Genome-wide identification of genetic determinants for the cytotoxicity of perifosine

Systems genetics identifies a role for Cacna2d1 regulation in elevated intraocular pressure and glaucoma susceptibility

Glaucoma is a multi-factorial blinding disease in which genetic factors play an important role. Elevated intraocular pressure is a highly heritable risk factor for primary open angle glaucoma and currently the only target for glaucoma therapy. Our study helps to better understand underlying genetic and molecular mechanisms that regulate intraocular pressure, and identifies a new candidate gene, Cacna2d1, that modulates intraocular pressure and a promising therapeutic, pregabalin, which binds to CACNA2D1 protein and lowers intraocular pressure significantly. Because our study utilizes a genetically diverse population of mice with known sequence variants, we are able to determine that the intraocular pressure-lowering effect of pregabalin is dependent on the Cacna2d1 haplotype. Using human genome-wide association study (GWAS) data, evidence for association of a CACNA2D1 single-nucleotide polymorphism and primary open angle glaucoma is found. Importantly, these results demonstrate that our systems genetics approach represents an efficient method to identify genetic variation that can guide the selection of therapeutic targets.

Elevated intraocular pressure (IOP) is a heritable risk factor for primary open angle glaucoma. Using forward mouse genetics, cell biology, pharmacology and human genetic data, the authors identify CACNA2D1 as an IOP risk gene that can be therapeutically targeted by the drug pregabalin in animal models.

A genome-wide association study of non-HPV-related head and neck squamous cell carcinoma identifies prognostic genetic sequence variants in the MAP-kinase and hormone pathways

BACKGROUND

Carcinomas of the oral cavity, pharynx and larynx are referred to as head and neck cancers (HNC); together they account for 2-3% of all newly diagnosed cancers in North America. Between 40-50% of HNC are early diagnosed at stages I-II. The 5-year and 10-year relative survival rates are 61% and 50%, respectively. Germline genetic sequence variants (GSV) have become increasingly found to have prognostic implications in a variety of cancers. Identifying these variants may have important clinical and biological implications.

METHODS

We conducted a genome-wide association study (GWAS) in 531 Stage I-II radiation-treated HNC patients (originally recruited for α-tocopherol/β-carotene placebo-controlled secondary prevention study) and used a replication cohort of 566 HNC patients of all stages, of mostly non-HPV-related cancers. Survival rates were estimated by the Kaplan-Meier method. Cox proportional hazards models adjusted for potential clinical factors and principal components were used to test for associations between the GSV and overall survival (OS) in these tumors.

RESULTS

The median follow-up time for OS was 9.21 years (GWAS cohort) and 2.37 years (replication cohort). In both cohorts, CACNA2D1:rs2299187, ESRRG:rs946465 and ESRRG:rs1416612 were each individually significantly associated with survival. In silico analysis of ESRRG:rs946465 identifies that it produces a splice variant in ESRRG. Variant alleles of CACNA2D1:rs2299187 and ESRRG:rs946465 were associated with higher expression of the corresponding protein.

CONCLUSIONS

Putatively functional polymorphisms in the MAP-Kinase and estrogen pathways, identified through GWAS and replicated in an independent dataset were associated with the survival of HNC patients.

Measuring circadian clock function in human cells

Circadian clocks are present in most cells and are essential for maintenance of daily rhythms in physiology, mood, and cognition. Thus, not only neurons of the central circadian pacemaker but also many other peripheral tissues possess the same functional and self-sustained circadian clocks. Surprisingly, however, their properties vary widely within the human population. In recent years, this clock variance has been studied extensively both in health and in disease using robust lentivirus-based reporter technologies to probe circadian function in human peripheral cells as proxies for those in neurologically and physiologically relevant but inaccessible tissues. The same procedures can be used to investigate other conserved signal transduction cascades affecting multiple aspects of human physiology, behavior, and disease. Accessing gene expression variation within human populations via these powerful in vitro cell-based technologies could provide important insights into basic phenotypic diversity or to better interpret patterns of gene expression variation in disease.

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

BACKGROUND

Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel.

RESULTS

43 SNPs were found significantly associated (FDR<0.005) with paclitaxel response, with 10 belonging to protein-coding genes (CFTR, ROBO1, PTPRD, BTBD12, DCT, SNTG1, SGCD, LPHN2, GRIK1, ZNF607). SNPs in GRIK1, DCT, SGCD and CFTR were predicted to be intronic enhancers, altering gene expression, while SNPs in ZNF607 and BTBD12 cause conservative missense mutations. mRNA expression analysis supported these findings as GRIK1, DCT, SNTG1, SGCD and CFTR showed significantly (p<0.05) increased expression among sensitive cell lines. Haplotypes found in GRIK1, SGCD, ROBO1, LPHN2, and PTPRD were more strongly associated with response than their individual SNPs.

CONCLUSIONS

Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.

Glycosidated phospholipids: uncoupling of signalling pathways at the plasma membrane

Cell expansion and metastasis are considered hallmarks of tumour progression. Therefore, efforts have been made to develop novel anti-cancer drugs that inhibit both the proliferation and the motility of tumour cells. Synthetic alkylphospholipids, compounds with aliphatic side chains that are ether linked to a glycerol backbone, are structurally derived from platelet-activating factor and represent a new class of drugs with anti-proliferative properties in tumour cells. These compounds do not interfere with the DNA or mitotic spindle apparatus of the cell. Instead, they are incorporated into cell membranes, where they accumulate and interfere with lipid metabolism and lipid-dependent signalling pathways. Recently, it has been shown that the most commonly studied alkylphospholipids inhibit proliferation by inducing apoptosis in malignant cells while leaving normal cells unaffected. This review focuses on a novel group of synthetic alkylphospholipids, the glycosidated phospholipids, which contain carbohydrates or carbohydrate-related molecules at the sn-2 position of the glycerol backbone. Members of this subfamily also exhibit anti-proliferative capacity and modulate the cell adhesion, differentiation, and migration of tumour cells. Among this group, Ino-C2-PAF shows the highest efficacy and low cytotoxicity. Apart from its anti-proliferative effect, Ino-C2-PAF strongly reduces cell motility via its inhibitory effect on the phosphorylation of the cytosolic tyrosine kinases FAK and Src. Signalling pathways under the control of the FAK/Src complex are normally required for both migration and proliferation and play a prominent role in tumour progression. We intend to highlight the potential of glycosidated phospholipids, especially Ino-C2-PAF, as a promising new group of drugs for the treatment of hyperproliferative and migration-based skin diseases.

Pharmacogenomic discovery using cell-based models

Quantitative variation in response to drugs in human populations is multifactorial; genetic factors probably contribute to a significant extent. Identification of the genetic contribution to drug response typically comes from clinical observations and use of classic genetic tools. These clinical studies are limited by our inability to control environmental factors in vivo and the difficulty of manipulating the in vivo system to evaluate biological changes. Recent progress in dissecting genetic contribution to natural variation in drug response through the use of cell lines has been made and is the focus of this review. A general overview of current cell-based models used in pharmacogenomic discovery and validation is included. Discussion includes the current approach to translate findings generated from these cell-based models into the clinical arena and the use of cell lines for functional studies. Specific emphasis is given to recent advances emerging from cell line panels, including the International HapMap Project and the NCI60 cell panel. These panels provide a key resource of publicly available genotypic, expression, and phenotypic data while allowing researchers to generate their own data related to drug treatment to identify genetic variation of interest. Interindividual and interpopulation differences can be evaluated because human lymphoblastoid cell lines are available from major world populations of European, African, Chinese, and Japanese ancestry. The primary focus is recent progress in the pharmacogenomic discovery area through ex vivo models.

Integrating Epigenomics into Pharmacogenomic Studies

The goal of personalized medicine is to recommend drug treatment based on an individual's genetic makeup. Pharmacogenomic studies utilize two main approaches: candidate gene and whole-genome. Both approaches analyze genetic variants such as single nucleotide polymorphisms (SNPs) to identify associations with drug response. In addition to DNA sequence variations, non-genetic but heritable epigenetic systems have also been implicated in regulating gene expression that could influence drug response. The International HapMap Project lymphoblastoid cell lines (LCLs) have been used to study genetic determinants responsible for expression variation and drug response. Recent studies have demonstrated that common genetic variants, including both SNPs and copy number variants (CNVs) account for a substantial fraction of natural variation in gene expression. Given the critical role played by DNA methylation in gene regulation and the fact that DNA methylation is currently the most studied epigenetic system, we suggest that profiling the variation in DNA methylation in the HapMap samples will provide new insights into the regulation of gene expression as well as the mechanisms of individual drug response at a new level of complexity. Epigenomics will substantially add to our knowledge of how genetics explains gene expression and pharmacogenomics.