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Genome-wide profiling of follicular lymphoma by array comparative genomic hybridization

ABSTRACT: The secondary genetic events associated with follicular lymphoma (FL) progression are not well defined. We applied genome-wide BAC array comparative genomic hybridization to 106 diagnostic biopsies of FL to characterize regional genomic imbalances. Using an analytical approach that defined regions of copy number change as intersections between visual annotations and a Hidden Markov model-based algorithm, we identified 71 regional alterations that were recurrent in ≥10% of cases. These ranged in size from ~200 kb to 44 Mb, affecting chromosomes 1, 5, 6, 7, 8, 10, 12, 17, 18, 19, and 22. We also demonstrated by cluster analysis that 46.2% of the 106 cases could be sub-grouped based on the presence of +1q, +6p/6q-, +7 or +18. Survival analysis showed that 21 of the 71 regions correlated significantly with inferior overall survival (OS). Of these 21 regions, 16 were independent predictors of OS using a multivariate Cox model that included the International Prognostic Index (IPI) Score. Two of these 16 regions (1p36.22-p36.33 and 6q21-q24.3) were also predictors of transformation risk and independent of IPI. These prognostic features may be useful to identify high-risk patients as candidates for risk-adapted therapies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE12393 | GEO | 2008/08/09

SECONDARY ACCESSION(S): PRJNA113149

REPOSITORIES: GEO

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Genome-wide profiling of follicular lymphoma by array comparative genomic hybridization

Project description:The secondary genetic events associated with follicular lymphoma (FL) progression are not well defined. We applied genome-wide BAC array comparative genomic hybridization to 106 diagnostic biopsies of FL to characterize regional genomic imbalances. Using an analytical approach that defined regions of copy number change as intersections between visual annotations and a Hidden Markov model-based algorithm, we identified 71 regional alterations that were recurrent in â?¥10% of cases. These ranged in size from ~200 kb to 44 Mb, affecting chromosomes 1, 5, 6, 7, 8, 10, 12, 17, 18, 19, and 22. We also demonstrated by cluster analysis that 46.2% of the 106 cases could be sub-grouped based on the presence of +1q, +6p/6q-, +7 or +18. Survival analysis showed that 21 of the 71 regions correlated significantly with inferior overall survival (OS). Of these 21 regions, 16 were independent predictors of OS using a multivariate Cox model that included the International Prognostic Index (IPI) Score. Two of these 16 regions (1p36.22-p36.33 and 6q21-q24.3) were also predictors of transformation risk and independent of IPI. These prognostic features may be useful to identify high-risk patients as candidates for risk-adapted therapies. Array comparative genomic hybridization analysis of 106 follicular lymphoma diagnostic biopsies

2010-05-25 | E-GEOD-12393 | biostudies-arrayexpress

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Project description:Malignant pleural mesothelioma (MPM) is an aggressive tumor with a dismal overall survival (OS) and to date few molecular markers are available to guide patient management. This study aimed to identify a prognostic miRNA signature in MPM patients who did not undergo tumor resection. Whole miRNA profiling using a microarray platform was performed on 26 unresected MPM with distinct clinical outcome: 15 patients had aggressive disease (OS<12 months) and 11 patients indolent disease (OS>36 months). Three prognostic miRNAs (mir-99a, let-7c and miR-125b) encoded at the same cluster (21q21) were selected for further validation and tested on publicly available miRNA sequencing data (TCGA) from 72 MPM patients with survival data. A risk model was built based on these 3 miRNAs that was validated by quantitative PCR in an independent set of 30 MPM patients. High risk patients had shorter median OS (7.6 months) as compared with low-risk patients (median not reached). In the multivariate Cox model, a high risk score was an independently associated with shorter OS (HR=3.14; 95% CI, 1.18–8.34; P=0.022). Our study identified that the downregulation of the miR-99a/let-7/miR-125b miRNA cluster predicts poor outcome in unresected MPM.

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RNA Sequencing Quantitative Analysis of cell lines derived from tumours from two mouse models of human osteosarcoma that recapitulate clinically distinct human osteosarcoma subtypes.

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Clinical impact of a novel microRNA chemo-sensitivity predictor in gastroesophageal cancer

Project description:Background: miRNAs might be potentially useful biomarkers for prediction of response to chemotherapeutic agents, radiotherapy and survival. The aim of this retrospective study was to validate miRNA response predictors in a cohort of patients with gastroesophageal cancer in order to predict overall survival (OS) and disease-specific survival (DSS). Material and methods: The study population encompassed 53 patients treated with curative intended for loco-regional gastroesophageal cancer. miRNA expression was quantified from pre-therapeutic and diagnostic, formalin-fixed, paraffin embedded tumor specimens using Affymetrix GeneChip miRNA 1.0 Array. Based on growth inhibition of the NCI60 panel in the presence of cisplatin, epirubicine and capecitabine, a miRNA based response predictor was developed. The Cox proportional hazards model was applied to assess the correlations of the response predictor with OS and DSS. Results: A univariate analysis demonstrated a statistical significant improvement of OS for patients who had undergone surgical resection with prediction scores above the median prediction score (HR: 0.41 (95% CI: 0.17-0.96). Adjusting for surgery and stage, this predictor was identified to be independently associated with both OS (HR: 0.37 (95% CI: 0.16-0.87)) and DSS (HR: 0.32 (0.12-0.87)). Conclusion: The miRNA profile predictive for sensitivity to cisplatin, epirubicine and capecitabine was shown to be independently associated with OS and DSS in patients with gastroesophageal cancer. Tumor biopsies from 53 patients with gastroesophageal cancer *** Submitter has provided limited clinical information. Thus, this submission is incomplete. ***

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