, which is an antipsychotic drug with strong anticancer activity in PDAC. We demonstrate that TFP induces cell death by apoptosis and necroptosis, which can be partially inhibited by Z-VAD-FMK as well as necrostatin-1, respectively. This cell death promotion is triggered by a poor ATP content, observed in TFP-treated cells as a consequence of a dramatic decrease in OXPHOS metabolism due to mitochondrial stress. Remarkably, mitochondrial homeostasis was seriously affected, and a loss of mitochondrial membrane potential and ROS overproduction was observed. Moreover, this mitochondrial stress was coupled with an ER stress and the activation of the endoplasmic-reticulum-associated protein degradation (ERAD) and the unf olded protein response (UPR) pathways. We took advantage of this information and inhibited this process by using the proteasome inhibitors MG-132 or bortezomib compounds in combination with TFP and found a significant improvement of the anticancer effect of the TFP on primary PDAC-derived cells. In conclusion, this study not only uncovers the molecular mechanisms that are triggered upon TFP-treatment but also its possible combination with bortezomib for the future development of therapies for pancreatic cancer.

Application of Big Data analysis in gastrointestinal research

Big Data, which are characterized by certain unique traits like volume, velocity and value, have revolutionized the research of multiple fields including medicine. Big Data in health care are defined as large datasets that are collected routinely or automatically, and stored electronically. With the rapidly expanding volume of health data collection, it is envisioned that the Big Data approach can improve not only individual health, but also the performance of health care systems. The application of Big Data analysis in the field of gastroenterology and hepatology research has also opened new research approaches. While it retains most of the advantages and avoids some of the disadvantages of traditional observational studies (case-control and prospective cohort studies), it allows for phenomapping of disease heterogeneity, enhancement of drug safety, as well as development of precision medicine, prediction models and personalized treatment. Unlike randomized controlled trials, it reflects the real-world situation and studies patients who are often under-represented in randomized controlled trials. However, residual and/or unmeasured confounding remains a major concern, which requires meticulous study design and various statistical adjustment methods. Other potential drawbacks include data validity, missing data, incomplete data capture due to the unavailability of diagnosis codes for certain clinical situations, and individual privacy. With continuous technological advances, some of the current limitations with Big Data may be further minimized. This review will illustrate the use of Big Data research on gastrointestinal and liver diseases using recently published examples.

Trifluoperazine as an alternative strategy for the inhibition of tumor growth of colorectal cancer

The development of cancer in patients with schizophrenia is affected by genetic and environmental factors and antipsychotic medication. Several studies found that schizophrenia was associated with decreased risk of some cancers, and the neuroleptic medication might help to reduce the risk of colorectal cancer (CRC). Phenothiazine drugs including trifluoperazine (TFP) are widely used antipsychotic drugs and showed some antitumor effects, we here investigated the potential application of TFP in the treatment of colon cancer. A series doses of TFP were treated to the colon cancer cell line HCT116 and the inhibitory concentration (IC₅₀ ) of TFP for HCT116 was determined by cell counting kit-8. The results indicated that the treatment of TFP impaired the cell vitality of HCT116 in a dose- and time-dependent manner. Meanwhile, the Edu assay demonstrated that the proliferation was also inhibited by TFP, which was accompanied with the induction of apoptosis and autophagy. The expression of CCNE1, CDK4, and antiapoptosis factor BCL-2 was downregulated but the proapoptosis factor BAX was upregulated. The autophagy inhibitor chloroquine could significantly reverse the TFP-induced apoptosis. Moreover, the ability of migration and invasion of HCT116 was found to be suppressed by TFP, which was associated with the inhibition of epithelial-mesenchymal transition (EMT). The function of TFP in vivo was further confirmed. The results showed that the administration of TFP remarkably abrogated the tumor growth with decreased tumor volume and proliferation index Ki-67 level in tumor tissues. The EMT phenotype was also confirmed to be inhibited by TFP in vivo, suggesting the promising antitumor effects of TFP in CRC.

Computational Drug Repositioning for Gastric Cancer using Reversal Gene Expression Profiles

Treatment of gastric cancer (GC) often produces poor outcomes. Moreover, predicting which GC treatments will be effective remains challenging. Computational drug repositioning using public databases is a promising and efficient tool for discovering new uses for existing drugs. Here we used a computational reversal of gene expression approach based on effects on gene expression signatures by GC disease and drugs to explore new GC drug candidates. Gene expression profiles for individual GC tumoral and normal gastric tissue samples were downloaded from the Gene Expression Omnibus (GEO) and differentially expressed genes (DEGs) in GC were determined with a meta-signature analysis. Profiles drug activity and drug-induced gene expression were downloaded from the ChEMBL and the LINCS databases, respectively. Candidate drugs to treat GC were predicted using reversal gene expression score (RGES). Drug candidates including sorafenib, olaparib, elesclomol, tanespimycin, selumetinib, and ponatinib were predicted to be active for treatment of GC. Meanwhile, GC-related genes such as PLOD3, COL4A1, UBE2C, MIF, and PRPF5 were identified as having gene expression profiles that can be reversed by drugs. These findings support the use of a computational reversal gene expression approach to identify new drug candidates that can be used to treat GC.

Gene expression profile-based drug screen identifies SAHA as a novel treatment for NAFLD

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide.

EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to improve prediction accuracy

Motivation

Availability of large-scale genomic, epigenetic and proteomic data in complex diseases makes it possible to objectively and comprehensively identify the therapeutic targets that can lead to new therapies. The Connectivity Map has been widely used to explore novel indications of existing drugs. However, the prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic remains low. Here we present a novel high-performance drug repositioning approach that improves over the state-of-the-art methods.

Results

We first designed an expression weighted cosine (EWCos) method to minimize the influence of the uninformative expression changes and then developed an ensemble approach termed ensemble of multiple drug repositioning approaches (EMUDRA) to integrate EWCos and three existing state-of-the-art methods. EMUDRA significantly outperformed individual drug repositioning methods when applied to simulated and independent evaluation datasets. We predicted using EMUDRA and experimentally validated an antibiotic rifabutin as an inhibitor of cell growth in triple negative breast cancer. EMUDRA can identify drugs that more effectively target disease gene signatures and will thus be a useful tool for identifying novel therapies for complex diseases and predicting new indications for existing drugs.

Availability and implementation

The EMUDRA R package is available at doi: 10.7303/syn11510888.

Supplementary information

Supplementary data are available at Bioinformatics online.

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 in cancer

Cancer is a major health issue worldwide, and the global burden of cancer is expected to increase in the coming years. Whereas the limited success with current therapies has driven huge investments into drug development, the average number of FDA approvals per year has declined since the 1990s. This unmet need for more effective anti-cancer drugs has sparked a growing interest for drug repurposing, i.e. using drugs already approved for other indications to treat cancer. As such, data both from pre-clinical experiments, clinical trials and observational studies have demonstrated anti-tumor efficacy for compounds within a wide range of drug classes other than cancer. Whereas some of them induce cancer cell death or suppress various aspects of cancer cell behavior in established tumors, others may prevent cancer development. Here, we provide an overview of promising candidates for drug repurposing in cancer, as well as studies describing the biological mechanisms underlying their anti-neoplastic effects.

Computational Discovery of Niclosamide Ethanolamine, a Repurposed Drug Candidate That Reduces Growth of Hepatocellular Carcinoma Cells In Vitro and in Mice by Inhibiting Cell Division Cycle 37 Signaling

BACKGROUND & AIMS

Drug repositioning offers a shorter approval process than new drug development. We therefore searched large public datasets of drug-induced gene expression signatures to identify agents that might be effective against hepatocellular carcinoma (HCC).

METHODS

We searched public databases of messenger RNA expression patterns reported from HCC specimens from patients, HCC cell lines, and cells exposed to various drugs. We identified drugs that might specifically increase expression of genes that are down-regulated in HCCs and reduce expression of genes up-regulated in HCCs using a nonparametric, rank-based pattern-matching strategy based on the Kolmogorov-Smirnov statistic. We evaluated the anti-tumor activity of niclosamide and its ethanolamine salt (NEN) in HCC cell lines (HepG2, Huh7, Hep3B, Hep40, and PLC/PRF/5), primary human hepatocytes, and 2 mouse models of HCC. In one model of HCC, liver tumor development was induced by hydrodynamic delivery of a sleeping beauty transposon expressing an activated form of Ras (v12) and truncated β-catenin (N90). In another mouse model, patient-derived xenografts were established by implanting HCC cells from patients into livers of immunocompromised mice. Tumor growth was monitored by bioluminescence imaging. Tumor-bearing mice were fed a regular chow diet or a chow diet containing niclosamide or NEN. In a separate experiment using patient-derived xenografts, tumor-bearing mice were given sorafenib (the standard of care for patients with advanced HCC), NEN, or niclosamide alone; a combination of sorafenib and NEN; or a combination sorafenib and niclosamide in their drinking water, or regular water (control), and tumor growth was monitored.

RESULTS

Based on gene expression signatures, we identified 3 anthelmintics that significantly altered the expression of genes that are up- or down-regulated in HCCs. Niclosamide and NEN specifically reduced the viability of HCC cells: the agents were at least 7-fold more cytotoxic to HCCs than primary hepatocytes. Oral administration of NEN to mice significantly slowed growth of genetically induced liver tumors and patient-derived xenografts, whereas niclosamide did not, coinciding with the observed greater bioavailability of NEN compared with niclosamide. The combination of NEN and sorafenib was more effective at slowing growth of patient-derived xenografts than either agent alone. In HepG2 cells and in patient-derived xenografts, administration of niclosamide or NEN increased expression of 20 genes down-regulated in HCC and reduced expression of 29 genes up-regulated in the 274-gene HCC signature. Administration of NEN to mice with patient-derived xenografts reduced expression of proteins in the Wnt-β-catenin, signal transducer and activator of transcription 3, AKT-mechanistic target of rapamycin, epidermal growth factor receptor-Ras-Raf signaling pathways. Using immunoprecipitation assays, we found NEN to bind cell division cycle 37 protein and disrupt its interaction with heat shock protein 90.

CONCLUSIONS

In a bioinformatics search for agents that alter the HCC-specific gene expression pattern, we identified the anthelmintic niclosamide as a potential anti-tumor agent. Its ethanolamine salt, with greater bioavailability, was more effective than niclosamide at slowing the growth of genetically induced liver tumors and patient-derived xenografts in mice. Both agents disrupted interaction between cell division cycle 37 and heat shock protein 90 in HCC cells, with concomitant inhibition of their downstream signaling pathways. NEN might be effective for treatment of patients with HCC.

Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases

Technologies such as genome sequencing, gene expression profiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health information have produced large amounts of data from various populations, cell types, and disorders (big data). However, these data must be integrated and analyzed if they are to produce models or concepts about physiological function or mechanisms of pathogenesis. Many of these data are available to the public, allowing researchers anywhere to search for markers of specific biological processes or therapeutic targets for specific diseases or patient types. We review recent advances in the fields of computational and systems biology and highlight opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology to complement traditional means of diagnostic and therapeutic discovery.

Repositioning antipsychotic chlorpromazine for treating colorectal cancer by inhibiting sirtuin 1

Investigating existing drugs for repositioning can enable overcoming bottlenecks in the drug development process. Here, we investigated the effect and molecular mechanism of the antipsychotic drug chlorpromazine (CPZ) and identified its potential for treating colorectal cancer (CRC). Human CRC cell lines harboring different p53 statuses were used to investigate the inhibitory mechanism of CPZ. CPZ effectively inhibited tumor growth and induced apoptosis in CRC cells in a p53-dependent manner. Activation of c-jun N-terminal kinase (JNK) was crucial for CPZ-induced p53 expression and the subsequent induction of tumor apoptosis. Induction of p53 acetylation at lysine382 was involved in CPZ-mediated tumor apoptosis, and this induction was attenuated by sirtuin 1 (SIRT1), a class III histone deacetylase. By contrast, knocking down SIRT1 sensitized tumor cells to CPZ treatment. Moreover, CPZ induced the degradation of SIRT1 protein participating downstream of JNK, and JNK suppression abrogated CPZ-mediated SIRT1 downregulation. Clinical analysis revealed a significant association between high SIRT1 expression and poor outcome in CRC patients. These data suggest that SIRT1 is an attractive therapeutic target for CRC and that CPZ is a potential repositioned drug for treating CRC.

Identification of 1,2,3,4,6-Penta-O-galloyl-β-d-glucopyranoside as a Glycine N-Methyltransferase Enhancer by High-Throughput Screening of Natural Products Inhibits Hepatocellular Carcinoma

Glycine N-methyltransferase (GNMT) expression is vastly downregulated in hepatocellular carcinomas (HCC). High rates of GNMT knockout mice developed HCC, while overexpression of GNMT prevented aflatoxin-induced carcinogenicity and inhibited liver cancer cell proliferation. Therefore, in this study, we aimed for the identification of a GNMT inducer for HCC therapy. We established a GNMT promoter-driven luciferase reporter assay as a drug screening platform. Screening of 324 pure compounds and 480 crude extracts from Chinese medicinal herbs resulted in the identification of Paeonia lactiflora Pall (PL) extract and the active component 1,2,3,4,6-penta-O-galloyl-β-d-glucopyranoside (PGG) as a GNMT inducer. Purified PL extract and PGG induced GNMT mRNA and protein expression in Huh7 human hepatoma cells and in xenograft tumors. PGG and PL extract had potent anti-HCC effects both in vitro and in vivo. Furthermore, PGG treatment induced apoptosis in Huh7 cells. Moreover, PGG treatment sensitized Huh7 cells to sorafenib treatment. Therefore, these results indicated that identifying a GNMT enhancer using the GNMT promoter-based assay might be a useful approach to find drugs for HCC. These data also suggested that PGG has therapeutic potential for the treatment of HCC.

Transcriptional response networks for elucidating mechanisms of action of multitargeted agents

Drug discovery is moving away from the single target-based approach towards harnessing the potential of polypharmacological agents that modulate the activity of multiple nodes in the complex networks of deregulations underlying disease phenotypes. Computational network pharmacology methods that use systems-level drug-response phenotypes, such as those originating from genome-wide transcriptomic profiles, have proved particularly effective for elucidating the mechanisms of action of multitargeted compounds. Here, we show, via the case study of the natural product pinosylvin, how the combination of two complementary network-based methods can provide novel, unexpected mechanistic insights. This case study also illustrates that elucidating the mechanism of action of multitargeted natural products through transcriptional response-based approaches is a challenging endeavor, often requiring multiple computational-experimental iterations.

Network pharmacology applications to map the unexplored target space and therapeutic potential of natural products

It is widely accepted that drug discovery often requires a systems-level polypharmacology approach to tackle problems such as lack of efficacy and emerging resistance of single-targeted compounds. Network pharmacology approaches are increasingly being developed and applied to find new therapeutic opportunities and to re-purpose approved drugs. However, these recent advances have been relatively slow to be translated into the field of natural products. Here, we argue that a network pharmacology approach would enable an effective mapping of the yet unexplored target space of natural products, hence providing a systematic means to extend the druggable space of proteins implicated in various complex diseases. We give an overview of the key network pharmacology concepts and recent experimental-computational approaches that have been successfully applied to natural product research, including unbiased elucidation of mechanisms of action as well as systematic prediction of effective therapeutic combinations. We focus specifically on anticancer applications that use in vivo and in vitro functional phenotypic measurements, such as genome-wide transcriptomic response profiles, which enable a global modelling of the multi-target activity at the level of the biological pathways and interaction networks. We also provide representative examples of other disease applications, databases and tools as well as existing and emerging resources, which may prove useful for future natural product research. Finally, we offer our personal view of the current limitations, prospective developments and open questions in this exciting field.

A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions

We present a novel strategy to identify drug-repositioning opportunities. The starting point of our method is the generation of a signature summarising the consensual transcriptional response of multiple human cell lines to a compound of interest (namely the seed compound). This signature can be derived from data in existing databases, such as the connectivity-map, and it is used at first instance to query a network interlinking all the connectivity-map compounds, based on the similarity of their transcriptional responses. This provides a drug neighbourhood, composed of compounds predicted to share some effects with the seed one. The original signature is then refined by systematically reducing its overlap with the transcriptional responses induced by drugs in this neighbourhood that are known to share a secondary effect with the seed compound. Finally, the drug network is queried again with the resulting refined signatures and the whole process is carried on for a number of iterations. Drugs in the final refined neighbourhood are then predicted to exert the principal mode of action of the seed compound. We illustrate our approach using paclitaxel (a microtubule stabilising agent) as seed compound. Our method predicts that glipizide and splitomicin perturb microtubule function in human cells: a result that could not be obtained through standard signature matching methods. In agreement, we find that glipizide and splitomicin reduce interphase microtubule growth rates and transiently increase the percentage of mitotic cells-consistent with our prediction. Finally, we validated the refined signatures of paclitaxel response by mining a large drug screening dataset, showing that human cancer cell lines whose basal transcriptional profile is anti-correlated to them are significantly more sensitive to paclitaxel and docetaxel.

Monocyte-macrophage differentiation of acute myeloid leukemia cell lines by small molecules identified through interrogation of the Connectivity Map database

The transcription factor C/EBPα is required for granulocytic differentiation of normal myeloid progenitors and is frequently inactivated in acute myeloid leukemia (AML) cells. Ectopic expression of C/EBPα in AML cells suppresses proliferation and induces differentiation suggesting that restoring C/EBPα expression/activity in AML cells could be therapeutically useful. Unfortunately, current approaches of gene or protein delivery in leukemic cells are unsatisfactory. However, "drug repurposing" is becoming a very attractive strategy to identify potential new uses for existing drugs. In this study, we assessed the biological effects of candidate C/EBPα-mimetics identified by interrogation of the Connectivity Map database. We found that amantadine, an antiviral and anti-Parkinson agent, induced a monocyte-macrophage-like differentiation of HL60, U937, Kasumi-1 myeloid leukemia cell lines, as indicated by morphology and differentiation antigen expression, when used in combination with suboptimal concentration of all trans retinoic acid (ATRA) or Vit D3. The effect of amantadine depends, in part, on increased activity of the vitamin D receptor (VDR), since it induced VDR expression and amantadine-dependent monocyte-macrophage differentiation of HL60 cells was blocked by expression of dominant-negative VDR. These results reveal a new function for amantadine and support the concept that screening of the Connectivity Map database can identify small molecules that mimic the effect of transcription factors required for myelo-monocytic differentiation.

The BCL2 Family: Key Mediators of the Apoptotic Response to Targeted Anticancer Therapeutics

The ability of cancer cells to suppress apoptosis is critical for carcinogenesis. The BCL2 family proteins comprise the sentinel network that regulates the mitochondrial or intrinsic apoptotic response. Recent advances in our understanding of apoptotic signaling pathways have enabled methods to identify cancers that are "primed" to undergo apoptosis, and have revealed potential biomarkers that may predict which cancers will undergo apoptosis in response to specific therapies. Complementary efforts have focused on developing novel drugs that directly target antiapoptotic BCL2 family proteins. In this review, we summarize the current knowledge of the role of BCL2 family members in cancer development and response to therapy, focusing on targeted therapeutics, recent progress in the development of apoptotic biomarkers, and therapeutic strategies designed to overcome deficiencies in apoptosis.

SIGNIFICANCE

Apoptosis, long known to be important for response to conventional cytotoxic chemotherapy, has more recently been shown to be essential for the efficacy of targeted therapies. Approaches that increase the likelihood of a cancer to undergo apoptosis following therapy may help improve targeted treatment strategies. Cancer Discov; 5(5); 475-87. ©2015 AACR.

Pathway and network approaches for identification of cancer signature markers from omics data

The advancement of high throughput omic technologies during the past few years has made it possible to perform many complex assays in a much shorter time than the traditional approaches. The rapid accumulation and wide availability of omic data generated by these technologies offer great opportunities to unravel disease mechanisms, but also presents significant challenges to extract knowledge from such massive data and to evaluate the findings. To address these challenges, a number of pathway and network based approaches have been introduced. This review article evaluates these methods and discusses their application in cancer biomarker discovery using hepatocellular carcinoma (HCC) as an example.

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.

Differential network biology reveals a positive correlation between a novel protein-protein interaction and cancer cells migration

This paper introduces a differential network biology for discovering tumor migration. We applied statistical methods to prioritize PPI candidates and an in situ proximity ligation assay to verify 67 endogenous PPIs among 21 interlinked pathways in two hepatocellular carcinoma (HCC) cells, Huh7 (minimally migratory cells) and Mahlavu (highly migratory cells). Differential network biology analysis was applied to determine the novel interaction, CRKL-FLT1, has a high centrality ranking, and the expression of this interaction is strongly correlated with the migratory ability of HCC and other cancer cell lines. Knockdown of CRKL and FLT1 in HCC cells leads to a decrease in cell migration. This study demonstrated that functional exploration of a disease network with differential network in interlinked pathways via PPIs can be used to discover tumor migration.

Analysis of protein-protein interactions in cross-talk pathways reveals CRKL protein as a novel prognostic marker in hepatocellular carcinoma

Deciphering the network of signaling pathways in cancer via protein-protein interactions (PPIs) at the cellular level is a promising approach but remains incomplete. We used an in situ proximity ligation assay to identify and quantify 67 endogenous PPIs among 21 interlinked pathways in two hepatocellular carcinoma (HCC) cells, Huh7 (minimally migratory cells) and Mahlavu (highly migratory cells). We then applied a differential network biology analysis and determined that the novel interaction, CRKL-FLT1, has a high centrality ranking, and the expression of this interaction is strongly correlated with the migratory ability of HCC and other cancer cell lines. Knockdown of CRKL and FLT1 in HCC cells leads to a decrease in cell migration via ERK signaling and the epithelial-mesenchymal transition process. Our immunohistochemical analysis shows high expression levels of the CRKL and CRKL-FLT1 pair that strongly correlate with reduced disease-free and overall survival in HCC patient samples, and a multivariate analysis further established CRKL and the CRKL-FLT1 as novel prognosis markers. This study demonstrated that functional exploration of a disease network with interlinked pathways via PPIs can be used to discover novel biomarkers.

In-silico drug screening and potential target identification for hepatocellular carcinoma using Support Vector Machines based on drug screening result

Hepatocellular carcinoma (HCC) is a severe liver malignancy with few drug treatment options. In finding an effective treatment for HCC, screening drugs that are already FDA-approved will fast track the clinical trial and drug approval process. Connectivity Map (CMap), a large repository of chemical-induced gene expression profiles, provides the opportunity to analyze drug properties on the basis of gene expression. Support Vector Machines (SVM) were utilized to classify the effectiveness of drugs against HCC using gene expression profiles in CMap. The results of this classification will help us (1) identify genes that are chemically sensitive, and (2) predict the effectiveness of remaining chemicals in CMap in the treatment of HCC and provide a prioritized list of possible HCC drugs for biological verification. Four HCC cell lines were treated with 146 distinct chemicals, and cell viability was examined. SVM successfully classified the effectiveness of the chemicals with an average Area Under ROC Curve (AUROC) of 0.9. Using reported HCC patient samples, we identified chemically sensitive genes that may be possible HCC therapeutic targets, including MT1E, MYC, and GADD45B. Using SVM, several known HCC inhibitors, such as geldanamycin, alvespimycin (HSP90 inhibitors), and doxorubicin (chemotherapy drug), were predicted. Seven out of the 23 predicted drugs were cardiac glycosides, suggesting a link between this drug category and HCC inhibition. The study demonstrates a strategy of in silico drug screening with SVM using a large repository of microarrays based on initial in vitro drug screening. Verifying these results biologically would help develop a more accurate chemical sensitivity model.

Transcriptional data: a new gateway to drug repositioning?

Recent advances in computational biology suggest that any perturbation to the transcriptional programme of the cell can be summarised by a proper ‘signature’: a set of genes combined with a pattern of expression. Therefore, it should be possible to generate proxies of clinicopathological phenotypes and drug effects through signatures acquired via DNA microarray technology.

Gene expression signatures have recently been assembled and compared through genome-wide metrics, unveiling unexpected drug–disease and drug–drug ‘connections’ by matching corresponding signatures. Consequently, novel applications for existing drugs have been predicted and experimentally validated.

Here, we describe related methods, case studies and resources while discussing challenges and benefits of exploiting existing repositories of microarray data that could serve as a search space for systematic drug repositioning.

Gene expression-based chemical genomics identifies heat-shock protein 90 inhibitors as potential therapeutic drugs in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma (CCA) is an aggressive tumor with a poor prognosis. There is no standard therapy for CCA, and novel drugs for treating refractory CCA need to be identified.

METHODS

The authors hypothesized that, if a drug could reverse the gene expression signature of CCA, then it may inhibit the carcinogenesis of CCA and, hence, would be a potential therapeutic agent. Thus, the gene expression signatures from patients with CCA were queried using the bioinformatic method Connectivity Map, resulting in the enrichment of heat-shock protein 90 (HSP90) inhibitors with therapeutic potentials.

RESULTS

Two HSP90 inhibitors, 17-AAG (tanespimycin) and the synthetic diarylisoxazole amide resorcinol NVP-AUY922, demonstrated potent antiproliferative activity in in vitro studies. In a thioacetamide-induced animal model, NVP-AUY922 also had antitumor activity and resulted in objective tumor regression. In addition, NVP-AUY922 reduced the expression of client oncoproteins involved in CCA oncogenesis and inhibited downstream proteins of both the phosphatidylinositol 3-kinase catalytic subunit α/v-akt murine thymoma viral oncogene homolog 1 protein kinase (PIK3/AKT) pathway and the v-Ki-ras2 Kirsten rat sarcoma viral oncogene/mitogen-activated protein kinase (KRAS/MAPK) pathway.

CONCLUSIONS

Preclinical data from the current study suggest that NVP-AUY922 may be an effective treatment option for patients with CCA.