scholarly journals The Gene Expression Profiles of Medulloblastoma Cell Lines Resistant to Preactivated Cyclophosphamide

2008 ◽  
Vol 8 (3) ◽  
pp. 172-179 ◽  
Author(s):  
M. Bacolod ◽  
S. Lin ◽  
S. Johnson ◽  
N. Bullock ◽  
M. Colvin ◽  
...  
2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Megan Rose Paul ◽  
Yuchen Huo ◽  
Andrea Liu ◽  
Jacqueline Lesperance ◽  
Alexandra Garancher ◽  
...  

Abstract Background Identifying mechanisms of medulloblastoma recurrence is a key to improving patient survival, and targeting treatment-resistant subpopulations within tumors could reduce disease recurrence. Expression of the granulocyte colony-stimulating factor receptor (G-CSF-R, CD114) is a potential marker of cancer stem cells, and therefore we hypothesized that a subpopulation of medulloblastoma cells would also express CD114 and would demonstrate chemoresistance and responsiveness to G-CSF. Methods Prevalence of CD114-positive (CD114+) cells in medulloblastoma cell lines, patient-derived xenograft (PDX) tumors, and primary patient tumor samples were assessed by flow cytometry. Growth rates, chemoresistance, and responses to G-CSF of CD114+ and CD114-negative (CD114−) cells were characterized in vitro using continuous live cell imaging and flow cytometry. Gene expression profiles were compared between CD114+ and CD114− medulloblastoma cells using quantitative RT-PCR. Results CD114+ cells were identifiable in medulloblastoma cell lines, PDX tumors, and primary patient tumors and have slower growth rates than CD114− or mixed populations. G-CSF accelerates the growth of CD114+ cells, and CD114+ cells are more chemoresistant. The CD114+ population is enriched when G-CSF treatment follows chemotherapy. The CD114+ population also has higher expression of the CSF3R, NRP-1, TWIST1, and MYCN genes. Conclusions Our data demonstrate that a subpopulation of CD114+ medulloblastoma cells exists in cell lines and tumors, which may evade traditional chemotherapy and respond to exogenous G-CSF. These properties invite further investigation into the role of G-CSF in medulloblastoma therapy and methods to specifically target these cells.


Oncogene ◽  
2002 ◽  
Vol 21 (42) ◽  
pp. 6549-6556 ◽  
Author(s):  
Jiafu Ji ◽  
Xin Chen ◽  
Suet Yi Leung ◽  
Jen-Tsan A Chi ◽  
Kent Man Chu ◽  
...  

2006 ◽  
Vol 2 ◽  
pp. S552-S552
Author(s):  
Boe-Hyun Kim ◽  
Jae-Il Kim ◽  
Eun-Kyoung Choi ◽  
Richard I. Carp ◽  
Yong-Sun Kim

Oncogene ◽  
1999 ◽  
Vol 18 (17) ◽  
pp. 2711-2717 ◽  
Author(s):  
Chang Hun Rhee ◽  
Kenneth Hess ◽  
James Jabbur ◽  
Maribelis Ruiz ◽  
Yu Yang ◽  
...  

Cells ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 675 ◽  
Author(s):  
Xia ◽  
Liu ◽  
Zhang ◽  
Guo

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/.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1344-1344
Author(s):  
Holly A. F. Stessman ◽  
Tian Xia ◽  
Aatif Mansoor ◽  
Raamesh Deshpande ◽  
Linda B. Baughn ◽  
...  

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.


2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 403-403
Author(s):  
Loredana Vecchione ◽  
Valentina Gambino ◽  
Giovanni d'Ario ◽  
Sun Tian ◽  
Iris Simon ◽  
...  

403 Background: Approximately 8-15% of colorectal (CRC) patients carry an activating mutation in BRAF. This CRC subtype is associated with poor outcome and with resistance, both to chemotherapeutic treatments and to tailored drugs. We recently showed that BRAF (V600E) colon cancers (CCs) have a characteristic gene expression signature (1, 2) which is found also in subsets of KRAS mutant and KRAS-BRAF wild type (WT2) tumors. Tumors having this gene signature, referred as “BRAF-like”, have a similar poor prognosis irrespective of the presence of the BRAF (V600E) mutation. By using a shRNA-based genetic screen in BRAF mutant CC cell lines we aimed to identify genes and pathways necessary for survival and growth of BRAFmutant CC. Such studies may reveal additional targets for therapy and potentially provide new biomarkers for patient stratification Methods: We identified 363 genes that are selectively overexpressed in BRAF mutant tumors as compared to WT2 type tumors, based on gene expression profiles of the PETACC3 (1) and Agendia (2) datasets. The TRC human genome-wide shRNA collection (TRC-Hs1.0) was used to generate a 1815 hairpins sub-library targeting those identified genes (BRAF library). BRAF(V600E) CC cell lines were infected with the BRAF library and screened for shRNAs that cause lethality. LIM1215 CC cell line (WT2) was used as a control. Cells stably expressing the shRNA library were cultured for 13 days, after which shRNAs were recovered by PCR. Deep sequencing was applied to determine the specific depletion of shRNA in BRAF(V600E) cells as compared to LIM1215 cells Results: Candidate genes were identified by using following filtering criteria: depletion in BRAF(V600E) cells by at least 50% and depletion in BRAF(V600E) cells 1, 5-fold higher than in control cells with the corresponding p-value to be ≤ 0.1. A total of 34 genes met our criteria of which 6 genes were presented with more than one hairpin and were concordant across the cell lines selected for validation. Conclusions: We identified candidate synthetic lethal genes in BRAF mutant CC cell lines. Functional analysis is ongoing. Data will be presented. References 1. J Clin Oncol 2012 Apr 20;30(12):1288-9 2. Gut (2012). doi:10.1136/gutjnl-2012-302423


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