Bioinformatic analyses identifies novel protein-coding pharmacogenomic markers associated with paclitaxel sensitivity in NCI60 cancer cell lines

New phenothiazine conjugates as apoptosis inducing agents: Design, synthesis, In-vitro anti-cancer screening and 131I-radiolabeling for in-vivo evaluation

Phenothiazines (PTZs) are a group of compounds characterized by the presence of the 10H-dibenzo-[b,e]-1,4-thiazine system. PTZs used in clinics as antipsychotic drugs with other diverse biological activities. The current aim of the study is to investigate and understand the effect of potent PTZs compounds using a group of In-vitro and In-vivo assays. A total of seventeen novel phenothiazine derivatives have been designed, synthesized, and evaluated primarily in-vitro for their ability to inhibit proliferation activity against NCI-60 cancer cell lines, including several multi-drug resistant (MDR) tumor cell lines. Almost all compounds were active and displayed promising cellular activities with GI50 values in the sub-micromolar range. Four of the most promising derivatives (4b, 4h, 4g and 6e) have been further tested against two selected sensitive cancer cell lines (colon cancer; HCT-116 and breast cancer; MDA-MB231). The apoptosis assay showed that all the selected compounds were able to induce early apoptosis and compound 6e was able to induce additional cellular necrosis. Cell cycle assay showed all selected compounds were able to induce cell cycle arrest at sub-molecular phase of G0-G1 with compound 6e induced cell cycle arrest at G2M in HCT-116 cells. Accordingly, the apoptotic effect of the selected compounds was extensively investigated on genetic level and Casp-3, Casp-9 and Bax gene were up-regulated with down-regulation of Bcl-2 gene suggesting the activation of both intrinsic and extrinsic pathways. In-vivo evaluation of the antitumor activity of compound 4b in solid tumor bearing mice showed promising therapeutic effect with manifestation of dose and time dependent toxic effects at higher doses. For better evaluation of the degree of localization of 4b, its 131I-congener (131I-4b) was injected intravenously in Ehrlich solid tumor bearing mice that showed good localization at tumor site with rapid distribution and clearance from the blood. In-silico study suggested NADPH oxidases (NOXs) as potential molecular target. The compounds introduced in the current study work provided a cutting-edge phenothiazine hybrid scaffold with promising anti-proliferation action that may suggest their anti-cancer activity.

Drug Repurposing in Cancer Therapy: Influence of Patient’s Genetic Background in Breast Cancer Treatment

Cancer is among the leading causes of death worldwide and it is estimated that in 2040 more than 29 million people will be diagnosed with some type of cancer. The most prevalent type of cancer in women, worldwide, is breast cancer, a type of cancer associated with a huge death rate. This high mortality is mainly a consequence of the development of drug resistance, which is one of the major challenges to overcome in breast cancer treatment. As a result, research has been focused on finding novel therapeutical weapons, specifically ones that allow for a personalized treatment, based on patients’ characteristics. Although the scientific community has been concerned about guaranteeing the quality of life of cancer patients, researchers are also aware of the increasing costs related to cancer treatment, and efforts have been made to find alternatives to the development of new drugs. The development of new drugs presents some disadvantages as it is a multistep process that is time- and money-consuming, involving clinical trials that commonly fail in the initial phases. A strategy to overcome these disadvantages is drug repurposing. In this review, we focused on describing potential repurposed drugs in the therapy of breast cancer, considering their pharmacogenomic profile, to assess the relationship between patients’ genetic variations and their response to a certain therapy. This review supports the need for the development of further fundamental studies in this area, in order to investigate and expand the knowledge of the currently used and novel potential drugs to treat breast cancer. Future clinical trials should focus on developing strategies to group cancer patients according to their clinical and biological similarities and to discover new potential targets, to enable cancer therapy to be more effective and personalized.

Absolute Neutrophil Count after the First Chemotherapy Cycle as a Surrogate Marker for Treatment Outcomes in Patients with Neuroblastoma

Purpose

We performed this study to determine whether the degree of neutropenia after the first chemotherapy cycle can be used as a surrogate marker of individual susceptibility to chemotherapeutic agents affecting treatment outcome in patients with neuroblastoma.

Materials and Methods

The study included 313 patients who received the first cycle chemotherapy with a CEDC (cisplatin+etoposide+doxorubicin+cyclophosphamide) regimen and had absolute neutrophil count (ANC) data available. The cumulative incidences of progression and treatment-related mortality (TRM) were estimated. To identify genetic variations associated with the ANC, a genome-wide association study (GWAS) was performed.

Results

An ANC of 32.5/μL was determined as the cutoff point to categorize patients into the good and poor prognosis subgroups in terms of progression. Patients with a high nadir ANC had a higher cumulative incidence of progression than those with a low nadir ANC (p < 0.001). In multivariate analysis, high nadir ANC, age, bone marrow involvement, and unfavorable histology were poor prognostic factors. With regard to the TRM, patients with a low nadir ANC (ANC < 51.0/μL) had a higher cumulative incidence of TRM than those with a high nadir ANC (p=0.010). In GWAS, single-nucleotide polymorphisms of LPHN2 and CRHR1 were significantly associated with the nadir ANC.

Conclusion

In neuroblastoma patients, the degree of neutropenia after the first chemotherapy cycle can be used as a surrogate marker to predict an individual’s susceptibility to chemotherapeutic agents. Tailoring of treatment based on the degree of neutropenia needs to be considered.

MicroRNA-32 and MicroRNA-548a Promote the Drug Sensitivity of Non-Small Cell Lung Cancer Cells to Cisplatin by Targeting ROBO1 and Inhibiting the Activation of Wnt/β-Catenin Axis

Background

The roles of microRNA (miR)-32 and miR-548a in non-small cell lung cancer (NSCLC) have been studied. But their influences on NSCLC cells to cisplatin (DDP) resistance remain elusive. This study estimated the mechanisms of miR-32 and miR-548a in NSCLC cells to DDP.

Methods

Differentially expressed miRs in DDP-sensitive and resistant tissues were screened out using a GSE56036 chip. Then the predictive efficacies of miR-32 and miR-548a on DDP resistance were analyzed in NSCLC patients. The target mRNAs of miR-548a and miR-32 were predicted. miR-548a and miR-32 were knocked down to assess the influences of miR-32 and miR-548a on NSCLC growth. DDP-resistant cells were constructed and miR-32 and miR-548a expression was detected in resistant cells. After miR-32 and miR-548a knockdown, the IC50 value of DDP was detected. Then, the activation level of Wnt/β-catenin pathway was detected. The roles of miR-32 and miR-548a in NSCLC growth in vivo were detected by tumorigenesis experiment.

Results

miR-32 and miR-548a were poorly expressed in DDP-resistant NSCLC. miR-32 and miR-548a mimic enhanced the DDP sensitivity of NSCLC cells. Both miR-32 and miR-548a targeted ROBO1, and overexpression of ROBO1 inhibited the promotion of miR-32 and miR-548a mimic on DDP sensitivity. ROBO1 activated the Wnt/β-catenin pathway, thus enhancing the DDP resistance.

Conclusion

miR-32 and miR-548a target ROBO1 and inhibit Wnt/β-catenin activation, thus promoting the drug sensitivity of NSCLC cells to DDP.

A genome-wide association study of cocaine use disorder accounting for phenotypic heterogeneity and gene–environment interaction

BACKGROUND

Phenotypic heterogeneity and complicated gene–environment interplay in etiology are among the primary factors that hinder the identification of genetic variants associated with cocaine use disorder.

METHODS

To detect novel genetic variants associated with cocaine use disorder, we derived disease traits with reduced phenotypic heterogeneity using cluster analysis of a study sample (n = 9965). We then used these traits in genome-wide association tests, performed separately for 2070 African Americans and 1570 European Americans, using a new mixed model that accounted for the moderating effects of 5 childhood environmental factors. We used an independent sample (918 African Americans, 1382 European Americans) for replication.

RESULTS

The cluster analysis yielded 5 cocaine use disorder subtypes, of which subtypes 4 (n = 3258) and 5 (n = 1916) comprised heavy cocaine users, had high heritability estimates (h2 = 0.66 and 0.64, respectively) and were used in association tests. Seven of the 13 identified genetic loci in the discovery phase were available in the replication sample. In African Americans, rs114492924 (discovery p = 1.23 × E−8), a single nucleotide polymorphism in LINC01411, was replicated in the replication sample (p = 3.63 × E−3). In a meta-analysis that combined the discovery and replication results, 3 loci in African Americans were significant genome-wide: rs10188036 in TRAK2 (p = 2.95 × E−8), del-1:15511771 in TMEM51 (p = 9.11 × E−10) and rs149843442 near LPHN2 (p = 3.50 × E−8).

LIMITATIONS

Lack of data prevented us from replicating 6 of the 13 identified loci.

CONCLUSION

Our results demonstrate the importance of considering phenotypic heterogeneity and gene–environment interplay in detecting genetic variations that contribute to cocaine use disorder, because new genetic loci have been identified using our novel analytic method.

The genomic alterations of lung adenocarcinoma and lung squamous cell carcinoma can explain the differences of their overall survival rates

In the US, lung carcinoma accounted for over 150,000 deaths in 2018 and the advances in increasing survival rates are still limited. In this study, we investigated the cohorts with lung adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC) from The Cancer Genome Atlas to figure out the risk factors and genomic alterations that affected their prognosis. The histoclinical factors that differed between LUAD and LUSC were identified and the risk factors affecting the overall survival were figured out for both LUAD and LUSC. Next, the patterns of nucleotides substitutions and the mutational signatures were extracted to illustrate whether different mutational processes performed for them. Finally, the genes that had different frequencies of mutation were identified. LUAD and LUSC presented differences in histoclinical factors including age at the time of diagnosis, sex, smoking history, pathological T classification, and overall survival. This was caused by the distinct genomic alterations including the transition-to-transversion ratios, mutational signatures, and the frequently mutated genes. We proposed that the mutational signature associated with aging could be used to predict the prognosis of patients with LUAD. On the other hand, the AID/APOBEC family was associated with the prognosis of LUSC. Finally, SNTG1 and LRRK2 might be important in LUAD and LUSC, respectively.

Cystic fibrosis transmembrane conductance regulator-emerging regulator of cancer

Mutations of cystic fibrosis transmembrane conductance regulator (CFTR) cause cystic fibrosis, the most common life-limiting recessive genetic disease among Caucasians. CFTR mutations have also been linked to increased risk of various cancers but remained controversial for a long time. Recent studies have begun to reveal that CFTR is not merely an ion channel but also an important regulator of cancer development and progression with multiple signaling pathways identified. In this review, we will first present clinical findings showing the correlation of genetic mutations or aberrant expression of CFTR with cancer incidence in multiple cancers. We will then focus on the roles of CFTR in fundamental cellular processes including transformation, survival, proliferation, migration, invasion and epithelial-mesenchymal transition in cancer cells, highlighting the signaling pathways involved. Finally, the association of CFTR expression levels with patient prognosis, and the potential of CFTR as a cancer prognosis indicator in human malignancies will be discussed.

Pharmacogenetics of response to neoadjuvant paclitaxel treatment for locally advanced breast cancer

Locally advanced breast cancer (LABC) cases have a varying five-year survival rate, mainly influenced by the tumor response to chemotherapy. Paclitaxel activity (response rate) varies across populations from 21.5% to 84%. There are some reports on genetic traits and paclitaxel; however, there is still considerable residual unexplained variability. In this study, we aimed to test the association between eleven novel markers and tumor response to paclitaxel and to explore if any of them influenced tumor protein expression. We studied a cohort of 140 women with LABC. At baseline, we collected a blood sample (for genotyping), fine needle aspirates (for Western blot), and tumor measurements by imaging. After follow-up, we ascertained the response to paclitaxel monotherapy by comparing the percent change in the pre-, post- tumor measurements after treatment. To allocate exposure, we genotyped eleven SNPs with TaqMan probes on RT-PCR and regressed them to tumor response using linear modeling. In addition, we compared protein expression, between breast tumors and healthy controls, of those genes whose genetic markers were significantly associated with tumor response. After adjusting for multiple clinical covariates, SNPs on the LPHN2, ROBO1, SNTG1, and GRIK1 genes were significant independent predictors of poor tumor response (tumor growth) despite paclitaxel treatment. Moreover, proteins encoded by those genes are significantly downregulated in breast tumor samples.

A Genome-Wide Association Study to Identify Potential Germline Copy Number Variants for Sporadic Breast Cancer Susceptibility

Breast cancer (BC) predisposition in populations arises from both genetic and nongenetic risk factors. Structural variations such as copy number variations (CNVs) are heritable determinants for disease susceptibility. The primary objectives of this study are (1) to identify CNVs associated with sporadic BC using a genome-wide association study (GWAS) design; (2) to utilize 2 distinct CNV calling algorithms to identify concordant CNVs as a strategy to reduce false positive associations in the hypothesis-generating GWAS discovery phase, and (3) to identify potential candidate CNVs for follow-up replication studies. We used Affymetrix SNP Array 6.0 data profiled on Caucasian subjects (422 cases/348 controls) to call CNVs using algorithms implemented in Nexus Copy Number and Partek Genomics Suite software. Nexus algorithm identified CNVs associated with BC (731 autosomal CNVs with >5% frequency in the total sample and Q < 0.05). Thirteen CNVs were identified when Partek algorithm-called CNVs were overlapped with Nexus-identified CNVs; these CNVs showed concordances for frequency, effect size, and direction. Coding genes present within BC-associated CNVs were known to play a role in disease etiology and prognosis. Long noncoding RNAs identified within CNVs showed tissue-specific expression, indicating potential functional relevance of the findings. The identified candidate CNVs warrant independent replication.

The CC genotype of the delta-sarcoglycan gene polymorphism rs13170573 is associated with obstructive sleep apnea in the Chinese population

Obstructive sleep apnea (OSA) is a highly heterogeneous sleep disorder, and increasing evidence suggests that genetic factors play a role in the etiology of OSA. Airway muscle dysfunction might promote pharyngeal collapsibility, mutations or single nucleotide polymorphisms (SNPs) in the delta-sarcoglycan (SCGD) gene associated with muscle dysfunction. To evaluate if SCGD gene SNPs are associated with OSA, 101 individuals without OSA and 97 OSA patients were recruited randomly. The genotype distributions of SNPs (rs157350, rs7715464, rs32076, rs13170573 and rs1835919) in case and control populations were evaluated. The GG, GC and CC genotypes of rs13170573 in control and OSA groups were 51.5% and 37.1%, 36.6% and 35.1%, and 11.9% and 27.8%, respectively. Significantly fewer OSA patients possessed the GG genotype and significantly more possessed the CC genotype compared with controls. Further multivariate logistic regression analysis showed that the CC genotype was an independent risk factor for OSA, with an odds ratio (OR) of 2.17 (95% confidence interval [CI]: 1.19-6.01). Other factors, such as age ≥ 50 years, male gender, body mass index (BMI) ≥ 25 kg/m(2), low-density lipoprotein cholesterol (LDL-C) level ≥ 3.33 mg/dL, smoking and hypertension, were also independent risk factors for OSA in our multivariate logistic regression model.

Prediction of individual response to anticancer therapy: historical and future perspectives

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Effects of SC-560 in combination with cisplatin or taxol on angiogenesis in human ovarian cancer xenografts

This study was designed to evaluate the effect of cyclooxygenase-1 (COX-1) inhibitor, SC-560, combined with cisplatin or taxol, on angiogenesis in human ovarian cancer xenografts. Mice were treated with intraperitoneal (i.p.) injections of SC-560 6 mg/kg/day, i.p. injections of cisplatin 3 mg/kg every other day and i.p. injections of taxol 20 mg/kg once a week for 21 days. Vascular endothelial growth factor (VEGF) mRNA levels were detected by reverse transcription-polymerase chain reaction (RT-PCR); microvessel density (MVD) was determined by immunohistochemistry; and prostaglandin E₂ (PGE₂) levels were determined using ELISA. Expression levels of VEGF mRNA and MVD in treatment groups were inhibited significantly when compared with the control group (p < 0.05 for all), and SC-560 combined with cisplatin displayed a greater reduction in the expression of VEGF and MVD than SC-560 or cisplatin alone (p < 0.05). SC-560 combined with taxol showed a greater inhibition on VEGF mRNA expression than SC-560 or taxol alone (p < 0.05). The level of PGE₂ in treatment groups was significantly reduced when compared with the control group (p < 0.01 for all). These findings may indicate that cisplatin or taxol supplemented by SC-560 in human ovarian cancer xenografts enhances the inhibition effect of cisplatin or taxol alone on angiogenesis.

VEGF pathway polymorphisms as prognostic and pharmacogenetic factors in cancer: a 2013 update

With the recent advances in genomic medicine and the development of targeted antiangiogenic therapy for cancer patients, there has been an increased interest in the role of predictive and prognostic markers for antiangiogenic therapy. Here, we provide a summary of the angiogenesis pathway, the role of predictive and prognostic markers in cancer and a summary of the current literature and studies on predictive and prognostic markers for antiangiogenic therapy. Our aim is to summarize those studies that are currently in the literature with an emphasis on the future directions of the field from 2013 and beyond. We conclude by providing our perspective on the future directions of this growing field, as well as possible challenges and pitfalls along the way.

Comparative expression study of the endo-G protein coupled receptor (GPCR) repertoire in human glioblastoma cancer stem-like cells, U87-MG cells and non malignant cells of neural origin unveils new potential therapeutic targets

Glioblastomas (GBMs) are highly aggressive, invasive brain tumors with bad prognosis and unmet medical need. These tumors are heterogeneous being constituted by a variety of cells in different states of differentiation. Among these, cells endowed with stem properties, tumor initiating/propagating properties and particularly resistant to chemo- and radiotherapies are designed as the real culprits for tumor maintenance and relapse after treatment. These cells, termed cancer stem-like cells, have been designed as prominent targets for new and more efficient cancer therapies. G-protein coupled receptors (GPCRs), a family of membrane receptors, play a prominent role in cell signaling, cell communication and crosstalk with the microenvironment. Their role in cancer has been highlighted but remains largely unexplored. Here, we report a descriptive study of the differential expression of the endo-GPCR repertoire in human glioblastoma cancer stem-like cells (GSCs), U-87 MG cells, human astrocytes and fetal neural stem cells (f-NSCs). The endo-GPCR transcriptome has been studied using Taqman Low Density Arrays. Of the 356 GPCRs investigated, 138 were retained for comparative studies between the different cell types. At the transcriptomic level, eight GPCRs were specifically expressed/overexpressed in GSCs. Seventeen GPCRs appeared specifically expressed in cells with stem properties (GSCs and f-NSCs). Results of GPCR expression at the protein level using mass spectrometry and proteomic analysis are also presented. The comparative GPCR expression study presented here gives clues for new pathways specifically used by GSCs and unveils novel potential therapeutic targets.

Facilitating the use of large-scale biological data and tools in the era of translational bioinformatics

As both the amount of generated biological data and the processing compute power increase, computational experimentation is no longer the exclusivity of bioinformaticians, but it is moving across all biomedical domains. For bioinformatics to realize its translational potential, domain experts need access to user-friendly solutions to navigate, integrate and extract information out of biological databases, as well as to combine tools and data resources in bioinformatics workflows. In this review, we present services that assist biomedical scientists in incorporating bioinformatics tools into their research. We review recent applications of Cytoscape, BioGPS and DAVID for data visualization, integration and functional enrichment. Moreover, we illustrate the use of Taverna, Kepler, GenePattern, and Galaxy as open-access workbenches for bioinformatics workflows. Finally, we mention services that facilitate the integration of biomedical ontologies and bioinformatics tools in computational workflows.

Whole-exome sequencing to identify novel somatic mutations in squamous cell lung cancers

Squamous cell lung cancer is a major histotype of non-small cell lung cancer (NSCLC) that is distinct from lung adenocarcinoma. We used whole-exome sequencing to identify novel non-synonymous somatic mutations in squamous cell lung cancer. We identified 101 single-nucleotide variants (SNVs) including 77 non-synonymous SNVs (67 missense and 10 nonsense mutations) and 11 INDELs causing frameshifts. We also found four SNVs located within splicing sites. We verified 62 of the SNVs (51 missense, 10 nonsense and 1 splicing-site mutation) and 10 of the INDELs as somatic mutations in lung cancer tissue. Sixteen of the mutated genes were also mutated in at least one patient with a different type of lung cancer in the Catalogue of Somatic Mutation in Cancer (COSMIC) database. Four genes (LPHN2, TP53, MYH2 and TGM2) were mutated in approximately 10% of the samples in the COSMIC database. We identified two missense mutations in C10orf137 and MS4A3 that also occurred in other solid-tumor tissues in the COSMIC database. We found another somatic mutation in EP300 that was mutated in 4.2% of the 2,020 solid-tumor samples in the COSMIC database. Taken together, our results implicate TP53, EP300, LPHN2, C10orf137, MYH2, TGM2 and MS4A3 as potential driver genes of squamous cell lung cancer.

Comparison and validation of genomic predictors for anticancer drug sensitivity

BACKGROUND

An enduring challenge in personalized medicine lies in selecting the right drug for each individual patient. While testing of drugs on patients in large trials is the only way to assess their clinical efficacy and toxicity, we dramatically lack resources to test the hundreds of drugs currently under development. Therefore the use of preclinical model systems has been intensively investigated as this approach enables response to hundreds of drugs to be tested in multiple cell lines in parallel.

METHODS

Two large-scale pharmacogenomic studies recently screened multiple anticancer drugs on over 1000 cell lines. We propose to combine these datasets to build and robustly validate genomic predictors of drug response. We compared five different approaches for building predictors of increasing complexity. We assessed their performance in cross-validation and in two large validation sets, one containing the same cell lines present in the training set and another dataset composed of cell lines that have never been used during the training phase.

RESULTS

Sixteen drugs were found in common between the datasets. We were able to validate multivariate predictors for three out of the 16 tested drugs, namely irinotecan, PD-0325901, and PLX4720. Moreover, we observed that response to 17-AAG, an inhibitor of Hsp90, could be efficiently predicted by the expression level of a single gene, NQO1.

CONCLUSION

These results suggest that genomic predictors could be robustly validated for specific drugs. If successfully validated in patients' tumor cells, and subsequently in clinical trials, they could act as companion tests for the corresponding drugs and play an important role in personalized medicine.

Effects of cyclooxygenase inhibitors in combination with taxol on expression of cyclin D1 and Ki-67 in a xenograft model of ovarian carcinoma

The present study was designed to investigate the effects of cyclooxygenase (COX) inhibitors in combination with taxol on the expression of cyclin D1 and Ki-67 in human ovarian SKOV-3 carcinoma cells xenograft-bearing mice. The animals were treated with 100 mg/kg celecoxib (a COX-2 selective inhibitor) alone, 3 mg/kg SC-560 (a COX-1 selective inhibitor) alone by gavage twice a day, 20 mg/kg taxol alone by intraperitoneally (i.p.) once a week, or celecoxib/taxol, SC-560/celecoxib, SC-560/taxol or SC-560/celecoxib/taxol, for three weeks. To test the mechanism of the combination treatment, the index of cell proliferation and expression of cyclin D1 in tumor tissues were determined by immunohistochemistry. The mean tumor volume in the treated groups was significantly lower than control (p < 0.05), and in the three-drug combination group, tumor volume was reduced by 58.27% (p < 0.01); downregulated cell proliferation and cyclin D1 expression were statistically significant compared with those of the control group (both p < 0.01). This study suggests that the effects of COX selective inhibitors on the growth of tumors and decreased cell proliferation in a SKOV-3 cells mouse xenograft model were similar to taxol. The three-drug combination showing a better decreasing tendency in growth-inhibitory effect during the experiment may have been caused by suppressing cyclin D1 expression.

GWAS identifies novel susceptibility loci on 6p21.32 and 21q21.3 for hepatocellular carcinoma in chronic hepatitis B virus carriers

Genome-wide association studies (GWAS) have recently identified KIF1B as susceptibility locus for hepatitis B virus (HBV)–related hepatocellular carcinoma (HCC). To further identify novel susceptibility loci associated with HBV–related HCC and replicate the previously reported association, we performed a large three-stage GWAS in the Han Chinese population. 523,663 autosomal SNPs in 1,538 HBV–positive HCC patients and 1,465 chronic HBV carriers were genotyped for the discovery stage. Top candidate SNPs were genotyped in the initial validation samples of 2,112 HBV–positive HCC cases and 2,208 HBV carriers and then in the second validation samples of 1,021 cases and 1,491 HBV carriers. We discovered two novel associations at rs9272105 (HLA-DQA1/DRB1) on 6p21.32 (OR = 1.30, P = 1.13×10⁻¹⁹) and rs455804 (GRIK1) on 21q21.3 (OR = 0.84, P = 1.86×10⁻⁸), which were further replicated in the fourth independent sample of 1,298 cases and 1,026 controls (rs9272105: OR = 1.25, P = 1.71×10⁻⁴; rs455804: OR = 0.84, P = 6.92×10⁻³). We also revealed the associations of HLA-DRB1*0405 and 0901*0602, which could partially account for the association at rs9272105. The association at rs455804 implicates GRIK1 as a novel susceptibility gene for HBV–related HCC, suggesting the involvement of glutamate signaling in the development of HBV–related HCC.

Previous studies strongly suggest the importance of genetic susceptibility for hepatocellular carcinoma (HCC). However, the studies about genetic etiology on HBV–related HCC were limited. Our genome-wide association study included 523,663 autosomal SNPs in 1,538 HBV–positive HCC patients and 1,465 chronic HBV carriers for the discovery analysis. 2,112 HBV–positive HCC cases and 2,208 HBV carriers (the initial validation), and 1,021 cases and 1,491 HBV carriers (the second validation), were then analyzed for validation. The fourth independent samples of 1,298 cases and 1,026 controls were analyzed as replication. We discovered two novel associations at rs9272105 (HLA-DQA1/DRB1) on 6p21.32 and rs455804 (GRIK1) on 21q21.3. HLA-DRB1 molecules play an important role in chronic HBV infection and progression to HCC. The association at rs455804 implicates GRIK1 as a novel susceptibility gene for HBV–related HCC, suggesting the involvement of glutamate signaling in the development of HBV–related HCC.

Integrative genomics strategies to elucidate the complexity of drug response

Pharmacogenomic investigation from both genome-wide association studies and experiments focused on candidate loci involved in drug mechanism and metabolism has yielded a substantial and increasing list of robust genetic effects on drug therapy in humans. At the same time, reasonably comprehensive molecular data such as gene expression, proteomic and metabolomic data are now available for collections of hundreds to thousands of individuals. If these data are structured in a statistically robust and computationally tractable way, such as a network model, they can aid in the analysis of new pharmacogenomics studies by suggesting novel hypotheses for the regulation of genes involved in drug metabolism and response. Similarly, hypotheses taken from these same models can direct genome-wide association studies by focusing the genome-wide association studies analysis on a number of specific hypotheses informed by the relationships customarily seen between a gene's expression or protein activity and genetic variation at a particular locus. Network models based on other sorts of systematic biological data such as cell-based surveys of drug effect on gene expression and mining of literature and electronic medical records for associations between clinical and molecular phenotypes also promise similar utility. Although surely primitive in comparison with what will be developed, these model-based approaches to leveraging the increasing volume of data generated in the course of patient care and medical research nevertheless suggest a huge opportunity to improve our understanding of biological systems involved in pharmacogenomics and apply them to questions of medical relevance.

NCI60 cancer cell line panel data and RNAi analysis help identify EAF2 as a modulator of simvastatin and lovastatin response in HCT-116 cells

Simvastatin and lovastatin are statins traditionally used for lowering serum cholesterol levels. However, there exists evidence indicating their potential chemotherapeutic characteristics in cancer. In this study, we used bioinformatic analysis of publicly available data in order to systematically identify the genes involved in resistance to cytotoxic effects of these two drugs in the NCI60 cell line panel. We used the pharmacological data available for all the NCI60 cell lines to classify simvastatin or lovastatin resistant and sensitive cell lines, respectively. Next, we performed whole-genome single marker case-control association tests for the lovastatin and simvastatin resistant and sensitive cells using their publicly available Affymetrix 125K SNP genomic data. The results were then evaluated using RNAi methodology. After correction of the p-values for multiple testing using False Discovery Rate, our results identified three genes (NRP1, COL13A1, MRPS31) and six genes (EAF2, ANK2, AKAP7, STEAP2, LPIN2, PARVB) associated with resistance to simvastatin and lovastatin, respectively. Functional validation using RNAi confirmed that silencing of EAF2 expression modulated the response of HCT-116 colon cancer cells to both statins. In summary, we have successfully utilized the publicly available data on the NCI60 cell lines to perform whole-genome association studies for simvastatin and lovastatin. Our results indicated genes involved in the cellular response to these statins and siRNA studies confirmed the role of the EAF2 in response to these drugs in HCT-116 colon cancer cells.