Prevalence of the GFI1-36N SNP in Multiple Myeloma Patients and Its Impact on the Prognosis.

Transcription factor Growth Factor Independence 1 (GFI1) regulates the expression of genes important for survival, proliferation and differentiation of hematopoietic cells. A single nucleotide polymorphism (SNP) variant of GFI1 (GFI1-36N: serine replaced by asparagine at position 36), has a prevalence of 5-7% among healthy Caucasians and 10-15% in patients with myelodysplastic syndrome (MDS) and acute myeloid leukaemia (AML) predisposing GFI-36N carriers to these diseases. Since GFI1 is implicated in B cell maturation and plasma cell (PC) development, we examined its prevalence in patients with multiple myeloma (MM), a haematological malignancy characterized by expansion of clonal PCs. Strikingly, as in MDS and AML, we found that the GFI1-36N had a higher prevalence among MM patients compared to the controls. In subgroup analyses, GFI1-36N correlates to a shorter overall survival of MM patients characterized by the presence of t(4;14) translocation and gain of 1q21 (≤3 copies). MM patients carrying gain of 1q21 (≥3 copies) demonstrated poor progression free survival. Furthermore, gene expression analysis implicated a role for GFI1-36N in epigenetic regulation and metabolism, potentially promoting the initiation and progression of MM.

CXCL9 Predicts Severity at the Onset of Chronic Graft-versus-host Disease.

BACKGROUND: Chronic graft-versus-host disease (cGVHD) represents a double-edged sword. In its nonsevere form, cGVHD associates with better control of the malignant disease, thus highlighting graft-versus-leukemia effects. However, severe cGVHD leads to debilitating morbidity and increased nonrelapse mortality. The prediction of severe cGVHD, in particular at disease onset, is therefore of high importance for ensuing clinical decisions and overall success of allogeneic stem cell transplantations. CXC-chemokine ligand 9 (CXCL9) is an interferon-inducible chemokine of the CXC family and is increased in cGVHD. Endothelial activation and stress index (EASIX) was shown to predict death after acute graft-versus-host disease. We explored CXCL9 and EASIX as predictors of severe cGVHD. METHODS: Sera and clinical data of 480 patients were available who survived at least 6 months following allogeneic stem cell transplantation without steroid-refractory acute graft-versus-host disease and without early relapse. CXCL9 and EASIX were measured on day +100 and onset of cGVHD. RESULTS: Development of nonsevere cGVHD was significantly associated with improved overall survival (hazard ratio 0.53, P < 0.001). CXCL9 serum levels at the onset of cGVHD predicted the development of severe cGVHD later on (hazard ratio 1.33, P = 0.02). In contrast, EASIX at the onset of cGVHD was not associated with cGVHD severity but was a significant independent risk factor for overall mortality and nonrelapse mortality. CONCLUSIONS: CXCL9 levels at the onset of cGVHD can help to predict severe courses of the disease and have potential for optimizing tailored administration of immunosuppressive therapy.

Marginal variable screening for survival endpoints.

When performing survival analysis in very high dimensions, it is often required to reduce the number of covariates using preliminary screening. During the last years, a large number of variable screening methods for the survival context have been developed. However, guidance is missing for choosing an appropriate method in practice. The aim of this work is to provide an overview of marginal variable screening methods for survival and develop recommendations for their use. For this purpose, a literature review is given, offering a comprehensive and structured introduction to the topic. In addition, a novel screening procedure based on distance correlation and martingale residuals is proposed, which is particularly useful in detecting nonmonotone associations. For evaluating the performance of the discussed approaches, a simulation study is conducted, comparing the true positive rates of competing variable screening methods in different settings. A real data example on mantle cell lymphoma is provided.

EASIX for prediction of survival in lower-risk myelodysplastic syndromes.

Patients with myelodysplastic syndromes (MDS) are at risk of early death from cardiovascular complications due to the link between clonal hematopoiesis and endothelial dysfunction. EASIX (Endothelial Activation and Stress Index) has been established to predict endothelial complications after allogeneic transplantation. We investigated the impact of EASIX measured at first diagnosis on survival of patients with lower- and higher-risk MDS (no allogeneic transplantation) in two independent institutions: n = 192 (training cohort) and n = 333 (validation cohort). Serum markers of endothelial cell distress were measured and correlated to EASIX. While no effects of EASIX on survival were observed in higher-risk patients, EASIX was associated with shorter survival in patients with lower-risk MDS in both cohorts (univariate: Cohort I: hazard ratio (HR): 1.46; 95% confidence interval (CI) 1.24-1.71; p-value < 0.001/Cohort II: HR 1.31 [1.17-1.48]; p-value < 0.001). Multivariate Cox regression analysis and prediction error analyses confirmed that EASIX remained a significant predictor of survival after adjustment for age, sex, cytogenetic abnormalities and bone marrow blasts in lower-risk patients. The model of the training cohort could be validated. Serum levels of Angiopioetin-2 correlated significantly with EASIX. We introduce EASIX as an easily accessible and independent predictor for survival in patients with lower-risk MDS.

No Evidence for Effect of Exercise on Transcriptome of NK Cells in Breast Cancer Patients Undergoing Adjuvant Therapy: Results From a Pilot Study.

BACKGROUND: Mobilization and activation of natural killer cells (NK cells) have been hypothesized to contribute to observed protective effects of exercise on cancer development and progression. Some evidence exists for acute effects of aerobic exercise on NK cell mobilization and function, i.e., alteration of the gene expression profile of NK cells. Yet, the chronic effects of exercise training, and effects of other modalities than endurance exercise are still understudied. Here, we investigated the chronic effects of a 12-week resistance exercise program on NK cell gene expression in breast cancer patients undergoing adjuvant chemo- or radiotherapy. METHODS: Breast cancer patients were randomly assigned to either a 12-week resistance exercise program or a relaxation control group concomitant to adjuvant therapy. In a subsample of 19 participants, RNA was extracted from magnet bead isolated NK cells and subsequently analyzed for differential gene expression using microarray Illumina HumanHT-12 v4 before and after the intervention. RESULTS: After chronic exercise intervention several genes showed higher differential expression compared to the control group. However, after correction for multiple testing, baseline-adjusted analyses of covariance indicated no significant differences between the intervention and the control group with regard to the gene expression profile. DISCUSSION: Our findings suggest that 12-week resistance-exercise did not alter the gene expression profile of NK cells in breast cancer patients undergoing adjuvant therapy on the long term. Further studies with larger sample sizes and specifically designed to investigate whether exercise-induced changes in NK cell function are attributed to acute effects are warranted.

Association of resilience with health-related quality of life and depression in multiple myeloma and its precursors: results of a German cross-sectional study.

OBJECTIVES: To investigate the relation between resilience, health-related quality of life (HRQOL) and depression in multiple myeloma (MM) and its premalignant stages. MM is one of the most frequent haematological disorders. It is regularly preceded by asymptomatic stages of the disease namely monoclonal gammopathy of undetermined significance (MGUS) and smouldering multiple myeloma (SMM). Survivors have to cope with mental and physical impairment in terms of HRQOL and depression. The concept of resilience refers to a person's ability to adapt to adversity. DESIGN: Cross-sectional study. SETTING: MM outpatient department at a University Hospital in Germany (tertiary care). PARTICIPANTS: 292 consecutive patients from our MM outpatient department. OUTCOME MEASURES: HRQOL, depression and psychological resilience were assessed with validated questionnaires. RESULTS: Regression analyses were performed to determine associations between resilience, HRQOL and depression. 98 patients (33.6%) had a new diagnosis of active MM, 106 patients (36.3%) were already treated for MM and 88 patients had the diagnosis of a precursor (MGUS or SMM; 30.1%) of MM. Multivariate linear regression analyses revealed a strong positive impact of resilience on physical (b 7.20; 95% CI 4.43 to 9.98; p<0.001) and mental (b 12.12; 95% CI 9.36 to 14.87; p<0.001) HRQOL. Ordered logistic regression analysis showed that the odds for higher depression severity were lowered for individuals with a high level of resilience in comparison to the individuals with a low level of resilience (OR 0.11; 95% CI 0.06 to 0.19; p<0.001). CONCLUSIONS: Resilience may be a protective factor in the disease trajectory of MM and its precursors. As a next step, future research should focus on longitudinal assessments at various time points to elucidate the role of resilience in one of the most frequent haematological malignancies.

Multiple-rater kappas for binary data: Models and interpretation.

Interrater agreement on binary measurements with more than two raters is often assessed using Fleiss' κ, which is known to be difficult to interpret. In situations where the same raters rate all items, however, the far less known κ suggested by Conger, Hubert, and Schouten is more appropriate. We try to support the interpretation of these characteristics by investigating various models or scenarios of rating. Our analysis, which is restricted to binary data, shows that conclusions concerning interrater agreement by κ heavily depend on the population of items or subjects considered, even if the raters have identical behavior. The standard scale proposed by Landis and Koch, which verbally interprets numerical values of κ, appears to be rather subjective. On the basis of one of the models for rater behavior, we suggest an alternative verbal interpretation for kappa. Finally, we reconsider a classical example from pathology to illustrate the application of our methods and models. We also look for subgroups of raters with similar rating behavior using hierarchical clustering.

Clustering of samples and variables with mixed-type data.

Analysis of data measured on different scales is a relevant challenge. Biomedical studies often focus on high-throughput datasets of, e.g., quantitative measurements. However, the need for integration of other features possibly measured on different scales, e.g. clinical or cytogenetic factors, becomes increasingly important. The analysis results (e.g. a selection of relevant genes) are then visualized, while adding further information, like clinical factors, on top. However, a more integrative approach is desirable, where all available data are analyzed jointly, and where also in the visualization different data sources are combined in a more natural way. Here we specifically target integrative visualization and present a heatmap-style graphic display. To this end, we develop and explore methods for clustering mixed-type data, with special focus on clustering variables. Clustering of variables does not receive as much attention in the literature as does clustering of samples. We extend the variables clustering methodology by two new approaches, one based on the combination of different association measures and the other on distance correlation. With simulation studies we evaluate and compare different clustering strategies. Applying specific methods for mixed-type data proves to be comparable and in many cases beneficial as compared to standard approaches applied to corresponding quantitative or binarized data. Our two novel approaches for mixed-type variables show similar or better performance than the existing methods ClustOfVar and bias-corrected mutual information. Further, in contrast to ClustOfVar, our methods provide dissimilarity matrices, which is an advantage, especially for the purpose of visualization. Real data examples aim to give an impression of various kinds of potential applications for the integrative heatmap and other graphical displays based on dissimilarity matrices. We demonstrate that the presented integrative heatmap provides more information than common data displays about the relationship among variables and samples. The described clustering and visualization methods are implemented in our R package CluMix available from https://cran.r-project.org/web/packages/CluMix.

miR-99a reveals two novel oncogenic proteins E2F2 and EMR2 and represses stemness in lung cancer.

Lung cancer is one of the most aggressive tumours with very low life expectancy. Altered microRNA expression is found in human tumours because it is involved in tumour growth, progression and metastasis. In this study, we analysed microRNA expression in 47 lung cancer biopsies. Among the most downregulated microRNAs we focussed on the miR-99a characterisation. In vitro experiments showed that miR-99a expression decreases the proliferation of H1650, H1975 and H1299 lung cancer cells causing cell cycle arrest and apoptosis. We identified two novel proteins, E2F2 (E2F transcription factor 2) and EMR2 (EGF-like module-containing, mucin-like, hormone receptor-like 2), downregulated by miR-99a by its direct binding to their 3'-UTR. Moreover, miR-99a expression prevented cancer cell epithelial-to-mesenchymal transition (EMT) and repressed the tumourigenic potential of the cancer stem cell (CSC) population in both these cell lines and mice tumours originated from H1975 cells. The expression of E2F2 and EMR2 at protein level was studied in 119 lung cancer biopsies. E2F2 and EMR2 are preferentially expressed in adenocarcinomas subtypes versus other tumour types (squamous and others). Interestingly, the expression of E2F2 correlates with the presence of vimentin and both E2F2 and EMR2 correlate with the presence of ß-catenin. Moreover, miR-99a expression correlates inversely with E2F2 and directly with ß-catenin expression in lung cancer biopsies. In conclusion, miR-99a reveals two novel targets E2F2 and EMR2 that play a key role in lung tumourigenesis. By inhibiting E2F2 and EMR2, miR-99a represses in vivo the transition of epithelial cells through an EMT process concomitantly with the inhibition of stemness features and consequently decreasing the CSC population.

Gene expression changes in blood RNA after swimming in a chlorinated pool.

Exposure to disinfection by-products (DBP) such as trihalomethanes (THM) in swimming pools has been linked to adverse health effects in humans, but their biological mechanisms are unclear. We evaluated short-term changes in blood gene expression of adult recreational swimmers after swimming in a chlorinated pool. Volunteers swam 40min in an indoor chlorinated pool. Blood samples were drawn and four THM (chloroform, bromodichloromethane, dibromochloromethane and bromoform) were measured in exhaled breath before and after swimming. Intensity of physical activity was measured as metabolic equivalents (METs). Gene expression in whole blood mRNA was evaluated using IlluminaHumanHT-12v3 Expression-BeadChip. Linear mixed models were used to evaluate the relationship between gene expression changes and THM exposure. Thirty-seven before-after pairs were analyzed. The median increase from baseline to after swimming were: 0.7 to 2.3 for MET, and 1.4 to 7.1µg/m3 for exhaled total THM (sum of the four THM). Exhaled THM increased on average 0.94µg/m3 per 1 MET. While 1643 probes were differentially expressed post-exposure. Of them, 189 were also associated with exhaled levels of individual/total THM or MET after False Discovery Rate. The observed associations with the exhaled THM were low to moderate (Log-fold change range: -0.17 to 0.15). In conclusion, we identified short-term gene expression changes associated with swimming in a pool that were minor in magnitude and their biological meaning was unspecific. The high collinearity between exhaled THM levels and intensity of physical activity precluded mutually adjusted models with both covariates. These exploratory results should be validated in future studies.

Cyclic AMP signaling restricts activation and promotes maturation and antioxidant defenses in astrocytes.

BACKGROUND: cAMP signaling produces dramatic changes in astrocyte morphology and physiology. However, its involvement in phenotype acquisition and the transcriptionally mediated mechanisms of action are largely unknown. RESULTS: Here we analyzed the global transcriptome of cultured astroglial cells incubated with activators of cAMP pathways. A bulk of astroglial transcripts, 6221 annotated genes, were differentially regulated by cAMP signaling. cAMP analogs strongly upregulated genes involved in typical functions of mature astrocytes, such as homeostatic control, metabolic and structural support to neurons, antioxidant defense and communication, whereas they downregulated a considerable number of proliferating and immaturity-related transcripts. Moreover, numerous genes typically activated in reactive cells, such as scar components and immunological mediators, were repressed by cAMP. GSEA analysis contrasting gene expression profiles with transcriptome signatures of acutely isolated astrocytes and in situ evaluation of protein levels in these cells showed that cAMP signaling conferred mature and in vivo-like transcriptional features to cultured astrocytes. CONCLUSIONS: These results indicate that cAMP signaling is a key pathway promoting astrocyte maturation and restricting their developmental and activation features. Therefore, a positive modulation of cAMP signaling may promote the normal state of differentiated astrocytes and favor the protection and function of neuronal networks.

Next-generation sequencing in routine brain tumor diagnostics enables an integrated diagnosis and identifies actionable targets.

With the number of prognostic and predictive genetic markers in neuro-oncology steadily growing, the need for comprehensive molecular analysis of neuropathology samples has vastly increased. We therefore developed a customized enrichment/hybrid-capture-based next-generation sequencing (NGS) gene panel comprising the entire coding and selected intronic and promoter regions of 130 genes recurrently altered in brain tumors, allowing for the detection of single nucleotide variations, fusions, and copy number aberrations. Optimization of probe design, library generation and sequencing conditions on 150 samples resulted in a 5-workday routine workflow from the formalin-fixed paraffin-embedded sample to neuropathological report. This protocol was applied to 79 retrospective cases with established molecular aberrations for validation and 71 prospective cases for discovery of potential therapeutic targets. Concordance of NGS compared to established, single biomarker methods was 98.0 %, with discrepancies resulting from one case where a TERT promoter mutation was not called by NGS and three ATRX mutations not being detected by Sanger sequencing. Importantly, in samples with low tumor cell content, NGS was able to identify mutant alleles that were not detectable by traditional methods. Information derived from NGS data identified potential targets for experimental therapy in 37/47 (79 %) glioblastomas, 9/10 (90 %) pilocytic astrocytomas, and 5/14 (36 %) medulloblastomas in the prospective target discovery cohort. In conclusion, we present the settings for high-throughput, adaptive next-generation sequencing in routine neuropathology diagnostics. Such an approach will likely become highly valuable in the near future for treatment decision making, as more therapeutic targets emerge and genetic information enters the classification of brain tumors.

Microarray and deep sequencing cross-platform analysis of the mirRNome and isomiR variation in response to epidermal growth factor.

BACKGROUND: Epidermal Growth Factor (EGF) plays an important function in the regulation of cell growth, proliferation, and differentiation by binding to its receptor (EGFR) and providing cancer cells with increased survival responsiveness. Signal transduction carried out by EGF has been extensively studied at both transcriptional and post-transcriptional levels. Little is known about the involvement of microRNAs (miRNAs) in the EGF signaling pathway. miRNAs have emerged as major players in the complex networks of gene regulation, and cancer miRNA expression studies have evidenced a direct involvement of miRNAs in cancer progression. RESULTS: In this study, we have used an integrative high content analysis approach to identify the specific miRNAs implicated in EGF signaling in HeLa cells as potential mediators of cancer mediated functions. We have used microarray and deep-sequencing technologies in order to obtain a global view of the EGF miRNA transcriptome with a robust experimental cross-validation. By applying a procedure based on Rankprod tests, we have delimited a solid set of EGF-regulated miRNAs. After validating regulated miRNAs by reverse transcription quantitative PCR, we have derived protein networks and biological functions from the predicted targets of the regulated miRNAs to gain insight into the potential role of miRNAs in EGF-treated cells. In addition, we have analyzed sequence heterogeneity due to editing relative to the reference sequence (isomiRs) among regulated miRNAs. CONCLUSIONS: We propose that the use of global genomic miRNA cross-validation derived from high throughput technologies can be used to generate more reliable datasets inferring more robust networks of co-regulated predicted miRNA target genes.

Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis.

BACKGROUND: Epidermal Growth Factor (EGF) is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer. RESULTS: By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. CONCLUSIONS: We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing) can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data.

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

PURPOSE: Published 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. METHODS: Immunohistochemistry 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-validation RESULTS: Correlation 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). CONCLUSIONS: Our 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.

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.

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.

MiRNA expression profile of human subcutaneous adipose and during adipocyte differentiation.

BACKGROUND: Potential regulators of adipogenesis include microRNAs (miRNAs), small non-coding RNAs that have been recently shown related to adiposity and differentially expressed in fat depots. However, to date no study is available, to our knowledge, regarding miRNAs expression profile during human adipogenesis. Thereby, the aim of this study was to investigate whether miRNA pattern in human fat cells and subcutaneous adipose tissue is associated to obesity and co-morbidities and whether miRNA expression profile in adipocytes is linked to adipogenesis. METHODOLOGY/PRINCIPAL FINDINGS: We performed a global miRNA expression microarray of 723 human and 76 viral mature miRNAs in human adipocytes during differentiation and in subcutaneous fat samples from non-obese (n = 6) and obese with (n = 9) and without (n = 13) Type-2 Diabetes Mellitus (DM-2) women. Changes in adipogenesis-related miRNAs were then validated by RT-PCR. Fifty of 799 miRNAs (6.2%) significantly differed between fat cells from lean and obese subjects. Seventy miRNAs (8.8%) were highly and significantly up or down-regulated in mature adipocytes as compared to pre-adipocytes. Otherwise, 17 of these 799 miRNAs (2.1%) were correlated with anthropometrical (BMI) and/or metabolic (fasting glucose and/or triglycerides) parameters. We identified 11 miRNAs (1.4%) significantly deregulated in subcutaneous fat from obese subjects with and without DM-2. Interestingly, most of these changes were associated with miRNAs also significantly deregulated during adipocyte differentiation. CONCLUSIONS/SIGNIFICANCE: The remarkable inverse miRNA profile revealed for human pre-adipocytes and mature adipocytes hints at a closely crosstalk between miRNAs and adipogenesis. Such candidates may represent biomarkers and therapeutic targets for obesity and obesity-related complications.

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.