Citations

Genetic variants in the gene encoding integrin α2 ( ITGA2) have been reported to be associated with an increased risk for ischemic stroke. The purpose of this study was to investigate the association between haplotype-tagging single-nucleotide polymorphisms (tSNPs) in ITGA2 and risk of ischemic stroke in a collection of North American stroke cases and controls. The study included 484 cases and 263 controls. Thirteen tSNPs were genotyped. Association tests at and across each tSNP were performed, including haplotype association analysis. Secondary analyses considered stroke subtypes on the basis of Trial of Org 10172 in Acute Stroke Treatment (TOAST) criteria. We observed significant association between tSNP rs3756541 (additive model, odds ratio (OR), 1.49; 95% confidence interval (CI), 1.11 to 2.04; P = 0.009) and disease and a trend toward association at rs2303124 (recessive model, OR, 1.56; 95% CI, 1.05 to 2.33; P = 0.03). These associations remained significant in the haplotype analyses. The associated tSNPs did not distinguish stroke etiology after application of TOAST criteria. Our results suggest that genetic variability within ITGA2 may confer risk for ischemic stroke independent of conventional risk factors. These results provide additional support for a role for platelet receptor genes in the pathogenesis of ischemic stroke of diverse subtypes.

Multiple myeloma is a radiosensitive malignancy that is currently incurable. Here, we generated a novel recombinant vesicular stomatitis virus [VSV(Δ51)-NIS] that has a deletion of methionine 51 in the matrix protein and expresses the human sodium iodide symporter (NIS) gene. VSV(Δ51)-NIS showed specific oncolytic activity against myeloma cell lines and primary myeloma cells and was able to replicate to high titers in myeloma cells in vitro. Iodide uptake assays showed accumulation of radioactive iodide in VSV(Δ51)-NIS–infected myeloma cells that was specific to the function of the NIS transgene. In bg/nd/xid mice with established subcutaneous myeloma tumors, administration of VSV(Δ51)-NIS resulted in high intratumoral virus replication and tumor regression. VSV-associated neurotoxicity was not observed. Intratumoral spread of the infection was monitored noninvasively by serial gamma camera imaging of 123I-iodide biodistribution. Dosimetry calculations based on these images pointed to the feasibility of combination radiovirotherapy with VSV(Δ51)-NIS plus 131I. Immunocompetent mice with syngeneic 5TGM1 myeloma tumors (either subcutaneous or orthotopic) showed significant enhancements of tumor regression and survival when VSV(Δ51)-NIS was combined with 131I. These results show that VSV(Δ51)-NIS is a safe oncolytic agent with significant therapeutic potential in multiple myeloma.

Abstract Hyperdiploid multiple myeloma (H-MM) is the most common form of myeloma. In this gene expression profiling study, we show that H-MM is defined by a protein biosynthesis signature that is primarily driven by a gene dosage mechanism as a result of trisomic chromosomes. Within H-MM, four independently validated patient clusters overexpressing nonoverlapping sets of genes that form cognate pathways/networks that have potential biological importance in multiple myeloma were identified. One prominent cluster, cluster 1, is characterized by high expression of cancer testis antigen and proliferation-associated genes. Tumors from these patients were more proliferative than tumors in other clusters (median plasma cell labeling index, 3.8; P < 0.05). Another cluster, cluster 3, is characterized by genes involved in tumor necrosis factor/nuclear factor-κB signaling and antiapoptosis. These patients have better response to bortezomib as compared with patients within other clusters (70% versus 29%; P = 0.02). Furthermore, for a group of patients generally thought to have better prognosis, a cluster of patients with short survival (cluster 1; median survival, 27 months) could be identified. This analysis illustrates the heterogeneity within H-MM and the importance of defining specific cytogenetic prognostic factors. Furthermore, the signatures that defined these clusters may provide a basis for tailoring treatment to individual patients. [Cancer Res 2007;67(7):2982–9]

Type 2 diabetes is characterized by muscle insulin resistance. Nondiabetic first-degree relatives of type 2 diabetic patients have also been reported to have insulin resistance. A polygenic basis for pathogenesis of type 2 diabetes has been proposed. A gene expression profile was evaluated in the skeletal muscle of patients with type 2 diabetes while not on treatment for 2 weeks and after 10 days of intensive insulin treatment. Comparison of gene expression pattern with age-, sex-, and BMI-matched people with no family history of diabetes was performed using a microarray technique (Hu6800 arrays; Affymetrix, Santa Clara, CA). Only those gene transcripts showing ≥1.9-fold changes and an average difference in fluorescence intensity of ≥1,000 in all subjects are reported. Insulin sensitivity (SI) was measured using an intravenous glucose tolerance test. Of 6,451 genes surveyed, transcriptional patterns of 85 genes showed alterations in the diabetic patients after withdrawal of treatment, when compared with patterns in the nondiabetic control subjects. Insulin treatment reduced the difference in patterns between diabetic and nondiabetic control subjects (improved) in all but 11 gene transcripts, which included genes involved in structural and contractile functions, growth and tissue development, stress response, and energy metabolism. These improved transcripts included genes involved in insulin signaling, transcription factors, and mitochondrial maintenance. However, insulin treatment altered the transcription of 29 additional genes involved in signal transduction; structural and contractile functions; growth and tissue development; and protein, fat, and energy metabolism. Type 2 diabetic patients had elevated circulating insulin during the insulin-treated phase, although their blood glucose levels (98.8 ± 6.4 vs. 90.0 ± 2.9 mg/dl for diabetic vs. control) were similar to those of the control subjects. In contrast, after withdrawal of treatment, the diabetic patients had reduced SI and elevated blood glucose (224.0 ± 26.2 mg/dl), although their insulin levels were similar to those of the nondiabetic control subjects. This study identified several candidate genes for muscle insulin resistance, complications associated with poor glycemic control, and effects of insulin treatment in people with type 2 diabetes.

AbstractRecent gene-expression data have suggested that host immune genetic signatures may predict outcomes in patients with follicular lymphoma. We evaluated the hypothesis that germ line common variation in candidate immune genes is associated with survival. Cox models were used to estimate hazard ratios (HR) and corresponding 95% confidence intervals for individual SNPs after accounting for age, clinical, and other demographic factors. The median age at diagnosis of the 278 patients was 57 years, and 59 (21%) of the patients died during follow-up, with a median follow-up of 59 months (range, 27-78 months) for surviving patients. SNPs in IL8 (rs4073; HRTT = 2.14, 1.26-3.63), IL2 (rs2069762; HRGT/TT = 1.80, 1.06-3.05), IL12B (rs3212227; HRAC/CC = 1.83, 1.06-3.06), and IL1RN (rs454078; HRAA = 1.93, 1.11-3.34) were the most robust predictors of survival. A summary score of the number of deleterious genotypes from these genes was strongly associated with survival (P = .001). A risk score that combined the 4 SNPs with the clinical and demographic factors was even more strongly associated with survival (P < .001); the 5-year Kaplan-Meier survival estimates were 96% (93%-100%), 72% (62%-83%), and 58% (48%-72%) for groups at low, intermediate, and high risk, respectively. Common variation in host immune genes warrants further evaluation as a promising class of prognostic factors in follicular lymphoma.

Abstract In this study, we observed loss of heterozygosity (LOH) in human chromosomal fragment 6q25.1 in sporadic lung cancer patients. LOH was observed in 65% of the 26 lung tumors examined and was narrowed down to a 2.2-Mb region. Single-nucleotide polymorphism (SNP) analysis of genes located within this region identified a candidate gene, termed p34. This gene, also designated as ZC3H12D, C6orf95, FLJ46041, or dJ281H8.1, carries an A/G nonsynonymous SNP at codon 106, which alters the amino acid from lysine to arginine. Nearly 73% of heterozygous lung cancer tissues with LOH and the A/G SNP also exhibited loss of the A allele. In vitro clonogenic and in vivo nude mouse studies showed that overexpression of the A allele exerts tumor suppressor function compared with the G allele. p34 is located within a recently mapped human lung cancer susceptibility locus, and association of the p34 A/G SNP was tested among these families. No significant association between the less frequent G allele and lung cancer susceptibility was found. Our results suggest that p34 may be a novel tumor suppressor gene involved in sporadic lung cancer but it seems not to be the candidate familial lung cancer susceptibility gene linked to chromosomal region 6q23-25. [Cancer Res 2007;67(1):93–9]

Abstract The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents.