Respiratory chain protein analysis, gene expression profiles of fibroblast cell lines from 9 patients with SURF1 gene mutations

High-throughput technologies generate a tremendous amount of expression data on mRNA, miRNA and protein levels. Mining and visualizing the large amount of expression data requires sophisticated computational skills. An easy to use and user-friendly web-server for the visualization of gene expression profiles could greatly facilitate data exploration and hypothesis generation for biologists. Here, we curated and normalized the gene expression data on mRNA, miRNA and protein levels in 23315, 9009 and 9244 samples, respectively, from 40 tissues (The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GETx)) and 1594 cell lines (Cancer Cell Line Encyclopedia (CCLE) and MD Anderson Cell Lines Project (MCLP)). Then, we constructed the Gene Expression Display Server (GEDS), a web-based tool for quantification, comparison and visualization of gene expression data. GEDS integrates multiscale expression data and provides multiple types of figures and tables to satisfy several kinds of user requirements. The comprehensive expression profiles plotted in the one-stop GEDS platform greatly facilitate experimental biologists utilizing big data for better experimental design and analysis. GEDS is freely available on http://bioinfo.life.hust.edu.cn/web/GEDS/.

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Acute Myeloid Leukemia With Biallelic CEBPA Gene Mutations and Normal Karyotype Represents a Distinct Genetic Entity Associated With a Favorable Clinical Outcome

Journal of Clinical Oncology ◽

10.1200/jco.2008.21.6010 ◽

2010 ◽

Vol 28 (4) ◽

pp. 570-577 ◽

Cited By ~ 180

Author(s):

Annika Dufour ◽

Friederike Schneider ◽

Klaus H. Metzeler ◽

Eva Hoster ◽

Stephanie Schneider ◽

...

Keyword(s):

Gene Expression ◽

Acute Myeloid Leukemia ◽

Clinical Outcome ◽

Myeloid Leukemia ◽

Expression Profiles ◽

Gene Mutations ◽

Gene Expression Profiles ◽

Similar Frequency ◽

Favorable Clinical Outcome ◽

Acute Myeloid

Purpose CEBPA mutations are found as either biallelic (biCEBPA) or monoallelic (moCEBPA). We set out to explore whether the kind of CEBPA mutation is of prognostic relevance in cytogenetically normal (CN) acute myeloid leukemia (AML). Patients and Methods Four hundred sixty-seven homogeneously treated patients with CN-AML were subdivided into moCEBPA, biCEBPA, and wild-type (wt) CEBPA patients. The subgroups were analyzed for clinical parameters and for additional mutations in the NPM1, FLT3, and MLL genes. Furthermore, we obtained gene expression profiles using oligonucleotide microarrays. Results Only patients with biCEBPA had an improved median overall survival when compared with patients with wtCEBPA (not reached v 20.4 months, respectively; P = .018), whereas patients with moCEBPA (20.9 months) and wtCEBPA had a similar outcome (P = .506). Multivariable analysis confirmed biCEBPA, but not moCEBPA, mutations as an independent favorable prognostic factor. Interestingly, biCEBPA mutations, compared with wtCEBPA, were never associated with mutated NPM1 (0% v 43%, respectively; P < .001) and rarely associated with FLT3 internal tandem duplication (ITD; 5% v 23%, respectively; P = .059), whereas patients with moCEBPA had a similar frequency of mutated NPM1 and a significantly higher association with FLT3-ITD compared with patients with wtCEBPA (44% v 23%, respectively; P = .037). Furthermore, patients with biCEBPA showed a homogeneous gene expression profile that was characterized by downregulation of HOX genes, whereas patients with moCEBPA showed greater heterogeneity in their gene expression profiles. Conclusion Biallelic disruption of the N and C terminus of CEBPA is required for the favorable clinical outcome of CEBPA-mutated patients and represents a distinct molecular subtype of CN-AML with a different frequency of associated gene mutations. These findings are of great significance for risk-adapted therapeutic strategies in AML.

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In Silico Prediction of Novel Drug Combinations to Combat Bortezomib-Resistant Multiple Myeloma

Blood ◽

10.1182/blood.v120.21.1344.1344 ◽

2012 ◽

Vol 120 (21) ◽

pp. 1344-1344

Author(s):

Holly A. F. Stessman ◽

Tian Xia ◽

Aatif Mansoor ◽

Raamesh Deshpande ◽

Linda B. Baughn ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

Cell Lines ◽

In Silico ◽

Research Funding ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Mouse Cell ◽

Resistant Mouse ◽

Novel Therapeutic

Abstract Abstract 1344 Bortezomib/VELCADE® (Bz) is a proteasome inhibitor that has been used successfully in the treatment of multiple myeloma (MM) patients. However, acquired resistance to Bz is an emerging problem. Thus, there is a need for novel therapeutic combinations that enhance Bz sensitivity or re-sensitize Bz resistant MM cells to Bz. The Connectivity Map (CMAP; Broad Institute) database contains treatment-induced transcriptional signatures from 1,309 bioactive compounds in 4 human cancer cell lines. An input signature can be used to query the database for correlated drug signatures, a technique that has been used previously to identify drugs that combat chemoresistance in cancer (Wei, et al. Cancer Cell (2006) 10:331). In this study we used in silico bioinformatic screening of gene expression profiles from isogenic pairs of Bz sensitive and resistant mouse cell lines derived from the iMycCα/Bcl-xL mouse model of plasma cell malignancy to identify compounds that combat Bz resistance. We established Bz-induced kinetic gene expression profiles (GEPs) in 3 pairs of Bz sensitive and resistant mouse cell lines over the course of 24 hours. GEPs were collected in the absence of large-scale cell death. The 16 and 24 hour time points were averaged and compared between each Bz sensitive and resistant pair. Genes in the sensitive cell line with a fold change greater than 2, relative to the resistant line, were given the binary distinction of “up” or “down” depending on the direction of change. Genes that met these criteria were assembled into signatures, and then used as inputs for CMAP queries to identify compounds that induce similar transcriptional responses. In all pairs, treatment of the Bz sensitive line correlated with GEPs of drugs that target the proteasome, NF-κB, HSP90 and microtubules, as indicated by positive connectivity scores. However eight compounds, all classified as Topoisomerase (Topo) I and/or II inhibitors, were negatively correlated to our input signature. A negative connectivity score could have two interpretations: (1) this could indicate simply that Topos are upregulated by Bz treatment in Bz sensitive lines, which has been previously reported (Congdan, et al. Biochem. Pharmacol. (2008) 74: 883); or (2) this score could be interpreted as Topos are inhibited in Bz resistant cells upon Bz treatment. This led us to ask whether Topo inhibitors could target Bz resistant MM cells and re-sensitize them to Bz. Indeed, we found that multiple Topo inhibitors were significantly more active against Bz resistant cells as single agents and restored sensitivity to Bz when combined with Bz as a cocktail regimen. This work demonstrates the potential of this in silico bioinformatic approach for identifying novel therapeutic combinations that overcome Bz resistance in MM. Furthermore, it identifies Topo inhibitors – drugs that are already approved for clinical use – as agents that may have utility in combating Bz resistance in refractory MM patients. Disclosures: Stessman: Millennium: The Takeda Oncology Company: Research Funding. Van Ness:Millennium: The Takeda Oncology Company: Research Funding.

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