Genomics and Systems Biology.

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.

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.


2021 ◽  
Vol 9 (Suppl 1) ◽  
pp. A12.1-A12
Author(s):  
Y Arjmand Abbassi ◽  
N Fang ◽  
W Zhu ◽  
Y Zhou ◽  
Y Chen ◽  
...  

Recent advances of high-throughput single cell sequencing technologies have greatly improved our understanding of the complex biological systems. Heterogeneous samples such as tumor tissues commonly harbor cancer cell-specific genetic variants and gene expression profiles, both of which have been shown to be related to the mechanisms of disease development, progression, and responses to treatment. Furthermore, stromal and immune cells within tumor microenvironment interact with cancer cells to play important roles in tumor responses to systematic therapy such as immunotherapy or cell therapy. However, most current high-throughput single cell sequencing methods detect only gene expression levels or epigenetics events such as chromatin conformation. The information on important genetic variants including mutation or fusion is not captured. To better understand the mechanisms of tumor responses to systematic therapy, it is essential to decipher the connection between genotype and gene expression patterns of both tumor cells and cells in the tumor microenvironment. We developed FocuSCOPE, a high-throughput multi-omics sequencing solution that can detect both genetic variants and transcriptome from same single cells. FocuSCOPE has been used to successfully perform single cell analysis of both gene expression profiles and point mutations, fusion genes, or intracellular viral sequences from thousands of cells simultaneously, delivering comprehensive insights of tumor and immune cells in tumor microenvironment at single cell resolution.Disclosure InformationY. Arjmand Abbassi: None. N. Fang: None. W. Zhu: None. Y. Zhou: None. Y. Chen: None. U. Deutsch: None.


Science ◽  
2020 ◽  
Vol 371 (6531) ◽  
pp. eaba5257 ◽  
Author(s):  
Anna Kuchina ◽  
Leandra M. Brettner ◽  
Luana Paleologu ◽  
Charles M. Roco ◽  
Alexander B. Rosenberg ◽  
...  

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.


2018 ◽  
Vol 16 (3) ◽  
pp. 162-176 ◽  
Author(s):  
Hans De Wolf ◽  
Laure Cougnaud ◽  
Kirsten Van Hoorde ◽  
An De Bondt ◽  
Joerg K. Wegner ◽  
...  

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.


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


2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Hui Cui ◽  
Menghuan Zhang ◽  
Qingmin Yang ◽  
Xiangyi Li ◽  
Michael Liebman ◽  
...  

The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for further refinement towards addressing a large clinical need.


2015 ◽  
Vol 11 (11) ◽  
pp. 509-511
Author(s):  
Jae-Hee Lee ◽  
◽  
Sang-Ho Kang ◽  
Jong-Yeol Lee ◽  
Chang-Kug Kim ◽  
...  

2020 ◽  
Author(s):  
Reza Yarani ◽  
Oana Palasca ◽  
Nadezhda T. Doncheva ◽  
Christian Anthon ◽  
Bartosz Pilecki ◽  
...  

1.AbstractBACKGROUND & AIMSUlcerative colitis (UC) is an inflammatory bowel disorder with unknown etiology. Given its complex nature, in vivo studies to investigate its pathophysiology is vital. Animal models play an important role in molecular profiling necessary to pinpoint mechanisms that contribute to human disease. Thus, we aim to identify common conserved gene expression signatures and differentially regulated pathways between human UC and a mouse model hereof, which can be used to identify UC patients from healthy individuals and to suggest novel treatment targets and biomarker candidates.METHODSTherefore, we performed high-throughput total and small RNA sequencing to comprehensively characterize the transcriptome landscape of the most widely used UC mouse model, the dextran sodium sulfate (DSS) model. We used this data in conjunction with publicly available human UC transcriptome data to compare gene expression profiles and pathways.RESULTSWe identified differentially regulated protein-coding genes, long non-coding RNAs and microRNAs from colon and blood of UC mice and further characterized the involved pathways and biological processes through which these genes may contribute to disease development and progression. By integrating human and mouse UC datasets, we suggest a set of 51 differentially regulated genes in UC colon and blood that may improve molecular phenotyping, aid in treatment decisions, drug discovery and the design of clinical trials.CONCLUSIONGlobal transcriptome analysis of the DSS-UC mouse model supports its use as an efficient high-throughput tool to discover new targets for therapeutic and diagnostic applications in human UC through identifying relationships between gene expression and disease phenotype.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 3440-3440
Author(s):  
Vera Grossmann ◽  
Ulrike Bacher ◽  
Valentina Artusi ◽  
Hans-Ulrich Klein ◽  
Wolfgang Kern ◽  
...  

Abstract Abstract 3440 The t(10;11)(p13;q14)/PICALM-MLLT10 (CALM-AF10) rearrangement is most frequently associated with T-lineage acute lymphoblastic leukemia/lymphoma (T-ALL), and is rarely observed in AML. The EZH2 gene, located on 7q36.1, is a highly conserved histone H3 lysine 27 methyltransferase that influences stem cell renewal. EZH2 mutations were observed in 10% of patients with myelofibrosis, myelodysplastic/myeloproliferative neoplasms, or chronic myelomonocytic leukemia. In a previous study, we had investigated AML patients for EZH2 deletions using FISH. 6/20 (30%) of cases had been detected to carry a deletion. Additionally, we had screened these 6 cases for molecular mutations in EZH2 (transcript-ID: ENST00000320356) using an amplicon-based deep-sequencing assay, and one of the 6 patients was harboring both an EZH2 deletion and an EZH2 mutation. More interestingly, this double-mutated case was carrying a PICALM-MLLT10 rearrangement. Therefore, in this study, we were interested to investigate an expanded cohort of 13 cases (T-lineage ALL and AML) harboring a PICALM-MLLT10 rearrangement. Our cohort comprised 12 adults and one pediatric patient (7 males, 6 females) and was characterized by a predominant T-cell origin: 11 patients had T-ALL, 1 patient had mixed phenotype T/myeloid acute leukemia, and 1 patient had AML. EZH2 alterations were detected in 3/13 (including the index case). In more detail, the EZH2 mutation carriers were characterized as follows: Patient #1 (male, 26 years, AML) had a splice site mutation in exon 14 with a mutation load of 13% in a cysteine-rich region. Patient #2 (male, 19 years, T-ALL) harbored a missense mutation (Phe136Leu) with a mutation load of 93%. Patient #3 (female, 53 years, T-ALL) showed three concomitant EZH2 missense mutations in exon 5: His120Gln, Tyr124His, and Gly150Arg. The mutation load detected was 17% for each alteration. A fourth patient had a 1459G>A base substitution (corresponding to Ala487Thr) which to our knowledge had not been described before. However, this alteration had to be interpreted as germline as it was still detectable in the remission state. In contrast, in an independent cohort of 12 patients with PICALM-MLLT10 negative T-ALL (7 females, 5 males) analyzed for comparison no EZH2 mutation was detected. Interestingly, in patients #2 and #3, the mutations were located in exon 5 in the region which interacts with the DNMT1, DNMT3A, and DNMT3B DNA methyltransferase genes (D1). Moreover, DNMT3A mutations were recently identified in patients with AML and MDS in association with poor outcomes. Therefore, we additionally performed investigation for DNMT3A mutations in all 13 patients with PICALM-MLLT10 positive leukemias but detected no mutation. To investigate further molecular associations, we analyzed these cases also for RUNX1 mutations and FLT3-ITD, but we did not detect any mutation in these molecular genes. Further, we compared the gene expression profiles of 8 patients with PICALM-MLLT10 positive T-ALL to the profiles of 21 PICALM-MLLT10 negative T-ALL patients. Hierarchical clustering revealed a distinct gene expression signature of the PICALM-MLLT10 positive cases. Significant upregulation was found for HOXA5 and HOXA9 genes. Other differentially overexpressed HOX were HOXA3, A4, A6, A7, A10. Genes with a function for cell differentiation and regulation of apoptosis (ZAK) as well as for signal transduction (AKT3) were significantly underexpressed. Subsequently, we compared the gene expression profiles of 2 EZH2 mutated patients to 6 EZH2 wild-type patients in the PICALM-MLLT10 positive cohort. By hierarchical clustering, both EZH2 mutated cases showed a distinct gene expression signature. Increased expression was observed for genes with a role for the regulation of transcription (ZNF207, KDM5B, or CASZ1) or for intracellular transport (SARB1). In summary, we detected EZH2 mutations in 3/13 cases in this series of PICALM-MLLT10 positive malignancies, comprising mostly T-ALL, but also AML or mixed phenotype acute leukemia. This further emphasizes a cooperative effect of EZH2 mutations with the PICALM-MLLT10 fusion in acute leukemias of different lineages. Disclosures: Grossmann: MLL Munich Leukemia Laboratory: Employment. Artusi:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kohlmann:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.


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