BMX, a specific HDAC8 inhibitor, with TMZ for advanced CRC therapy: a novel synergic effect to elicit p53-, ß-catenin- and MGMT-dependent apoptotic cell death.

BACKGROUND: Despite advances in treatment, patients with refractory colorectal cancer (CRC) still have poor long-term survival, so there is a need for more effective therapeutic options. METHODS: To evaluate the HDAC8 inhibition efficacy as a CRC treatment, we examined the effects of various HDAC8 inhibitors (HDAC8i), including BMX (NBM-T-L-BMX-OS01) in combination with temozolomide (TMZ) or other standard CRC drugs on p53 mutated HT29 cells, as well as wild-type p53 HCT116 and RKO cells. RESULTS: We showed that HDAC8i with TMZ cotreatment resulted in HT29 arrest in the S and G2/M phase, whereas HCT116 and RKO arrest in the G0/G1 phase was accompanied by high sub-G1. Subsequently, this combination approach upregulated p53-mediated MGMT inhibition, leading to apoptosis. Furthermore, we observed the cotreatment also enabled triggering of cell senescence and decreased expression of stem cell biomarkers. Mechanistically, we found down-expression levels of ß-catenin, cyclin D1 and c-Myc via GSK3ß/ß-catenin signaling. Intriguingly, autophagy also contributes to cell death under the opposite status of ß-catenin/p62 axis, suggesting that there exists a negative feedback regulation between Wnt/ß-catenin and autophagy. Consistently, the Gene Set Enrichment Analysis (GSEA) indicated both apoptotic and autophagy biomarkers in HT29 and RKO were upregulated after treating with BMX. CONCLUSIONS: BMX may act as a HDAC8 eraser and in combination with reframed-TMZ generates a remarkable synergic effect, providing a novel therapeutic target for various CRCs. Video Abstract.

Synthesis, biological evaluation, and structure-activity relationships of new tubulin polymerization inhibitors based on 5-amino-1,2,4-triazole scaffold.

Based on our previous research, thirty new 5-amino-1H-1,2,4-triazoles possessing 3,4,5-trimethoxyphenyl moiety were synthesized, and evaluated for antiproliferative activities. Among them, compounds IIa, IIIh, and IIIm demonstrated significant antiproliferative activities against a panel of tumor cell lines, and the promising compound IIIm dose-dependently caused G2/M phase arrest in HeLa cells. Furthermore, analogue IIa exhibited the most potent tubulinpolymerization inhibitory activity with an IC50 value of 9.4 µM, and molecular modeling studies revealed that IIa formed stable interactions in the colchicine-binding site of tubulin, suggesting that 5-amino-1H-1,2,4-triazole scaffold has potential for further investigation to develop novel tubulin polymerization inhibitors with anticancer activity.

Flux balance analysis predicts Warburg-like effects of mouse hepatocyte deficient in miR-122a.

The liver is a vital organ involving in various major metabolic functions in human body. MicroRNA-122 (miR-122) plays an important role in the regulation of liver metabolism, but its intrinsic physiological functions require further clarification. This study integrated the genome-scale metabolic model of hepatocytes and mouse experimental data with germline deletion of Mir122a (Mir122a-/-) to infer Warburg-like effects. Elevated expression of MiR-122a target genes in Mir122a-/-mice, especially those encoding for metabolic enzymes, was applied to analyze the flux distributions of the genome-scale metabolic model in normal and deficient states. By definition of the similarity ratio, we compared the flux fold change of the genome-scale metabolic model computational results and metabolomic profiling data measured through a liquid-chromatography with mass spectrometer, respectively, for hepatocytes of 2-month-old mice in normal and deficient states. The Ddc gene demonstrated the highest similarity ratio of 95% to the biological hypothesis of the Warburg effect, and similarity of 75% to the experimental observation. We also used 2, 6, and 11 months of mir-122 knockout mice liver cell to examined the expression pattern of DDC in the knockout mice livers to show upregulated profiles of DDC from the data. Furthermore, through a bioinformatics (LINCS program) prediction, BTK inhibitors and withaferin A could downregulate DDC expression, suggesting that such drugs could potentially alter the early events of metabolomics of liver cancer cells.

Using an in situ proximity ligation assay to systematically profile endogenous protein-protein interactions in a pathway network.

Signal transduction pathways in the cell require protein-protein interactions (PPIs) to respond to environmental cues. Diverse experimental techniques for detecting PPIs have been developed. However, the huge amount of PPI data accumulated from various sources poses a challenge with respect to data reliability. Herein, we collected ∼ 700 primary antibodies and employed a highly sensitive and specific technique, an in situ proximity ligation assay, to investigate 1204 endogenous PPIs in HeLa cells, and 557 PPIs of them tested positive. To overview the tested PPIs, we mapped them into 13 PPI public databases, which showed 72% of them were annotated in the Human Protein Reference Database (HPRD) and 8 PPIs were new PPIs not in the PubMed database. Moreover, TP53, CTNNB1, AKT1, CDKN1A, and CASP3 were the top 5 proteins prioritized by topology analyses of the 557 PPI network. Integration of the PPI-pathway interaction revealed that 90 PPIs were cross-talk PPIs linking 17 signaling pathways based on Reactome annotations. The top 2 connected cross-talk PPIs are MAPK3-DAPK1 and FAS-PRKCA interactions, which link 9 and 8 pathways, respectively. In summary, we established an open resource for biological modules and signaling pathway profiles, providing a foundation for comprehensive analysis of the human interactome.

A Self-Delivery Nanodrug Simultaneously Inhibits COX-2/PGE2 Mediated Inflammation and Downregulates PD-L1 to Boost Photoimmunotherapy.

Phototherapy promotes anti-tumor immunity by inducing immunogenic cell death (ICD), However, the accompanying inflammatory responses also trigger immunosuppression, attenuating the efficacy of photo-immunotherapy. Herein, they co-assembled a cell-membrane targeting chimeric peptide C16-Cypate-RRKK-PEG8-COOH (CCP) and anti-inflammatory diclofenac (DA) to develop a nanodrug (CCP@DA) that both enhances the immune effect of phototherapy and weakens the inflammation-mediated immunosuppression. CCP@DA achieves cell membrane-targeting photodynamic and photothermal synergistic therapies to damage programmed death ligand 1 (PD-L1) and induce a strong ICD to activate anti-tumor response. Simultaneously, the released DA inhibits the cycoperoxidase-2 (COX-2)/prostaglandin E2 (PGE2) pathway in tumor cells to inhibit pro-tumor inflammation and further down-regulate PD-L1 expression to relieve the immunosuppressive microenvironment. CCP@DA significantly inhibited tumor growth and inflammation both in vitro and in vivo, while maintaining a potent anti-tumor immune response. Additionally, it exhibits excellent anti-metastatic capabilities and prolongs mouse survival time with a single dose and low levels of near-infrared (NIR) light exposure. This work provides a valuable strategy to control the therapy-induced inflammation for high-efficiency photoimmunotherapy.

Nanodrugs mediate TAMs-related arginine metabolism interference to boost photodynamic immunotherapy.

As a potential treatment strategy for low immunogenic triple negative breast cancer (TNBC), photodynamic therapy (PDT) induced antitumor immunotherapy is greatly limited by the immunosuppressive tumor microenvironment (ITM), especially the M2 phenotype tumor-associated macrophages (TAMs). The balance of arginine metabolism plays an important role in TAMs polarization. Herein, a multifunctional nanoplatform (defined as HN-HFPA) was employed to burst the anti-tumor immunity of TNBC post PDT by reeducating TAMs through interfering the TAMs-associated arginine metabolism. The L-arginine (L-Arg) was loaded in the hollow cavity of HN-HFPA, which could not only generate nitric oxide (NO) for tumor therapy, but also serve as a substrate of arginine metabolism pathway. As an inhibitor of arginases-1 (Arg-1) of M2 TAMs, L-norvaline (L-Nor) was modified to the hyaluronic acid (HA), and coated in the surface of HFPA. After degradation of HA by hyaluronidase in tumor tissue and GSH-mediated disintegration, HN-HFPA depleted intracellular GSH, produced remarkable reactive oxygen species (ROS) under light irradiation and released L-Arg to generate NO, which induced tumor immunogenic cell death (ICD). Real-time ultrasound imaging of tumor was realized taking advantage of the gas feature of NO. The L-Nor suppressed the Arg-1 overexpressed in M2, which skewed the balance of arginine metabolism and reversed the ITM with increased ratios of M1 and CD8+ T cells, finally resulted in amplified antitumor immune response and apparent tumor metastasis inhibition. This study remodeled ITM to strengthen immune response post PDT, which provided a promising treatment strategy for TNBC.

Trifluoperazine, an antipsychotic agent, inhibits cancer stem cell growth and overcomes drug resistance of lung cancer.

RATIONALE: Cancer stem cell (CSC) theory has drawn much attention, with evidence supporting the contribution of stem cells to tumor initiation, relapse, and therapy resistance. OBJECTIVES: To screen drugs that target CSCs to improve the current treatment outcome and overcome drug resistance in patients with lung cancer. METHODS: We used publicly available embryonic stem cell and CSC-associated gene signatures to query the Connectivity Map for potential drugs that can, at least in part, reverse the gene expression profile of CSCs. High scores were noted for several phenothiazine-like antipsychotic drugs, including trifluoperazine. We then treated lung CSCs with different EGFR mutation status with trifluoperazine to examine its anti-CSC properties. Lung CSCs resistant to epidermal growth factor receptor-tyrosine kinase inhibitor or cisplatin were treated with trifluoperazine plus gefitinib or trifluoperazine plus cisplatin. Animal models were used for in vivo validation of the anti-CSC effect and synergistic effect of trifluoperazine with gefitinib. MEASUREMENTS AND MAIN RESULTS: We demonstrated that trifluoperazine inhibited CSC tumor spheroid formation and down-regulated the expression of CSC markers (CD44/CD133). Trifluoperazine inhibited Wnt/ß-catenin signaling in gefitinib-resistant lung cancer spheroids. The combination of trifluoperazine with either gefitinib or cisplatin overcame drug resistance in lung CSCs. Trifluoperazine inhibited the tumor growth and enhanced the inhibitory activity of gefitinib in lung cancer metastatic and orthotopic CSC animal models. CONCLUSIONS: Using in silico drug screening by Connectivity Map followed by empirical validations, we repurposed an existing phenothiazine-like antipsychotic drug, trifluoperazine, as a potential anti-CSC agent that could overcome epidermal growth factor receptor-tyrosine kinase inhibitor and chemotherapy resistance.

Identifying essential genes in genome-scale metabolic models of consensus molecular subtypes of colorectal cancer.

Identifying essential targets in the genome-scale metabolic networks of cancer cells is a time-consuming process. The present study proposed a fuzzy hierarchical optimization framework for identifying essential genes, metabolites and reactions. On the basis of four objectives, the present study developed a framework for identifying essential targets that lead to cancer cell death and evaluating metabolic flux perturbations in normal cells that have been caused by cancer treatment. Through fuzzy set theory, a multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem. We applied nested hybrid differential evolution to solve the trilevel MDM problem to identify essential targets in genome-scale metabolic models for five consensus molecular subtypes (CMSs) of colorectal cancer. We used various media to identify essential targets for each CMS and discovered that most targets affected all five CMSs and that some genes were CMS-specific. We obtained experimental data on the lethality of cancer cell lines from the DepMap database to validate the identified essential genes. The results reveal that most of the identified essential genes were compatible with the colorectal cancer cell lines obtained from DepMap and that these genes, with the exception of EBP, LSS, and SLC7A6, could generate a high level of cell death when knocked out. The identified essential genes were mostly involved in cholesterol biosynthesis, nucleotide metabolisms, and the glycerophospholipid biosynthetic pathway. The genes involved in the cholesterol biosynthetic pathway were also revealed to be determinable, if a cholesterol uptake reaction was not induced when the cells were in the culture medium. However, the genes involved in the cholesterol biosynthetic pathway became non-essential if such a reaction was induced. Furthermore, the essential gene CRLS1 was revealed as a medium-independent target for all CMSs.

Repurposing Astragalus Polysaccharide PG2 for Inhibiting ACE2 and SARS-CoV-2 Spike Syncytial Formation and Anti-Inflammatory Effects.

The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious threat to global public health. In an effort to develop novel anti-coronavirus therapeutics and achieve prophylactics, we used gene set enrichment analysis (GSEA) for drug screening and identified that Astragalus polysaccharide (PG2), a mixture of polysaccharides purified from Astragalus membranaceus, could effectively reverse COVID-19 signature genes. Further biological assays revealed that PG2 could prevent the fusion of BHK21-expressing wild-type (WT) viral spike (S) protein and Calu-3-expressing ACE2. Additionally, it specifically prevents the binding of recombinant viral S of WT, alpha, and beta strains to ACE2 receptor in our non-cell-based system. In addition, PG2 enhances let-7a, miR-146a, and miR-148b expression levels in the lung epithelial cells. These findings speculate that PG2 has the potential to reduce viral replication in lung and cytokine storm via these PG2-induced miRNAs. Furthermore, macrophage activation is one of the primary issues leading to the complicated condition of COVID-19 patients, and our results revealed that PG2 could regulate the activation of macrophages by promoting the polarization of THP-1-derived macrophages into an anti-inflammatory phenotype. In this study, PG2 stimulated M2 macrophage activation and increased the expression levels of anti-inflammatory cytokines IL-10 and IL-1RN. Additionally, PG2 was recently used to treat patients with severe COVID-19 symptoms by reducing the neutrophil-to-lymphocyte ratio (NLR). Therefore, our data suggest that PG2, a repurposed drug, possesses the potential to prevent WT SARS-CoV-2 S-mediated syncytia formation with the host cells; it also inhibits the binding of S proteins of WT, alpha, and beta strains to the recombinant ACE2 and halts severe COVID-19 development by regulating the polarization of macrophages to M2 cells.

Overexpression of T-LAK cell-originated protein kinase predicts poor prognosis in patients with stage I lung adenocarcinoma.

Tumor recurrence is the most common cause of disease failure after surgical resection in early-stage lung adenocarcinoma. Identification of clinically relevant prognostic markers could help to predict patients with high risk of disease recurrence. A meta-analysis of available lung adenocarcinoma microarray datasets revealed that T-LAK cell-originated protein kinase (TOPK), a serine/threonine protein kinase, is overexpressed in lung cancer. Using stable cell lines with overexpression or knockdown of TOPK, we have shown that TOPK can promote cell migration, invasion, and clonogenic activity in lung cancer cells, suggesting its crucial role in lung tumorigenesis. To evaluate the prognostic value of TOPK expression in resected stage I lung adenocarcinoma, a retrospective analysis of 203 patients diagnosed with pathological stage I lung adenocarcinoma was carried out to examine the expression of TOPK by immunohistochemistry (IHC). The prognostic significance of TOPK overexpression was examined. Overexpression of TOPK (IHC score >3) was detected in 67.0% of patients, and these patients were more frequently characterized with disease recurrence and angiolymphatic invasion. Using multivariate analysis, patient age (>65 years old; P = 0.002) and TOPK overexpression (IHC score >3; P < 0.001) significantly predicted a shortened overall survival. Moreover, TOPK overexpression (IHC score >3; P = 0.005) also significantly predicted a reduced time to recurrence in the patients. Our results indicate that overexpression of TOPK could predetermine the metastatic capability of tumors and could serve as a significant prognostic predictor of shortened overall survival and time to recurrence.

Autophagy-inhibiting biomimetic nanodrugs enhance photothermal therapy and boost antitumor immunity.

The instinctive protective stress responses of tumor cells hamper low-temperature photothermal therapy (LTPTT), resulting in tumor recurrence and metastasis. The rapid blood clearance and low-efficiency tumor enrichment of nanomedicines also decrease the efficacy of LTPTT. In this study, we fabricated coassembled photothermal agents (indocyanine green, ICG) and autophagy inhibitors (chloroquine, CQ) and red blood cell and cancer cell hybrid membrane (RCm)-camouflaged ICGCQ@RCm nanoparticles (ICGCQ@RCm NPs) to enhance tumor LTPTT. The ICGCQ@RCm NPs exhibited prolonged blood drug circulation and markedly enhanced drug accumulation in tumor tissues. The ICGCQ@RCm NPs reduced the thermal tolerance of tumor cells to sensitize ICG-mediated LTPTT by inhibiting protective autophagy. The ICGCQ@RCm NPs exerted strong immunogenic cell death (ICD) after efficient LTPTT to activate antitumor immunity. In addition, ICGCQ@RCms optimized the therapeutic efficacy by imaging-guided LTPTT, taking advantage of the near-infrared (NIR) fluorescence of ICG. Consequently, the ICGCQ@RCm NPs effectively inhibited tumors under mild LTPTT, significantly suppressed tumor metastasis and prolonged the survival time of tumor-bearing mice. Furthermore, the ICGCQ@RCm NPs showed high biosafety in vitro and in vivo. The ICGCQ@RCm NPs demonstrated tumor-targeting and imaging-guided autophagy inhibition-sensitized LTPTT using two Food and Drug Administration (FDA)-approved drugs, which have great potential for clinical application.

Virofree, an Herbal Medicine-Based Formula, Interrupts the Viral Infection of Delta and Omicron Variants of SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) remains a threat with the emergence of new variants, especially Delta and Omicron, without specific effective therapeutic drugs. The infection causes dysregulation of the immune system with a cytokine storm that eventually leads to fatal acute respiratory distress syndrome (ARDS) and further irreversible pulmonary fibrosis. Therefore, the promising way to inhibit infection is to disrupt the binding and fusion between the viral spike and the host ACE2 receptor. A transcriptome-based drug screening platform has been developed for COVID-19 to explore the possibility and potential of the long-established drugs or herbal medicines to reverse the unique genetic signature of COVID-19. In silico analysis showed that Virofree, an herbal medicine, reversed the genetic signature of COVID-19 and ARDS. Biochemical validations showed that Virofree could disrupt the binding of wild-type and Delta-variant spike proteins to ACE2 and its syncytial formation via cell-based pseudo-typed viral assays, as well as suppress binding between several variant recombinant spikes to ACE2, especially Delta and Omicron. Additionally, Virofree elevated miR-148b-5p levels, inhibited the main protease of SARS-CoV-2 (Mpro), and reduced LPS-induced TNF-α release. Virofree also prevented cellular iron accumulation leading to ferroptosis which occurs in SARS-CoV-2 patients. Furthermore, Virofree was able to reduce pulmonary fibrosis-related protein expression levels in vitro. In conclusion, Virofree was repurposed as a potential herbal medicine to combat COVID-19. This study highlights the inhibitory effect of Virofree on the entry of Delta and Omicron variants of SARS-CoV-2, which have not had any effective treatments during the emergence of the new variants spreading.

Aurora-A promotes gefitinib resistance via a NF-κB signaling pathway in p53 knockdown lung cancer cells.

Mutations of the p53 tumor suppressor gene are the most common mutations found in human tumors. There is increasing evidence that suggests that p53 status is a determinant of chemosensitivity of tumor cells. We have previously demonstrated that p53 is a crucial regulator in mediating gefitinib-induced cell death, which upregulates apoptosis-related molecules. However, the mechanism of p53 involvement in cellular resistance to gefitinib remains unclear. In this study, we found that human non-small cell lung cancer cells, A549, with wild-type p53 exhibited a low level of Aurora-A expression and were sensitive to treatment with gefitinib. p53-knockdown A549 cells exhibited a high level of Aurora-A expression and were resistant to gefitinib-mediated apoptosis induction. In addition, the silencing of Aurora-A expression using an Aurora-A specific siRNA in p53-knockdown cells sensitized the A549 cancer cells to gefitinib-mediated apoptosis, suggesting a role for Aurora-A in gefitinib resistance. The activation of Aurora-A was accompanied by destabilization of IκBα and an increase in NF-κB transcriptional activity and was correlated with gefitinib resistance. Conversely, knockdown of Aurora-A with a siRNA stabilized IκB protein suppressed NF-κB activation and reduced gefitinib resistance. Additionally, ectopic expression of an active form of Aurora-A increased the degradation of IκB, the activation of NF-κB and the enhancement of gefitinib resistance in comparison with parental cells. These results suggest that Aurora-A is potentially involved in promoting gefitinib resistance via the activation of NF-κB pathway. Our findings also suggest that p53 not only stimulates apoptosis-related event but also inhibits the drug-resistance ability of Aurora-A, and consequently promotes the gefitinib-induced cellular apoptotic process.

Computer-Aided Design for Identifying Anticancer Targets in Genome-Scale Metabolic Models of Colon Cancer.

The efficient discovery of anticancer targets with minimal side effects is a major challenge in drug discovery and development. Early prediction of side effects is key for reducing development costs, increasing drug efficacy, and increasing drug safety. This study developed a fuzzy optimization framework for Identifying AntiCancer Targets (IACT) using constraint-based models. Four objectives were established to evaluate the mortality of treated cancer cells and to minimize side effects causing toxicity-induced tumorigenesis on normal cells and smaller metabolic perturbations. Fuzzy set theory was applied to evaluate potential side effects and investigate the magnitude of metabolic deviations in perturbed cells compared with their normal counterparts. The framework was applied to identify not only gene regulator targets but also metabolite- and reaction-centric targets. A nested hybrid differential evolution algorithm with a hierarchical fitness function was applied to solve multilevel IACT problems. The results show that the combination of a carbon metabolism target and any one-target gene that participates in the sphingolipid, glycerophospholipid, nucleotide, cholesterol biosynthesis, or pentose phosphate pathways is more effective for treatment than one-target inhibition is. A clinical antimetabolite drug 5-fluorouracil (5-FU) has been used to inhibit synthesis of deoxythymidine-5'-triphosphate for treatment of colorectal cancer. The computational results reveal that a two-target combination of 5-FU and a folate supplement can improve cell viability, reduce metabolic deviation, and reduce side effects of normal cells.

Oncogene inference optimization using constraint-based modelling incorporated with protein expression in normal and tumour tissues.

Cancer cells are known to exhibit unusual metabolic activity, and yet few metabolic cancer driver genes are known. Genetic alterations and epigenetic modifications of cancer cells result in the abnormal regulation of cellular metabolic pathways that are different when compared with normal cells. Such a metabolic reprogramming can be simulated using constraint-based modelling approaches towards predicting oncogenes. We introduced the tri-level optimization problem to use the metabolic reprogramming towards inferring oncogenes. The algorithm incorporated Recon 2.2 network with the Human Protein Atlas to reconstruct genome-scale metabolic network models of the tissue-specific cells at normal and cancer states, respectively. Such reconstructed models were applied to build the templates of the metabolic reprogramming between normal and cancer cell metabolism. The inference optimization problem was formulated to use the templates as a measure towards predicting oncogenes. The nested hybrid differential evolution algorithm was applied to solve the problem to overcome solving difficulty for transferring the inner optimization problem into the single one. Head and neck squamous cells were applied as a case study to evaluate the algorithm. We detected 13 of the top-ranked one-hit dysregulations and 17 of the top-ranked two-hit oncogenes with high similarity ratios to the templates. According to the literature survey, most inferred oncogenes are consistent with the observation in various tissues. Furthermore, the inferred oncogenes were highly connected with the TP53/AKT/IGF/MTOR signalling pathway through PTEN, which is one of the most frequently detected tumour suppressor genes in human cancer.

Cliques in mitotic spindle network bring kinetochore-associated complexes to form dependence pathway.

The mitotic spindle is an essential molecular machine for chromosome segregation during mitosis. Achieving a better understanding of its organization at the topological level remains a daunting task. To determine the functional connections among 137 mitotic spindle proteins, a protein-protein interaction network among queries was constructed. Many hub proteins, which connect more than one query and serve as highly plausible candidates for expanding the mitotic spindle proteome, are ranked by conventional degree centrality and a new subnetwork specificity score. Evaluation of the ranking results by literature reviews and empirical verification of SEPT6, a novel top-ranked hub, suggests that the subnetwork specificity score could enrich for putative spindle-related proteins. Topological analysis of this expanded network shows the presence of 30 3-cliques and six 4-cliques (fully connected subgraphs) that, respectively, reside in eight kinetochore-associated complexes, of which seven are evolution conserved. Notably, these complexes strikingly form dependence pathways for the assembly of the kinetochore complex. These analyses indicate the feasibility of using network topology, i.e. cliques, to uncover novel pathways to accelerate our understanding of potential biological processes.

POINeT: protein interactome with sub-network analysis and hub prioritization.

BACKGROUND: Protein-protein interactions (PPIs) are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools. RESULTS: We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3) to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles. CONCLUSION: The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to selected tissues can be revealed. The straightforward interface of POINeT makes PPI search and analysis just a few clicks away. The modular design permits further functional enhancement without hampering the simplicity. POINeT is available at (http://poinet.bioinformatics.tw/).

From midbody protein-protein interaction network construction to novel regulators in cytokinesis.

Midbody, a transient organelle-like structure, is known as central for abscission and is indispensable for termination of cytokinesis. Here, we used the midbody proteome inventories to construct the potential midbody protein-protein interaction (PPI) network. To delineate novel regulators participating in cytokinesis, the z-score, a standard statistic score, rather than hub degree was implemented to prioritize the novel hubs. Of these hubs, KIAA0133, SEPT1, KIAA1377, and CRMP-1 were localized to the midbody, whereas HTR3A and ICAM2 were associated with the cleavage furrow as examined by immunofluorescence. Knockdown of SEPT1 and KIAA1377 resulted in increasing numbers of cytokinesis defect cells, suggesting these newly identified hubs play critical roles in cytokinesis progression. Moreover, ectopic expression of CRMP-1 mutant in which Aurora-A phosphorylation sites have been replaced with Ala results in a cytokinesis defect. This subproteome network construction not only sheds light on the intimate interactions of the midbody proteomes, but also prioritizes novel hubs or protein complexes that may govern the process of cytokinesis.

PhosphoPOINT: a comprehensive human kinase interactome and phospho-protein database.

MOTIVATION: To fully understand how a protein kinase regulates biological processes, it is imperative to first identify its substrate(s) and interacting protein(s). However, of the 518 known human serine/threonine/tyrosine kinases, 35% of these have known substrates, while 14% of the kinases have identified substrate recognition motifs. In contrast, 85% of the kinases have protein-protein interaction (PPI) datasets, raising the possibility that we might reveal potential kinase-substrate pairs from these PPIs. RESULTS: PhosphoPOINT, a comprehensive human kinase interactome and phospho-protein database, is a collection of 4195 phospho-proteins with a total of 15 738 phosphorylation sites. PhosphoPOINT annotates the interactions among kinases, with their down-stream substrates and with interacting (phospho)-proteins to modulate the kinase-substrate pairs. PhosphoPOINT implements various gene expression profiles and Gene Ontology cellular component information to evaluate each kinase and their interacting (phospho)-proteins/substrates. Integration of cSNPs that cause amino acids change with the proteins with the phosphoprotein dataset reveals that 64 phosphorylation sites result in a disease phenotypes when changed; the linked phenotypes include schizophrenia and hypertension. PhosphoPOINT also provides a search function for all phospho-peptides using about 300 known kinase/phosphatase substrate/binding motifs. Altogether, PhosphoPOINT provides robust annotation for kinases, their downstream substrates and their interaction (phospho)-proteins and this should accelerate the functional characterization of kinomemediated signaling. AVAILABILITY: PhosphoPOINT can be freely accessed in http://kinase. bioinformatics.tw/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Combination of microarray profiling and protein-protein interaction databases delineates the minimal discriminators as a metastasis network for esophageal squamous cell carcinoma.

Microarray profiling of 15 adjacent normal/tumor-matched esophageal squamous cell carcinoma (ESCC) specimens identified 40 up-regulated and 95 down-regulated genes. Verification of the microarray measurement by quantitative real-time reverse transcription PCR in the same set of samples as well as an additional 15 normal/tumor-matched samples revealed >95% consistency. These signatures can also be used to classify a recently reported ESCC microarray dataset. Moreover, these molecular signatures were used as templates to elucidate their corresponding protein-protein interaction (PPI) networks using the PPI databases, POINT and POINeT. As a result, 18 genes, of which six were not disclosed in the initial expression profile analysis, were found to be able to serve as the minimal discriminators for distinguishing ESCC tumors from normal specimens. Of these discriminators, ten (BGN, COL1A1, COL1A2, MMP9, CD44, FN1, TGFBI, PXN, SPARC and VWF) were associated with tumor metastasis and formed a highly interactive network with the first four molecules as 'hubs'. Our study not only reveals how novel insights can be obtained from gene expression profiling, but also highlights a group of highly interacting genes associated with metastasis in ESCC.