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  • neuroblastoma  (21)
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  • 1
    Keywords: EXPRESSION ; SURVIVAL ; tumor ; Germany ; MODEL ; CLASSIFICATION ; DIAGNOSIS ; SYSTEM ; SYSTEMS ; COHORT ; DISEASE ; RISK ; DISTINCT ; GENE ; GENE-EXPRESSION ; microarray ; ACCURACY ; validation ; PATIENT ; BREAST-CANCER ; STAGE ; TRIAL ; TRIALS ; gene expression ; microarrays ; DELETIONS ; HIGH-RISK ; PROBES ; UNITED-STATES ; PREDICTION ; pathology ; CHILDREN ; DIFFERENTIAL EXPRESSION ; neuroblastoma ; INTEGRATION ; REGRESSION ; SIGNATURE ; PREDICTOR ; SPECIMENS ; SUBGROUPS ; PREDICTS ; SET ; CLINICAL COURSE ; 11Q
    Abstract: Purpose To develop a gene expression - based classifier for neuroblastoma patients that reliably predicts courses of the disease. Patients and Methods Two hundred fifty-one neuroblastoma specimens were analyzed using a customized oligonucleotide microarray comprising 10,163 probes for transcripts with differential expression in clinical subgroups of the disease. Subsequently, the prediction analysis for microarrays (PAM) was applied to a first set of patients with maximally divergent clinical courses ( n = 77). The classification accuracy was estimated by a complete 10-times-repeated 10-fold cross validation, and a 144-gene predictor was constructed from this set. This classifier's predictive power was evaluated in an independent second set ( n = 174) by comparing results of the gene expression based classification with those of risk stratification systems of current trials from Germany, Japan, and the United States. Results The first set of patients was accurately predicted by PAM (cross-validated accuracy, 99%). Within the second set, the PAM classifier significantly separated cohorts with distinct courses (3-year event-free survival [EFS] 0.86 +/- 0.03 [ favorable; n = 115] v 0.52 +/- 0.07 [ unfavorable; n = 59] and 3-year overall survival 0.99 +/- 0.01 v 0.84 +/- 0.05; both P 〈.0001) and separated risk groups of current neuroblastoma trials into subgroups with divergent outcome (NB2004: low-risk 3-year EFS 0.86 +/- 0.04 v 0.25 +/- 0.15, P 〈.0001; intermediate-risk 1.00 v 0.57 +/- 0.19, P =.018; high-risk 0.81 +/- 0.10 v 0.56 +/- 0.08, P =.06). In a multivariate Cox regression model, the PAM predictor classified patients of the second set more accurately than risk stratification of current trials from Germany, Japan, and the United States ( P 〈.001; hazard ratio, 4.756 [95% CI, 2.544 to 8.893]). Conclusion Integration of gene expression - based class prediction of neuroblastoma patients may improve risk estimation of current neuroblastoma trials
    Type of Publication: Journal article published
    PubMed ID: 17075126
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  • 2
    Keywords: tumor ; Germany ; COHORT ; GENE ; HYBRIDIZATION ; TUMORS ; PATIENT ; MARKER ; SEQUENCE ; DELETION ; STAGE ; AMPLIFICATION ; COMPARATIVE GENOMIC HYBRIDIZATION ; COPY NUMBER ; PATTERNS ; microarrays ; NUMBER ; MARKERS ; REGION ; REGIONS ; PHENOTYPE ; REVEALS ; CHILDREN ; SEGMENTS ; 1p ; neuroblastoma ; CHROMOSOMES ; SUBSET ; CYTOGENETIC ANALYSIS ; BREAKPOINTS ; MYCN-AMPLIFICATION ; function ; LOSSES ; HIGH-RESOLUTION ANALYSIS ; genomic ; GENOMIC ALTERATIONS ; 11Q ; CGH ANALYSIS ; DNA-COPY-NUMBER
    Abstract: The study of genomic alterations in neuroblastoma is of particular importance since several cytogenetic markers proved to be closely associated with the clinical phenotype. To disclose patterns of gains and losses, we performed high-resolution oligonucleotide array-based comparative genomic hybridization (aCGH). A total cohort of 90 patients was classified into 6 subsets according to tumor stage and outcome: Stages 1-3+ (with event), Stage 1-3- (no event), Stage 4+/-, and Stage 4S+/-. The aberration patterns in Stages 1-3- and 4S- tumors differed from all other groups as they were predominantly characterized by losses (3, 4, 14, X) and gains (7, 17) of whole chromosomes. However, 59/65 (91%) tumors of Stages 1-3+ or Stage 4 revealed numerous structural copy number alterations (sCNA). While deletions in chromosomes 1, 3, and I I discriminated outcome in Stage 4, there were no specific sCNA that distinguished tumor stage within the subgroup of unfavorable tumors. sCNA in 1p, 3p, 11q, 17q, or MYCN amplification (MNA) was seen among 22/24 patients who died, 10/12 with metastatic relapses, and 5/9 with local recurrences. Detailed breakpoint analyses on chromosomes 1, 3, 11, and 17 disclosed preferred breaking areas, although breakpoints were not identical. Amplifications were found in 18 patients and involved 2p24 (MYCN) and other segments of chromosome 2, as well as regions on chromosome arms 6q, 12q, and 17q. One single feature in 21q21.1 (BU678720, without known function yet) attracted particular attention since five patients showed a homozygous loss of this sequence. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat. (c) 2006 Wiley-Liss, Inc
    Type of Publication: Journal article published
    PubMed ID: 16958102
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  • 3
    Keywords: CANCER ; EXPRESSION ; Germany ; MODEL ; PATHWAY ; THERAPY ; CLASSIFICATION ; DIAGNOSIS ; COHORT ; DISEASE ; DISTINCT ; GENE ; GENE-EXPRESSION ; GENES ; microarray ; ACCURACY ; validation ; PATIENT ; MARKER ; tumour ; STAGE ; PROGRESSION ; AMPLIFICATION ; PATTERNS ; gene expression ; meta-analysis ; PHENOTYPE ; PREDICTION ; SELECTION ; pathology ; MYCN ; neuroblastoma ; SINGLE ; ONCOLOGY ; REGRESSION ; RE ; METAANALYSIS ; analysis ; methods ; PROFILES ; EXPRESSION PROFILES ; RISK STRATIFICATION ; RARE ; SET ; PLATFORM
    Abstract: Background: Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients. Methods: We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage ( 3 or 4) tumours without MYCN amplification that show contrasting outcomes ( alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms. Results: In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification. Conclusion: Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome
    Type of Publication: Journal article published
    PubMed ID: 17531100
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  • 4
    Keywords: EXPRESSION ; tumor ; evaluation ; Germany ; THERAPY ; DIAGNOSIS ; SYSTEM ; SYSTEMS ; DISEASE ; RISK ; DISTINCT ; GENE ; GENE-EXPRESSION ; PATIENT ; DNA ; MARKER ; TRIAL ; TRIALS ; PROGRESSION ; COMPARATIVE GENOMIC HYBRIDIZATION ; PATTERNS ; gene expression ; NUMBER ; AGE ; ABERRATIONS ; MARKERS ; ONCOGENE ; PHENOTYPE ; PROGNOSTIC-SIGNIFICANCE ; PREDICTION ; CHILDREN ; neuroblastoma ; N-MYC ; molecular ; REGRESSION ; review ; PATTERN ; THERAPIES ; PROTOCOL ; PROGNOSTIC MARKER ; PROFILES ; EXPRESSION PROFILES ; LOSSES ; PEDIATRIC-ONCOLOGY-GROUP ; VARIABLES ; PREDICT ; pediatric ; STAGE NEUROBLASTOMA ; PROFILE ; pediatrics ; neoplasm ; MICRORNA EXPRESSION ; CHROMOSOME ARM 17Q ; CLINICAL RELEVANCE ; genomic aberration ; MYC GENE AMPLIFICATION ; risk estimation ; TUMOR-CELL PLOIDY
    Abstract: The pediatric tumor neuroblastoma is a heterogeneous disease: Patients' clinical courses can range from spontaneous regression to fatal progression of the disease. Accordingly, treatment protocols vary from "wait and see" approaches to intensive multimodal therapies. Accurate risk estimation of the patients is therefore mandatory to choose the most adequate therapy. Current trials stratify by a limited number of clinical variables, such as stage of the disease and age of the patient at diagnosis, as well as molecular markers, such as amplification of the oncogene MYCN and loss of the short arm of chromosome 1. However, misclassifications of patients still occur, and thus, a precise prediction of the clinical courses remains a challenge of neuroblastoma research. In recent years, genomic alterations and gene expression profiles of this neoplasm have been characterized thoroughly. It has been shown that the diverse clinical phenotypes are reflected by both specific cytogenetic aberrations and distinct gene expression patterns. Moreover, a variety of DNA copy number changes and gene expression-based classifiers have been described that could predict the outcome of neuroblastoma patients more precisely than established prognostic variables. In this review, the recent advances in the detection and evaluation of molecular prognostic markers for neuroblastoma patients are summarized, and their current and potential contribution to risk stratification systems is discussed
    Type of Publication: Journal article published
    PubMed ID: 18478485
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  • 5
    Keywords: STAGE ; PROGRESSION ; AMPLIFICATION ; chemotherapy ; DELETIONS ; SPONTANEOUS REGRESSION ; PREDICTION ; pathology ; N-MYC ; EXPRESSION-BASED CLASSIFICATION
    Abstract: Purpose: To optimize neuroblastoma treatment stratification, we aimed at developing a novel risk estimation system by integrating gene expression-based classification and established prognostic markers. Material and Methods: Gene expression profiles were generated from 709 neuroblastoma specimens using customized 4x44K microarrays. Classification models were built using 75 tumors with contrasting courses of disease. Validation was performed in an independent test set (n=634) by Kaplan-Meier estimates and Cox regression analyses. Results: The best-performing classifier predicted patient outcome with an accuracy of 0.95 (sensitivity 0.93, specificity 0.97) in the validation cohort. The highest potential clinical value of this predictor was observed for current low-risk patients (LR: 5-year EFS 0.84+/-0.02 vs 0.29+/-0.10; 5-year OS 0.99+/-0.01vs 0.76+/-0.11; both p〈0.001) and intermediate-risk patients (IR: 5-year EFS 0.88+/-0.06 vs 0.41+/-0.10; 5-year OS 1.0 vs 0.70+/-0.09; both p〈0.001). In multivariate Cox regression models for LR/IR patients the classifier outperformed risk assessment of the current German trial NB2004 (EFS: HR 5.07, 95%-CI 3.20-8.02, OS: HR 25.54, 95%-CI 8.40-77.66; both p〈0.001). Based on these findings, we propose to integrate the classifier into a revised risk stratification system for LR/IR patients. According to this system, we identified novel subgroups with poor outcome (5-year EFS 0.19+/-0.08; 5-year OS 0.59+/-0.1), for whom we propose intensified treatment, and with beneficial outcome (5-year EFS 0.87+/-0.05; 5-year OS 1.0), who may benefit from treatment de-escalation. Conclusion: Combination of gene expression-based classification and established prognostic markers improves risk estimation of LR/IR neuroblastoma patients. We propose to implement our revised treatment stratification system in a prospective clinical trial.
    Type of Publication: Journal article published
    PubMed ID: 25231397
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  • 6
    Keywords: CELLS ; EXPRESSION ; proliferation ; SURVIVAL ; carcinoma ; CELL ; Germany ; CLASSIFICATION ; LUNG-CANCER ; GENE ; GENE-EXPRESSION ; PATIENT ; MARKER ; primary ; BIOLOGY ; MOLECULAR-BIOLOGY ; MOLECULE ; NO ; PROGRESSION ; MALIGNANCIES ; gene expression ; AGE ; MUTATION ; genetics ; CERVICAL-CANCER ; MARKERS ; MUTATIONS ; ADHESION ; ONCOGENE ; CHILDREN ; ADHESION MOLECULE ; OVEREXPRESSION ; heredity ; HYPERMETHYLATION ; neuroblastoma ; molecular biology ; molecular ; ONCOLOGY ; cell adhesion ; cell proliferation ; analysis ; SUPPRESSOR ; IMMUNOGLOBULIN SUPERFAMILY ; DISEASE PROGRESSION ; LOSSES ; PROMOTER METHYLATION ; ENGLAND ; STAGE NEUROBLASTOMA ; tumor suppressor ; IN-SILICO ; CADM1 ; LACTATE-DEHYDROGENASE RELEASE ; outcome assessment (health care) ; TSLC1 GENE
    Abstract: Cell adhesion molecule 1 (CADM1) is a putative tumour suppressor gene, which is downregulated in many solid tumours. In neuroblastoma, loss of CADM1 expression has recently been found in disseminated tumours with adverse outcome, prompting us to investigate its role in neuroblastoma tumour progression. Oligonucleotide-microarray analysis of 251 neuroblastoma specimens demonstrated that CADM1 downregulation is associated with unfavourable prognostic markers like disseminated stage 4, age 〉 18 months, MYCN amplification and chromosome 11q alterations (P 〈 0.001 each). Furthermore, low CADM1 expression was signficantly correlated with unfavourable gene expression-based classification (P 〈 0.001) and adverse patient outcome (P 〈 0.001). Bisulphite sequencing and genetic analysis of 18 primary neuroblastomas suggested that neither haploinsufficiency nor hypermethylation is regularly involved in CADM1 gene silencing in neuroblastoma, which is in contrast to results obtained in other malignancies. In addition, no mutations disrupting the CADM1 reading frame were found in 25 primary neuroblastomas. Over-expression of CADM1 in neuroblastoma cells resulted in significant reduction of proliferation, viability and colony formation in soft agar. Collectively, our results suggest that downregulation of CADM1 tumour suppressor gene expression is a critical event in neuroblastoma pathogenesis resulting in tumour progression and unfavourable patient outcome
    Type of Publication: Journal article published
    PubMed ID: 18084322
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  • 7
    Keywords: RECEPTOR ; APOPTOSIS ; CELLS ; EXPRESSION ; SURVIVAL ; tumor ; TUMOR-CELLS ; CELL ; human ; KINASE ; PATHWAY ; PATHWAYS ; TYROSINE KINASE ; COHORT ; DEATH ; LONG-TERM ; GENE ; DIFFERENTIATION ; TUMORS ; NEUROBLASTOMA-CELLS ; PATIENT ; ACTIVATION ; MECHANISM ; DOMAIN ; BINDING ; CELL-DEATH ; REGION ; LONG-TERM SURVIVAL ; specificity ; DOMAINS ; neuroblastoma ; signaling ; NEURONS ; medulloblastoma ; interaction ; LEVEL ; cell death ; TECHNOLOGY ; USA ; pediatric ; MEDIATOR ; TYROSINE ; 2-HIT MECHANISM ; CEREBRAL CAVERNOUS MALFORMATIONS ; P75 NEUROTROPHIN RECEPTOR
    Abstract: The TrkA receptor tyrosine kinase is crucial for differentiation and survival of nerve-growth-factor-dependent neurons. Paradoxically, TrkA also induces cell death in pediatric tumor cells of neural origin, via an unknown mechanism. Here, we show that CCM2, a gene product associated with cerebral cavernous malformations, interacts with the juxtamembrane region of TrkA via its phosphotyrosine binding (PTB) domain and mediates TrkA-induced death in diverse cell types. Both the PTB and Karet domains of CCM2 are required for TrkA-dependent cell death, such that the PTB domain determines the specificity of the interaction, and the Karet domain links to death pathways. Downregulation of CCM2 in medulloblastoma or neuroblastoma cells attenuates TrkA-dependent death. Combined high expression levels of CCM2 and TrkA are correlated with long-term survival in a large cohort of human neuroblastoma patients. Thus, CCM2 is a key mediator of TrkA-dependent cell death in pediatric neuroblastic tumors
    Type of Publication: Journal article published
    PubMed ID: 19755102
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  • 8
    Keywords: tumor ; Germany ; PATHWAY ; PATHWAYS ; CLASSIFICATION ; DISEASE ; RISK ; GENE-EXPRESSION ; microarray ; TUMORS ; ACCURACY ; PATIENT ; MARKER ; PROGRESSION ; COMPARATIVE GENOMIC HYBRIDIZATION ; gene expression ; MUTATION ; TUMOR PROGRESSION ; TUMOR-SUPPRESSOR GENE ; SIGNALING PATHWAY ; SIGNALING PATHWAYS ; MUTATIONS ; CHILDREN ; BEHAVIOR ; neuroblastoma ; N-MYC ; signaling ; review ; GENE-EXPRESSION PROFILES ; ACCURATE ; MOLECULAR CLASSIFICATION ; STAGE NEUROBLASTOMA ; ARRAY-CGH ; outcome ; CHROMOSOME ARM 17Q ; pediatric oncology ; HIGH-RISK NEUROBLASTOMAS ; Genetic ; therapeutic ; STRATEGY ; 4S NEUROBLASTOMA ; CHILDRENS ONCOLOGY GROUP ; embryonal tumors ; METASTATIC NEUROBLASTOMA ; oncogenomics
    Abstract: For many decades, neuroblastoma has remained a challenging disease for both clinicians and researchers. Now, techniques that efficiently specify both comprehensive genetic and gene-expression alterations of neuroblastoma tumors have provided molecular markers that indicate tumor behavior and patient outcome with very high accuracy, Once the anticipated value of these markers has been confirmed in ongoing studies, patients may profit from more accurate risk assessment by integrating these markers into clinical routine. Moreover, disclosing further tumor-initiating events, such as the recently revealed oncogenic mutations of ALK, will further promote the elucidation of the genetic etiology of the disease. Together with recent information on altered signaling pathways in aggressively growing tumors, this knowledge will help to establish therapeutic strategies specifically targeting molecular key factors of neuroblastoma tumor progression
    Type of Publication: Journal article published
    PubMed ID: 19519203
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  • 9
    Keywords: EXPRESSION ; SURVIVAL ; tumor ; CELL LUNG-CANCER ; Germany ; CLASSIFICATION ; DISEASE ; RISK ; DISTINCT ; GENE ; GENE-EXPRESSION ; GENES ; microarray ; transcription ; DIFFERENTIATION ; TUMORS ; PATIENT ; MARKER ; STAGE ; IDENTIFICATION ; AMPLIFICATION ; PATTERNS ; gene expression ; microarrays ; DESIGN ; AGE ; PCR ; TUMOR-SUPPRESSOR GENE ; PREDICTION ; CHILDREN ; MUTANT MICE ; DIFFERENTIAL EXPRESSION ; neuroblastoma ; CANDIDATE GENES ; REVERSE TRANSCRIPTION-PCR ; LEVEL ; TARGET GENES ; SUBTYPES ; PROFILES ; EXPRESSION PATTERNS ; SIGNATURE ; DEVELOPMENTAL EXPRESSION ; CANDIDATE ; VARIABLES ; SUBGROUPS ; CANNABINOID RECEPTOR ; MICROTUBULE-ASSOCIATED PROTEIN ; NICOTINIC RECEPTORS ; STAGE NEUROBLASTOMA ; SYNAPSIN-III
    Abstract: Purpose: Identification of molecular characteristics of spontaneously regressing stage IVS and progressing stage IV neuroblastoma to improve discrimination of patients with metastatic disease following favorable and unfavorable clinical courses. Experimental Design: Serial analysis of gene expression profiles were generated from five stage IVS and three stage IV neuroblastoma. Differential expression of candidate genes was evaluated by real-time quantitative reverse transcription-PCR in 76 pretreatment tumor samples (stage IVS n = 27 and stage IV n = 49). Gene expression-based outcome prediction was determined by Prediction Analysis for Microarrays using 38 tumors as a training set and 38 tumors as a test set. Results: Comparison of serial analysis of gene expression profiles from stage IV and IVS neuroblastoma revealed similar to 500 differentially expressed transcripts, Genes related to neuronal differentiation were observed more frequently in stage IVS tumors as determined by associating transcripts to Gene Ontology annotations. Forty-one candidate genes were evaluated by quantitative reverse transcription- PCR and 18 were confirmed to be differentially expressed (P 〈= 0.001). Classification of patients according to expression patterns of these 18 genes using Prediction Analysis for Microarrays discriminated two subgroups with significantly differing event-free survival (96 +/- 6% versus 40 +/- 8% at 3 years; P 〈 0.0001) and overall survival (100% versus 72 +/- 7 % at 3 years; P = 0.0003). This classifier was the only independent covariate marker in a multivariate analysis considering the variables stage, age, MYCN amplification, and gene signature. Conclusions: Spontaneously regressing and progressing metastatic neuroblastoma differ by specific gene expression patterns, indicating distinct levels of neuronal differentiation and allowing for an improved risk estimation of children with disseminated disease
    Type of Publication: Journal article published
    PubMed ID: 16951229
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  • 10
    Keywords: CANCER ; EXPRESSION ; SURVIVAL ; CLASSIFICATION ; DIAGNOSIS ; INFORMATION ; SYSTEM ; COHORT ; DISEASE ; RISK ; GENE ; GENE-EXPRESSION ; GENES ; microarray ; validation ; PATIENT ; prognosis ; SEQUENCE ; SEQUENCES ; IDENTIFICATION ; AMPLIFICATION ; gene expression ; MICROARRAY DATA ; microarrays ; DESIGN ; NUMBER ; CANCER-PATIENTS ; PREDICTION ; SELECTION ; CANCER PATIENTS ; neuroblastoma ; ONCOLOGY ; GENE-EXPRESSION PROFILES ; development ; prospective ; RISK STRATIFICATION ; outcome ; SIGNATURES ; EXPRESSION SIGNATURES ; STRATIFICATION
    Abstract: Purpose: Reliable prognostic stratification remains a challenge for cancer patients, especially for diseases with variable clinical course such as neuroblastoma. Although numerous studies have shown that outcome might be predicted using gene expression signatures, independent cross-platform validation is often lacking. Experimental Design: Using eight independent studies comprising 933 neuroblastoma patients, a prognostic gene expression classifier was developed, trained, tested, and validated. The classifier was established based on reanalysis of four published studies with updated clinical information, reannotation of the probe sequences, common risk definition for training cases, and a single method for gene selection (prediction analysis of microarray) and classification (correlation analysis). Results: Based on 250 training samples from four published microarray data sets, a correlation signature was built using 42 robust prognostic genes. The resulting classifier was validated on 351 patients from four independent and unpublished data sets and on 129 remaining test samples from the published studies. Patients with divergent outcome in the total cohort, as well as in the different risk groups, were accurately classified (log-rank P 〈 0.001 for overall and progression-free survival in the four independent data sets). Moreover, the 42-gene classifier was shown to be an independent predictor for survival (odds ratio, 〉5). Conclusion: The strength of this 42-gene classifier is its small number of genes and its cross-platform validity in which it outperforms other published prognostic signatures. The robustness and accuracy of the classifier enables prospective assessment of neuroblastoma patient outcome. Most importantly, this gene selection procedure might be an example for development and validation of robust gene expression signatures in other cancer entities. Clin Cancer Res; 16(5); 1532-41. (C)2010 AACR
    Type of Publication: Journal article published
    PubMed ID: 20179214
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