scholarly journals Quantitative relationships for radiation induced chromosome instability: data analysis

2017 ◽  
Author(s):  
Y.A. Eidelman ◽  
S.V. Slanina ◽  
V.S. Pyatenko ◽  
I.K. Khvostunov ◽  
S.G. Andreev

ABSTRACTThe experimental observations demonstrate that different cell lines reveal various shape of dynamic curves for radiation-induced chromosomal instability (RICI). We analyzed our own and published data on RICI for three cell lines, CHO-K1, V79 and TK6, on the basis of the mechanistic RICI model. We demonstrate that all three dynamic curves can be successfully described by the proposed model with partially cell line specific parameters.


2017 ◽  
Author(s):  
Y.A. Eidelman ◽  
S.V. Slanina ◽  
V.S. Pyatenko ◽  
I.K. Khvostunov ◽  
S.G. Andreev

ABSTRACTDifferent cell lines demonstrate various dose response for radiation-induced chromosomal instability (RICI). To clarify the origin of differences we analyzed own and published data on RICI for four cell lines, V79, TK6, WTK1 and CHO-K1 on the basis of the mechanistic RICI model. We conclude that observable dose-response shapes, both plateau-like and strong dose dependent behavior, may be jointly explained by the same model of RICI. Mechanistic modeling reveals that a variation of certain set of RICI parameters leads to strong modification of dose-response curve.



Author(s):  
Ajita Narayan ◽  
Cathy Tuck-Muller ◽  
Karen Weissbecker ◽  
Dominique Smeets ◽  
Melanie Ehrlich


2021 ◽  
Author(s):  
Ali Reza Ebadi ◽  
Ali Soleimani ◽  
Abdulbaghi Ghaderzadeh

Abstract Anti-cancer medicine for a particular patient has been a personal medical goal. Many computational models have been proposed by researchers to predict drug response. But predictive accuracy still remains a challenge. Base on this concept which “Similar cells have similar responses to drugs”, we developed the basic method of matrix factorization method by adding fines to similarity. So that the distance of latent factors to two cell lines or (drug) should be inversely related to similarity. This means that two similar drugs or similar cell lines should have a short distance, whereas two similar cell lines or non-similar drugs should have a large gap with their latent factors. We proposed a Dual similarity-regularized matrix factorization (DSRMF) model, then generated new data for drug similarity from the two-dimensional three-dimensional chemical structure, which were obtained from the CCLE and GDSC databases. In this research, by using the proposed model, and generating new drug similarity data we achieved the average Pearson correlation coefficient (PCC) about 0.96, and average mean square error (RMSE) Root about 0.30, between the observed value and the predicted value for the cell line response to the drug. Our analysis in this research showed, using heterogeneous data, has better results, and can be obtained with the proposed model, using other panels’ cancer cell lines, to calculate similarity between cells. Also, by imposing more restrictions on the similarity between cells, we were able to achieve more accurate prediction for the response of the cell line to the anticancer drug.



2020 ◽  
Author(s):  
ALI REZA EBADI ◽  
Ali Soleimani ◽  
ABDULBAGHI GHADERZADEH

Abstract Background:Anti-cancer medicine for a particular patient has been a personal medical goal. Many computational models have been proposed by researchers to predict drug response. But predictive accuracy still remains a challenge. Base on this concept which “Similar cells have similar responses to drugs”, we developed the basic method of matrix factorization method by adding fines to similarity. So that the distance of latent factors to two cell lines or (drug) should be inversely related to similarity. This means that two similar drugs or similar cell lines should have a short distance, whereas two similar cell lines or non-similar drugs should have a large gap with their latent factors.Results:We proposed a Dual similarity-regularized matrix factorization (DSRMF) model, then generated new data for drug similarity from the two-dimensional three-dimensional chemical structure, which were obtained from the CCLE and GDSC databases. In this research, by using the proposed model, and generating new drug similarity data we achieved the average Pearson correlation coefficient (PCC) about 0.96, and average mean square error (RMSE) Root about 0.30, between the observed value and the predicted value for the cell line response to the drug, Conclusions:Our analysis in this research showed, using heterogeneous data, has better results, and can be obtained with the proposed model, using other panels’ cancer cell lines, to calculate similarity between cells. Also, by imposing more restrictions on the similarity between cells, we were able to achieve more accurate prediction for the response of the cell line to the anticancer drug.



2009 ◽  
Vol 110 (3) ◽  
pp. 594-604 ◽  
Author(s):  
Yoshifumi Tsuboi ◽  
Masanori Kurimoto ◽  
Shoichi Nagai ◽  
Yumiko Hayakawa ◽  
Hironaga Kamiyama ◽  
...  

Object The intrinsic radioresistance of certain cancer cells may be closely associated with the constitutive activation of nuclear factor–kappa B (NF-κB) activity, which may lead to protection from apoptosis. Recently, nonapoptotic cell death, or autophagy, has been revealed as a novel response of cancer cells to ionizing radiation. In the present study, the authors analyzed the effect of pitavastatin as a potential inhibitor of NF-κB activation on the radiosensitivity of A172, U87, and U251 human glioma cell lines. Methods The pharmacological inhibition of NF-κB activation was achieved using pitavastatin, an inhibitor of 3-hydroxy-3-methylglutaryl coenzyme A reductase. Growth and radiosensitivity assays were performed using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Hoechst 33258 staining, supravital acridine orange staining, and electron microscopy were performed utilizing 3 glioma cell lines with or without pitavastatin pretreatment to identify apoptosis or autophagy after irradiation. Results The growth of these 3 glioma cell lines was not significantly inhibited by pitavastatin at a concentration of up to 1 μM. Treatment with 0.1 μM of pitavastatin enhanced radiation-induced cell death in all glioma cell lines, with different sensitivity. Apoptosis did not occur in any pretreated or untreated (no pitavastatin) cell line following irradiation. Instead, autophagic cell changes were observed regardless of the radiosensitivity of the cell line. An inhibitor of autophagy, 3-methyladenine suppressed the cytotoxic effect of irradiation with pitavastatin, indicating that autophagy is a result of an antitumor mechanism. Using the most radiosensitive A172 cell line, the intracellular localization of p50, a representative subunit of NF-κB, was evaluated through immunoblotting and immunofluorescence studies. The NF-κB of A172 cells was immediately activated and translocated from the cytosol to the nucleus in response to irradiation. Pitavastatin inhibited this activation and translocation of NF-κB. Conclusions Autophagic cell death rather than apoptosis is a possible mechanism of radiation-induced and pitavastatin-enhanced cell damage, and radiosensitization by the pharmacological inhibition of NF-κB activation may be a novel therapeutic strategy for malignant gliomas.



Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2024-2024
Author(s):  
Laura Spence ◽  
Sophie Hambleton ◽  
Venetia Bigley ◽  
Sarah Pagan ◽  
Matthew Collin

Abstract Abstract 2024 Poster Board II-1 The combination of tumor-sensitizing drugs with NK cell infusion is beginning to emerge as a novel anti-tumor therapy. A growing body of in vitro studies show that drugs such as proteosome inhibitors, histone deacetylase inhibitors and thiazolidinediones are able to sensitize tumor cells but not their healthy counterparts to NK-mediated lysis. Drug induced NK-sensitization has shown promise in acute myeloid leukemias but no studies have yet proven this principle in acute lymphoblastic leukemia (ALL); a tumor phenotype reported to be relatively NK-resistant. The mechanisms underlying sensitization have not been fully identified but up regulation of ligands for TRAIL and the NK activating receptor NKG2D: MICA MICB and the UL16-binding proteins, may have a role. We set out to explore ALL susceptibility to NK cytotoxicity and whether this could be modulated by drug treatment. In contrast to published data, untreated ALL cell lines were positive for surface expression of MICB and ULBP2. Median fluorescence intensity ratios (mean ± SD; n = 6) for MICB detection on the cell lines 697, NALM-6, BV173 and SEM were: 3.2 ± 0.9; 3.8 ± 1.3; 4.0 ± 0.5; 2.5 ± 0.9, respectively and for ULBP-2: 2.3 ± 0.4; 55 ± 4.9; 2.9 ± 0.2; 1.8 ± 0.4, respectively. NALM-6 was also positive for ULBP1 (3.3 ± 0.6) while all were negative for MICA and ULBP3. Susceptibility of untreated ALL lines to NK mediated killing was assessed by chromium release assay using an IL-2 stimulated primary NK cell line. At effector to target ratio 40:1, specific release was 2.3% with cell line 697, 12% with NALM-6, 36% with BV173 and 63% with SEM. These results correlated with CD107a exposure in a degranulation assay using IL-2 stimulated peripheral blood lymphocytes: specific degranulation (% CD107a+ target with effector minus %CD107a+ effector alone) was 0.68% (697), 7.1% (NALM-6), 10% (BV173) and 17% (SEM). There was no correlation between baseline expression of NKG2DL and susceptibility to NK killing. Bortezomib, sodium valproate and troglitazone were added to cell cultures at sub-IC50 doses for 48 hours and compared with equimolar vehicle controls. Surface NKG2DL expression was measured by flow cytometry. On NALM-6 troglitazone treatment increased ULBP1 MFI by 2.0 ± 0.33 fold compared with vehicle control and increased percentage of ULBP1 positive cells by 39.6% (paired t-test: p=0.063). Sodium valproate increased MICA expression by 2.91 ± 1.18 fold and percentage of MICA positive cells by 12.3% (p=0.0382). On BV173, sodium valproate treatment increased ULBP2 MFI by 1.55 ± 0.07 fold and percentage of ULBP2 positive cells by 8.6% (p=0.04). There were no significant ligand changes after drug treatment on cell line 697. No NKG2DL changes were seen after Bortezomib treatment on any cell line. The functional significance of NKG2DL changes was assessed by CD107a degranulation assay. NALM-6 treated for 48 hours with drugs yielded the following fold increases in specific degranulation of NK cells compared to NALM-6 vehicle controls: 5.02 ± 5.98 for Bortezomib (mean ± SD), 2.4 ± 0.67 for Troglitazone and 1.44 ± 0.13 for Valproate. Levels of NK degranulation with 697 were very low (<5%) and drug treatment had no effect. Finally, we demonstrated that sensitization of NALM-6 was at least partly dependent on NKG2DL recognition, since blocking antibody to NKG2D reduced CD107a exposure by all three drugs. Compared with controls, blocking reduced CD107a expression by 59 ± 12% for Bortezomib, 47 ± 1.1% for Troglitazone and 48 ±11% for valproate-treated cells. This result was unexpected for Bortezomib as no changes in surface NKG2DL expression were detected after drug treatment. However, we are investigating the possibility that Bortezomib may down-regulate HLA class I expression, thus reducing inhibitory signaling upon NALM-6/NK interaction and unmasking an activation pathway that signals through NKG2D. In conclusion, we found basal levels of expression of NKG2DL on ALL cell lines. There was no correlation between NKG2DL expression and susceptibility to NK lysis, although this was to be expected given that a wealth of other activating and inhibitory receptors that contribute to NK activation. Bortezimib, valproate and troglitazone induced NKG2DL expression and sensitization to NK recognition in a cell line-specific manner. These drugs may therefore be useful to augment conventional chemotherapy or immunotherapeutic approaches to ALL. Disclosures: No relevant conflicts of interest to declare.



2020 ◽  
Author(s):  
Dongdong Lin ◽  
Hima Yalamanchili ◽  
Xinmin Zhang ◽  
Nathan E. Lewis ◽  
Christina S. Alves ◽  
...  

ABSTRACTChinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. High-throughput omics approaches have been increasingly utilized to reveal cellular mechanisms associated with cell line phenotypes and guide process optimization, comprehensive omics data analysis and management have been a challenge. Here we developed CHOmics, a web-based tool for integrative analysis of CHO cell line omics data that provides an interactive visualization of omics analysis outputs and efficient data management. CHOmics has a built-in comprehensive pipeline for RNA sequencing data processing and multilayer statistical modules to explore relevant genes or pathways. Moreover, advanced functionalities were provided to enable users to customize their analysis and visualize the output systematically and interactively. The tool was also designed with the flexibility to allow other omics data input and thereby enabling multi-omics comparison and visualization at both gene and pathway levels. Collectively, CHOmics is an integrative platform for data analysis, visualization and management with expectations to promote the broader use of omics in CHO cell research. The open-source tool is freely available at http://www.chomics.org.



2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Bhanu Prasad Venkatesulu ◽  
Amrish Sharma ◽  
Julianne M. Pollard-Larkin ◽  
Ramaswamy Sadagopan ◽  
Jessica Symons ◽  
...  

AbstractRecent reports have shown that very high dose rate radiation (35–100 Gy/second) referred to as FLASH tends to spare the normal tissues while retaining the therapeutic effect on tumor. We undertook a series of experiments to assess if ultra-high dose rate of 35 Gy/second can spare the immune system in models of radiation induced lymphopenia. We compared the tumoricidal potency of ultra-high dose rate and conventional dose rate radiation using a classical clonogenic assay in murine pancreatic cancer cell lines. We also assessed the lymphocyte sparing potential in cardiac and splenic irradiation models of lymphopenia and assessed the severity of radiation-induced gastrointestinal toxicity triggered by the two dose rate regimes in vivo. Ultra-high dose rate irradiation more potently induces clonogenic cell death than conventional dose rate irradiation with a dose enhancement factor at 10% survival (DEF10) of 1.310 and 1.365 for KPC and Panc02 cell lines, respectively. Ultra-high dose rate was equally potent in depleting CD3, CD4, CD8, and CD19 lymphocyte populations in both cardiac and splenic irradiation models of lymphopenia. Radiation-induced gastrointestinal toxicity was more pronounced and mouse survival (7 days vs. 15 days, p = 0.0001) was inferior in the ultra-high dose rate arm compared to conventional dose rate arm. These results suggest that, contrary to published data in other models of radiation-induced acute and chronic toxicity, dose rates of 35 Gy/s do not protect mice from the detrimental side effects of irradiation in our models of cardiac and splenic radiation-induced lymphopenia or gastrointestinal mucosal injury.



2020 ◽  
Vol 16 (12) ◽  
pp. e1008498
Author(s):  
Dongdong Lin ◽  
Hima B. Yalamanchili ◽  
Xinmin Zhang ◽  
Nathan E. Lewis ◽  
Christina S. Alves ◽  
...  

Chinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. While high-throughput omics approaches have been increasingly utilized to reveal cellular mechanisms associated with cell line phenotypes and guide process optimization, comprehensive omics data analysis and management have been a challenge. Here we developed CHOmics, a web-based tool for integrative analysis of CHO cell line omics data that provides an interactive visualization of omics analysis outputs and efficient data management. CHOmics has a built-in comprehensive pipeline for RNA sequencing data processing and multi-layer statistical modules to explore relevant genes or pathways. Moreover, advanced functionalities were provided to enable users to customize their analysis and visualize the output systematically and interactively. The tool was also designed with the flexibility to accommodate other types of omics data and thereby enabling multi-omics comparison and visualization at both gene and pathway levels. Collectively, CHOmics is an integrative platform for data analysis, visualization and management with expectations to promote the broader use of omics in CHO cell research.



Sign in / Sign up

Export Citation Format

Share Document