Manuela Hummel

An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia.

Patients with cytogenetically normal acute myeloid leukemia (CN-AML) show heterogeneous treatment outcomes. We used gene-expression profiling to develop a gene signature that predicts overall survival (OS) in CN-AML. Based on data from 163 patients treated in the German AMLCG 1999 trial and analyzed on oligonucleotide microarrays, we used supervised principal component analysis to identify 86 probe sets (representing 66 different genes), which correlated with OS, and defined a prognostic score based on this signature. When applied to an independent cohort of 79 CN-AML patients, this continuous score remained a significant predictor for OS (hazard ratio [HR], 1.85; P = .002), event-free survival (HR = 1.73; P = .001), and relapse-free survival (HR = 1.76; P = .025). It kept its prognostic value in multivariate analyses adjusting for age, FLT3 ITD, and NPM1 status. In a validation cohort of 64 CN-AML patients treated on CALGB study 9621, the score also predicted OS (HR = 4.11; P < .001), event-free survival (HR = 2.90; P < .001), and relapse-free survival (HR = 3.14, P < .001) and retained its significance in a multivariate model for OS. In summary, we present a novel gene-expression signature that offers additional prognostic information for patients with CN-AML.

GlobalANCOVA: exploration and assessment of gene group effects

MOTIVATION Several authors have studied expression in gene sets with specific goals: overrepresentation of interesting genes in functional groups, predictive power for class membership and searches for groups where the constituent genes show coordinated changes in expression under the experimental conditions. The purpose of this article is to follow the third direction. One important aspect is that the gene sets under analysis are known a priori and are not determined from the experimental data at hand. Our goal is to provide a methodology that helps to identify the relevant structural constituents (phenotypical, experimental design, biological component) that determine gene expression in a group. RESULTS Gene-wise linear models are used to formalize the structural aspects of a study. The full model is contrasted with a reduced model that lacks the relevant design component. A comparison with respect to goodness of fit is made and quantified. An asymptotic test and a permutation test are derived to test the null hypothesis that the reduced model sufficiently explains the observed expression within the gene group of interest. Graphical tools are available to illustrate and interpret the results of the analysis. Examples demonstrate the wide range of application. AVAILABILITY The R-package GlobalAncova (http://www.bioconductor.org) offers data and functions as well as a vignette to guide the user through specific analysis steps.

ERG Expression Is an Independent Prognostic Factor and Allows Refined Risk Stratification in Cytogenetically Normal Acute Myeloid Leukemia: A Comprehensive Analysis of ERG, MN1, and BAALC Transcript Levels Using Oligonucleotide Microarrays

PURPOSE Recently, several novel molecular prognostic markers were identified in cytogenetically normal acute myeloid leukemia (CN-AML). In addition to the well-known influence of FLT3, NPM1, and CEBPA mutations, high transcript levels of the ERG, BAALC, and MN1 genes have been associated with inferior outcomes, but the relative importance of these risk markers remains to be defined. PATIENTS AND METHODS We analyzed ERG, BAALC, and MN1 expression levels in a cohort of 210 patients with CN-AML who received intensive chemotherapy. Expression levels of ERG, BAALC, and MN1 were determined in bone marrow samples by using oligonucleotide microarrays. RESULTS High transcript levels of ERG, BAALC, and MN1 were predictors for inferior overall survival (OS) and a lower rate of complete remissions (CRs). There were significant positive correlations between the expression levels of all three genes. ERG expression levels predicted OS in elderly patients (ie, age 60 years or older) with CN-AML (P = .006) as well as in younger patients (P = .013). In multivariate analyses, high ERG expression was independently associated with a lower CR rate (P = .013), shorter event-free survival (P = .008), and shorter OS (P = .005). Patients who had low ERG levels and absent FLT3 internal tandem duplication (ITD) had a 5-year OS of 44%, and patients who had high ERG expression and FLT3 ITD had a 5-year OS of only 5%. CONCLUSION We analyzed a comprehensive set of molecular risk factors in a large, homogeneous CN-AML patient cohort. In this study, high ERG expression levels emerged as a strong negative prognostic factor and provided prognostic information in addition to established molecular markers.

Transcriptome analysis reveals altered cholesterol metabolism during the neurodegeneration in mouse scrapie model

To identify the dynamic transcriptional alterations in CNS during the development of prion disease, brains of scrapie‐infected mice and age‐matched, mock‐inoculated controls were analyzed immediately before inoculation and at different time points post‐inoculation using Affymetrix microarray technique. A total of 449 probe sets, representing 430 genes, showed differential expression between scrapie‐ and mock‐inoculated mice over the time course. These genes could be separated into two clusters according to expression patterns: the genes in cluster 1 demonstrated lower mRNA levels in scrapie‐infected brains when compared with mock‐inoculated brains, whereas genes in cluster 2 showed higher mRNA levels in scrapie‐infected brains. Functional analysis of differentially expressed genes revealed the most severely affected biological process: cholesterol metabolism. The expression patterns of the cholesterol‐related genes indicated an inhibited cholesterol synthesis in the diseased brains. Conspicuously, a number of cluster 1 genes, including some of cholesterol‐related genes, showed not only decreasing mRNA levels in scrapie‐infected brains but also increasing mRNA levels in mock‐inoculated brains with increasing age. Quantitative RT‐PCR analysis of some cholesterol‐related genes in untreated mice suggested that changes of the examined genes observed in mock‐inoculated brains are mainly age related. This finding indicated a link between age‐related genes and scrapie‐associated neurodegeneration.

Tumor Infiltrated Hilar and Mediastinal Lymph Nodes are an Independent Prognostic Factor for Decreased Survival After Pulmonary Metastasectomy in Patients With Renal Cell Carcinoma

PURPOSE Surgical resection remains the most effective treatment in patients with pulmonary metastasis of renal cell carcinoma. To our knowledge the prognostic significance of mediastinal and hilar lymph node metastasis during pulmonary metastasectomy in patients with renal cell carcinoma is unknown. We analyzed the value of computerized tomography to predict mediastinal/hilar lymph node involvement as well as the impact of systematic lymphadenectomy on survival in patients with pulmonary renal cell carcinoma metastasis. MATERIALS AND METHODS We analyzed survival in 110 patients who underwent resection of pulmonary metastasis of renal cell carcinoma using the Kaplan-Meier method. Multivariate analysis was done by Cox regression analysis. RESULTS Lymph node metastasis was histologically proved in 35% of patients. Metastasis was not associated with initial tumor grade, lymph node status, the number of pulmonary metastases or recurrent pulmonary metastasis. Computerized tomography had 84% sensitivity and 97% specificity to predict lymph node metastasis. Sensitivity was markedly better for detecting mediastinal than hilar lymph node metastasis (90% vs 69%). Patients with lymph node metastasis had significantly shorter median survival than patients without lymph node metastasis (19 vs 102 months, p <0.001). Multivariate analysis revealed that tumor infiltrated mediastinal lymph nodes were an independent prognostic factor for patient survival. Match paired analysis showed that after lymph node dissection patients showed a trend toward improved survival. CONCLUSIONS Mediastinal and hilar lymph node metastases significantly correlate with decreased survival. Systematic lymphadenectomy provides valuable information on staging and prognosis in patients with pulmonary metastasis of renal cell carcinoma, and may prolong survival.

TEQC: an R package for quality control in target capture experiments

UNLABELLED TEQC is an R/Bioconductor package for quality assessment of target enrichment experiments. Quality measures comprise specificity and sensitivity of the capture, enrichment, per-target read coverage and its relation to hybridization probe characteristics, coverage uniformity and reproducibility, and read duplicate analysis. Several diagnostic plots allow visual inspection of the data quality. AVAILABILITY AND IMPLEMENTATION TEQC is implemented in the R language (version >2.12.0) and is available as a Bioconductor package for Linux, Windows and MacOS from www.bioconductor.org.

Molecular profiles and clinical outcome of stage UICC II colon cancer patients.

PurposePublished multigene classifiers suggesting outcome prediction for patients with stage UICC II colon cancer have not been translated into a clinical application so far. Therefore, we aimed at validating own and published gene expression signatures employing methods which enable their reconstruction in routine diagnostic specimens.MethodsImmunohistochemistry was applied to 68 stage UICC II colon cancers to determine the protein expression of previously published prognostic classifier genes (CDH17, LAT, CA2, EMR3, and TNFRSF11A). RNA from macrodissected tumor samples from 53 of these 68 patients was profiled on Affymetrix GeneChips (HG-U133 Plus 2.0). Prognostic signatures were generated by “nearest shrunken centroids” with cross-validation. Previously published gene signatures were applied to our data set using “global tests” and leave-one-out cross-validationResultsCorrelation of protein expression with clinical outcome failed to separate patients with disease-free follow-up (group DF) and relapse (group R). Although gene expression profiling allowed the identification of differentially expressed genes (“DF” vs. “R”), a stable classification/prognosis signature was not discernable. Furthermore, the application of previously published gene signatures to our data was unable to predict clinical outcome (prediction rate 75.5% and 64.2%; n.s.). T-stage was the only independent prognostic factor for relapse with established clinical and pathological parameters including microsatellite status (multivariate analysis).ConclusionsOur protein and gene expression analyses do not support application of molecular classifiers for prediction of clinical outcome in current routine diagnostic as a basis for patient-orientated therapy in stage UICC II colon cancer. Further studies are needed to develop prognosis signatures applicable in patient care.

Association Between a Prognostic Gene Signature and Functional Gene Sets

Background The development of expression-based gene signatures for predicting prognosis or class membership is a popular and challenging task. Besides their stringent validation, signatures need a functional interpretation and must be placed in a biological context. Popular tools such as Gene Set Enrichment have drawbacks because they are restricted to annotated genes and are unable to capture the information hidden in the signatures non-annotated genes. Methodology We propose concepts to relate a signature with functional gene sets like pathways or Gene Ontology categories. The connection between single signature genes and a specific pathway is explored by hierarchical variable selection and gene association networks. The risk score derived from an individual patients signature is related to expression patterns of pathways and Gene Ontology categories. Global tests are useful for these tasks, and they adjust for other factors. GlobalAncova is used to explore the effect on gene expression in specific functional groups from the interaction of the score and selected mutations in the patients genome. Results We apply the proposed methods to an expression data set and a corresponding gene signature for predicting survival in Acute Myeloid Leukemia (AML). The example demonstrates strong relations between the signature and cancer-related pathways. The signature-based risk score was found to be associated with development-related biological processes. Conclusions Many authors interpret the functional aspects of a gene signature by linking signature genes to pathways or relevant functional gene groups. The method of gene set enrichment is preferred to annotating signature genes to specific Gene Ontology categories. The strategies proposed in this paper go beyond the restriction of annotation and deepen the insights into the biological mechanisms reflected in the information given by a signature.

Increased Expression of Cell–Cell Signaling Genes by Stimulated Mononuclear Leukocytes in Patients with Previous Atherothrombotic Stroke

Background/Aims: Inflammation plays an important role in atherosclerosis and stroke. Acute infections are recognized as trigger factors for ischemic stroke. Methods: In this whole genome expression profile study of 15 patients and 15 control subjects, we tested the hypothesis that patients with a history of atherothrombotic stroke show enhanced transcription of inflammatory genes in circulating leukocytes. RNA from unstimulated or lipopolysaccharide (LPS)-stimulated peripheral blood mononuclear cells (PBMCs) was analyzed with Affymetrix U133A GeneChips using a pooling design. Expression of single genes and functional groups of genes was analyzed by global statistical tests. Results: A total of 10,197 probe sets showed positive calls. After correction for multiple testing no single probe set revealed significant differences either without or with LPS stimulation. However, significant global expression differences were found upon LPS stimulation for the group of genes that are involved in cell–cell signaling. Conclusion: LPS stimulation of PBMCs, a condition mimicking bacterial infection, induces differential expression of a group of cell–cell signaling genes in patients with previous atherothrombotic stroke. This finding can be caused by genetic differences between both groups, but acquired risk factors, medication and technical factors may also have contributed to the result.