Dataset Information

Primary human neuroblastoma

ABSTRACT: Reference1: Ohira M, Oba S, Nakamura Y, Isogai E, Kaneko S, Nakagawa A, Hirata T, Kubo H, Goto T, Yamada S, Yoshida Y, Fuchioka M, Ishii S, Nakagawara A. Expression profiling of human primary Expression profiling using a tumor-specific cDNA microarray predicts the prognosis of intermediate risk neuroblastomas. Cancer Cell. 2005 Apr;7(4):337-50. To predict the prognosis of neuroblastoma patients and choose a better therapeutic protocol, we developed a cDNA microarray carrying 5340 genes obtained from primary neuroblastomas and examined 136 tumor samples. We made a probabilistic output statistical classifier that provided a high accuracy in prognosis prediction (89% at 5 years) and a highly reliable method to validate it. Kaplan-Meier analysis indicated that the patients in an intermediate group defined by existing markers are divided by microarray into two further groups with 5 year survivals for 36% and 89% of patients (p < 10(-4)), i.e., with unfavorably and favorably predicted neuroblastomas, respectively. According to these results, we developed a gene subset chip for a clinical tool, for which our classifier exhibited 88% prediction accuracy. Datasets: neuroblastomas by CCC-NB200-Chip: GSM42338-GSM42387 Expression profiling of human primary neuroblastomas by CCC-NB5000-Chip: GSM42391-GSM42526 Keywords = Neuroblastoma Keywords: other

ORGANISM(S): Homo sapiens

PROVIDER: GSE2283 | GEO | 2005/05/12

SECONDARY ACCESSION(S): PRJNA91339

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Background: Validated markers to predict outcome in rectal cancer patients treated with multimodal therapy remain elusive. Identifying molecular profiles for disease prognosis would be required for the design of clinical trials aimed at optimizing risk-adapted therapies. We have therefore used whole genome expression profiling of tumors of a large cohort of patients enrolled in the multicenter trials of the German Rectal Cancer Study Group (GRCSG) to identify molecular profiles for individualized therapy. Methods: We prospectively collected pretherapeutic biopsies from patients (n=300) treated according to the GRCSG trial guidelines from seven different German surgical departments using rigid quality controls. These samples were profiled by global gene expression analysis and a classifier developed to predict postoperative lymph node status and Disease Free Survival (DFS). The performance of the classifier was validated with an independent, prospectively collected set of samples. Findings: The final training and test set included 198 patients. Analyzes for postoperative nodal status and DFS revealed 69 and 674 differentially regulated genes, respectively. Depending on the classifier the accuracy to predict lymph node status ranged from 64% to 69% with negative predictive values between 72% and 74%. Stratification according to DFS resulted in a good (n=99), bad (n=96) and a small very bad prognosis group (n=3). Based on linear discriminant analysis the classifier for positive lymph node status was validated in 47 independent patients and revealed an accuracy of 72% and a positive predictive value of 100%. Thereby, prediction based on molecular profiling is superior to prediction based on conventional clinical markers. Interpretation: Whole genome expression analysis of pretherapeutical biopsies resulted in a molecular classifier of disease prognosis. This classifier was successfully validated. The high positive predictive value for post therapeutic lymph node status allows identification of patients requiring alternative or intensified treatment protocols. These data are currently validated for their clinical applicability and should be taken as basis for future molecular driven clinical trials to develop risk-adapted treatments.

Dataset Information

Primary human neuroblastoma

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure