The dChip survival analysis module for microarray data

International audienceBACKGROUND: Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene expression based biomarkers in breast cancer. Similar predictions have recently been carried out using genome-wide copy number alterations and microRNAs. Existing software packages for microarray data analysis provide functions to define expression-based survival gene signatures. However, there is no software that can perform survival analysis using SNP array data or draw survival curves interactively for expression-based sample clusters. RESULTS: We have developed the survival analysis module in the dChip software that performs survival analysis across the genome for gene expression and copy number microarray data. Built on the current dChip software's microarray analysis functions such as chromosome display and clustering, the new survival functions include interactive exploring of Kaplan-Meier (K-M) plots using expression or copy number data, computing survival p-values from the log-rank test and Cox models, and using permutation to identify significant chromosome regions associated with survival. CONCLUSIONS: The dChip survival module provides user-friendly way to perform survival analysis and visualize the results in the context of genes and cytobands. It requires no coding expertise and only minimal learning curve for thousands of existing dChip users. The implementation in Visual C++ also enables fast computation. The software and demonstration data are freely available at http://dchip-surv.chenglilab.org

Reversible Resistance Induced by FLT3 Inhibition: A Novel Resistance Mechanism in Mutant FLT3-Expressing Cells

Clinical responses achieved with FLT3 kinase inhibitors in acute myeloid leukemia (AML) are typically transient and partial. Thus, there is a need for identification of molecular mechanisms of clinical resistance to these drugs. In response, we characterized MOLM13 AML cell lines made resistant to two structurally-independent FLT3 inhibitors.MOLM13 cells were made drug resistant via prolonged exposure to midostaurin and HG-7-85-01, respectively. Cell proliferation was determined by Trypan blue exclusion. Protein expression was assessed by immunoblotting, immunoprecipitation, and flow cytometry. Cycloheximide was used to determine protein half-life. RT-PCR was performed to determine FLT3 mRNA levels, and FISH analysis was performed to determine FLT3 gene expression.We found that MOLM13 cells readily developed cross-resistance when exposed to either midostaurin or HG-7-85-01. Resistance in both lines was associated with dramatically elevated levels of cell surface FLT3 and elevated levels of phosphor-MAPK, but not phospho-STAT5. The increase in FLT3-ITD expression was at least in part due to reduced turnover of the receptor, with prolonged half-life. Importantly, the drug-resistant phenotype could be rapidly reversed upon withdrawal of either inhibitor. Consistent with this phenotype, no significant evidence of FLT3 gene amplification, kinase domain mutations, or elevated levels of mRNA was observed, suggesting that protein turnover may be part of an auto-regulatory pathway initiated by FLT3 kinase activity. Interestingly, FLT3 inhibitor resistance also correlated with resistance to cytosine arabinoside. Over-expression of FLT3 protein in response to kinase inhibitors may be part of a novel mechanism that could contribute to clinical resistance

Intronic splicing of hyaluronan synthase 1 (HAS1): a biologically relevant indicator of poor outcome in multiple myeloma

In this study, we show that the hyaluronan synthase 1 (HAS1) gene undergoes aberrant intronic splicing in multiple myeloma (MM). In addition to HAS1 full length (HAS1FL), we identify 3 novel splice variants of HAS1, HAS1Va, HAS1Vb, and HAS1Vc, detected in patients with MM or monoclonal gammopathy of undetermined significance (MGUS). HAS1Vb and HAS1Vc undergo intronic splicing with creation of a premature stop codon. MM cells expressing one or more HAS1 variants synthesize extracellular and/or intracellular hyaluronan (HA). Expression of the HAS1Vb splice variant was significantly correlated with reduced survival (P = .001). Together, alternative HAS1 gene splicing, the correlations between HAS1 splicing and HA synthesis, and the correlations between HAS1 splicing and reduced survival of MM patients support the hypothesis that the family of HAS1 protein plays a significant role in disease progression. Further, expression of HAS1Vb, in conjunction with HAS1FL and/or other HAS1 variants, may lead to accumulation of intracellular HA molecules and an impact on receptor for HA-mediated motility (RHAMM)-mediated mitotic abnormalities in MM. This study highlights the potential importance of HAS1 and its alternative splicing in pathophysiology of MGUS and MM. (Blood. 2005;105: 4836-4844

The dChip survival analysis module for microarray data

Abstract Background Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene expression based biomarkers in breast cancer. Similar predictions have recently been carried out using genome-wide copy number alterations and microRNAs. Existing software packages for microarray data analysis provide functions to define expression-based survival gene signatures. However, there is no software that can perform survival analysis using SNP array data or draw survival curves interactively for expression-based sample clusters. Results We have developed the survival analysis module in the dChip software that performs survival analysis across the genome for gene expression and copy number microarray data. Built on the current dChip software's microarray analysis functions such as chromosome display and clustering, the new survival functions include interactive exploring of Kaplan-Meier (K-M) plots using expression or copy number data, computing survival p-values from the log-rank test and Cox models, and using permutation to identify significant chromosome regions associated with survival. Conclusions The dChip survival module provides user-friendly way to perform survival analysis and visualize the results in the context of genes and cytobands. It requires no coding expertise and only minimal learning curve for thousands of existing dChip users. The implementation in Visual C++ also enables fast computation. The software and demonstration data are freely available at http://dchip-surv.chenglilab.org.</p

Molecular targets for therapy The effects of MicroRNA deregulation on pre-RNA processing network in multiple myeloma

International audienceOver the last few years, a detailed map of genetic and epigenetic lesions that underlie multiple myeloma (MM) has been created. Regulation of microRNA (miR)-dependent gene expression and mRNA splicing play significant roles in MM pathogenesis; however, to date an interplay between these processes is not yet delineated. Here we investigated miR-mediated regulation of splicing networks at the transcriptome level. Our studies show that a significant number (78%) of miRs which are either up-or down-regulated in patient CD138+ MM cells, but not in healthy donors (HD) CD138+ plasma cells (PC), target genes involved in early stages of pre-mRNA splicing. We also identified deregulated miRs that target core splicing factors (SF) and modifiers (SM, enhancers/silencers) which cause altered splicing in MM. Our studies suggest that Let-7f, in combination other miRs which are frequently and significantly deregulated in patients with overt MM, targets genes that regulate intron excision. Importantly, deregulated expression of certain miRs in MM promote increased intron retention, a novel characteristic of the MM genome, by inducing deregulated expression of the genes that regulate the splicing network. Our studies, therefore, provide the rationale for therapeutically targeting deregulated miRs to reverse aberrant splicing and improve patient outcome in MM