Project description:Title: Array-based gene expression, CGH and tissue data define a 12q24 gain in neuroblastic tumors with prognostic implication. Background: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. Methods: A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumour tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s). Results: In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42%) neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis) and to those with no MYCN amplification or 12q24.31 gain (good prognosis) (P = 0.001). Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC8, RSRC2, KNTC1 and MPHOSPH9). Among these, DIABLO showed the strongest activation suggesting a putative role in neuroblastoma progression. Conclusions: The presented systematic and rapid framework, which integrates aCGH, gene expression and tissue data to obtain novel targets and biomarkers for cancer, identified a low-level gain of the 12q24.31 as a potential new biomarker for neuroblastoma progression. Furthermore, results of in silico data mining suggest a new neuroblastoma target gene, DIABLO, within this region, whose functional and therapeutic role remains to be elucidated in follow-up studies.

Project description:BACKGROUND: Malignant peripheral nerve sheath tumors (MPNSTs) are rare and highly aggressive soft tissue tumors showing complex chromosomal aberrations. In order to identify recurrent chromosomal regions of gain and loss, and thereby novel gene targets of potential importance for MPNST development and/or progression, we have analyzed DNA copy number changes in seven high-grade MPNSTs using microarray-based comparative genomic hybridization (array CGH). RESULTS: Considerable more gains than losses were observed, and the most frequent minimal recurrent regions of gain included 1q24.1-q24.2, 1q24.3-q25.1, 8p23.1-p12, 9q34.11-q34.13 and 17q23.2-q25.3, all gained in five of seven samples. The 17q23.2-q25.3 region was gained in all five patients with poor outcome and not in the two patients with disease-free survival. cDNA microarray analysis and quantitative real-time reverse transcription PCR were used to investigate expression of genes located within these regions. The gene lysyl oxidase-like 2 (LOXL2) was identified as a candidate target for the 8p23.1-p12 gain. Within 17q, the genes topoisomerase II-alpha (TOP2A), ets variant gene 4 (E1A enhancer binding protein, E1AF) (ETV4) and baculoviral IAP repeat-containing 5 (survivin) (BIRC5) showed increased expression in all samples compared to two benign tumors. Increased expression of these genes has previously been associated with poor survival in other malignancies, and for TOP2A, in MPNSTs as well. In addition, we have analyzed the expression of five micro RNAs located within the 17q23.2-q25.3 region, but none of them showed high expression levels compared to the benign tumors. CONCLUSION: Our study shows the potential of using DNA copy number changes obtained by array CGH to predict the prognosis of MPNST patients. Although no clear correlations between the expression level and patient outcome were observed, the genes TOP2A, ETV4 and BIRC5 are interesting candidate targets for the 17q gain associated with poor survival.

Project description:Array CGH analysis of breast tumors has contributed to the identification of different genomic profiles in these tumors. Loss of DNA repair by BRCA1 functional deficiency in breast cancer has been proposed as a relevant contribution to breast cancer progression for tumors with no germline mutation. Identifying the genomic alterations taking place in BRCA1 not expressing tumors will lead us to a better understanding of the cellular functions affected in this heterogeneous disease. Moreover, specific genomic alterations may contribute to the identification of potential therapeutic targets and offer a more personalized treatment to breast cancer patients.Forty seven tumors from hereditary breast cancer cases, previously analyzed for BRCA1 expression, and screened for germline BRCA1 and 2 mutations, were analyzed by Array based Comparative Genomic Hybridization (aCGH) using Agilent 4x44K arrays. Overall survival was established for tumors in different clusters using Log-rank (Mantel-Cox) Test. Gene lists obtained from aCGH analysis were analyzed for Gene Ontology enrichment using GOrilla and DAVID tools.Genomic profiling of the tumors showed specific alterations associated to BRCA1 or 2 mutation status, and BRCA1 expression in the tumors, affecting relevant cellular processes. Similar cellular functions were found affected in BRCA1 not expressing and BRCA1 or 2 mutated tumors. Hierarchical clustering classified hereditary breast tumors in four major, groups according to the type and amount of genomic alterations, showing one group with a significantly poor overall survival (p = 0.0221). Within this cluster, deletion of PLEKHO1, GDF11, DARC, DAG1 and CD63 may be associated to the worse outcome of the patients.These results support the fact that BRCA1 lack of expression in tumors should be used as a marker for BRCAness and to select these patients for synthetic lethality approaches such as treatment with PARP inhibitors. In addition, the identification of specific alterations in breast tumors associated with poor survival, immune response or with a BRCAness phenotype will allow the use of a more personalized treatment in these patients.

Project description:BackgroundDevelopment of breast cancer is a multistage process influenced by hormonal and environmental factors as well as by genetic background. The search for genes underlying this malignancy has recently been highly productive, but the etiology behind this complex disease is still not understood. In studies using animal cancer models, heterogeneity of the genetic background and environmental factors is reduced and thus analysis and identification of genetic aberrations in tumors may become easier. To identify chromosomal regions potentially involved in the initiation and progression of mammary cancer, in the present work we subjected a subset of experimental mammary tumors to cytogenetic and molecular genetic analysis.MethodsMammary tumors were induced with DMBA (7,12-dimethylbenz[a]anthrazene) in female rats from the susceptible SPRD-Cu3 strain and from crosses and backcrosses between this strain and the resistant WKY strain. We first produced a general overview of chromosomal aberrations in the tumors using conventional kartyotyping (G-banding) and Comparative Genome Hybridization (CGH) analyses. Particular chromosomal changes were then analyzed in more details using an in-house developed BAC (bacterial artificial chromosome) CGH-array platform.ResultsTumors appeared to be diploid by conventional karyotyping, however several sub-microscopic chromosome gains or losses in the tumor material were identified by BAC CGH-array analysis. An oncogenetic tree analysis based on the BAC CGH-array data suggested gain of rat chromosome (RNO) band 12q11, loss of RNO5q32 or RNO6q21 as the earliest events in the development of these mammary tumors.ConclusionsSome of the identified changes appear to be more specific for DMBA-induced mammary tumors and some are similar to those previously reported in ACI rat model for estradiol-induced mammary tumors. The later group of changes is more interesting, since they may represent anomalies that involve genes with a critical role in mammary tumor development. Genetic changes identified in this work are at very small scales and thus may provide a more feasible basis for the identification of the target gene(s). Identification of the genes underlying these chromosome changes can provide new insights to the mechanisms of mammary carcinogenesis.

Project description:Title: Array-based gene expression, CGH and tissue data define a 12q24 gain in neuroblastic tumors with prognostic implication. Background: Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. Methods: A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumour tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s). Results: In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42%) neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis) and to those with no MYCN amplification or 12q24.31 gain (good prognosis) (P = 0.001). Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC8, RSRC2, KNTC1 and MPHOSPH9). Among these, DIABLO showed the strongest activation suggesting a putative role in neuroblastoma progression. Conclusions: The presented systematic and rapid framework, which integrates aCGH, gene expression and tissue data to obtain novel targets and biomarkers for cancer, identified a low-level gain of the 12q24.31 as a potential new biomarker for neuroblastoma progression. Furthermore, results of in silico data mining suggest a new neuroblastoma target gene, DIABLO, within this region, whose functional and therapeutic role remains to be elucidated in follow-up studies. High-resolution aCGH was utilized to identify novel genetic alterations in two neuroblastoma cell lines, NGP and IMR-32. Through the integration of gene copy number and gene expression data, the impact of copy number changes on expression levels was determined. Fluorescence in situ hybridization (FISH) on a tissue microarray (TMA) format was used to assess the clinical significance of the identified copy number increase at 12q24.31 in neuroblastoma patients. Finally, we used in silico data mining of publicly available transcriptomics data, to evaluate the transcriptional consequences of the detected 12q24.31 alteration and to identify subsequently activated gene(s). Here, gene expression analysis of the NGP and IMR-32 cell lines was performed. A pooled sample of 16 cancer cell lines was used as reference.

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Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication.

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Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication.

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