scholarly journals Genome-Wide Role of HSF1 in Transcriptional Regulation of Desiccation Tolerance in the Anhydrobiotic Cell Line, Pv11

2021 ◽  
Vol 22 (11) ◽  
pp. 5798
Author(s):  
Shoko Tokumoto ◽  
Yugo Miyata ◽  
Ruslan Deviatiiarov ◽  
Takahiro G. Yamada ◽  
Yusuke Hiki ◽  
...  
Keyword(s):  
Cell Line ◽  
Cell Lines ◽  
Desiccation Tolerance ◽  
Expression Profiles ◽  
Insect Cell Line ◽  
Gene Expression Profiles ◽  
Late Embryogenesis Abundant ◽  
Heat Shock Factor 1 ◽  
Genome Wide ◽  
A Genome

The Pv11, an insect cell line established from the midge Polypedilum vanderplanki, is capable of extreme hypometabolic desiccation tolerance, so-called anhydrobiosis. We previously discovered that heat shock factor 1 (HSF1) contributes to the acquisition of desiccation tolerance by Pv11 cells, but the mechanistic details have yet to be elucidated. Here, by analyzing the gene expression profiles of newly established HSF1-knockout and -rescue cell lines, we show that HSF1 has a genome-wide effect on gene regulation in Pv11. The HSF1-knockout cells exhibit a reduced desiccation survival rate, but this is completely restored in HSF1-rescue cells. By comparing mRNA profiles of the two cell lines, we reveal that HSF1 induces anhydrobiosis-related genes, especially genes encoding late embryogenesis abundant proteins and thioredoxins, but represses a group of genes involved in basal cellular processes, thus promoting an extreme hypometabolism state in the cell. In addition, HSF1 binding motifs are enriched in the promoters of anhydrobiosis-related genes and we demonstrate binding of HSF1 to these promoters by ChIP-qPCR. Thus, HSF1 directly regulates the transcription of anhydrobiosis-related genes and consequently plays a pivotal role in the induction of anhydrobiotic ability in Pv11 cells.

scholarly journals Genome-Wide Role of HSF1 in Transcriptional Regulation of Desiccation Tolerance in the Anhydrobiotic Cell Line, Pv11

2021 ◽  
Author(s):  
Shoko Tokumoto ◽  
Yugo Miyata ◽  
Ruslan Deviatiiarov ◽  
Takahiro G. Yamada ◽  
Yusuke Hiki ◽  
...  
Keyword(s):  
Cell Line ◽  
Cell Lines ◽  
Desiccation Tolerance ◽  
Expression Profiles ◽  
Insect Cell Line ◽  
Gene Expression Profiles ◽  
Late Embryogenesis Abundant ◽  
Heat Shock Factor 1 ◽  
Genome Wide ◽  
A Genome

Pv11, an insect cell line established from the midge Polypedilum vanderplanki, is capable of ametabolic desiccation tolerance, so-called anhydrobiosis. We previously discovered that heat shock factor 1 (HSF1) contributes to the acquisition of desiccation tolerance by Pv11 cells, but the mechanistic details have yet to be elucidated. Here, by analyzing the gene expression profiles of newly established HSF1-knockout and -rescue cell lines, we show that HSF1 has a genome-wide effect on gene regulation in Pv11. HSF1-knockout cells exhibit a reduced desiccation survival rate, but this is completely restored in HSF1-rescue cells. By comparing mRNA profiles of the two cell lines, we reveal that HSF1 induces anhydrobiosis-related genes, especially genes encoding late embryogenesis abundant proteins and thioredoxins, but represses a group of genes involved in basal cellular processes, thus promoting an ametabolic state in the cell. In addition, HSF1 binding motifs are enriched in the promoters of anhydrobiosis-related genes and we demonstrate binding of HSF1 to these promoters by ChIP-qPCR. Thus, HSF1 directly regulates the transcription of anhydrobiosis-related genes and consequently plays a pivotal role in the induction of anhydrobiotic ability in Pv11 cells.

scholarly journals Engineering Enhanced Vaccine Cell Lines To Eradicate Vaccine-Preventable Diseases: the Polio End Game

2015 ◽  
Vol 90 (4) ◽  
pp. 1694-1704 ◽  
Author(s):  
Sabine M. G. van der Sanden ◽  
Weilin Wu ◽  
Naomi Dybdahl-Sissoko ◽  
William C. Weldon ◽  
Paula Brooks ◽  
...  
Keyword(s):  
Gene Silencing ◽  
Cell Line ◽  
Cell Lines ◽  
Enterovirus 71 ◽  
Vaccine Production ◽  
Wild Type ◽  
Vaccine Preventable Diseases ◽  
Manufacturing Cell ◽  
Genome Wide ◽  
A Genome

ABSTRACTVaccine manufacturing costs prevent a significant portion of the world's population from accessing protection from vaccine-preventable diseases. To enhance vaccine production at reduced costs, a genome-wide RNA interference (RNAi) screen was performed to identify gene knockdown events that enhanced poliovirus replication. Primary screen hits were validated in a Vero vaccine manufacturing cell line using attenuated and wild-type poliovirus strains. Multiple single and dual gene silencing events increased poliovirus titers >20-fold and >50-fold, respectively. Host gene knockdown events did not affect virus antigenicity, and clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9-mediated knockout of the top candidates dramatically improved viral vaccine strain production. Interestingly, silencing of several genes that enhanced poliovirus replication also enhanced replication of enterovirus 71, a clinically relevant virus to which vaccines are being targeted. The discovery that host gene modulation can markedly increase virus vaccine production dramatically alters mammalian cell-based vaccine manufacturing possibilities and should facilitate polio eradication using the inactivated poliovirus vaccine.IMPORTANCEUsing a genome-wide RNAi screen, a collection of host virus resistance genes was identified that, upon silencing, increased poliovirus and enterovirus 71 production by from 10-fold to >50-fold in a Vero vaccine manufacturing cell line. This report provides novel insights into enterovirus-host interactions and describes an approach to developing the next generation of vaccine manufacturing through engineered vaccine cell lines. The results show that specific gene silencing and knockout events can enhance viral titers of both attenuated (Sabin strain) and wild-type polioviruses, a finding that should greatly facilitate global implementation of inactivated polio vaccine as well as further reduce costs for live-attenuated oral polio vaccines. This work describes a platform-enabling technology applicable to most vaccine-preventable diseases.

scholarly journals Synergistic Use of Geniposide and Ginsenoside Rg1 Balance Microglial TNF-αand TGF-β1 following Oxygen-Glucose DeprivationIn Vitro: A Genome-Wide Survey

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Jun Wang ◽  
Jincai Hou ◽  
Hui Zhao ◽  
Jianxun Liu
Keyword(s):  
Cell Viability ◽  
Transforming Growth Factor ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Glucose Deprivation ◽  
Ginsenoside Rg1 ◽  
Neuroprotective Effects ◽  
Genome Wide ◽  
A Genome ◽  
Bv2 Microglial Cells

Ischemia-activated microglia are like a double-edged sword, characterized by both neurotoxic and neuroprotective effects. The aim of this study was to reveal the synergistic effect of geniposide and ginsenoside Rg1 based on tumor necrosis factor- (TNF-)αand transforming growth factor- (TGF-)β1 balance of microglia. BV2 microglial cells were divided into 5 groups: control, model (oxygen-glucose deprivation (OGD)), geniposide-treated, ginsenoside-Rg1-treated, and combination-treated. A series of assays were used to detect on (i) cell viability; (ii) NO content; (iii) expression (content) of TNF-αand TGF-β1; and (iv) gene expression profiles. The results showed that integrated use of geniposide and ginsenoside Rg1 significantly inhibited NO level and protected cell viability, improved the content and expression of TGF-β1, and reduced the content and expression of TNF-α. Separated use of geniposide or ginsenoside Rg1 showed different effects at different emphases. Next-generation sequencing showed that Fcγ-receptor-mediated phagocytosis pathway played a key regulatory role in the balance of TNF-αand TGF-β1 when cotreated with geniposide and ginsenoside Rg1. These findings suggest that synergistic drug combination of geniposide and ginsenoside Rg1 in the treatment of stroke is a feasible avenue for the application.

scholarly journals Predicting breast cancer drug response using a multiple-layer cell line drug response network model

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shujun Huang ◽  
Pingzhao Hu ◽  
Ted M. Lakowski
Keyword(s):  
Cell Line ◽  
Cell Lines ◽  
Drug Response ◽  
Expression Profiles ◽  
Pearson Correlation ◽  
Gene Expression Profiles ◽  
Response Prediction ◽  
Layer Cell ◽  
Response Network ◽  
Line Drug

Abstract Background Predicting patient drug response based on a patient’s molecular profile is one of the key goals of precision medicine in breast cancer (BC). Multiple drug response prediction models have been developed to address this problem. However, most of them were developed to make sensitivity predictions for multiple single drugs within cell lines from various cancer types instead of a single cancer type, do not take into account drug properties, and have not been validated in cancer patient-derived data. Among the multi-omics data, gene expression profiles have been shown to be the most informative data for drug response prediction. However, these models were often developed with individual genes. Therefore, this study aimed to develop a drug response prediction model for BC using multiple data types from both cell lines and drugs. Methods We first collected the baseline gene expression profiles of 49 BC cell lines along with IC50 values for 220 drugs tested in these cell lines from Genomics of Drug Sensitivity in Cancer (GDSC). Using these data, we developed a multiple-layer cell line-drug response network (ML-CDN2) by integrating a one-layer cell line similarity network based on the pathway activity profiles and a three-layer drug similarity network based on the drug structures, targets, and pan-cancer IC50 profiles. We further used ML-CDN2 to predict the drug response for new BC cell lines or patient-derived samples. Results ML-CDN2 demonstrated a good predictive performance, with the Pearson correlation coefficient between the observed and predicted IC50 values for all GDSC cell line-drug pairs of 0.873. Also, ML-CDN2 showed a good performance when used to predict drug response in new BC cell lines from the Cancer Cell Line Encyclopedia (CCLE), with a Pearson correlation coefficient of 0.718. Moreover, we found that the cell line-derived ML-CDN2 model could be applied to predict drug response in the BC patient-derived samples from The Cancer Genome Atlas (TCGA). Conclusions The ML-CDN2 model was built to predict BC drug response using comprehensive information from both cell lines and drugs. Compared with existing methods, it has the potential to predict the drug response for BC patient-derived samples.

scholarly journals Essentiality of CREBBP in EP300 truncated B-cell lymphoma revealed by genome-wide CRISPR-Cas9 screen

2019 ◽  
Author(s):  
Man Nie ◽  
Likun Du ◽  
Bo Zhang ◽  
Weicheng Ren ◽  
Julia Joung ◽  
...  
Keyword(s):  
B Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Time Course ◽  
Course Design ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Genetic Alterations ◽  
Genome Wide ◽  
A Genome

AbstractHistone acetyltransferases (HATs), including CREBBP and EP300, are frequently mutated in B-cell malignancies and usually play a tumor-suppressive role. In this study, we performed whole genome and transcriptome sequencing and a genome-wide CRISPR-Cas9 knockout screen to study a germinal center B-cell like diffuse large B-cell lymphoma (DLBCL) cell line (RC-K8). Using a summarizing method that is optimized to address the complexity introduced by the time-course design, we identified a distinct pattern of genetic essentialities in RC-K8, including a dependency on CREBBP and MDM2, shown already at early time points and a gradually increased dependency on oxidative phosphorylation related genes. The dependency on CREBBP is associated with the corresponding genetic alterations identified in this cell line, i.e. a balanced translocation involves EP300, which resulted in a truncated form of protein that lacks the critical bromodomain and HAT domain. We further evaluated the previously published CRISPR-Cas9 screens and identified a genetic essentiality of CREBBP or EP300 gene in a small set of cancer cell lines, including several DLBCL cell lines that are highly sensitive for EP300 knockout and with CREBBP mutations or copy number loss. The dependency of the remaining HAT function in CREBBP and/or EP300-deficient genotype was validated by testing the HAT-domain inhibitor A-485. Our study suggests that integration of the unbiased, time-course-based functional screen results with the genomic and transcriptomic data can identify druggable vulnerability in individual or subgroups of cell lines/patients, which may help to develop more effective therapeutic strategies for cancers that are genetically highly heterogeneous, like DLBCL.

Melphalan Resistance in Multiple Myeloma Can Be Overcome by Proteasome Inhibition or Histone Deacetylation: Lack of Syngergism of the Combination.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3393-3393
Author(s):  
Pieter Sonneveld ◽  
Eric Kamst ◽  
Yvonne de Knegt ◽  
Naomi Klarenbeek ◽  
Martijn Schoester
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Line ◽  
Cell Lines ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Proteasome Inhibition ◽  
Histone Deacetylation ◽  
Interaction Factor ◽  
Resistant Cells

Abstract Multiple Myeloma (MM) is a disease of monoclonal plasma cells in the bone marrow which has a transient response to classic chemotherapy. At diagnosis, induction chemotherapy followed by high-dose melphalan (HDM) with stem cell support is used in most patients to achieve a clinical response. Because all patients will ultimately relapse, the treatment of melphalan-refractory disease represents a major clinical challenge and new agents are needed to overcome melphalan resistance. We have investigated the anti-myeloma efficacy of two new classes of targeted agents, i.e. proteasome inhibition and histone deacetylation inhibition alone or in combination in the melphalan sensitive MM1S and the Melphalan refractory MM1MEL2000 cell lines. The IC50 values of Bortezomib (B), Melphalan (M) and LAQ824 (L) in MM1S were 2.1 nM, 1.9 uM and 1.7 nM, respectively and in MM1MEL2000 3.9 nM, 50 uM and 4.0 nM. Using isobologram analysis a synergysm between B and L was observed in the sensitive, however not in the melphalan refractory cell line. These data indicate that B proteasome inhibition and histone deacetylation inhibition may be effective ways to overcome melphalan resistance. However, the previously reported synergism between these drugs does not seem to occur in melphalan resistant cells. The gene expression profiles of these cell lines were analysed using the Affymetrix U133plus 2.0 gene chip before and after treatment with melfaphalan or the proteasome inhibitor B or the histone deacetylation inhibitor L or the combination of B and L. Genes that were highly expressed in the melphalan refractory derivate cell line MM1MEL2000 as compared with wild-type MM1S included GP M6B, ADAM23 and HTPAP. Following melphalan exposure, TMF1, a CEBp glucocorticoid interaction factor, WHSC1L1, a MMSET homologue with EGF like domain and several transcription factors had highly increased expression as compared to MM1S. With exposure to B combined with L, increased expression in MM1MEL2000 over MM1S was observed for GTP exchange factor TIAM1 which interacts with RAS and JNK, and the lymphoid enhancer factor, a notch transcription factor. It is concluded that Bortezomib and the histone deacetylase inhibitor LAQ824 are effective agents to overcome melphalan resistance in multiple myeloma. However, the combination fails to show the synergism observed in melphalan sensitive cells. Gene analysis sofar does not provide a clear explanation for this lack of synergism. A comprehensive summary of the observed shifts of gene expression profiles in melphalan resistant cells following exposure to these agents, will be presented.

Metabolic evaluation of sporadic papillary kidney cancer.

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 377-377
Author(s):  
Brian Shuch ◽  
Christopher Ricketts ◽  
Carole Sourbier ◽  
Shinji Tsutsumi ◽  
Xiu-ying Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Membrane Potential ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Kidney Cancer ◽  
Expression Profiles ◽  
Fumarate Hydratase ◽  
Gene Expression Profiles ◽  
Cancer Cell Lines

377 Background: Papillary kidney cancer, which occurs in 15% of patients with kidney cancer, can be aggressive and there is currently no effective form of therapy for this disease. To evaluate the metabolic characteristics of sporadic papillary kidney cancer, we have evaluated metabolic parameters of several papillary kidney cancer cell lines and available gene expression profiles. Methods: Established cell lines derived from patients with sporadic papillary kidney cancer (LABAZ, MDACC-55, HRC-86T2) and from a hereditary form of fumarate hydratase-deficient kidney cancer (UOK262) were evaluated. All sporadic lines were initially sequenced for fumarate hydratase (FH). All cell lines were metabolically profiled using the Seahorse Extracellular Flux Analyzer and further evaluated for reactive oxygen species (ROS), mitochondrial membrane potential, and glucose dependence. Finally gene expression profiles of publically available datasets of papillary and HLRCC tumors were downloaded, normalized, and analyzed. Results: Sporadic lines had no alterations in FH and metabolic analysis demonstrated normal oxygen consumption and minimal lactate production, in contrast to highly glycolytic UOK262. Also unlike UOK262, the sporadic papillary kidney cancer lines were not sensitive to glucose withdrawal, had low levels of ROS, and had normal mitochondria membrane potential. Principal component analysis (PCA) demonstrated that HLRCC tumor specimens are very different from sporadic papillary tumors at the molecular level. Conclusions: Our study of established sporadic papillary RCC and fumarate hydratase-deficient HLRCC cell line together with analysis of available gene expression profiles demonstrates that these sporadic papillary kidney cancer cell lines appear to have a distinct metabolic profile from those in the fumarate hydratase deficient kidney cancer cell line. Understanding the metabolic basis of papillary kidney cancer could provide the foundation for the development of targeted approaches to therapy for patients with this disease.

scholarly journals CTDPathSim: Cell line-tumor deconvoluted pathway-based similarity in the context of precision medicine in cancer *

2020 ◽  
Author(s):  
Banabithi Bose ◽  
Serdar Bozdag
Keyword(s):  
Precision Medicine ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Drug Response ◽  
Expression Profiles ◽  
Cancer Cell Lines ◽  
List Type ◽  
Primary Tumors ◽  
A Genome

ABSTRACTIn cancer research and drug development, human tumor-derived cell lines are used as popular model for cancer patients to evaluate the biological functions of genes, drug efficacy, side-effects, and drug metabolism. Using these cell lines, the functional relationship between genes and drug response and prediction of drug response based on genomic and chemical features have been studied. Knowing the drug response on the real patients, however, is a more important and challenging task. To tackle this challenge, some studies integrate data from primary tumors and cancer cell lines to find associations between cell lines and tumors. These studies, however, do not integrate multi-omics datasets to their full extent. Also, several studies rely on a genome-wide correlation-based approach between cell lines and bulk tumor samples without considering the heterogeneous cell population in bulk tumors. To address these gaps, we developed a computational pipeline, CTDPathSim, a pathway activity-based approach to compute similarity between primary tumor samples and cell lines at genetic, genomic, and epigenetic levels integrating multi-omics datasets. We utilized a deconvolution method to get cell type-specific DNA methylation and gene expression profiles and computed deconvoluted methylation and expression profiles of tumor samples. We assessed CTDPathSim by applying on breast and ovarian cancer data in The Cancer Genome Atlas (TCGA) and cancer cell lines data in the Cancer Cell Line Encyclopedia (CCLE) databases. Our results showed that highly similar sample-cell line pairs have similar drug response compared to lowly similar pairs in several FDA-approved cancer drugs, such as Paclitaxel, Vinorelbine and Mitomycin-c. CTDPathSim outperformed state-of-the-art methods in recapitulating the known drug responses between samples and cell lines. Also, CTDPathSim selected higher number of significant cell lines belonging to the same cancer types than other methods. Furthermore, our aligned cell lines to samples were found to be clinical biomarkers for patients’ survival whereas unaligned cell lines were not. Our method could guide the selection of appropriate cell lines to be more intently serve as proxy of patient tumors and could direct the pre-clinical translation of drug testing into clinical platform towards the personalized therapies. Furthermore, this study could guide the new uses for old drugs and benefits the development of new drugs in cancer treatments.CCS CONCEPTSComputational biologyGenomicsSystems biologyBioinformaticsGeneticsACM Reference formatBanabithi Bose, Serdar Bozdag. 2020. CTDPathSim: Cell line-tumor deconvoluted pathway-based similarity in the context of precision medicine in cancer.

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