Diagnosis of influenza A infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with influenza A virus infection represents a novel approach to infection diagnosis
A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.
Specimen part, Subject, TimeView Samples
Venous thromboembolism (VTE) is a major cause of morbidity and mortality. Pulmonary embolism is a life threatening manifestation of VTE that occurs in at least half the patients on presentation. In addition, VTE recurs in up to 30% of patients after a standard course of anticoagulation, and there is not a reliable way of predicting recurrence. We investigated whether gene expression profiles of whole blood could distinguish patients with VTE from healthy controls, single VTE from those with recurrence, and DVT alone from those with PE. 70 adults with VTE on warfarin and 63 healthy controls were studied. Patients with antiphospholipid syndrome or cancer were excluded. Blood was collected in PAXgene tubes, RNA isolated, and gene expression profiles obtained using Affymetrix arrays. We developed a 50 gene model that distinguished healthy controls from subjects with VTE with excellent receiver operating characteristics (AUC 0.94; P < 0.0001). We also discovered a separate 50 gene model that distinguished subjects with a single VTE from those with recurrent VTE with good receiver operating characteristics (AUC 0.75; P=0.008). In contrast, we were unable to distinguish subjects with DVT from those with PE using gene expression profiles. Gene expression profiles of whole blood can distinguish subjects with VTE from healthy controls and subjects with a single VTE from those with recurrence. Additional studies should be performed to validate these results and develop diagnostic tests. Gene expression profiling is likely translatable to other thrombotic disorders(e.g., patients with cancer and VTE).
Whole blood gene expression analyses in patients with single versus recurrent venous thromboembolism.
Sex, Age, RaceView Samples
Recurrent venous thromboembolism (VTE) occurs infrequently following a provoked event but occurs in up to 30% of individuals following an initial unprovoked event. We studied 134 patients with VTE separated into 3 groups: (1) low-risk patients had 1 provoked VTE; (2) moderate-risk patients had no more than 1 unprovoked VTE; (3) high-risk patients had 2 unprovoked VTE. 44 individuals with no history of VTE were enrolled as healthy controls. Consented individuals were enrolled at 4 medical centers in the US. Total RNA from whole blood was isolated and hybridized to Illumina HT-12 V4 Beadchips to assay whole genome expression. Using class prediction analysis, we distinguished high-risk patients from healthy controls with good receiver operating curve characteristics (AUC=0.88). We also distinguished high-risk from low-risk individuals, moderate-risk individuals from healthy controls, and low-risk individuals from healthy controls with AUCs of 0.72, 0.77 and 0.72, respectively. Using differential expression analysis, we identified genes relevant to coagulation, immune response and vascular biology, such as SELP and CD46, which were differentially expressed in at least two comparisons. Neither approach distinguished the moderate-risk patients from the high-risk or low-risk groups. Gene expression profiles may provide insights into biological mechanisms associated with patients at risk for recurrent VTE. Prospective studies are needed to validate these findings.
Whole blood gene expression profiles distinguish clinical phenotypes of venous thromboembolism.
Specimen partView Samples
Purpose: Gene expression signatures developed to measure the activity of oncogenic signaling pathways have been used to dissect the heterogeneity of tumor samples and to predict sensitivity to various cancer drugs that target components of the relevant pathways, thus potentially identifying therapeutic options for subgroups of patients. To facilitate broad use, including in a clinical setting, the ability to generate data from formalin-fixed, paraffin-embedded (FFPE) tissues is essential. Experimental Design: Patterns of pathway activity in matched fresh-frozen and FFPE xenograft tumor samples were generated using the MessageAmp Premier methodology in combination with assays using Affymetrix arrays. Results generated were compared with those obtained from fresh-frozen samples using a standard Affymetrix assay. In addition, gene expression data from patient matched fresh-frozen and FFPE melanomas were also utilized to evaluate the consistency of predictions of oncogenic signaling pathway status. Results: Significant correlation of pathway activity predictions was observed between paired fresh-frozen and FFPE xenograft tumor samples. In addition, significant concordance of pathway activity predictions was also observed between patient matched fresh-frozen and FFPE melanomas. Conclusion: Reliable and consistent predictions of oncogenic pathway activities can be obtained from FFPE tumor tissue samples. The ability to reliably utilize FFPE patient tumor tissue samples for genomic analyses will lead to a better understanding of the biology of disease progression and, in the clinical setting, will provide tools to guide the choice of therapeutics to those most likely to be effective in treating a patients disease.
A methodology for utilization of predictive genomic signatures in FFPE samples.
Specimen partView Samples
Epithelial ovarian cancer is the leading cause of death among gynecologic malignancies. Diagnosis usually occurs after metastatic spread, largely reflecting vague symptoms of early disease combined with lack of an effective screening strategy. Epigenetic mechanisms of gene regulation, including DNA methylation, are fundamental to normal cellular function and also play a major role in carcinogenesis. To elucidate the biological and clinical relevance of DNA methylation in ovarian cancer, we conducted expression microarray analysis of 39 cell lines and 17 primary culture specimens grown in the presence or absence of DNA methyltransferase (DNMT) inhibitors. Two parameters, induction of expression and standard deviation among untreated samples, identified 378 candidate methylated genes, many relevant to TGF-beta signaling. We analyzed 43 of these genes and they all exhibited methylation. Treatment with DNMT inhibitors increased TGF-beta pathway activity. Hierarchical clustering of ovarian cancers using the 378 genes reproducibly generated a distinct gene cluster strongly correlated with TGF-beta pathway activity that discriminates patients based on age. These data suggest that accumulation of age-related epigenetic modifications leads to suppression of TGF-beta signaling and contributes to ovarian carcinogenesis.
Epigenetic suppression of the TGF-beta pathway revealed by transcriptome profiling in ovarian cancer.
Sex, Specimen part, Cell line, TreatmentView Samples
Nonalcoholic fatty liver disease represents a spectrum of pathology that ranges from benign steatosis to potentially-progressive steatohepatitis and affects more than 30% of US adults. Advanced NAFLD is associated with increased morbidity and mortality from cirrhosis, primary liver cancer, cardiovascular disease and extrahepatic cancers.
Hepatic gene expression profiles differentiate presymptomatic patients with mild versus severe nonalcoholic fatty liver disease.
Specimen part, DiseaseView Samples