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Cell Survival

Cell Survival is the ability of cells to maintain viability and function under various environmental conditions.
This process involves complex mechanisms that allow cells to adapt, repair damage, and resist apoptosis or necrosis.
Understanding cell survival is crucial for advancinig research in areas such as tissue regeneration, cancer biology, and neurodegenerative diseases.
PubCompare.ai is an innovtaive AI-driven tool that can help optimize cell survival experiments by identifying the best protocols from literature, preprints, and patents, using advanced comparison techniques to improve reproducibility and drive research forward.

Most cited protocols related to «Cell Survival»

1
Comprehensive Cancer Cell Line Profiling
A total of 947 independent cancer cell lines were profiled at the genomic level (data available at www.broadinstitute.org/ccle and Gene Expression Omnibus (GEO) using accession numbers GSE36139) and compound sensitivity data was obtained for 479 lines (Supplementary Table 11). Mutation information was obtained both by using massively parallel sequencing of >1,600 genes (Supplementary Table 12) and by mass spectrometric genotyping (OncoMap), which interrogated 492 mutations in 33 known oncogenes and tumor suppressors. Genotyping/copy number analysis was performed using Affymetrix Genome-Wide Human SNP Array 6.0 and expression analysis using the GeneChip Human Genome U133 Plus 2.0 Array. 8-point dose response curves were generated for 24 anticancer drugs using an automated compound-screening platform. Compound sensitivity data were used for two types of predictive models that utilized the naive Bayes classifier or the elastic net regression algorithm. The effects of AHR expression silencing on cell viability were assessed by stable expression of shRNA lentiviral vectors targeting either this gene or luciferase as control. The effect of compound treatment on AHR target gene expression was assessed by quantitative RT-PCR. A full description of the Methods is included in the Supplementary Information.
Barretina J., Caponigro G., Stransky N., Venkatesan K., Margolin A.A., Kim S., Wilson C.J., Lehár J., Kryukov G.V., Sonkin D., Reddy A., Liu M., Murray L., Berger M.F., Monahan J.E., Morais P., Meltzer J., Korejwa A., Jané-Valbuena J., Mapa F.A., Thibault J., Bric-Furlong E., Raman P., Shipway A., Engels I.H., Cheng J., Yu G.K., Yu J., Aspesi P J.r., de Silva M., Jagtap K., Jones M.D., Wang L., Hatton C., Palescandolo E., Gupta S., Mahan S., Sougnez C., Onofrio R.C., Liefeld T., MacConaill L., Winckler W., Reich M., Li N., Mesirov J.P., Gabriel S.B., Getz G., Ardlie K., Chan V., Myer V.E., Weber B.L., Porter J., Warmuth M., Finan P., Harris J.L., Meyerson M., Golub T.R., Morrissey M.P., Sellers W.R., Schlegel R, & Garraway L.A. (2012). The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity. Nature, 483(7391), 603-607.
Publication 2012
Cell Lines Cell Survival Cloning Vectors Gene Chips Gene Expression Genes Genome, Human Hypersensitivity Luciferases Malignant Neoplasms Mass Spectrometry Mutation Oncogenes Pharmaceutical Preparations Reverse Transcriptase Polymerase Chain Reaction Short Hairpin RNA Tumor Suppressor Genes
2
Reprogramming Fibroblasts to iPSCs
A schematic diagram of the procedure is described in Figure 4. Episomal plasmids and methods were described previously15 (link). Plasmid combination #19 (pEP4-E-O2S-E-T2K, pEP4-E-O2S-E-N2K and pCEP4M2L) was used for most reprogramming unless mentioned otherwise. Plasmids and EBNA mRNA were electroporated into fibroblast cells on Amaxa apparatus according to company instructions. One million cells were used in each electroporation, which were then plated into two 6-well plates. E8 + hydrocortisone media were used for the first 5–10 days, according to cell survival and proliferation after electroporation. When confluency was reached ~20%, hydrocortisone was removed. ES-like iPS cell colonies usually appear after ~25 days. Cells were then picked into individual wells with E8 (TGFβ or NODAL). Cells were passaged for ~ 15 passages before subcloning with Y27632 on Matrigel or vitronectin.
Chen G., Gulbranson D.R., Hou Z., Bolin J.M., Ruotti V., Probasco M.D., Smuga-Otto K., Howden S.E., Diol N.R., Propson N.E., Wagner R., Lee G.O., Antosiewicz-Bourget J., Teng J.M, & Thomson J.A. (2011). Chemically defined conditions for human iPS cell derivation and culture. Nature methods, 8(5), 424-429.
Publication 2011
Cells Cell Survival Electroporation Episomes Fibroblasts Hydrocortisone Induced Pluripotent Stem Cells matrigel Plasmids RNA, Messenger Transforming Growth Factor beta Vitronectin Y 27632
3
Episomal Reprogramming of Fibroblasts to iPSCs
Episomal plasmids and methods were described previously15 (link). Plasmid combination #19 (pEP4-E-O2S-E-T2K, pEP4-E-O2S-E-N2K and pCEP4M2L) was used for most reprogramming unless mentioned otherwise. Plasmids and EBNA mRNA were electroporated into fibroblast cells on Amaxa apparatus according to company instructions. One million cells were used in each electroporation, which were then plated into two 6-well plates. E8 + hydrocortisone media were used for the first 5–10 days, according to cell survival and proliferation after electroporation. When confluency was reached ~20%, hydrocortisone was removed. ES-like iPS cell colonies usually appear after ~25 days. Cells were then picked into individual wells with E8 (TGFβ or NODAL). Cells were passaged for ~ 15 passages before subcloning with Y27632 on Matrigel or vitronectin.
Chen G., Gulbranson D.R., Hou Z., Bolin J.M., Ruotti V., Probasco M.D., Smuga-Otto K., Howden S.E., Diol N.R., Propson N.E., Wagner R., Lee G.O., Antosiewicz-Bourget J., Teng J.M, & Thomson J.A. (2011). Chemically defined conditions for human iPS cell derivation and culture. Nature methods, 8(5), 424-429.
Publication 2011
Cells Cell Survival Electroporation Episomes Fibroblasts Hydrocortisone Induced Pluripotent Stem Cells matrigel Plasmids RNA, Messenger Transforming Growth Factor beta Vitronectin Y 27632
4
Compound Screening and Viability Analysis
Experimental protocols used for compound screening are detailed in the Supplemental Experimental Procedures. Effects on cell viability were measured, and a curve-fitting algorithm was applied to this raw dataset to derive a multiparameter description of the drug response (half maximal inhibitory concentration (IC50),and area under the curve [AUC]) through a multilevel mixed model (Vis et al., 2016 (link)) (Supplemental Experimental Procedures).
Iorio F., Knijnenburg T.A., Vis D.J., Bignell G.R., Menden M.P., Schubert M., Aben N., Gonçalves E., Barthorpe S., Lightfoot H., Cokelaer T., Greninger P., van Dyk E., Chang H., de Silva H., Heyn H., Deng X., Egan R.K., Liu Q., Mironenko T., Mitropoulos X., Richardson L., Wang J., Zhang T., Moran S., Sayols S., Soleimani M., Tamborero D., Lopez-Bigas N., Ross-Macdonald P., Esteller M., Gray N.S., Haber D.A., Stratton M.R., Benes C.H., Wessels L.F., Saez-Rodriguez J., McDermott U, & Garnett M.J. (2016). A Landscape of Pharmacogenomic Interactions in Cancer. Cell, 166(3), 740-754.
Publication 2016
Cell Survival Pharmaceutical Preparations Psychological Inhibition
5
Quantifying Synergistic Drug Interactions
To demonstrate the performance of the ZIP-based delta scoring, we considered a recent cancer drug screen study involving ibrutinib in combination with 466 compounds for the activated B-cell-like subtype (ABC) of diffuse large B-cell lymphoma (DLBCL) [14] (link). Ibrutinib is a small molecule targeting Bruton's tyrosine kinase (BTK) approved for the treatment of mantle cell lymphoma and chronic lymphocytic leukemia [16] (link). In this study, a high-throughput drug combination screening was used to identify other compounds that can synergistically interact with ibrutinib to improve its anticancer efficacy and circumvent drug resistance. For each drug pair, a 6 × 6 dose–response matrix design was utilized, where the drug effect was measured as percentage of cell viability using TMD8 cancer cell line. The raw combination data was provided by the authors via personal communication, but can now be downloaded from https://tripod.nih.gov/matrix-client/rest/matrix/export/241. We transformed the original percentage viability data into the percentage inhibition data before applying the drug combination analysis to be compatible with the mathematical formulation defined in the Methods section.
We ran the ZIP model on the drug combination data and calculated a summary delta score Δ for each drug pair by taking the average of all the delta scores over its dose combinations, i.e., Δ=1n∑i=1nδ, where n is the number of dose combinations and n = 25 for a 6 × 6 dose–response matrix (monotherapy responses were removed). We compared the summary delta scores with the other scores derived from the HSA-, Bliss- and Loewe-based models. For HSA and Bliss, there were existing scores implemented in the original study [14] (link), which were based on the following methods: 1) NumExcess is the number of wells in the dose matrix that produced higher effect than both of the individual drug effects; 2) ExcessHSA is the sum of differences between the combination effect and the expected HSA effect; 3) MedianExcess is the median of the HSA excess; 4) ExcessCRX is an extension of the HSA model that was adjusted by dilution factors; 5) LS3 × 3 is the ExcessHSA applied to a 3 × 3 block showing the best HSA synergy in the dose matrix; 6) Beta (β) is the interaction parameter minimizing the deviance from the Bliss independence model over all dose combinations defined as argminβ∑1−yc−β1−y11−y22 ; and 7) Gamma (γ) is a combination of HSA and Bliss models minimizing argminγ∑1−yc−γmax1−y1,1−y22. For the Loewe-based models, we calculated the two common interaction indices CI (Eq. (8)) and alpha(a) (Eq. (9)). The CI was calculated using an R package SYNERGY [13] (link) and the alpha score was estimated using the R package drc[12] .
Yadav B., Wennerberg K., Aittokallio T, & Tang J. (2015). Searching for Drug Synergy in Complex Dose–Response Landscapes Using an Interaction Potency Model. Computational and Structural Biotechnology Journal, 13, 504-513.
Publication 2015
B-Lymphocytes Cell Lines Cell Survival Chronic Lymphocytic Leukemia Diffuse Large B-Cell Lymphoma Drug Combinations Gamma Rays ibrutinib Malignant Neoplasms Mantle-Cell Lymphoma Pharmaceutical Preparations Psychological Inhibition Resistance, Drug Technique, Dilution Tyrosine Kinase, Agammaglobulinaemia

Most recents protocols related to «Cell Survival»

1
Cytotoxicity Evaluation of Nanomaterials
Not available on PMC !

Example 5

MTT cytotoxicity assays were used to assess the cytotoxicity of RGQDs/Nd-GQDs/Tm-GQDs. HeLa cells were plated in a 96-well plate with 5000 cells per well (100 μL/well) and kept in an incubator overnight at 37.1° C. while maintaining the CO2/air ratio of 1:19. After 24 h of incubation, the samples were added into each well at different concentrations for different materials (0 to 70 μg/mL, 1 mg/ml, 0.25 mg/ml for RGQDs, Nd-GQDs, Tm-GQDs, respectively). After 24 h of incubation, the medium was replaced by 100 μL of 1 mg/mL thiazolyl blue tetrazolium bromide. After 4 h of further incubation, MTT (3-(4-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) was replaced with 100 μL of DMSO (dimethyl sulfoxide) to solubilize the precipitation. Reduction in MTT influences the metabolic activity of living cells, which can be assessed with absorbance measurements because living cells metabolize the MTT and form a highly absorbing purple colored byproduct known as formazan. The absorbance (essentially the cell viability) of the final sample was measured at 540 nm wavelength using the FLUOstar Omega microplate reader.

US11873433B2. Near-infrared emissive graphene quantum dots method of manufacture and uses thereof (2024-01-16). Texas Christian University [US]. Inventors: Anton V. Naumov [US], Tanvir Hasan [US].
Patent 2024
Biological Assay Bromides Cells Cell Survival Cytotoxin Formazans HeLa Cells Sulfoxide, Dimethyl thiazolyl blue tetrazolium bromide
2
Adipocyte Lipid Accumulation Inhibition by Compound A
Not available on PMC !

Example 8

Human subcutaneous pre-adipocytes (Zenbio (RTP, NC, U.S.A.)) were received pre-plated in white-walled 96-well plates. A schematic description of the protocol used for examining the effects of Compound A on lipid accumulation in differentiating human adipocytes is shown in FIG. 9. Upon arrival of cells (Day 1) 150 μL media in the wells was replaced with adipocyte differentiation media (Zenbio (RTP, NC, U.S.A.)). The following day media was replaced as described for Day 1. Media was subsequently replaced as described every two to three days. On Day 6, 150 μL of the adipocyte differentiation media was replaced with vehicle (0.1% DMSO), or the SCD1 inhibitors at the concentrations indicated. After two days (Day 8) 150 μL media was replaced with 150 μL adipocyte maintenance media containing vehicle (0.1% DMSO) or the SCD1 inhibitors at the concentrations indicated as described above. Following a further four days of incubation (Day 12) cells were stained with AdipoRed™ (Lonza Bioscience (Walkersville, MD, U.S.A.)) according to the manufacturer's instructions. Cytotoxicity following incubation of adipocytes with Compound A was determined in separate wells, not used for Adipored™ staining, and was measured using CellTiter-Glo® (Promega (Madison, WI)) according to the manufacturer's instructions. Following a 10 min room temperature incubation the luminescence measured as relative light units (RLU) was determined in a luminescent plate reader. For adipocytes treated with concentrations of 1.2-100 nM Compound A for 6 days, cell viability as determined by RLU following CellTiter-Glo® remained greater than 75% of the value obtained with vehicle-treated adipocytes. The RLU dropped to 72% of vehicle in adipocytes treated with 1 μM Compound A (data not shown). These findings indicate that the decrease in lipid accumulation in the differentiating primary human adipocytes following Compound A treatment is not associated with cytotoxicity at least up to 100 nM Compound A.

Calculation of the IC50 for inhibition of triglyceride accumulation in human adipocytes was determined by non-linear regression analysis of the RFU, using a variable slope, 4-parameter fit (GraphPad PRISM®). FIG. 10 Shows the reduction in lipid accumulation following treatment of differentiating primary human adipocytes with 100 nM Compound A and analogs Compounds B, D, E, G and H for six days. FIG. 11 shows a representative study comparing the concentration-dependent reduction in lipid accumulation with Compounds A, G and H. Compound D was tested at 5 μM only. The relative IC50 values for Compound A, G and H in this study were 9.3 nM, 24.2 nM and 56 nM respectively.

US11865113B2. Methods of treating a patient afflicted with non-alcoholic steatohepatitis (NASH) (2024-01-09). Lipidio Pharmaceuticals Inc. [US]. Inventors: Nigel R. A. Beeley [US], J. Gordon Foulkes [US], Kieran George Mooney [US], Charles Rodney Greenaway Evans [GB], Keith Arthur Johnson [US], Howard G. Welgus [US], Celia P. Jenkinson [US].
Patent 2024
Adipocytes Cells Cell Survival Cytotoxin Homo sapiens inhibitors Light Lipids Luminescence prisma Promega Psychological Inhibition Sulfoxide, Dimethyl Triglycerides
3
Cytotoxicity of Plant Stem Cell Extracts
Not available on PMC !

Example 7

The MTT Cell Proliferation assay determines cell survival following apple stem cell extract treatment. The purpose was to evaluate the potential anti-tumor activity of apple stem cell extracts as well as to evaluate the dose-dependent cell cytotoxicity.

Principle: Treated cells are exposed to 3-(4,5-dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT). MTT enters living cells and passes into the mitochondria where it is reduced by mitochondrial succinate dehydrogenase to an insoluble, colored (dark purple) formazan product. The cells are then solubilized with DMSO and the released, solubilized formazan is measured spectrophotometrically. The MTT assay measures cell viability based on the generation of reducing equivalents. Reduction of MTT only occurs in metabolically active cells, so the level of activity is a measure of the viability of the cells. The percentage cell viability is calculated against untreated cells.

Method: A549 and NCI-H520 lung cancer cell lines and L132 lung epithelial cell line were used to determine the plant stem cell treatment tumor-specific cytotoxicity. The cell lines were maintained in Minimal Essential Media supplemented with 10% FBS, penicillin (100 U/ml) and streptomycin (100 μg/ml) in a 5% CO2 at 37 Celsius. Cells were seeded at 5×103 cells/well in 96-well plates and incubated for 48 hours. Triplicates of eight concentrations of the apple stem cell extract were added to the media and cells were incubated for 24 hours. This was followed by removal of media and subsequent washing with the phosphate saline solution. Cell proliferation was measured using the MTT Cell Proliferation Kit I (Boehringer Mannheim, Indianapolis, IN) New medium containing 50 μl of MTT solution (5 mg/ml) was added to each well and cultures were incubated a further 4 hours. Following this incubation, DMSO was added and the cell viability was determined by the absorbance at 570 nm by a microplate reader.

In order to determine the effectiveness of apple stem cell extracts as an anti-tumor biological agent, an MTT assay was carried out and IC50 values were calculated. IC50 is the half maximal inhibitory function concentration of a drug or compound required to inhibit a biological process. The measured process is cell death.

Results: ASC-Treated Human Lung Adenocarcinoma Cell Line A549.

TABLE 7
Results of cytotoxicity of apple stem cell extract on lung cancer cell
line A549 as measured by MTT assay (performed in triplicate).
Values of replicates are % of cell death.
Concentration*replicatereplicatereplicateMean of% Live
(μg/ml)123replicatesSDSEMCells
25093.1890.8690.3491.461.510.878.54
10086.8885.1885.6985.920.870.5014.08
5080.5879.4981.0480.370.800.4619.63
2574.2873.8176.3974.831.380.7925.17
12.567.9868.1371.7569.282.131.2330.72
6.2561.6762.4567.1063.742.931.6936.26
3.12555.3756.7762.4558.203.752.1641.80
1.56249.0751.0857.8052.654.572.6447.35
0.78142.7745.4053.1547.115.403.1252.89

Results: ASC-Treated Human Squamous Carcinoma Cell Line NCI-H520.

TABLE 8
Results of cytotoxicity of apple stem cell extract on lung cancer
cell line NCI-H520 measured by MTT assay (performed in triplicate).
Values of replicates are % of cell death.
Concen-%
tration*replicatereplicatereplicateMean ofLive
(μg/ml)123replicatesSDSEMcell
25088.2889.2987.7388.430.790.4611.57
10078.1379.1978.1378.480.610.3521.52
5067.9869.0968.5468.540.560.3231.46
2557.8358.9958.9458.590.660.3841.41
12.547.6848.8949.3448.640.860.5051.36
6.2537.5338.7939.7538.691.110.6461.31
3.12527.3728.6930.1528.741.390.8071.26
1.56217.2218.5920.5618.791.680.9781.21
0.781 7.07 8.4810.96 8.841.971.1491.16

Results: ASC-treated Lung Epithelial Cell Line L132.

TABLE 9
Results of cytotoxicity of apple stem cell extract on
lung epithelial cell line L132 as measured by MTT assay
(performed in triplicate). Values of replicates are % of cell death.
Concen-rep-rep-rep-Mean%
tration*licatelicatelicateofLive
(μg/ml)123replicatesSDSEMcell
25039.5142.5244.0342.022.301.3357.98
10032.9334.4433.6933.690.750.4466.31
5030.6028.9430.5230.020.940.5469.98
2527.9627.8127.1327.630.440.2572.37
12.525.6225.5525.4025.520.120.0774.48
6.2523.1320.8718.6120.872.261.3179.13
3.12513.3411.0811.8312.081.150.6687.92
1.562 6.56 7.31 9.57 7.811.570.9192.19
0.781 8.06 4.30 3.54 5.302.421.4094.70

Summary Results: Cytotoxicity of Apple Stem Cell Extracts.

TABLE 10
IC50 values of the apple stem cell extracts on the on the target
cell lines as determined by MTT assay.
Target Cell
LineIC50
A54912.58
NCI-H52010.21
L132127.46

Apple stem cell extracts killed lung cancer cells lines A549 and NCI-H520 at relatively low doses: IC50s were 12.58 and 10.21 μg/ml respectively as compared to 127.46 μg/ml for the lung epithelial cell line L132. Near complete anti-tumor activity was seen at a dose of 250 μg/ml in both the lung cancer cell lines. This same dose spared more than one half of the L132 cells. See Tables 7-10. The data revealed that apple stem cell extract is cytotoxic to lung cancer cells while sparing lung epithelial cells. FIG. 6 shows a graphical representation of cytotoxicity activity of apple stem cell extracts on lung tumor cell lines A549, NCIH520 and on L132 lung epithelial cell line (marked “Normal”). The γ-axis is the mean % of cells killed by the indicated treatment compared to unexposed cells. The difference in cytotoxicity levels was statistically significant at p≤05.

Example 9

The experiment of Example 7 was repeated substituting other plant materials for ASC. Plant stem cell materials included Dandelion Root Extract (DRE), Aloe Vera Juice (AVJ), Apple Fiber Powder (AFP), Ginkgo Leaf Extract (GLE), Lingonberry Stem Cells (LSC), Orchid Stem Cells (OSC) as described in Examples 1 and 2. The concentrations of plant materials used were nominally 250, 100, 50, 25, 6.25, 3.125, 1.562, and 0.781 μg/mL. These materials were tested only for cells the human lung epithelial cell line L132 (as a proxy for normal epithelial cells) and for cells of the human lung adenocarcinoma cell line A549 (as a proxy for lung cancer cells).

A549 cells lung cancer cell line cytotoxicity results for each of the treatment materials.

DRE-Treated Lung Cancer Cell Line A549 Cells.

TABLE 11
Triplicate results of cell death of DRE-treated
A549 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates.
Concentration%
(μg/mL)-DRE-Live
treated A549% of cell deathMeanSDSEMcell
25080.4376.4074.8477.232.891.6722.77
10067.6075.2663.7768.885.853.3831.12
5065.3262.9459.9462.732.701.5637.27
2556.8357.9748.1454.315.383.1145.69
6.2555.5949.6949.1751.483.572.0648.52
3.12551.7648.4545.3448.523.211.8551.48
1.56243.6944.0036.0241.244.522.6158.76
0.78137.4726.1919.5727.749.055.2372.26

AVJ-Treated Lung Cancer Cell line A549 Cells.

TABLE 12
Triplicate results of cell death of AVJ-treated
A549 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates.
Concentration%
(μg/mL)-AVJ-treatedLive
A549% of cell deathMeanSDSEMcell
25076.8178.1675.8876.951.140.6623.05
10076.4075.2673.7175.121.350.7824.88
5065.3266.1559.9463.803.371.9536.20
2550.1048.4556.6351.734.322.5048.27
6.2547.5246.3846.1746.690.720.4253.31
3.12539.8638.6143.7940.752.701.5659.25
1.56232.4019.7730.5427.576.823.9472.43
0.78120.5015.6332.1922.778.514.9277.23

AFP-Treated Lung Cancer Cell line A549 Cells.

TABLE 13
Triplicate results of cell death of AFP-treated
A549 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates.
Concentration%
(μg/mL)-AFP-treatedLive
A549% of cell deathMeanSDSEMcell
25086.1387.9986.6586.920.960.5613.08
10079.5081.0682.0980.881.300.7519.12
5073.6072.4671.3372.461.140.6627.54
2568.0167.7066.9867.560.530.3132.44
6.2560.8762.1160.7761.250.750.4338.75
3.12549.4851.7650.7250.661.140.6649.34
1.56240.0641.7247.0042.933.622.0957.07
0.78139.2337.7836.8537.961.200.6962.04

GLE-treated Lung Cancer Cell line A549 Cells.

TABLE 14
Triplicate results of cell death of GLE-treated
A549 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates.
Concentration%
(μg/mL)-GLE-treatedLive
A549% of cell deathMeanSDSEMcell
25088.4291.4990.4490.121.560.909.88
10084.3983.7783.1683.770.610.3516.23
5079.4781.5876.7579.272.421.4020.73
2573.6072.5471.4072.511.100.6327.49
6.2562.8963.6859.9162.161.991.1537.84
3.12550.1854.4751.8452.162.171.2547.84
1.56246.9344.3043.3344.851.861.0755.15
0.78139.5639.3940.9639.970.870.5060.03

LSC-treated lung cancer cell lines A549 cells.

TABLE 15
Triplicate results of cell death of LSC-treated
A549 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates.
Concentration
(μg/mL)% Live
LSC treated A549% of cell deathMeanSDSEMcell
25077.5478.8578.2078.200.650.3821.80
10077.1476.0476.5976.590.550.3223.41
5066.4268.5266.8267.251.120.6532.75
2559.8067.2264.1663.733.732.1536.27
6.2550.5348.8248.0749.141.260.7350.86
3.12541.1443.6042.7242.491.240.7257.51
1.56239.4739.7440.6139.940.600.3460.06
0.78138.5531.8336.7935.723.482.0164.28

OSC-treated Lung Cancer Cell line A549 Cells.

TABLE 16
Triplicate results of cell death of OSC-treated
A549 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates.
Concentration
(μg/mL)% Live
OSC-treated A549% of cell deathMeanSDSEMcell
25070.8465.5771.4969.303.251.8730.70
10048.8150.9157.2852.334.412.5547.67
5046.5949.6053.3349.843.381.9550.16
2538.7740.8136.5838.722.111.2261.28
6.2535.7440.7941.0539.193.001.7360.81
3.12534.5533.6837.0235.081.731.0064.92
1.56233.8633.4427.6331.643.482.0168.36
0.78121.3220.0034.8225.388.214.7474.62

L132 cells (“normal” lung epithelial cell line) cytotoxicity results for each of the treatment materials.

DRE-Treated Lung Epithelial Cell Line L132 cells.

TABLE 17
Triplicate results of cell death of DRE-treated
L132 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates.
Concentration% of %
(μg/mL)cellLive
DRE-treated L132deathMeanSDSEMcell
25086.6686.6186.6686.640.030.0213.36
10076.2977.3976.8476.840.550.3223.16
5065.9268.1767.0167.031.130.6532.97
2555.5458.9557.1957.231.700.9842.77
6.2545.1749.7347.3747.422.281.3252.58
3.12534.8040.5037.5437.612.851.6562.39
1.56224.4231.2827.7227.813.431.9872.19
0.78114.0522.0617.8918.004.012.3182.00

AVJ-Treated Lung Epithelial Cell Line L132 cells.

TABLE 18
Triplicate results of cell death of AVJ-treated
L132 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates
AFP-treated lung epithelial cell line L132 cells.
Concentration % of %
(μg/mL)cellLive
AVJ-treated L132deathMeanSDSEMcell
25057.0355.9353.6255.531.741.0044.47
10050.9949.7847.0449.272.031.1750.73
5044.9543.6340.4543.012.311.3456.99
2538.9137.4933.8636.752.601.5063.25
6.2532.8831.3427.2830.502.891.6769.50
3.12526.8425.1920.6924.243.181.8475.76
1.56220.8019.0514.1117.983.472.0082.02
0.78114.7612.90 7.5211.733.762.1788.27

AFP-Treated Lung Epithelial Cell Line L132 cells.

TABLE 19
Triplicate results of cell death of AFP-treated
L132 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates
AFP-treated lung epithelial cell line L132 cells.
Concentration
(μg/mL)% Live
AFP-treated L132% of cell deathMeanSDSEMcell
25056.1555.4357.1956.260.880.5143.74
10049.9548.2447.6448.611.200.6951.39
5043.7441.0538.0940.962.831.6359.04
2537.5433.8628.5433.324.532.6166.68
6.2531.3426.6718.9925.676.243.6074.33
3.12525.1419.489.4418.027.954.5981.98
1.56218.9412.2910.8714.034.312.4985.97
0.78112.73 5.10 6.81 8.214.002.3191.79

GLE-Treated Lung Epithelial Cell Line L132 cells.

TABLE 20
Triplicate results of cell death of GLE-treated
L132 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates
AFP-treated lung epithelial cell line L132 cells.
Concentration
(μg/mL)% Live
GLE-treated L132% of cell deathMeanSDSEMcell
25084.4283.2083.0883.570.740.4316.43
10080.0579.2978.5979.310.730.4220.69
5072.7571.5974.1072.811.260.7227.19
2580.0581.8679.9980.631.060.6119.37
6.2568.2670.1368.2668.881.080.6231.12
3.12560.6263.0760.6261.441.410.8238.56
1.56248.0748.7748.8348.560.420.2451.44
0.78146.2745.5746.6746.170.560.3253.83

LSC-Treated Lung Epithelial Cell Line L132 cells.

TABLE 21
Triplicate results of cell death of LSC-treated
L132 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates
AFP-treated lung epithelial cell line L132 cells.
Concentration
(μg/mL)% Live
LSC-treated L132% of cell deathMeanSDSEMcell
25086.4185.8285.7686.000.350.2014.00
10081.2181.2779.9980.820.720.4219.18
5075.9674.7473.5174.741.230.7125.26
2574.7472.7571.4772.991.650.9527.01
6.2570.1368.3268.2668.901.060.6131.10
3.12554.0358.0553.4455.172.511.4544.83
1.56253.9751.9851.9852.641.150.6647.36
0.78146.7945.6244.9245.78 0.940.54 54.22

OSC-Treated Lung Epithelial Cell Line L132 cells.

TABLE 22
Triplicate results of cell death of OSC-treated
L132 cells measured by MTT assay.
Percentage of live cells calculated as 100% − Mean of triplicates
AFP-treated lung epithelial cell line L132 cells.
Concentration %
(μg/mL)Live
OSC-treated L132% of cell deathMeanSDSEMcell
25061.8462.3760.4461.551.000.5738.45
10054.1453.4452.1053.231.040.6046.77
5042.9442.3040.3241.851.370.7958.15
2535.9434.4833.3134.581.320.7665.42
6.2533.9632.6732.0332.890.980.5767.11
3.12527.4826.2026.7226.800.650.3773.20
1.562 9.80 7.29 7.35 8.151.430.8391.85
0.781 7.29 8.98 8.05 8.110.850.4991.89

Calculated values.

TABLE 23
Calculated IC50 doses (ug/mL) and therapeutic ratios
(IC50 for L132 cells/IC50 for A549 cells) for each
treatment material. Values greater than one indicate
that a material would be more selective in killing cancer
cells than normal cells. ASC results imported from
Example 8. These studies indicate that at least
some of the materials may be effective anti-cancer agents.
ASC has outstanding selectivity compared to other materials.
ASCDREAVJAFPGLELSCOSC
A549 12.589.82211.4811.9811.1 13.733.9 
IC50
L132 127.4656.88 62.6682.6577.6369.26715.38
IC50
Ther.10.15.8 5.56.97.0 0.70.5
Ratio

US11872258B2. Oral cavity treatments (2024-01-16). None [US]. Inventors: Maryam Rahimi [US].
Patent 2024
14-3-3 Proteins 43-63 61-26 A549 Cells Action Potentials Adenocarcinoma of Lung Aloe Aloe vera Antineoplastic Agents Biological Assay Biological Factors Biological Processes Bromides Cardiac Arrest Cell Death Cell Extracts Cell Lines Cell Proliferation Cells Cell Survival Cytotoxin diphenyl DNA Replication Epistropheus Epithelial Cells Fibrosis Formazans Genetic Selection Ginkgo biloba Ginkgo biloba extract Homo sapiens Lingonberry Lung Lung Cancer Lung Neoplasms Malignant Neoplasms Mitochondria Mitochondrial Inheritance Neoplasms Neoplastic Stem Cells Oral Cavity PEG SD-01 Penicillins Pharmaceutical Preparations Phosphates Plant Cells Plant Leaves Plant Roots Plants Powder Psychological Inhibition Saline Solution SD 31 SD 62 SEM-76 Squamous Cell Carcinoma Stem, Plant Stem Cells Streptomycin Succinate Dehydrogenase Sulfoxide, Dimethyl Taraxacum Tetrazolium Salts
4
Quantitative s4U RNA labeling and sequencing
Not available on PMC !

Example 3

We tested the ability of mouse embryonic stem cells to tolerate s4U metabolic RNA-labeling after 12 h or 24 h at varying s4U concentrations (FIG. 6A). As reported previously, high concentrations of s4U compromised cell viability with an EC50 of 3.1 mM or 380 μM after 12 h or 24 h labeling, respectively (FIG. 6A). Hence, we employed labeling conditions of 100 μM s4U, which did not severely affect cell viability. Under these conditions, we detected a steady increase in s4U-incorporation in total RNA preparation 3 h, 6 h, 12 h, and 24 h post labeling, as well as a steady decrease 3 h, 6 h, 12 h, and 24 h after uridine chase (FIG. 6B). As expected, the incorporation follows a single exponential kinetics, with a maximum average incorporation of 1.78% s4U, corresponding to one s4U incorporation in every 56 uridines in total RNA (FIG. 6C). These experiments establish s4U-labeling conditions in mES cells, which can be employed to measure RNA biogenesis and turnover rates under unperturbed conditions.

To test the ability of the method to uncover s4U incorporation events in high throughput sequencing datasets we generated mRNA 3′ end libraries (employing Lexogen's QuantSeq, 3′ mRNA-sequencing library preparation kit) using total RNA prepared from cultured cells following s4U-metabolic RNA labeling for 24 h (FIG. 7) (Moll et al., supra). Quant-seq 3′ mRNA-Seq Library Prep Kit generates Illumina-compatible libraries of the sequences close to the 3′end of the polyadenylated RNA, as exemplified for the gene Trim28 (FIG. 8A). In contrast to other mRNA-sequencing protocols, only one fragment per transcript is generated and therefore no normalization of reads to gene length is needed. This results in accurate gene expression values with high strand-specificity.

Furthermore, sequencing-ready libraries can be generated within only 4.5 h, with ˜2 h hands-on time. When combined with the invention, Quant-seq facilitates the accurate determination of mutation rates across transcript-specific regions because libraries exhibit a low degree of sequence-heterogeneity. Indeed, upon generating libraries of U-modified RNA through the Quant-seq protocol from total RNA of mES cells 24 h after s4U metabolic labeling we observed a strong accumulation of T>C conversions when compared to libraries prepared from total RNA of unlabeled mES cells (FIG. 8B). In order to confirm this observation transcriptome-wide, we aligned reads to annotated 3′ UTRs and inspected the occurrence of any given mutation per UTR (FIG. 9). In the absence of s4U metabolic labeling, we observed a median mutation rate of 0.1% or less for any given mutation, a rate that is consistent with Illumina-reported sequencing error rates. After 24 h of s4U metabolic labeling, we observed a statistically significant (p<10−4, Mann-Whitney test), 25-fold increase in T>C mutation rates, while all other mutations rates remained below expected sequencing error rates (FIG. 9). More specifically, we measured a median s4U-incorporation of 2.56% after 24 h labeling, corresponding to one s4U incorporation in every 39 uridines. (Note, that median incorporation frequency for mRNA are higher than estimated by HPLC in total RNA [FIG. 6C], most certainly because stable non-coding RNA species, such as rRNA, are strongly overrepresented in total RNA.) These analyses confirm that the new method uncovers s4U-incorporation events in mRNA following s4U-metabolic RNA labeling in cultured cells.

We expect the same incorporation results of other modified nucleotides, such as s6G or 5-ethynyluridine, as reported previously (Eidinoff et al., Science. 129, 1550-1551 (1959); Jao et al. PNAS 105, 15779-15784 (2008); Melvin et al. Eur. J. Biochem. 92, 373-379 (1978); Woodford et al. Anal. Biochem. 171, 166-172 (1988)).

US11859248B2. Nucleic acid modification and identification method (2024-01-02). IMBA—INSTITUT FÜR MOLEKULARE BIOTECHNOLOGIE GMBH [AT]. Inventors: Stefan L. Ameres [AT], Brian Reichholf [AT], Veronika A. Herzog [AT], Johannes Zuber [AT], Matthias Muhar [AT].
Patent 2024
Anabolism Anus Cells Cell Survival Cultured Cells DNA Library Gene Expression Genes Genetic Heterogeneity High-Performance Liquid Chromatographies Kinetics Mouse Embryonic Stem Cells Mutation Nucleotides Peptide Nucleic Acids Preparation H Ribosomal RNA RNA, Messenger RNA, Polyadenylated RNA, Untranslated Transcriptome TRIM28 protein, human Uridine Whole Transcriptome Sequencing
5
Tucaresol Combination Therapy Evaluation
Not available on PMC !

Example 1

1) Tucaresol

Tucaresol (0-1200 μM) is exposed for 72 hours to a panel of human liquid, hematological, and solid tumors such as multiple myeloma, leukemia, colorectal, non-small cell lung cancer (squamous and adenocarcinoma), hepatocellular, renal, pancreatic and breast cancer cell lines, and human non-tumor such as HUVEC, PBMC, skin fibroblast cells lines. Tucaresol is studied either alone or in combination with standard-of-care agents (1-100 μM). All cell lines are grown in standard serum-containing media with an exposure time of 24-144 hours. Cell viability is measured using, for example, the Cell TiterGlo® Viability Assay. The potency (IC50) and efficacy (% cell kill) are determined from the percent cell growth of the vehicle control.

2) Tucaresol Plus PD-1 Antibody

Tucaresol (0-1200 μM) in the presence of a PD-1 antibody is exposed for 72 hours to a panel of human liquid, hematological, and solid tumor such as multiple myeloma, leukemia, colorectal, non-small cell lung cancer (squamous and adenocarcinoma), hepatocellular, renal, pancreatic and breast cancer cell lines, and human non-tumor such as HUVEC, PBMC, skin fibroblast cells lines, and the viability of the cell lines are measured as described above. The viability of the cell lines in the presence of tucaresol plus PD-1 antibody is compared to the viability of the cell lines in the presence of a CTLA-4 antibody plus the PD-1 antibody or PD-1 antibody alone.

3) CTLA-4 Antibody Plus PD-1 Antibody

CTLA-4 antibody in the presence of a PD-1 antibody is exposed for 72 hours to a panel of human liquid, hematological, and solid tumor such as multiple myeloma, leukemia, colorectal, non-small cell lung cancer (squamous and adenocarcinoma), hepatocellular, renal, pancreatic and breast cancer cell lines, and human non-tumor such as HUVEC, PBMC, skin fibroblast cells lines, and the viability of the cell lines are measured as described above.

4) Tucaresol Plus Plinabulin

Tucaresol (0-1200 μM) in the presence of Plinabulin is exposed for 72 hours to a panel of human liquid, hematological, and solid tumor such as multiple myeloma, leukemia, colorectal, non-small cell lung cancer (squamous and adenocarcinoma), hepatocellular, renal, pancreatic and breast cancer cell lines, and human non-tumor such as HUVEC, PBMC, skin fibroblast cells lines, and the viability of the cell lines are measured as described above.

The viability of the cell lines in the presence of tucaresol, tucaresol plus PD-1 antibody, CTLA-4 antibody plus the PD-1 antibody, and tucaresol plus plinabulin are compared.

US11857522B2. Compositions containing tucaresol or its analogs (2024-01-02). BeyondSpring Pharmaceuticals, Inc. [US]. Inventors: Ramon Mohanlal [US], Lan Huang [US], George Kenneth Lloyd [US].
Patent 2024
Adenocarcinoma Biological Assay Cell Lines Cells Cell Survival Cytotoxic T-Lymphocyte Antigen 4 Fibroblasts Homo sapiens Immunoglobulins Kidney Leukemia MCF-7 Cells Multiple Myeloma Neoplasms Non-Small Cell Lung Carcinoma Pancreas plinabulin Serum Skin tucaresol

Top products related to «Cell Survival»

1
Methyl thiazolyl tetrazolium (mtt) by Merck Group
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MTT is a colorimetric assay used to measure cell metabolic activity. It is a lab equipment product developed by Merck Group. MTT is a tetrazolium dye that is reduced by metabolically active cells, producing a colored formazan product that can be quantified spectrophotometrically.
2
Celltiter glo luminescent cell viability assay by Promega
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The CellTiter-Glo Luminescent Cell Viability Assay is a quantitative method for determining the number of viable cells in a cell-based assay. The assay measures the amount of ATP present, which is an indicator of metabolically active cells.
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Cell counting kit 8 (cck8) by Dojindo Laboratories
Sourced in Japan, United States, China, Germany, United Kingdom
The Cell Counting Kit-8 is a colorimetric assay for the determination of cell viability and cytotoxicity. It utilizes a water-soluble tetrazolium salt that produces a water-soluble formazan dye upon reduction in the presence of an electron carrier. The amount of the formazan dye generated is directly proportional to the number of living cells.
4
Microplate reader by Bio-Rad
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The Microplate reader is a laboratory instrument used to measure the absorbance or fluorescence of samples in a microplate format. It can be used to conduct various assays, such as enzyme-linked immunosorbent assays (ELISA), cell-based assays, and other biochemical analyses. The core function of the Microplate reader is to precisely quantify the optical properties of the samples in a multi-well microplate.
5
Microplate reader by Agilent Technologies
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The Microplate reader is a versatile laboratory instrument used to measure and analyze the optical properties of samples in microplates. It is designed to quantify absorbance, fluorescence, or luminescence signals from various assays and applications.
6
Dimethyl sulfoxide (dmso) by Merck Group
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DMSO is a versatile organic solvent commonly used in laboratory settings. It has a high boiling point, low viscosity, and the ability to dissolve a wide range of polar and non-polar compounds. DMSO's core function is as a solvent, allowing for the effective dissolution and handling of various chemical substances during research and experimentation.
7
Fetal bovine serum (fbs) by Thermo Fisher Scientific
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
8
Celltiter glo by Promega
Sourced in United States, United Kingdom, Germany, France, Switzerland, Italy, Japan, Belgium, Australia, China
CellTiter-Glo is a cell viability assay that quantifies the amount of ATP present in metabolically active cells. It provides a luminescent readout proportional to the amount of ATP, which is an indicator of the presence of viable cells.
9
Microplate reader by Thermo Fisher Scientific
Sourced in United States, China, Finland, Germany, Japan, United Kingdom, Spain, France, Italy, Australia, Sweden, Singapore, Canada, India, Denmark
The Microplate reader is a laboratory instrument designed to measure the absorbance, fluorescence, or luminescence of samples in a microplate format. It is a versatile tool used in various applications, such as enzyme-linked immunosorbent assays (ELISAs), cell-based assays, and drug discovery screens.
10
Cck 8 by Dojindo Laboratories
Sourced in Japan, United States, China, Germany
CCK-8 is a cell counting kit used to measure cell viability and proliferation. It utilizes a water-soluble tetrazolium salt that is reduced by living cells, producing a colored formazan dye that can be quantified using a spectrophotometer. The amount of formazan dye produced is directly proportional to the number of living cells in the sample.

More about "Cell Survival"

Cell survival is a critical process that allows cells to maintain viability and function under various environmental conditions.
This complex mechanism involves the ability of cells to adapt, repair damage, and resist apoptosis (programmed cell death) or necrosis (uncontrolled cell death).
Understanding cell survival is crucial for advancing research in areas such as tissue regeneration, cancer biology, and neurodegenerative diseases.
One of the key methods used to assess cell survival is the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay.
This colorimetric assay measures the metabolic activity of cells, which is an indicator of their viability.
Another popular method is the CellTiter-Glo Luminescent Cell Viability Assay, which measures the amount of ATP (adenosine triphosphate) present in viable cells, providing a quantitative assessment of cell survival.
The Cell Counting Kit-8 (CCK-8) is another useful tool for measuring cell viability.
This assay relies on a water-soluble tetrazolium salt that is reduced by cellular dehydrogenases, resulting in a colorimetric change that can be detected using a microplate reader.
Researchers often utilize DMSO (dimethyl sulfoxide) and FBS (fetal bovine serum) in cell culture experiments to maintain cell health and promote cell survival.
DMSO is a commonly used cryoprotectant, while FBS provides essential nutrients and growth factors for cells.
PubCompare.ai is an innovative AI-driven tool that can help optimize cell survival experiments by identifying the best protocols from literature, preprints, and patents.
This platform uses advanced comparison techniques to improve reproducibility and drive research forward in the field of cell survival.