Project description:Distinct genetic abnormalities such as TP53 deletion at 17p13.1, have been identified as having an adverse prognostic relevance in B-cell chronic lymphocytic leukemia (B-CLL). Conventional cytogenetic studies have shown that TP53 deletion in B-CLL is associated predominantly with 17p loss resulting from complex chromosomal rearrangements. We performed genome-wide DNA (SNPs arrays), fluorescence in situ hybridization (FISH) and gene expression profiling (GEP) analyses to investigate the significance of 17p loss in a panel of 71 genetically well-characterized B-CLLs in Binet stage A, 18 of which carried a TP53 monoallelic deletion. Combined SNP arrays and FISH approaches showed 17p loss in all of the TP53-deleted cases, with breakpoints scattered along the 17p11.2 region. Mutations in exons 5 to 9 of TP53 were found in 9/12 deleted samples. GEP of 60 B-CLLs, including 7 patients with 17p loss, identified 40 differentially expressed genes in 17p- versus 17p normal samples, 35 of which were down-regulated in 17p- tumors. The majority (30/35) of these transcripts, including putative tumor suppressor genes, mapped to 17p. Overall, these data indicate that, beside TP53 deletion, the concomitant loss of 17p arm may contribute to the strong negative prognostic impact known to be associated with this lesion in B-CLL. Keywords: genomic analysis of B-CLL with 17p loss patients This series of microarray experiments contains the genome-wide profiles of purified B-cell chronic lymphocytic leukemia (B-CLL) cells obtained from 12 newly diagnosed patients (Binet stage A). Peripheral blood mononuclear cells from B-CLL patients were isolated by Ficoll-Hypaque density-gradient centrifugation and the proportion of CD5/CD19/CD23 triple positive B cells in the suspension was determined by direct immunofluorescence performed using a FACS-sort flow cytometer with antibodies to: CD19 FITC/PE, CD23 PE and CD5 Cy-Chrome. If B-CLL cells were less than 90%, T cells, NK cells and monocytes were removed by negative selection using CD3, CD56, CD16, and CD14 monoclonal antibody treatment followed by magnetic beads. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 40 micrograms of fragmented biotin-labelled DNA were hybridized on GeneChip Human Mapping 50K XbaI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChipÂ® Operating Software (GCOS version 1.4). Copy number values for individual SNPs were extracted and converted from CEL files into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares. Genomic Smoothing analysis was performed by using the smoothing window of 1 Mb, and inferred copy number states were derived from a Hidden Markov Model (HMM) based algorithm implemented in CNAT 4.0.1.

Project description:A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide dosage effect on gene and microRNA expression Multiple myeloma (MM) is characterized by marked genomic instability. Beyond structural rearrangements, a relevant role in its biology is represented by allelic imbalances leading to significant variations in ploidy status. To better elucidate the genomic complexity of MM, we analyzed a panel of 45 patients using combined FISH and microarray approaches. Using a self-developed procedure to infer exact local copy numbers for each sample, we identified a significant fraction of patients showing marked aneuploidy. A conventional clustering analysis showed that aneuploidy, chromosome 1 alterations, hyperdiploidy and recursive deletions at 1p and chromosomes 13, 14 and 22 were the main aberrations driving samples grouping. Then, we integrated mapping information with gene and microRNAs expression profiles: a multiclass analysis of the identified clusters showed a marked gene-dosage effect, particularly concerning 1q transcripts, also confirmed by correlating gene expression levels and local copy number alterations. A wide dosage effect affected also microRNAs, indicating that structural abnormalities in MM closely reflect in their expression imbalances. Finally, we identified several loci in which genes and microRNAs expression correlated with loss-of-heterozygosity occurrence. Our results provide insights into the composite network linking genome structure and gene/microRNA transcriptional features in MM. Keywords: Integrated genomics approach based on SNP microarray and FISH procedures to detect allelic imbalances in multiple myeloma. Pathological bone marrow specimens from 41 MM and four plasma cell leukemia (PCL) patients at diagnosis. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 40 micrograms of fragmented biotin-labelled DNA were hybridized on GeneChip Human Mapping 50K XbaI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChip® Operating Software (GCOS version 1.4). Copy number values for individual SNPs were extracted and converted from CEL files into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares. Genomic Smoothing analysis was performed by using the smoothing window of 0 Mb, and inferred copy number states were derived from a Hidden Markov Model (HMM) based algorithm implemented in CNAT 4.0.1. Circular Binary Segmentation (Ohlsen et al., 2004) was applied using DNAcopy package for R Bioconductor on raw data. FBN procedure was finally applied to infer exact local copy number as described in the mentioned Reference.

Project description:Lung cancer is the leading cause of death from malignant diseases worldwide, with the non-small cell (NSCLC) subtype accounting for the majority of cases. NSCLC is characterized by frequent genomic imbalances and copy number variations (CNVs), but the epigenetic aberrations that are associated with clinical prognosis and therapeutic failure remain not completely identify. In the present study, a total of 55 lung cancer patients were included and we conducted genomic and genetic expression analyses, immunohistochemical protein detection, DNA methylation and chromatin immunoprecipitation assays to obtain genetic and epigenetic profiles associated to prognosis and chemoresponse of NSCLC patients. Finally, siRNA transfection-mediated genetic silencing and cisplatinum cellular cytotoxicity assays in NSCLC cell lines A-427 and INER-37 were assesed to described chemoresistance mechanisms involved. Our results identified high frequencies of CNVs (60% of cases) in the 7p22.3-p21.1 and 7p15.3-p15.2 cytogenetic regions. However, overexpression of genes, such as MEOX2, HDAC9, TWIST1 and AhR, at 7p21.2-p21.1 locus occurred despite the absence of CNVs and little changes in DNA methylation. In contrast, the promoter sequences of MEOX2 and TWIST1 displayed significantly lower/decrease in the repressive histone mark H3K27me3 and increased in the active histone mark H3K4me3 levels. Finally these results correlate with poor survival in NSCLC patients and cellular chemoresistance to oncologic drugs in NSCLC cell lines in a MEOX2 and TWIST1 overexpression dependent-manner. In conclusion, we report for the first time that MEOX2 participates in chemoresistance irrespective of high CNV, but it is significantly dependent upon H3K27me3 enrichment probably associated with aggressiveness and chemotherapy failure in NSCLC patients, however additional clinical studies must be performed to confirm our findings as new probable clinical markers in NSCLC patients. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from fresh frozen, and paraffin embedded lung tumor samples Copy number analysis of Affymetrix 500K SNP arrays was performed for 33 lung tumor samples, including lung precursor metaplasia, lung tumors and cell lines. Six samples were also hybridized on the Affymetrix SNP 6.0 array

Project description:Chromosomal DNA copy number alterations are a hallmark of human malignancies, including hepatocellular carcinoma (HCC). However, which oncogenes or tumor suppressors located on regions with DNA copy number aberration may contribute to HCC initiation and progression still remain obscure. Here we performed a genome-wide DNA copy number analysis on human HCC samples to identify novel potential oncogenes or tumor suppressors with DNA copy number aberrations. Genome-wide DNA copy numbers analysis was performed with single nucleotide polymorphism micoarray. RT-PCR and immunohistochemical staining were employed to evaluate the NOXIN expression in HCC samples. Colony formation, cell cycle analysis and tumor xenograft assays were performed to assess the role of NOXIN in HCC cells. Reciprocal co-immunoprecipitation experiments were used to detect the interaction between NOXIN and DNA polymerase a primase. Genome-wide DNA copy number analysis on 43 paired HCC samples indentified the smallest DNA amplification region containing NOXIN, along with the elevated transcript. NOXIN overexpression was significantly associated with HCC tumor stage. Enforced NOXIN promoted cellular proliferation, colony formation, cell migration and in vivo tumorigenicity, whereas RNA interference against NOXIN can attenuate these effects. Interestingly, NOXIN overexpression can accelerate the G1-S transition of cell cycle progression through enhancing DNA synthesis in HCC cells, as indicated by bromodeoxyuridine incorporation. Furthermore, NOXIN can interact with DNA polymerase a, implying that NOXIN may promote de novo DNA synthesis via affiliating formation of DNA polymerase-primase complex. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from hepatocellular carcinoma and adjacent liver tissue samples. Copy number analysis of Affymetrix 500K SNP arrays was performed for 43 hepatocellular carcinoma tissue samples, which their adjacent liver tissues were used as references for copy number inference.

Dataset Information

Amplification in alveolar rhabdomyosarcoma

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets