Review




Structured Review

Epigenomics ag epigenetic modifications
Epigenetic Modifications, supplied by Epigenomics ag, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/epigenetic+modifications/pmc12204941-61-11-16
Average 90 stars, based on 1 article reviews
epigenetic modifications - by Bioz Stars, 2026-09
90/100 stars

Images

Related Articles

Biomarker Discovery:

Article Title: Integrating multi-omics and machine learning for disease resistance prediction in legumes.
Article Snippet: .. Multi-omics integrates data from various molecular levels, including DNA sequences (genomics), gene expression (transcriptomics), epigenetic modifications (epigenomics), protein (proteomics) and metabolite levels (metabolomics) (Yang et al. 2021). ..

Article Title: Integrating multi-omics and machine learning for disease resistance prediction in legumes
Article Snippet: .. Multi-omics integrates data from various molecular levels, including DNA sequences (genomics), gene expression (transcriptomics), epigenetic modifications (epigenomics), protein (proteomics) and metabolite levels (metabolomics) ( Yang et al. ) . ..

Gene Expression:

Article Title: Integrating multi-omics and machine learning for disease resistance prediction in legumes.
Article Snippet: .. Multi-omics integrates data from various molecular levels, including DNA sequences (genomics), gene expression (transcriptomics), epigenetic modifications (epigenomics), protein (proteomics) and metabolite levels (metabolomics) (Yang et al. 2021). ..

Article Title: Integrating multi-omics and machine learning for disease resistance prediction in legumes
Article Snippet: .. Multi-omics integrates data from various molecular levels, including DNA sequences (genomics), gene expression (transcriptomics), epigenetic modifications (epigenomics), protein (proteomics) and metabolite levels (metabolomics) ( Yang et al. ) . ..

Article Title: An extensive review on infectious disease diagnosis using machine learning techniques and next generation sequencing: State-of-the-art and perspectives.
Article Snippet: Infectious diseases, including tuberculosis (TB), HIV/AIDS, and emerging pathogens like COVID-19 pose severe global health challenges due to their rapid spread and significant morbidity and mortality rates.. Next-generation sequencing (NGS) and machine learning (ML) have emerged as transformative technologies for enhancing disease diagnosis and management.. Objective: This review aims to explore integrating ML techniques with NGS for diagnosing infectious diseases, highlighting their effectiveness and identifying existing challenges.

Article Title: Domestication of ornamental plants: Breeding innovations and molecular breakthroughs to bring wild into limelight
Article Snippet: Wild ornamental plants offer a rich reservoir of genetic resources, essential for developing new, improved cultivars.. Domestication of wild ornamental plant species transforms them into distinct cultivars with enhanced attributes, imperative for enhancing the diversity, adaptability of cultivated plants and addressing the evolving demands of the floriculture industry.. This review offers a novel perspective on the domestication of wild ornamentals by highlighting advancements in breeding methods, genomics, genetic engineering, and cutting-edge technologies like CRISPR-Cas9.

other:

Article Title: Understanding Genetic Screening: Harnessing Health Information to Prevent Disease Risks
Article Snippet: Integration of Epigenomics: - In addition to gene sequences, epigenetic modifications will also be included in screening .

DNA Methylation Assay:

Article Title: Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues
Article Snippet: .. Epigenomics, which examines the full spectrum of epigenetic modifications such as DNA methylation and histone modification, plays a crucial role in understanding how environmental factors and genetic predispositions interact to influence the development of diseases [ ]. ..

Article Title: Domestication of ornamental plants: Breeding innovations and molecular breakthroughs to bring wild into limelight
Article Snippet: Wild ornamental plants offer a rich reservoir of genetic resources, essential for developing new, improved cultivars.. Domestication of wild ornamental plant species transforms them into distinct cultivars with enhanced attributes, imperative for enhancing the diversity, adaptability of cultivated plants and addressing the evolving demands of the floriculture industry.. This review offers a novel perspective on the domestication of wild ornamentals by highlighting advancements in breeding methods, genomics, genetic engineering, and cutting-edge technologies like CRISPR-Cas9.

Modification:

Article Title: Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues
Article Snippet: .. Epigenomics, which examines the full spectrum of epigenetic modifications such as DNA methylation and histone modification, plays a crucial role in understanding how environmental factors and genetic predispositions interact to influence the development of diseases [ ]. ..

Chromatin Immunoprecipitation:

Article Title: Precision medicine and Treat-to-Target approach in atopic dermatitis: enhancing personalized care and outcomes
Article Snippet: Lipidomics , The study of lipids within a cell or tissue. , Lipids , Mass Spectrometry (MS). .. Epigenomics , The study of the complete set of epigenetic modifications on the genetic material of a cell (epigenome). , DNA , ChIP-Seq/Hi-C/ChIA-PET. .. Metallomics , The study of metalloproteins, metalloids, and metals within a cell or tissue. It is a branch of metabolomics. , Metalloproteins, metalloids, and metals. , Atomic Absorption Spectroscopy (AAS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS).

Sequencing:

Article Title: An extensive review on infectious disease diagnosis using machine learning techniques and next generation sequencing: State-of-the-art and perspectives.
Article Snippet: Infectious diseases, including tuberculosis (TB), HIV/AIDS, and emerging pathogens like COVID-19 pose severe global health challenges due to their rapid spread and significant morbidity and mortality rates.. Next-generation sequencing (NGS) and machine learning (ML) have emerged as transformative technologies for enhancing disease diagnosis and management.. Objective: This review aims to explore integrating ML techniques with NGS for diagnosing infectious diseases, highlighting their effectiveness and identifying existing challenges.

Article Title: Domestication of ornamental plants: Breeding innovations and molecular breakthroughs to bring wild into limelight
Article Snippet: Wild ornamental plants offer a rich reservoir of genetic resources, essential for developing new, improved cultivars.. Domestication of wild ornamental plant species transforms them into distinct cultivars with enhanced attributes, imperative for enhancing the diversity, adaptability of cultivated plants and addressing the evolving demands of the floriculture industry.. This review offers a novel perspective on the domestication of wild ornamentals by highlighting advancements in breeding methods, genomics, genetic engineering, and cutting-edge technologies like CRISPR-Cas9.



Similar Products

94
TargetMol targetmol epigenetic inhibitors
High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including SGC <t>epigenetic</t> compounds, FDA-approved oncology drugs, and TargetMol epigenetic <t>inhibitors.</t> (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.
Targetmol Epigenetic Inhibitors, supplied by TargetMol, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/Histone+Modification+Compound+Library/bio_rxiv__64898__2026__04__16__719008-139-10-10
Average 94 stars, based on 1 article reviews
targetmol epigenetic inhibitors - by Bioz Stars, 2026-09
94/100 stars
  Buy from Supplier

94
TargetMol 380 targetmol epigenetic inhibitors
High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including SGC <t>epigenetic</t> compounds, FDA-approved oncology drugs, and TargetMol epigenetic <t>inhibitors.</t> (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.
380 Targetmol Epigenetic Inhibitors, supplied by TargetMol, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/Histone+Modification+Compound+Library/bio_rxiv__64898__2026__04__16__719008-78-19-20
Average 94 stars, based on 1 article reviews
380 targetmol epigenetic inhibitors - by Bioz Stars, 2026-09
94/100 stars
  Buy from Supplier

94
TargetMol sgc epigenetic compounds
High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including <t>SGC</t> <t>epigenetic</t> compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.
Sgc Epigenetic Compounds, supplied by TargetMol, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/Histone+Modification+Compound+Library/bio_rxiv__64898__2026__04__16__719008-78-16-20
Average 94 stars, based on 1 article reviews
sgc epigenetic compounds - by Bioz Stars, 2026-09
94/100 stars
  Buy from Supplier

86
Biomark Inc rna epigenetic modifications
High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including <t>SGC</t> <t>epigenetic</t> compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.
Rna Epigenetic Modifications, supplied by Biomark Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/epigenetic+modifications+rna/pm41928252-984-26-39
Average 86 stars, based on 1 article reviews
rna epigenetic modifications - by Bioz Stars, 2026-09
86/100 stars
  Buy from Supplier

86
Abbott Laboratories epigenetic modifications
High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including <t>SGC</t> <t>epigenetic</t> compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.
Epigenetic Modifications, supplied by Abbott Laboratories, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/epigenetic+modifications/pm41866754-363-1-32
Average 86 stars, based on 1 article reviews
epigenetic modifications - by Bioz Stars, 2026-09
86/100 stars
  Buy from Supplier

94
TargetMol epigenetic inhibitors
High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including <t>SGC</t> <t>epigenetic</t> compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.
Epigenetic Inhibitors, supplied by TargetMol, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/Histone+Modification+Compound+Library/pm41713838-53-7-15
Average 94 stars, based on 1 article reviews
epigenetic inhibitors - by Bioz Stars, 2026-09
94/100 stars
  Buy from Supplier

94
TargetMol epigenetic compound screen
A Mean viability of the three UM cell lines following 72 h treatment with 932 <t>epigenetic</t> modulators at a concentration of 1 μM ( n = 2) relative to the negative control (0.1% DMSO treatment). Hit cut-offs (dashed lines) were determined as the mean percentage viability of the negative controls in each cell line minus three standard deviations. Yellow dashed line is the hit cut-off for MP41 cells (65.8% viability), purple dashed line is the hit cut-off for MP46 cells (74.0% viability), and the green dashed line is the hit cut-off for MP38 cells (58.9% viability). For full list of compounds and average UM cell viabilities, see Supplementary Data . B Radar plot showing the mean difference in percent of cell viability of UM cells caused by 72 h 1 μM treatment with 932 compounds, relative to the DMSO control. Negative values, shown in gray, indicate ineffective compounds leading to greater cell viability than the negative control. The positive values, shown in color, indicate compounds that induced cell death, with higher peaks indicating greater cell death. Compounds are grouped by drug mechanism of action. C Pie charts of the molecular activities of all screened compounds ( n = 932) (left) and the hits identified ( n = 24) (right). D Concentration-response experiments for the 24 hit compounds (10 concentrations, n = 4 per concentration per cell line). Center values represent mean viability, error bars represent standard error of mean (SEM). E Log IC 50 (M) values of the top hit compounds for each cell line. Error bars represent 95% confidence interval. F Log IC 50 (M) of BAP1 mutant cell lines (MP46 and MP38) plotted against the log IC 50 (M) of the BAP1 wildtype cell line (MP41) for each drug treatment.
Epigenetic Compound Screen, supplied by TargetMol, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/Histone+Modification+Compound+Library/pmc12830624-24-13-30
Average 94 stars, based on 1 article reviews
epigenetic compound screen - by Bioz Stars, 2026-09
94/100 stars
  Buy from Supplier

90
Epigenomics ag epigenetic modifications
A Mean viability of the three UM cell lines following 72 h treatment with 932 <t>epigenetic</t> modulators at a concentration of 1 μM ( n = 2) relative to the negative control (0.1% DMSO treatment). Hit cut-offs (dashed lines) were determined as the mean percentage viability of the negative controls in each cell line minus three standard deviations. Yellow dashed line is the hit cut-off for MP41 cells (65.8% viability), purple dashed line is the hit cut-off for MP46 cells (74.0% viability), and the green dashed line is the hit cut-off for MP38 cells (58.9% viability). For full list of compounds and average UM cell viabilities, see Supplementary Data . B Radar plot showing the mean difference in percent of cell viability of UM cells caused by 72 h 1 μM treatment with 932 compounds, relative to the DMSO control. Negative values, shown in gray, indicate ineffective compounds leading to greater cell viability than the negative control. The positive values, shown in color, indicate compounds that induced cell death, with higher peaks indicating greater cell death. Compounds are grouped by drug mechanism of action. C Pie charts of the molecular activities of all screened compounds ( n = 932) (left) and the hits identified ( n = 24) (right). D Concentration-response experiments for the 24 hit compounds (10 concentrations, n = 4 per concentration per cell line). Center values represent mean viability, error bars represent standard error of mean (SEM). E Log IC 50 (M) values of the top hit compounds for each cell line. Error bars represent 95% confidence interval. F Log IC 50 (M) of BAP1 mutant cell lines (MP46 and MP38) plotted against the log IC 50 (M) of the BAP1 wildtype cell line (MP41) for each drug treatment.
Epigenetic Modifications, supplied by Epigenomics ag, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/epigenetic+modifications/epigenetic+modifications/pmc12204941-61-11-16
Average 90 stars, based on 1 article reviews
epigenetic modifications - by Bioz Stars, 2026-09
90/100 stars
  Buy from Supplier

Image Search Results


High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including SGC epigenetic compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.

Journal: bioRxiv

Article Title: Acquired resistance to the PRMT5 inhibitor confers collateral sensitivity to MEK inhibition in MTAP-null non-small cell lung cancer

doi: 10.64898/2026.04.16.719008

Figure Lengend Snippet: High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including SGC epigenetic compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.

Article Snippet: The screening library comprised 619 compounds, including SGC epigenetic compounds, TargetMol epigenetic inhibitors, and FDA-approved oncology drugs ( ).

Techniques: High Throughput Screening Assay, Drug discovery, Control

High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including SGC epigenetic compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.

Journal: bioRxiv

Article Title: Acquired resistance to the PRMT5 inhibitor confers collateral sensitivity to MEK inhibition in MTAP-null non-small cell lung cancer

doi: 10.64898/2026.04.16.719008

Figure Lengend Snippet: High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including SGC epigenetic compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.

Article Snippet: A high-throughput drug screen was performed using a compound library consisting of 619 compounds, including 59 SGC epigenetic compounds, 380 TargetMol epigenetic inhibitors and 180 FDA-approved oncology drugs.

Techniques: High Throughput Screening Assay, Drug discovery, Control

High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including SGC epigenetic compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.

Journal: bioRxiv

Article Title: Acquired resistance to the PRMT5 inhibitor confers collateral sensitivity to MEK inhibition in MTAP-null non-small cell lung cancer

doi: 10.64898/2026.04.16.719008

Figure Lengend Snippet: High-throughput drug screen and MEK inhibitor sensitivity in MRTX1719-resistant NSCLC cells. (A) Composition of the compound library used for drug screen, including SGC epigenetic compounds, FDA-approved oncology drugs, and TargetMol epigenetic inhibitors. (B) IC50 values of MRTX1719 and anisomycin in DMSO and MRTXR cells. Anisomycin was included as a nonselective control in the drug screen. (C) Dose-response curves of DMSO and MRTXR cells treated with the MEK inhibitor selumetinib. Data are presented as mean ± SD. (D) Synergy heatmaps of MRTX1719 and selumetinib in DMSO and MRTXR cells. Synergy mean scores were calculated using the Bliss model with the SynergyFinder+ tool.

Article Snippet: A high-throughput drug screen was performed using a compound library consisting of 619 compounds, including 59 SGC epigenetic compounds, 380 TargetMol epigenetic inhibitors and 180 FDA-approved oncology drugs.

Techniques: High Throughput Screening Assay, Drug discovery, Control

A Mean viability of the three UM cell lines following 72 h treatment with 932 epigenetic modulators at a concentration of 1 μM ( n = 2) relative to the negative control (0.1% DMSO treatment). Hit cut-offs (dashed lines) were determined as the mean percentage viability of the negative controls in each cell line minus three standard deviations. Yellow dashed line is the hit cut-off for MP41 cells (65.8% viability), purple dashed line is the hit cut-off for MP46 cells (74.0% viability), and the green dashed line is the hit cut-off for MP38 cells (58.9% viability). For full list of compounds and average UM cell viabilities, see Supplementary Data . B Radar plot showing the mean difference in percent of cell viability of UM cells caused by 72 h 1 μM treatment with 932 compounds, relative to the DMSO control. Negative values, shown in gray, indicate ineffective compounds leading to greater cell viability than the negative control. The positive values, shown in color, indicate compounds that induced cell death, with higher peaks indicating greater cell death. Compounds are grouped by drug mechanism of action. C Pie charts of the molecular activities of all screened compounds ( n = 932) (left) and the hits identified ( n = 24) (right). D Concentration-response experiments for the 24 hit compounds (10 concentrations, n = 4 per concentration per cell line). Center values represent mean viability, error bars represent standard error of mean (SEM). E Log IC 50 (M) values of the top hit compounds for each cell line. Error bars represent 95% confidence interval. F Log IC 50 (M) of BAP1 mutant cell lines (MP46 and MP38) plotted against the log IC 50 (M) of the BAP1 wildtype cell line (MP41) for each drug treatment.

Journal: Cell Death & Disease

Article Title: Identification of targetable epigenetic vulnerabilities for uveal melanoma

doi: 10.1038/s41419-025-08295-4

Figure Lengend Snippet: A Mean viability of the three UM cell lines following 72 h treatment with 932 epigenetic modulators at a concentration of 1 μM ( n = 2) relative to the negative control (0.1% DMSO treatment). Hit cut-offs (dashed lines) were determined as the mean percentage viability of the negative controls in each cell line minus three standard deviations. Yellow dashed line is the hit cut-off for MP41 cells (65.8% viability), purple dashed line is the hit cut-off for MP46 cells (74.0% viability), and the green dashed line is the hit cut-off for MP38 cells (58.9% viability). For full list of compounds and average UM cell viabilities, see Supplementary Data . B Radar plot showing the mean difference in percent of cell viability of UM cells caused by 72 h 1 μM treatment with 932 compounds, relative to the DMSO control. Negative values, shown in gray, indicate ineffective compounds leading to greater cell viability than the negative control. The positive values, shown in color, indicate compounds that induced cell death, with higher peaks indicating greater cell death. Compounds are grouped by drug mechanism of action. C Pie charts of the molecular activities of all screened compounds ( n = 932) (left) and the hits identified ( n = 24) (right). D Concentration-response experiments for the 24 hit compounds (10 concentrations, n = 4 per concentration per cell line). Center values represent mean viability, error bars represent standard error of mean (SEM). E Log IC 50 (M) values of the top hit compounds for each cell line. Error bars represent 95% confidence interval. F Log IC 50 (M) of BAP1 mutant cell lines (MP46 and MP38) plotted against the log IC 50 (M) of the BAP1 wildtype cell line (MP41) for each drug treatment.

Article Snippet: Given the global epigenetic changes elicited by BAP1 loss, we performed a comprehensive epigenetic compound screen on UM cells, using a well-characterized drug library consisting of 932 cell-permeable, small-molecule modulators (TargetMol, L1200, July 2022; Supplementary Data ).

Techniques: Concentration Assay, Negative Control, Control, Mutagenesis