scholarly journals Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data

Blood ◽  
2008 ◽  
Vol 111 (12) ◽  
pp. 5654-5662 ◽  
Author(s):  
Duane C. Hassane ◽  
Monica L. Guzman ◽  
Cheryl Corbett ◽  
Xiaojie Li ◽  
Ramzi Abboud ◽  
...  

Abstract Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene expression-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. sci-51-sci-51
Author(s):  
Todd R. Golub

Genomics holds particular potential for the elucidation of biological networks that underlie disease. For example, gene expression profiles have been used to classify human cancers, and have more recently been used to predict graft rejection following organ transplantation. Such signatures thus hold promise both as diagnostic approaches and as tools with which to dissect biological mechanism. Such systems-based approaches are also beginning to impact the drug discovery process. For example, it is now feasible to measure gene expression signatures at low cost and high throughput, thereby allowing for the screening libraries of small molecule libraries in order to identify compounds capable of perturbing a signature of interest (even if the critical drivers of that signature are not yet known). This approach, known as Gene Expression-Based High Throughput Screening (GE-HTS), has been shown to identify candidate therapeutic approaches in AML, Ewing sarcoma, and neuroblastoma, and has identified tool compounds capable of inhibiting PDGF receptor signaling. A related approach, known as the Connectivity Map (www.broad.mit.edu/cmap) attempts to use gene expression profiles as a universal language with which to connect cellular states, gene product function, and drug action. In this manner, a gene expression signature of interest is used to computationally query a database of gene expression profiles of cells systematically treated with a large number of compounds (e.g., all off-patent FDA-approved drugs), thereby identifying potential new applications for existing drugs. Such systems level approaches thus seek chemical modulators of cellular states, even when the molecular basis of such altered states is unknown.


2021 ◽  
Vol 11 ◽  
Author(s):  
Lijun Huang ◽  
Xiaohong Yi ◽  
Xiankuo Yu ◽  
Yumei Wang ◽  
Chen Zhang ◽  
...  

Transcriptional reprogramming contributes to the progression and recurrence of cancer. However, the poorly elucidated mechanisms of transcriptional reprogramming in tumors make the development of effective drugs difficult, and gene expression signature is helpful for connecting genetic information and pharmacologic treatment. So far, there are two gene-expression signature-based high-throughput drug discovery approaches: L1000, which measures the mRNA transcript abundance of 978 “landmark” genes, and high-throughput sequencing-based high-throughput screening (HTS2); they are suitable for anticancer drug discovery by targeting transcriptional reprogramming. L1000 uses ligation-mediated amplification and hybridization to Luminex beads and highlights gene expression changes by detecting bead colors and fluorescence intensity of phycoerythrin signal. HTS2 takes advantage of RNA-mediated oligonucleotide annealing, selection, and ligation, high throughput sequencing, to quantify gene expression changes by directly measuring gene sequences. This article summarizes technological principles and applications of L1000 and HTS2, and discusses their advantages and limitations in anticancer drug discovery.


2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Yulong Zheng ◽  
Yongfeng Ding ◽  
Qifeng Wang ◽  
Yifeng Sun ◽  
Xiaodong Teng ◽  
...  

Abstract Background Brain metastases (BM) are the most common intracranial tumors. 2–14% of BM patients present with unknown primary site despite intensive evaluations. This study aims to evaluate the performance of a 90-gene expression signature in determining the primary sites for BM samples. Methods The sequence-based gene expression profiles of 708 primary brain tumors (PBT) collected from The Cancer Genome Atlas (TCGA) database were analyzed by the 90-gene expression signature, with a similarity score for each of 21 common tumor types. We then used Optimal Binning algorithm to generate a threshold for separating PBT from BM. Eighteen PBT samples were analyzed to substantiate the reliability of the threshold. In addition, the performance of the 90-gene expression signature for molecular classification of metastatic brain tumors was validated in a cohort of 48 BM samples with the known origin. For each BM sample, the tumor type with the highest similarity score was considered tissue of origin. When a sample was diagnosed as PBT, but the similarity score below the threshold, the second prediction was considered as the primary site. Results A threshold of the similarity score, 70, was identified to discriminate PBT from BM (PBT: > 70, BM: ≤ 70) with an accuracy of 99% (703/708, 95% CI 98–100%). The 90-gene expression signature was further validated with 18 PBT and 44 BM samples. The results of 18 PBT samples matched reference diagnosis with a concordance rate of 100%, and all similarity scores were above the threshold. Of 44 BM samples, the 90-gene expression signature accurately predicted primary sites in 89% (39/44, 95% CI 75–96%) of the cases. Conclusions Our findings demonstrated the potential that the 90-gene expression signature could serve as a powerful tool for accurately identifying the primary sites of metastatic brain tumors.


2016 ◽  
Vol 45 ◽  
pp. 1-7 ◽  
Author(s):  
Hao Ho ◽  
Alyza M. Skaist ◽  
Aparna Pallavajjala ◽  
Raluca Yonescu ◽  
Denise Batista ◽  
...  

2003 ◽  
Vol 185 (16) ◽  
pp. 4973-4982 ◽  
Author(s):  
Jaime Bjarnason ◽  
Carolyn M. Southward ◽  
Michael G. Surette

ABSTRACT The importance of iron to bacteria is shown by the presence of numerous iron-scavenging and transport systems and by many genes whose expression is tightly regulated by iron availability. We have taken a global approach to gene expression analysis of Salmonella enterica serovar Typhimurium in response to iron by combining efficient, high-throughput methods with sensitive, luminescent reporting of gene expression using a random promoter library. Real-time expression profiles of the library were generated under low- and high-iron conditions to identify iron-regulated promoters, including a number of previously identified genes. Our results indicate that approximately 7% of the genome may be regulated directly or indirectly by iron. Further analysis of these clones using a Fur titration assay revealed three separate classes of genes; two of these classes consist of Fur-regulated genes. A third class was Fur independent and included both negatively and positively iron-responsive genes. These may reflect new iron-dependent regulons. Iron-responsive genes included iron transporters, iron storage and mobility proteins, iron-containing proteins (redox proteins, oxidoreductases, and cytochromes), transcriptional regulators, and the energy transducer tonB. By identifying a wide variety of iron-responsive genes, we extend our understanding of the global effect of iron availability on gene expression in the bacterial cell.


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 719-719 ◽  
Author(s):  
Jacqueline E. Payton ◽  
Nicole R. Grieselhuber ◽  
Li-Wei Chang ◽  
Mark A. Murakami ◽  
Wenlin Yuan ◽  
...  

Abstract In order to better understand the pathogenesis of acute promyelocytic leukemia (APL, FAB M3), we sought to determine its gene expression signature by comparing the expression profiles of 14 APL samples to that of other AML subtypes (M0, M1, M2, M4, n=62) and to fractionated normal whole bone marrow cells (CD34 cells, promyelocytes, PMNs, n=5 each). We used ANOVA and SAM (Significance Analysis of Microarrays) to select genes that were highly expressed in APL cells and that displayed low to no expression in other AML subtypes. The APL signature was then further refined by filtering genes whose expression in APL was not significantly different from that of normal promyelocytes, yielding 1121 annotated genes that reliably distinguish APL from the other FAB subtypes using unsupervised hierarchical clustering, both in training and validation datasets. Fold change differences in expression between M3 and other AML FAB classes were striking, for example: GABRE 35.4, HGF 21.3, ANXA8 21.3, PTPRG 16.9, PTGDS 12.1, PPARG 11.1, STAB1 9.8. A large proportion of the APL versus other FAB dysregulome was recapitulated when we compared APL expression to that of the normal pattern of myeloid development. We identified 733 annotated genes with significantly different expression in APL versus normal myeloid cell fractions. These dysregulated genes were assigned to 4 classes: persistently expressed CD34 cell-specific genes, repressed promyelocyte-specific genes, prematurely expressed neutrophil-specific genes and genes with high expression in APL and low/no expression in normal myeloid cell fractions. Expression differences in several of the most dysregulated genes were validated by qRT-PCR. We then examined the expression of the APL signature genes in myeloid cell lines and tumors from a murine APL model. The bona fide M3 signature was not apparent in resting NB4 cells (which contain t(15;17), and which express PML-RARA), nor in PR-9 cells following Zn induction of PML-RARA expression, suggesting that neither cell line accurately models the gene expression signature of primary APL cells. Most of the nodal genes of the mCG-PML-RARA murine APL dysregulome (Yuan, et al, 2007) are similarly dysregulated in human M3 cells; however, the human and mouse dysregulomes do not completely coincide. Finally, we have begun investigating which APL signature genes are direct transcriptional targets of PML-RARA. The promoters of the APL signature genes were analyzed for the presence of known PML-RARA binding sites using multiple computational methods. The analyses demonstrated that several transcription factors (EBF3, TWIST1, SIX3, PPARG) have putative retinoic acid response elements (RAREs) in their upstream regulatory regions. Additionally, we examined the promoters of some of the most upregulated genes (HGF, PTGDS, STAB1) for known consensus sites of these transcription factors, and found that all have putative binding sites for at least one. These results suggest that PML-RARA may initiate a transcriptional cascade that relies not only on its own activity, but also on the actions of downstream transcription factors. In summary, our studies indicate that primary APL cells have a gene expression signature that is consistent and highly reproducible, but different from commonly used human APL cell lines and a mouse model of APL. The molecular mechanisms that govern this unique signature are currently under investigation.


2018 ◽  
Vol 36 (15_suppl) ◽  
pp. e20547-e20547
Author(s):  
Alejandro Herreros-Pomares ◽  
Juan Diego de Maya ◽  
Héctor Amado ◽  
Cristóbal Aguilar-Gallardo ◽  
Eva Escorihuela ◽  
...  

2011 ◽  
Vol 301 (3) ◽  
pp. R727-R745 ◽  
Author(s):  
Hady Felfly ◽  
Jin Xue ◽  
Alexander C. Zambon ◽  
Alysson Muotri ◽  
Dan Zhou ◽  
...  

Stem cells are a potential key strategy for treating neurodegenerative diseases in which the generation of new neurons is critical. A better understanding of the characteristics and molecular properties of neural stem cells (NSCs) and differentiated neurons can help with assessing neuronal maturity and, possibly, in devising better therapeutic strategies. We have performed an in-depth gene expression profiling study of murine NSCs and primary neurons derived from embryonic mouse brains. Microarray analysis revealed a neuron-specific gene expression signature that distinguishes primary neurons from NSCs, with elevated levels of transcripts involved in neuronal functions, such as neurite development and axon guidance in primary neurons and decreased levels of multiple cytokine transcripts. Among the differentially expressed genes, we found a statistically significant enrichment of genes in the ephrin, neurotrophin, CDK5, and actin pathways, which control multiple neuronal-specific functions. We then artificially blocked the cell cycle of NSCs with mitomycin C (MMC) and examined cellular morphology and gene expression signatures. Although these MMC-treated NSCs displayed a neuronal morphology and expressed some neuronal differentiation marker genes, their gene expression patterns were very different from primary neurons. We conclude that 1) fully differentiated mouse primary neurons display a specific neuronal gene expression signature; 2) cell cycle block at the S phase in NSCs with MMC does not induce the formation of fully differentiated neurons; 3) cytokines change their expression pattern during differentiation of NSCs into neurons; and 4) signaling pathways of ephrin, neurotrophin, CDK5, and actin, related to major neuronal features, are dynamically enriched in genes showing changes in expression level.


2008 ◽  
Vol 216 (2) ◽  
pp. 158-166 ◽  
Author(s):  
S Boeuf ◽  
P Kunz ◽  
T Hennig ◽  
B Lehner ◽  
PCW Hogendoorn ◽  
...  

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