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> Physiology > Cell Function > Apoptosis

Apoptosis

Apoptosis is a programmed cell death process that plays a crucial role in various biological processes, including development, homeostasis, and disease.
This highly regulated form of cell suicide involves a series of biochemical events leading to characteristic cell changes and death.
Apoptosis is essential for maintaining tissue homeostasis, eliminating damaged or unwanted cells, and regulating immune responses.
Dysregulation of apoptosis has been implicated in a wide range of pathological conditions, such as cancer, neurodegenerative disorders, and autoimmune diseases.
Understanding the mechanisms and signaling pathways underlying apoptosis is a key focus of biomedial research, as it may lead to the development of new therapeutic interventions targeting this fundamental cellular process.
Explore how PubCompare.ai can enhance your apoptosis research by providing access to the best protocols from literature, preprints, and patents, ensuring superior reproducibility and accuracy in your studeis.

Most cited protocols related to «Apoptosis»

1
Causal analysis of biological networks
Causal analysis algorithms are based on a ‘master’ network which is derived from the Ingenuity Knowledge Base, and given by a directed multigraph with nodes representing mammalian genes, chemicals, protein families, complexes, microRNA species and biological processes, and edges reflecting observed cause–effect relationships. For the following let be the set of all genes, and the set of all biological processes. For each edge we define functions and that map to its unique source and target nodes, respectively. The graph has no self-edges, i.e. Each edge in is associated with a set of underlying findings obtained from the literature, where each finding is associated with a ‘sign’ that represents the regulation direction of the causal effect. If effect is activating (inhibiting), and for the direction of the effect is unknown or ambiguous. Depending on the underlying findings, edges are classified into the distinct types, ‘T’, ‘A’ and ‘P’, represented by three disjoint subsets of E: Et, Ea and Ep. T-edges are related to transcription and expression events including protein–DNA binding (i.e. regulation of the abundance of the target node), while A-edges represent the functional activation or inhibition of the target node (e.g. through phosphorylation in a signaling cascade). P-edges are associated with the regulation of biological processes (e.g. apoptosis). The master network G is a multigraph since two given source and target nodes can be connected by a T-edge, and an A-edge at the same time.
The various finding categories and their respective association with edge types and signs are given in a table in the Supplementary Material. Findings about changes of molecular modification states (e.g. phosphorylation) are included in the A-edge type if an activating or inhibiting effect can be inferred. All T-edges are connected to genes as their target nodes, and all P-edges connect to biological processes, Depending on the signs of the underlying findings, each edge is in turn associated with a unique direction of the causal effect that is either activating, inhibiting or unknown, and represented by the sign In addition, we also associate edges with weights reflecting our confidence in the assigned direction of the effect. Details are given in the Supplementary Material.
Krämer A., Green J., Pollard J J.r, & Tugendreich S. (2013). Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics, 30(4), 523-530.
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Publication 2013
Apoptosis Biological Processes Genes Mammals MicroRNAs Phosphorylation Proteins Psychological Inhibition Transcription, Genetic
2
Genome-wide Analysis of Somatic Copy Number Alterations in Cancer
DNA extracted from cancer specimens and normal tissue was labeled and hybridized to the Affymetrix 250K Sty I array to obtain signal intensities and genotype calls. Signal intensities were normalized against data from 1480 normal samples. Copy-number profiles were inferred using GLAD48 (link) and changes of > 0.1 copies in either direction were called SCNAs. The significance of focal SCNAs (covering < 0.5 chromosome arms) was determined using GISTIC18 (link), with modifications to score SCNAs directly proportional to amplitude and to allow summation of non-overlapping deletions affecting the same gene. Peak region boundaries were determined so that the change in the GISTIC score from peak to boundary had < 5% likelihood of occurring by random fluctuation. P-values for Figures 2b and 4 were determined by comparing the gene densities of SCNAs and fraction overlap of peak regions respectively to the same quantities calculated from random permutations of the locations of these SCNAs and peak regions. RNAi was performed by inducible and stable expression of shRNA lentiviral vectors and by siRNA transfection. Proliferation in inducible shRNA experiments was measured in triplicate every half-hour on 96-well plates by a real time electric sensing system (ACEA Bioscience) and in stable shRNA expression and siRNA transfection experiments by CellTiterGlo (Promega). Apoptosis was measured by immunoblot against cleaved PARP and FACS analysis of cells stained with antibody to annexin V and propidium iodide. Tumor growth in nude mice was measured by caliper twice weekly. Expression of MYC, MCL1, and BCL2L1 was performed with retroviral vectors in lung epithelial cells immortalized by introduction of SV40 and hTERT49 (link).
Full methods are described in Supplementary Methods.
Beroukhim R., Mermel C.H., Porter D., Wei G., Raychaudhuri S., Donovan J., Barretina J., Boehm J.S., Dobson J., Urashima M., Mc Henry K.T., Pinchback R.M., Ligon A.H., Cho Y.J., Haery L., Greulich H., Reich M., Winckler W., Lawrence M.S., Weir B.A., Tanaka K.E., Chiang D.Y., Bass A.J., Loo A., Hoffman C., Prensner J., Liefeld T., Gao Q., Yecies D., Signoretti S., Maher E., Kaye F.J., Sasaki H., Tepper J.E., Fletcher J.A., Tabernero J., Baselga J., Tsao M.S., DeMichelis F., Rubin M.A., Janne P.A., Daly M.J., Nucera C., Levine R.L., Ebert B.L., Gabriel S., Rustgi A.K., Antonescu C.R., Ladanyi M., Letai A., Garraway L.A., Loda M., Beer D.G., True L.D., Okamoto A., Pomeroy S.L., Singer S., Golub T.R., Lander E.S., Getz G., Sellers W.R, & Meyerson M. (2010). The landscape of somatic copy-number alteration across human cancers. Nature, 463(7283), 899-905.
Publication 2010
Annexin A5 Apoptosis Arm, Upper bcl-X Protein Cells Chromosomes Cloning Vectors Electricity Epithelial Cells Gene Deletion Genes Genotype Immunoblotting Immunoglobulins Lung Malignant Neoplasms MCL1 protein, human Mice, Nude Neoplasms Promega Propidium Iodide Retroviridae RNA, Small Interfering RNA Interference Short Hairpin RNA Simian virus 40 Tissues Transfection
3
Genome-wide Analysis of Somatic Copy Number Alterations in Cancer
DNA extracted from cancer specimens and normal tissue was labeled and hybridized to the Affymetrix 250K Sty I array to obtain signal intensities and genotype calls. Signal intensities were normalized against data from 1480 normal samples. Copy-number profiles were inferred using GLAD48 (link) and changes of > 0.1 copies in either direction were called SCNAs. The significance of focal SCNAs (covering < 0.5 chromosome arms) was determined using GISTIC18 (link), with modifications to score SCNAs directly proportional to amplitude and to allow summation of non-overlapping deletions affecting the same gene. Peak region boundaries were determined so that the change in the GISTIC score from peak to boundary had < 5% likelihood of occurring by random fluctuation. P-values for Figures 2b and 4 were determined by comparing the gene densities of SCNAs and fraction overlap of peak regions respectively to the same quantities calculated from random permutations of the locations of these SCNAs and peak regions. RNAi was performed by inducible and stable expression of shRNA lentiviral vectors and by siRNA transfection. Proliferation in inducible shRNA experiments was measured in triplicate every half-hour on 96-well plates by a real time electric sensing system (ACEA Bioscience) and in stable shRNA expression and siRNA transfection experiments by CellTiterGlo (Promega). Apoptosis was measured by immunoblot against cleaved PARP and FACS analysis of cells stained with antibody to annexin V and propidium iodide. Tumor growth in nude mice was measured by caliper twice weekly. Expression of MYC, MCL1, and BCL2L1 was performed with retroviral vectors in lung epithelial cells immortalized by introduction of SV40 and hTERT49 (link).
Full methods are described in Supplementary Methods.
Beroukhim R., Mermel C.H., Porter D., Wei G., Raychaudhuri S., Donovan J., Barretina J., Boehm J.S., Dobson J., Urashima M., Mc Henry K.T., Pinchback R.M., Ligon A.H., Cho Y.J., Haery L., Greulich H., Reich M., Winckler W., Lawrence M.S., Weir B.A., Tanaka K.E., Chiang D.Y., Bass A.J., Loo A., Hoffman C., Prensner J., Liefeld T., Gao Q., Yecies D., Signoretti S., Maher E., Kaye F.J., Sasaki H., Tepper J.E., Fletcher J.A., Tabernero J., Baselga J., Tsao M.S., DeMichelis F., Rubin M.A., Janne P.A., Daly M.J., Nucera C., Levine R.L., Ebert B.L., Gabriel S., Rustgi A.K., Antonescu C.R., Ladanyi M., Letai A., Garraway L.A., Loda M., Beer D.G., True L.D., Okamoto A., Pomeroy S.L., Singer S., Golub T.R., Lander E.S., Getz G., Sellers W.R, & Meyerson M. (2010). The landscape of somatic copy-number alteration across human cancers. Nature, 463(7283), 899-905.
Publication 2010
Annexin A5 Apoptosis Arm, Upper bcl-X Protein Cells Chromosomes Cloning Vectors Electricity Epithelial Cells Gene Deletion Genes Genotype Immunoblotting Immunoglobulins Lung Malignant Neoplasms MCL1 protein, human Mice, Nude Neoplasms Promega Propidium Iodide Retroviridae RNA, Small Interfering RNA Interference Short Hairpin RNA Simian virus 40 Tissues Transfection
4
Comprehensive Neuronal Tracing and Characterization
For in situ hybridization analysis, cryostat sections were hybridized using digoxigenin-labeled probes [45 (link)] directed against mouse TrkA or TrkB, or rat TrkC (gift from L. F. Parada). Antibodies used in this study were as follows: rabbit anti-Er81 [14 (link)], rabbit anti-Pea3 [14 (link)], rabbit anti-PV [14 (link)], rabbit anti-eGFP (Molecular Probes, Eugene, Oregon, United States), rabbit anti-Calbindin, rabbit anti-Calretinin (Swant, Bellinzona, Switzerland), rabbit anti-CGRP (Chemicon, Temecula, California, United States), rabbit anti-vGlut1 (Synaptic Systems, Goettingen, Germany), rabbit anti-Brn3a (gift from E. Turner), rabbit anti-TrkA and -p75 (gift from L. F. Reichardt), rabbit anti-Runx3 (Kramer and Arber, unpublished reagent), rabbit anti-Rhodamine (Molecular Probes), mouse anti-neurofilament (American Type Culture Collection, Manassas, Virginia, United States), sheep anti-eGFP (Biogenesis, Poole, United Kingdom), goat anti-LacZ [14 (link)], goat anti-TrkC (gift from L. F. Reichardt), and guinea pig anti-Isl1 [14 (link)]. Terminal deoxynucleotidyl transferase-mediated biotinylated UTP nick end labeling (TUNEL) to detect apoptotic cells in E13.5 DRG on cryostat sections was performed as described by the manufacturer (Roche, Basel, Switzerland). Quantitative analysis of TUNEL+ DRG cells was performed essentially as described [27 (link)]. BrdU pulse-chase experiments and LacZ wholemount stainings were performed as previously described [46 (link)]. For anterograde tracing experiments to visualize projections of sensory neurons, rhodamine-conjugated dextran (Molecular Probes) was injected into single lumbar (L3) DRG at E13.5 or applied to whole lumbar dorsal roots (L3) at postnatal day (P) 5 using glass capillaries. After injection, animals were incubated for 2–3 h (E13.5) or overnight (P5). Cryostat sections were processed for immunohistochemistry as described [14 (link)] using fluorophore-conjugated secondary antibodies (1:1,000, Molecular Probes). Images were collected on an Olympus (Tokyo, Japan) confocal microscope. Images from in situ hybridization experiments were collected with an RT-SPOT camera (Diagnostic Instruments, Sterling Heights, Michigan, United States), and Corel (Eden Prairie, Minnesota, United States) Photo Paint 10.0 was used for digital processing of images.
Hippenmeyer S., Vrieseling E., Sigrist M., Portmann T., Laengle C., Ladle D.R, & Arber S. (2005). A Developmental Switch in the Response of DRG Neurons to ETS Transcription Factor Signaling. PLoS Biology, 3(5), e159.
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Publication 2005
Anabolism Animals Antibodies Apoptosis Bromodeoxyuridine Calbindins Calretinin Capillaries Cavia Cells Diagnosis Digoxigenin DNA Nucleotidylexotransferase Domestic Sheep Goat Immunohistochemistry In Situ Hybridization In Situ Nick-End Labeling LacZ Genes Lumbar Region Mice, House Microscopy, Confocal Molecular Probes Neurofilaments Neuron, Afferent Pulse Rate Rabbits Rhodamine rhodamine dextran Root, Dorsal Staining transcription factor PEA3 tropomyosin-related kinase-B, human
5
Characterizing Cancer Cell Functional States via scRNA-seq
After reviewing almost all cancer single-cell sequencing studies, we concluded 14 crucial functional states of cancer cells, including stemness, invasion, metastasis, proliferation, EMT, angiogenesis, apoptosis, cell cycle, differentiation, DNA damage, DNA repair, hypoxia, inflammation and quiescence. To characterize these functional states for cancer single cells, we built the corresponding gene signatures through searching literatures and known databases (including some general databases, such as Gene Ontology (17 (link)) and MSigDB (18 (link)), and some specialized databases, such as Cyclebase (19 (link)), HCMDB (20 (link)) and StemMapper (21 (link))) (Supplementary Table S2). For most of the signatures, the collected genes that were mentioned in more than two resources were kept. While for the invasion signature, genes mentioned in more than two invasion-associated terms collected from MSigDB were retained. Then, through functional annotations and literature searching, genes that negatively affect the corresponding functional states were removed.
Based on these signatures, the activities of 14 functional states across cancer single cells in each dataset were evaluated using Gene Set Variation Analysis (GSVA) with the GSVA package in R (22 (link)). In brief, for each gene, we first performed a non-parametric kernel estimation of its cumulative density function and then calculated an expression-level statistic to normalize expression profiles to a common scale. The expression-level statistic can reflect whether a gene is highly or lowly expressed in a specific cell in the context of the cell population distribution. Then, in each cell, the expression-level statistics of all genes were converted to normalized ranks. Next, we used the Kolmogorov–Smirnov like random walk statistic, similar to the GSEA method, to summarize the expression-level rank statistics of a given signature gene set into a final enrichment score (i.e. GSVA score), which is used to characterize the signature activity. At last, the enrichment scores of 14 signatures across cells in all scRNA-seq data were calculated. Then, for each single-cell dataset derived from tumor tissue, PDX and CTC, we identified significant correlations between gene expressions and functional state activities using Spearman's rank correlation test with Benjamini & Hochberg false discovery rate (FDR) correction for multiple comparisons (correlation > 0.3 and FDR < 0.05). Due to the low amount of mRNA within individual cells and sequencing technical noise, there is an excessive number of zeros in scRNA-seq data. During the calculation of gene-state associations, only cells with detectable expression of the genes of interest were used by setting the parameter ‘na.action’ to na.omit, and at least 30 cancer single cells were required.
Yuan H., Yan M., Zhang G., Liu W., Deng C., Liao G., Xu L., Luo T., Yan H., Long Z., Shi A., Zhao T., Xiao Y, & Li X. (2018). CancerSEA: a cancer single-cell state atlas. Nucleic Acids Research, 47(Database issue), D900-D908.
Publication 2018
angiogen Apoptosis Cell Cycle Cells DNA Damage DNA Repair Gene Expression Genes Genetic Diversity Hypoxia Inflammation Malignant Neoplasms Neoplasm Metastasis Neoplasms RNA, Messenger Single-Cell RNA-Seq Tissues

Most recents protocols related to «Apoptosis»

1
Bioceramic Composition Enhances Cell Adhesion
Not available on PMC !

Example 8

Cell adhesion was also evaluated by means of in vitro scratch wound-healing assay. HDPSCs cells were analyzed by difference in staining with phalloidin (cell nucleus) and DAPI to visualize actin cytoskeleton.

Cell adhesion results showed excellent interaction and adhesion between neighboring cells in the presence of bioceramic composition. The Bioceramic composition sealer (CB5) and Bioceramic composition repair (CB6), showed a gradual increase in growth over time, an extended morphology and a high content of F-Actin (cell microfilamen), reaching confluence after 72 hours of culture.

The analysis of cell proliferation (via cell viability study), apoptosis, cell adhesion and morphology (via cell adhesion study) and migration (via cell migration study) showed very positive results, indicating that the proposed bioceramic composition induces the odonto/osteogenic mineralization and differentiation process in the presence of tooth-specific human stem cells (hDPSCs pulp). While a market resin sealer was also used in the comparative studies, however, all results were not satisfactory for this product.

US11857558B2. Dental and medical compositions having a multiple source of metallic ions (2024-01-02). ANGELUS INDÚSTRIA DE PRODUTOS ODONTOLÓGICOS S/A [BR]. Inventors: César Eduardo Bellinati [BR], Cristiane Vila [BR], William Pereira Dos Santos [BR], Maíra Bendlin Calzavara [BR].
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Patent 2024
Apoptosis Biological Assay Cell Adhesion Cell Nucleus Cell Proliferation Cell Survival DAPI Dental Pulp Differentiations, Cell F-Actin Homo sapiens Microfilaments Migration, Cell Osteogenesis Phalloidine Physiologic Calcification Resins, Plant Stem, Plant Stem Cells Tooth
2
ARTS Mimetic Small Molecule A4 Effect on Premalignant Cells
Not available on PMC !

Example 6

The Effect of ARTS Mimetic Small Molecule A4 on Premalignant Cells

Acini-like organoids forms hollow lumen after 10 to 12 days in 3D culture system and remain hollow thereafter (Muthuswamy et al., 2001). Plasmids introduced by transient cell transfection are only expressed for a limited period of time, as they are not integrated into the genome and therefore may be lost by environmental factors and cell division. Therefore, the inventors next examined whether introduction of small-molecules may mimic ARTS function, specifically in inducing lumen formation and reversion of pre-malignant cells to a normal-like phenotype. The inventors thus tested initially the effect of the ARTS mimetic small molecule A4 on induction of apoptosis in 2D culture.

As shown in FIG. 10A-10B, treatment of M2 cells with the A4 molecule for 24 and 48 hours resulted in a decrease in cell proliferation. However, only low amount of apoptotic cells was apparent. Therefore, A4 molecule in these mammary epithelial cells induces decrease in cell proliferation.

US11866409B2. Apoptosis related protein in the tgf-beta signaling pathway (ARTS) mimetic compounds, compositions, methods and uses thereof in induction of differentiation and/or apoptosis of premalignant and malignant cells, thereby restoring their normal-like phenotype (2024-01-09). CARMEL-HAIFA UNIVERSITY ECONOMIC CORPORATION LTD. [IL]. Inventors: Sarit Larisch [IL], Dalit Barkan [IL].
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Patent 2024
Apoptosis Breast Cell Proliferation Cells Division, Cell Epithelial Cells Genome Inventors Organoids Phenotype Plasmids Precancerous Conditions Proteins Signal Transduction Pathways Transfection Transforming Growth Factor beta Transients
3
Targeting ADAR1 in High Interferon Tumors
Not available on PMC !

Example 17

Since interferon signaling is spontaneously activated in a subset of cancer cells and exposes potential therapeutic vulnerabilities, it was tested whether there is evidence for similar endogenous interferon activation in primary human tumors. An IFN-GES threshold was computed to predict ADAR dependency across the CCLE cell lines and was determined to be a z-score above 2.26 (FIG. 66, panel A). This threshold was applied to The Cancer Genome Atlas (TCGA) tumors, to identify primary cancers with similarly high interferon activation. Restricting the analysis to the 4,072 samples analyzed by TCGA with at least 70% tumor purity as estimated by the ABSOLUTE algorithm (Carter et al. (2012) Nat. Biotechnol. 30:413-421), 2.7% of TCGA tumors displayed IFN-GESs above this threshold (FIG. 66, panel B and. GSEA of amplified genes in these high purity, high interferon tumors revealed the top pathway as “Type I Interferon Receptor Binding”, comprising 17 genes that all encode type I interferons and are clustered on chromosome 9p21.3 (FIG. 67).

Furthermore, analysis of TCGA copy number data showed that the interferon gene cluster including IFN-β (IFNβI), IFN-ε (IFNE), IFN-ω (IFNWI), and all 13 subtypes of IFN-α on chromosome 9p21.3, proximal to the CDKN2A/CDKN2B tumor suppressor locus, is one of the most frequently homozygously deleted regions in the cancer genome. The interferon genes comprise 16 of the 26 most frequently deleted coding genes across 9,853 TCGA cancer specimens for which ABSOLUTE copy number data are available (FIG. 66, panels C and D). Interferon signaling and activation, both in tumors with high IFN-GESs or deletions in chromosome 9p, therefore represent a biomarker to stratify patients who benefit from interferon modulating therapies.

In summary, specific cancer cell lines have been identified with elevated IFN-β signaling triggered by an activated cytosolic DNA sensing pathway, conferring dependence on the RNA editing enzyme, ADAR1. In cells with low, basal interferon signaling, the cGAS-STING pathway is inactive and PKR levels are reduced (FIG. 68, panel A). Upon cGAS-STING activation, interferon signaling and PKR protein levels are elevated but ADAR1 is still able to suppress PKR activation (FIG. 68, panel B). However, once ADAR1 is deleted, the abundant PKR becomes activated and leads to downstream signaling and cell death (FIG. 68, panel C). This is also shown in normal cells lines (e.g. A549 and NCI-H1437) once exogenous interferon is introduced (FIG. 68, panel D). ADAR1 deficiency in cell lines with high interferon levels, whether from endogenous or exogenous sources, led to phosphorylation and activation of PKR, ATF4-mediated gene expression, and apoptosis. Recent studies have shown that cGAS activation and innate interferon signaling, induced by cytosolic DNA released from the nucleus by DNA damage and genome instability (Mackenzie et al. (2017) Nature 548:461-465; Harding et al. (2017) Nature 548:466-470), led to elevated interferon-related gene expression signatures, which have been linked to resistance to DNA damage, chemotherapy, and radiation in cancer cells (Weichselbaum et al. (2008) Proc. Natl. Acad. Sci. USA 105:18490-18495). In high-interferon tumors, blocking ADAR1 might be effective to induce PKR-mediated apoptotic pathways while upregulating type I interferon signaling, which could contribute to anti-tumor immune responses (Parker et al. (2016) Nature 16:131-144). Alternatively, in tumors without activated interferon signaling, ADAR1 inhibition can be combined with localized interferon inducers, such as STING agonists, chemotherapy, or radiation. Generation of specific small molecule inhibitors targeting ADAR1 exploits this novel vulnerability in lung and other cancers and serves to enhance innate immunity in combination with immune checkpoint inhibitors.

US11873486B2. Modulating dsRNA editing, sensing, and metabolism to increase tumor immunity and improve the efficacy of cancer immunotherapy and/or modulators of intratumoral interferon (2024-01-16). Dana-Farber Cancer Institute, Inc. [US]. Inventors: Matthew Meyerson [US], William N. Haining [US], Jeffrey Ishizuka [US], Robert Manguso [US], Hugh Gannon [US].
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Patent 2024
agonists Apoptosis ATF4 protein, human Biological Markers CDKN2A Gene Cell Death Cell Lines Cell Nucleus Cells Chromogranin A Chromosome Deletion Chromosomes, Human, Pair 3 Cytosol DNA Damage Electromagnetic Radiation Enzymes Gene, Cancer Gene Clusters Gene Expression Genes Genome Genomic Instability Homo sapiens IFNAR2 protein, human Immune Checkpoint Inhibitors Immunity, Innate inhibitors Interferon-alpha Interferon Inducers interferon omega 1 Interferons Interferon Type I Lung Malignant Neoplasms Neoplasms Oncogenes Patients Pharmacotherapy Phosphorylation Proteins Psychological Inhibition Response, Immune Tumor Suppressor Genes
4
Synergistic Cytotoxicity of OTS-412 and GCV
Not available on PMC !

Example 6

In order to confirm the anticancer effect of the combined administration of OTS-412 and GCV, the cytotoxicity according to the administration of OTS-412 and GCV was evaluated in two human lung cancer cell lines, A549 and NCI-H460 cancer cell lines, and two human colorectal cancer cell lines, HT-29 and HCT-116 cancer cell lines.

Specifically, A549, NCI-H460, HT-29 and HCT-116 cancer cell lines were infected with OTS-412 at 0.01, 0.1 or 1 MOI. Three infected cancer cell lines (A549, NCI-H460, and HT-29) were treated with 100 M GCV, and the infected HCT-116 cancer cell line, with 50 M GCV. The cells were cultured for 72 hours and analyzed for cytotoxicity using CCK8 (Cell Counting Kit 8).

As a result, in NCI-H460 and HCT-116 cancer cell lines, the viability of cancer cells treated with the combination of OTS-412 and GCV was significantly lower than that of cancer cells treated with OTS-412 alone. On the other hand, in A549 and HT-29 cancer cell lines, no significant difference was observed between the viability of cancer cells treated with the combination of OTS-412 and GCV and that of the cancer cells treated with OTS-412 alone. This result demonstrates the additional cytotoxic effect by GCV as well as the direct cancer cell death by OTS-412 (FIG. 9).

In addition, the apoptosis and necrosis according to the combined administration of OTS-412 and GCV were confirmed by flow cytometry (FACS). Specifically, A549 and NCI-H460 cell lines were treated with GCV alone, OTS-412 alone, or a combination of OTS-412 and GCV, respectively, and the cells were subjected to Annexin V/PI staining followed by flow cytometry. At this time, the viability of cell was determined based on the facts that: both Annexin V and PI are negative in living cells; Annexin V is positive in the early stage of apoptosis, wherein the permeability of cell membrane changes; and both Annexin V and PI are positive at the end of apoptosis, wherein the nucleus is exposed by destruction of the cell membrane.

As a result, the apoptosis by treatment with GCV alone was not confirmed. However, when A549 cells were treated with OTS-412 alone, the apoptosis rate was observed as 19.64%, and with combined treatment of OTS-412 and GCV, 35.06%. In addition, when NCI-H460 cells were treated with OTS-412 alone, the apoptosis rate was observed as 6.58%, and with combined treatment of OTS-412 and GCV, 12.78% (FIG. 10). In addition, FACS results were quantified and compared with each other. As a result, an additional toxic effect by GCV was confirmed, compared to the group treated with OTS-412 alone (FIG. 11).

US11857585B2. Oncolytic virus improved in safety and anticancer effect (2024-01-02). BIONOXX INC. [KR]. Inventors: Taeho Hwang [KR], Mong Cho [KR].
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Patent 2024
A549 Cells Annexin A5 Apoptosis Cell Lines Cell Membrane Permeability Cell Nucleus Cells Cell Survival Colorectal Carcinoma Combined Modality Therapy Cytotoxin Flow Cytometry HCT116 Cells Homo sapiens HT29 Cells Lung Cancer Malignant Neoplasms Necrosis Plasma Membrane
5
Cytotoxicity and Anti-Tumor Efficacy of Chimeric Protein
Not available on PMC !

Example 5

In Vitro Cytotoxicity Assay

Cells from the Jurkat cell line were treated with different doses of chimera. The result was that the chimera is toxic to Jurkat cells in a dose-dependent manner as can be seen in FIG. 10. Almost all the cells undergo apoptotic death with a chimera concentration of 6 μM.

HT29 cells were treated with different doses of GRNLY and chimera. The result was that both GRNLY and the chimera are toxic to HT29 cells in a dose-dependent manner as can be seen in FIG. 11. GRNLY or chimera concentrations of 4 or 5 μM seem to have a similar effect, but the chimera is more cytolytic than GRNLY at a concentration of 6 μM, achieving a percentage of growth of 30% with respect to the control, i.e., 70% cytotoxicity. To match said effect, a GRNLY concentration of about 20 μM must be used.

Furthermore, labeling was also performed with Alexa-46-conjugated annexin-V showing phosphatidylserine exposure and with 7AAD showing membrane integrity on HT29 cells treated with different concentrations of chimera for analyzing the type of induced cell death. By increasing the concentration of chimera, an increase in cells labeled with annexin which still have not lost membrane integrity is observed, indicating that cell death is caused by apoptosis (FIG. 12). Furthermore, a significant increase in cytotoxicity is observed when incubating the cells with a chimera concentration of 6 μM, as shown in FIG. 16. The maximum dose of chimera used was 6 μM, whereas in the case of GRNLY, a concentration of up to 20 μM was reached.

In Vivo Assay with HELA-CEA Cells

Five mice per group (control group, granulysin group, and MFE group (with the chimera) were assayed. Although there was a mouse in the MFE group that died after the sixth injection, the other 4 mice, however, reached the end of the experiment in good conditions state. The tumor was subcutaneously injected with Matrigel at 2 million cells. Treatments began when the tumors reached a size of 150 mm3. The treatments were systemic intraperitoneal treatments performed every two days (injections):

    • Control group, 500 ul of PBS.
    • Granulysin group, 220 ul of a stock at 500 ug/ml (40 uM), i.e., 110 ug per injection, which yields a concentration of about 5 uM in 2 ml of total blood.
    • MFE group, 500 ul of stocks of about 900 ug/ml (25 uM), i.e., 425 ug per injection, which yields a concentration of about 5 uM in 2 ml of total blood.

Ten injections were performed and the mice were sacrificed 2 days after the last injection.

The results are illustrated in FIGS. 13 to 19. FIG. 13 shows that if the control group is compared with MFE group (chimera), significant differences can be seen after the 7th injection, with the difference being very significant in the last injections. It can be seen how tumor growth in treated mice is somehow contained or attenuated. FIG. 14 shows that if the control group is compared with the (non-chimeric) granulysin group, there are no significant differences, although the granulysin curve is below the control curve for all the points. FIG. 15 shows all the results shown in FIG. 13 and FIG. 14. FIG. 16 shows the means±SD of the sizes of the tumors once removed and subjected to different treatments, a smaller tumor size with granulysin treatment, and an even smaller size when the chimera is used, being shown. FIG. 16 shows the means±SD of the weights of the tumors once removed and subjected to different treatments, a lower tumor weight with granulysin treatment, and an even lower weight when the chimera is used, being shown.

US11858973B2. Granulysin, method of obtaining same, and uses (2024-01-02). UNIVERSIDAD DE ZARAGOZA [ES], FUNDACIÓN AGENCIA ARAGONESA PARA LA INVESTIGACIÓN Y EL DESARROLLO (ARAID) [ES], FUNDACIÓN PARA LA INVESTIGACIÓN BIOMÉDICA HOSPITAL UNIVERSITARIO PUERTA DE HIERRO MAJADAHONDA [ES]. Inventors: Luis Alberto Anel Bernal [ES], Raquel Ibañez Perez [ES], Patricia Guerrero Ochoa [ES], Luis Martinez Lostao [ES], Blanca Conde Guerri [ES], Ramón Hurtado Guerrero [ES], Ana Laura Sanz Alcober [ES], Rocio Navarro Ortiz [ES].
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Patent 2024
7-aminoactinomycin D Annexin A5 Annexins Apoptosis BLOOD Cell Death Cell Lines Cells Chimera Cytotoxin GNLY protein, human HeLa Cells HT29 Cells Injections, Intraperitoneal Jurkat Cells matrigel Mus Neoplasms Phosphatidylserines Plasma Membrane Tissue, Membrane Vision

Top products related to «Apoptosis»

1
Facscalibur by BD
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The FACSCalibur is a flow cytometry system designed for multi-parameter analysis of cells and other particles. It features a blue (488 nm) and a red (635 nm) laser for excitation of fluorescent dyes. The instrument is capable of detecting forward scatter, side scatter, and up to four fluorescent parameters simultaneously.
2
Facscalibur flow cytometer by BD
Sourced in United States, Germany, United Kingdom, China, Canada, Japan, Belgium, France, Spain, Italy, Australia, Finland, Poland, Switzerland, Cameroon, Uruguay, Denmark, Jersey, Moldova, Republic of, Singapore, India, Brazil
The FACSCalibur flow cytometer is a compact and versatile instrument designed for multiparameter analysis of cells and particles. It employs laser-based technology to rapidly measure and analyze the physical and fluorescent characteristics of cells or other particles as they flow in a fluid stream. The FACSCalibur can detect and quantify a wide range of cellular properties, making it a valuable tool for various applications in biology, immunology, and clinical research.
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Fitc annexin 5 apoptosis detection kit by BD
Sourced in United States, Germany, China, United Kingdom, Poland, Belgium, Japan, Canada, India, Australia
The FITC Annexin V Apoptosis Detection Kit is a laboratory reagent used to detect and quantify apoptosis, a form of programmed cell death, in cell samples. The kit contains FITC-conjugated Annexin V, a protein that binds to phosphatidylserine, a molecule that is externalized during the early stages of apoptosis. The kit also includes a propidium iodide solution, which can be used to identify late-stage apoptotic or necrotic cells.
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In situ cell death detection kit by Roche
Sourced in Germany, United States, Switzerland, China, United Kingdom, France, Canada, Belgium, Japan, Italy, Spain, Hungary, Australia
The In Situ Cell Death Detection Kit is a laboratory product designed for the detection of programmed cell death, or apoptosis, in cell samples. The kit utilizes a terminal deoxynucleotidyl transferase (TdT) to label DNA strand breaks, allowing for the visualization and quantification of cell death. The core function of this product is to provide researchers with a tool to study and analyze cell death processes.
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Fitc annexin 5 apoptosis detection kit 1 by BD
Sourced in United States, Germany, China, United Kingdom, France, Portugal, Canada, Spain, Japan, Belgium
The FITC Annexin V Apoptosis Detection Kit is a laboratory tool used to detect and quantify apoptosis, a form of programmed cell death. The kit utilizes the binding properties of the protein Annexin V, which has a high affinity for the phospholipid phosphatidylserine, which becomes exposed on the cell surface during apoptosis. The Annexin V is conjugated with the fluorescent dye FITC, allowing for the detection of apoptotic cells through fluorescence microscopy or flow cytometry.
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Cellquest software by BD
Sourced in United States, Germany, United Kingdom, Italy, Canada, China, Japan, Belgium, France, Spain, Switzerland, Poland, Uruguay, Denmark, Singapore
CellQuest software is a data acquisition and analysis software designed for flow cytometry applications. It provides tools for acquiring, processing, and analyzing flow cytometry data.
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Facscanto 2 by BD
Sourced in United States, Germany, United Kingdom, Belgium, China, Australia, France, Japan, Italy, Spain, Switzerland, Canada, Uruguay, Netherlands, Czechia, Jersey, Brazil, Denmark, Singapore, Austria, India, Panama
The FACSCanto II is a flow cytometer instrument designed for multi-parameter analysis of single cells. It features a solid-state diode laser and up to four fluorescence detectors for simultaneous measurement of multiple cellular parameters.
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Flow cytometry by BD
Sourced in United States, Germany, China, Japan, United Kingdom, Australia, Uruguay, Switzerland
Flow cytometry is an analytical technique used to detect and measure physical and chemical characteristics of particles or cells suspended in a fluid as they pass through a laser beam. It allows for the rapid analysis and sorting of individual cells within a heterogeneous mixture.
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Facscan by BD
Sourced in United States, Germany, China, United Kingdom, Italy, Japan, Spain, France, Canada, Switzerland, Jersey, Macao
The FACScan is a flow cytometry instrument manufactured by BD. It is designed to analyze and sort cells or particles in a fluid stream. The FACScan uses laser technology to detect and measure the physical and fluorescent characteristics of individual cells or particles as they pass through the instrument's flow cell.
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Propidium iodide by Merck Group
Sourced in United States, Germany, United Kingdom, China, Italy, Japan, France, Sao Tome and Principe, Macao, Canada, Spain, India, Belgium, Australia, Israel, Switzerland, Poland, Ireland, Argentina, Austria, Brazil, Sweden, Portugal, New Zealand, Netherlands, Slovakia, Norway, Hungary, Czechia, Denmark
Propidium iodide is a fluorescent dye commonly used in molecular biology and flow cytometry applications. It binds to DNA and is used to stain cell nuclei, allowing for the identification and quantification of cells in various stages of the cell cycle.

More about "Apoptosis"

Apoptosis, also known as programmed cell death, is a crucial biological process that plays a pivotal role in various aspects of life, including development, homeostasis, and disease management.
This highly regulated form of cell suicide involves a complex series of biochemical events, leading to characteristic cellular changes and, ultimately, the demise of the cell.
Maintaining tissue homeostasis, eliminating damaged or unwanted cells, and regulating immune responses are essential functions of apoptosis.
Dysregulation of this process has been implicated in a wide range of pathological conditions, such as cancer, neurodegenerative disorders, and autoimmune diseases.
Understanding the mechanisms and signaling pathways underlying apoptosis is a key focus of biomedical research, as it may pave the way for the development of novel therapeutic interventions targeting this fundamental cellular process.
Flow cytometry techniques, such as the FACSCalibur flow cytometer and the FITC Annexin V Apoptosis Detection Kit, have become invaluable tools in the study of apoptosis.
These methods, along with the use of propidium iodide and CellQuest software, allow researchers to accurately identify and quantify apoptotic cells.
The FACSCanto II and FACScan instruments further enhance the capabilities of flow cytometry in apoptosis research, providing researchers with a powerful set of tools to unravel the complexities of this cellular phenomenon.
PubCompare.ai, a leading AI-driven platform, can significantly enhance your apoptosis research by providing access to the best protocols from literature, preprints, and patents.
This ensures superior reproducibility and accuracy in your studies, allowing you to take your apoptosis research to new heights and make groundbreaking discoveries.