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Journal: bioRxiv
Article Title: Enantiomer-Dependent Biological Activity of Cysteine-Coated Ceria Nanoparticles in Colorectal Cancer Cells
doi: 10.64898/2026.04.27.721174
Figure Lengend Snippet: The selected models represent a clinical spectrum ranging from healthy colon tissue to aggressive metastasis. CCD-18Co serves as the non-malignant, healthy fibroblast control. COLO-201 is a highly proliferative adenocarcinoma characterized by high stress sensitivity and low functional A20 expression. DLD-1 is an MSI-H model with intact, albeit modified, A20 feedback (SNV:single-nucleotide variation). LoVo represents a metastatic MSI-H line harboring a Loss-of-Function (LOF) A20 mutation, maintaining resilience through a robust GSH-mediated antioxidant shield. (Gradient bars: Green = Low; Red = High). Created with BioRender.com .
Article Snippet: The colorectal cancer cell lines DLD-1 and
Techniques: Control, Functional Assay, Expressing, Modification, Mutagenesis
Journal: bioRxiv
Article Title: Enantiomer-Dependent Biological Activity of Cysteine-Coated Ceria Nanoparticles in Colorectal Cancer Cells
doi: 10.64898/2026.04.27.721174
Figure Lengend Snippet: (A & B ): Cell viability of COLO-201, DLD-1, LoVo, and CCD-18Co cells treated with D-Cys@CeNP (A) and L-Cys@CeNP (B) for 24 h at increasing concentrations. (C & D) Cell viability of COLO-201, DLD-1, LoVo, and CCD-18Co cells treated with D-Cys@CeNP (C) and L- 34 C 0 ys@CeNP (D) for 72 h at increasing concentrations. (E) IC 50 values for D-Cys@CeNP and L-Cys@CeNP treatments at 24 h and 72 h for all cell lines. (F) Summary table displaying the mean IC 50 values (µg/mL) for each treatment condition across all cell lines. The results represent the mean ± SD of three independent biological replicates (n=3). The dotted vertical lines indicate the IC 50 values, which are also displayed in the figure. Statistical significance was analyzed using one-way ANOVA followed by Tukey’s post-hoc test: (ns = non-significant, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).
Article Snippet: The colorectal cancer cell lines DLD-1 and
Techniques:
Journal: bioRxiv
Article Title: Enantiomer-Dependent Biological Activity of Cysteine-Coated Ceria Nanoparticles in Colorectal Cancer Cells
doi: 10.64898/2026.04.27.721174
Figure Lengend Snippet: h. The Selectivity Index is defined as the ratio of IC50 values in healthy control cells (CCD-18Co) to those in CRC cell lines (LoVo, DLD-1, and COLO-201). (A) Enantiomeric Comparison at 24 h: Comparison of SI values between D-Cys@CeNP (orange) and L-Cys@CeNP (brown) after 24 hours of exposure . (B) Enantiomeric Comparison at 72 h: Comparison of SI values between D-Cys@CeNP and L-Cys@CeNP after 72 hours of exposure. (C) Time-dependent analysis of D-Cys@CeNP selectivity across CRC cell lines. Over time NPs become more selective in COLO-201 . (D) Time-dependent analysis of L-Cys@CeNP. The horizontal dashed line at SI=2.0 represents the baseline for selectivity. Data are presented as mean ± SD (n=3). Statistical significance is indicated by asterisks (, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001)
Article Snippet: The colorectal cancer cell lines DLD-1 and
Techniques: Control, Comparison
Journal: bioRxiv
Article Title: Enantiomer-Dependent Biological Activity of Cysteine-Coated Ceria Nanoparticles in Colorectal Cancer Cells
doi: 10.64898/2026.04.27.721174
Figure Lengend Snippet: (A) COLO-201 cells treated with D-Cys@CeNP and L-Cys@CeNP for 24 h; ROS fold change comparison. (B) DLD-1 cells treated with D-Cys@CeNP and L-Cys@CeNP for 24 h; ROS fold change comparison. (C) LoVo cells treated with D-Cys@CeNP and L-Cys@CeNP for 24 h; ROS fold change comparison. (D) CCD-18Co cells treated with D-Cys@CeNP and L-Cys@CeNP for 24 h; ROS fold change comparison. (E) Mechanistic Efficiency Index values for D-Cys@CeNP (orange) and L-Cys@CeNP (blue) across four cell lines: COLO-201, DLD-1, LoVo, and CCD-18Co . (F) ROS fold change at IC₅₀ concentrations in colorectal cancer and control cell lines treated with D-Cys@CeNP (red) and L-Cys@CeNP (blue) at their respective IC₅₀ concentrations.The vertical dashed lines indicate the IC 50 values on the X-axis. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).
Article Snippet: The colorectal cancer cell lines DLD-1 and
Techniques: Comparison, Control
Journal: bioRxiv
Article Title: Enantiomer-Dependent Biological Activity of Cysteine-Coated Ceria Nanoparticles in Colorectal Cancer Cells
doi: 10.64898/2026.04.27.721174
Figure Lengend Snippet: (A) Representative flow cytometry plots for each treatment condition in COLO-201 cells. Quadrant analysis distinguishes healthy (Q4; Annexin V-/PI-), early apoptotic (Q1; Annexin V+/PI-), late apoptotic (Q2; Annexin V+/PI+), and necrotic (Q3; Annexin V-/PI+) populations (B-C) Comparative analysis of apoptotic and cytotoxic responses induced by D-Cys@CeNP and L-Cys@CeNP in colorectal cancer (CRC) and healthy colon fibroblast cell lines at IC 50 concentrations for 24 hours. (B) Cell line-specific radar plots comparing D-Cys@CeNP (red) and L-Cys@CeNP (blue) responses, highlighting differences in apoptotic phases and cytotoxicity profiles between the two nanoparticle enantiomers. (C) Bar plot comparing radar plot areas to represent the overall biological response magnitude for each nanoparticle in each cell line in B.
Article Snippet: The colorectal cancer cell lines DLD-1 and
Techniques: Flow Cytometry
Journal: bioRxiv
Article Title: Enantiomer-Dependent Biological Activity of Cysteine-Coated Ceria Nanoparticles in Colorectal Cancer Cells
doi: 10.64898/2026.04.27.721174
Figure Lengend Snippet: (A) Expression levels of TNFAIP3, IKBKG, and NFKBIA in all cell lines (COLO-201, DLD-1, LoVo, and CCD-18Co) after CeNP treatment. (B) Comparison of TNFAIP3, IKBKG, and NFKBIA expression within each cell lineand each nanoparticle treatment (D-Cys@CeNP vs. L-Cys@CeNP) across all cell lines. (ns = non-significant, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001).
Article Snippet: The colorectal cancer cell lines DLD-1 and
Techniques: Expressing, Comparison
Journal: bioRxiv
Article Title: Multi-omics and biophysical phosphoproteomics upon BRAF inhibition uncover functional networks of BRAFV600E-driven signaling
doi: 10.64898/2026.02.09.704793
Figure Lengend Snippet: (A) Experimental workflow for Dabrafenib treatment (100 nM, 4 hours) in BRAFV600E-mutant cell lines (A2058, COLO-201, MNT1), followed by phosphoproteomic and proteomic profiling. Phosphopeptides were enriched using an automated Fe³⁺-IMAC platform and quantified by TMT18-plex labeling. Both phosphoproteome and full proteome samples were prefractionated using porous graphitized carbon (PGC) prior to LC-MS/MS analysis. Default data processing included database search with fragpipe, variance-stabilizing normalization and differential expression analysis with limma. (B) Volcano plots showing differential phosphopeptide abundance upon Dabrafenib treatment (100 nM, 4 h) relative to DMSO control across all three cell lines combined (A2058, COLO-201, MNT1). Significantly upregulated (red) and downregulated (blue) phosphopeptides are highlighted (moderated t-test, adj. p-value < 0.05, |log₂ fold-change| > log₂(1.5) as indicated by dashed line). (C) Pathway enrichment analysis of genes with up- or downregulated phosphopeptides upon Dabrafenib treatment across cell lines (normalized weighted mean test, Reactome pathways, p-value < 0.05, selected top pathways). (D) Number of phosphopeptide hits, stratified by direction of change and by the number of cell lines in which they are significantly altered in abundance upon Dabrafenib treatment (100 nM, 4h). (E) Experimental design of the Dabrafenib treatment time course experiment. A2058 melanoma cells were treated with 100 nM Dabrafenib or DMSO control and harvested at six time points (0, 15, 30, 60, 120, 240 min) in three biological replicates in reverse order. (F) Volcano plots showing differential phosphopeptide abundance upon Dabrafenib treatment (100 nM) at each time point relative to DMSO control at 0 hours. Significantly upregulated (red) and downregulated (blue) phosphopeptides are highlighted (moderated t-test, adj. p-value < 0.05, |log₂ fold-change| > log₂(1.5) as indicated by dashed line). (G) Temporal dynamics of four phosphopeptide clusters identified by neural gas clustering based on phosphopeptides significantly affected by Dabrafenib treatment in at least one time point. Line plots show median log₂ fold changes over time per cluster. Cluster sizes are indicated. (H) Pathway enrichment analysis enrichment analysis for genes of each phosphopeptide cluster (normalized weighted mean test with GO terms and Reactome pathways, p-value < 0.05, selected top pathways). (I) Representative temporal phosphorylation profiles of regulatory proteins of the different clusters, including MYC (multiple sites), FOS (S374), ARHGEF2 (S129, S137, S940/S941, S956), and SMARCA4 (T609/S610).
Article Snippet:
Techniques: Mutagenesis, Labeling, Liquid Chromatography with Mass Spectroscopy, Quantitative Proteomics, Phospho-proteomics, Control
Journal: bioRxiv
Article Title: Multi-omics and biophysical phosphoproteomics upon BRAF inhibition uncover functional networks of BRAFV600E-driven signaling
doi: 10.64898/2026.02.09.704793
Figure Lengend Snippet: (A) Principal component analysis (PCA) of normalized phosphopeptide intensities in A2058 (circle), COLO-201 (triangle), and MNT-1 (square) cells treated with 100 nM Dabrafenib (green) or DMSO (grey) for 4 hours. The PCA was calculated using the top 10% most variable phosphopeptides across samples. (B) Normalized MYC S62 phosphorylation (KFELLPTPPLpSPSR) across the three cell lines in response to 100 nM Dabrafenib (4h, green) or DMSO (4h, grey). (C) Volcano plots showing differential protein (upper row) or phosphopeptide (lower row) abundance upon Dabrafenib treatment (100 nM, 4 h) relative to DMSO for each cell line or across cell lines (all, interaction effect model). Significantly upregulated (red) and downregulated (blue) features are highlighted (moderated t-test, adj. p-value < 0.05, |log₂ fold-change| > log₂(1.5) as indicated by dashed line). (D) Time-resolved phosphorylation dynamics of MAPK1 (Y187, VADPDHDHTGFLTEpYVATR) and MAPK3 (Y204, IADPEHDHTGFLTEpYVATR) activation loop sites, upon Dabrafenib treatment. Significantly downregulated (blue) phosphopeptides are highlighted (moderated t-test, adj. p-value < 0.05, |log₂ fold-change| > log₂(1.5)). (E) PCA of normalized phosphopeptide intensities in the Dabrafenib time course (100 nM) across six timepoints (indicated by colour and shape). The PCA was calculated using the top 10% most variable phosphopeptides across samples.
Article Snippet:
Techniques: Phospho-proteomics, Activation Assay
Journal: bioRxiv
Article Title: Multi-omics and biophysical phosphoproteomics upon BRAF inhibition uncover functional networks of BRAFV600E-driven signaling
doi: 10.64898/2026.02.09.704793
Figure Lengend Snippet: (A) Overview of the time-resolved transcriptomic profiling workflow. A2058, COLO-201 and MNT-1 cells (results here shown for A2058) were treated with 100 nM Dabrafenib or DMSO, and samples were collected at 0, 2, 4, and 8 hours for poly(A)-mRNA sequencing. Transcript abundance dynamics were used to infer the transcriptional programs downstream of BRAF inhibition. (B) PCA of gene counts of the top 10% most variable genes in Dabrafenib- (green) and DMSO-treated (grey) A2058 cells. (C) Inference of transcription factor (TF) activity using gene expression signatures upon Dabrafenib treatment (2-8 h) of known targets (normalized weighted mean test with CollecTRI database, p-value < 0.05). Heatmap shows scores of top TFs across time points for A2058 cells, highlighting both upregulated (red) and downregulated (blue) TFs. (D) Venn diagram showing the overlap between TFs with significantly altered phosphorylation in the Dabrafenib phosphoproteomics time course and TFs with inferred changes in activity upon Dabrafenib treatment based on the transcriptomics data. (E) Schematic overview of the thermal proteome profiling (TPP) experiment. A2058 cells treated with 100 nM Dabrafenib or DMSO for 4 hours were subjected to a temperature gradient, followed by lysis and multiplexed MS-based quantification of soluble proteins across the temperature range. (F) Volcano plot of differential protein thermal stability upon Dabrafenib treatment (100 nM, 4 h) relative to DMSO. Blue and red dots denote stabilizing and destabilizing responses, respectively (moderated t-test, adjusted p-value < 0.05). (G) Pathway enrichment analysis of proteins showing altered thermal stability upon Dabrafenib treatment (normalized weighted mean test, with GO terms and Reactome pathways, p-value < 0.05). (H) Venn diagram showing overlap between proteins with altered phosphorylation in the Dabrafenib phosphoproteomics time course and those with altered thermal stability in TPP upon Dabrafenib treatment.
Article Snippet:
Techniques: Sequencing, Inhibition, Activity Assay, Gene Expression, Phospho-proteomics, Transcriptomics, Lysis
Journal: bioRxiv
Article Title: Multi-omics and biophysical phosphoproteomics upon BRAF inhibition uncover functional networks of BRAFV600E-driven signaling
doi: 10.64898/2026.02.09.704793
Figure Lengend Snippet: (A) Overview of network construction. Left: Input node preparation. Around 2500 phosphosites affected upon Dabrafenib treatment are stratified into four sets with different weights (abundance, solubility-abundance, localization-abundance, combined biophysical evidence). Transcription factors (TFs) and thermal proteome profiling (TPP) altered upon Dabrafenib treatment are included as additional nodes (∼2900 nodes total). Middle: Prior knowledge network (PKN) preparation comprising kinase-substrate interactions (weighted for measured kinase phosphorylation), protein-protein interactions, and phosphorylation evidence (∼13k edges). Right: Resulting directed multi-omic networks generated across different kinase weights and cost additions and input sets (∼252 networks total) with 1454 - 41 edges. Example network shown. (B) Fraction of nodes per input modality (phosphosites, TFs, TPP) or inferred kinases. Each point represents one network. Boxplots indicate mean, first and third quartiles. (C–D) Edge and node overlap coefficients across all networks for a given input set. Boxplots indicate mean, first and third quartiles. (E) Comparison of node degree centralities for networks without and with combined biophysical evidence weighting strategy. (F) Fraction of sites affected globally across cell lines in abundance-only, abundance-solubility, abundance-localization, or combined networks. (G) Fraction of nodes per input set (abundance, solubility, localization, combined) across different edge costs for sets of phosphosites reaching 20% of their maximum observed fold-change at different time points during Dabrafenib treatment. (H) Fraction of substrates with biophysical evidence for the top kinases in the network model coloured by overall network degree. Black line indicates 50%. (I) Temporal phosphorylation dynamics in the Dabrafenib time course data of TNIK coloured by direction of regulation (S570 and S678 upregulated, S795 downregulated). (J) Cell viability after 48 hours in COLO-201 and MNT-1 cells treated with Dabrafenib (100 nM) alone, TNIK-IN-3 alone (10 µM) or the combination (unpaired, two-sided t-test). The experiment was performed in three biological replicates (points), 56 data points were generated per replicate and condition (violin shape). Black lines indicate the mean.
Article Snippet:
Techniques: Solubility, Phospho-proteomics, Protein-Protein interactions, Generated, Comparison
Journal: bioRxiv
Article Title: Multi-omics and biophysical phosphoproteomics upon BRAF inhibition uncover functional networks of BRAFV600E-driven signaling
doi: 10.64898/2026.02.09.704793
Figure Lengend Snippet: (A) Number of sites across all network models, coloured by whether prior annotation on site function or an upstream kinase is available in literature. (B) Time-resolved predicted MYC transcription factor activity following Dabrafenib treatment in A2058 cells. (C) log₂ localization ratios for the MYC protein and phosphopeptides in A2058 cells. Significance was assessed using limma’s moderated t-test. Black lines indicate the mean. (D) log₂ solubility ratios for the MYC protein and phosphopeptides in A2058 cells. Significance was assessed using limma’s moderated t-test. Black lines indicate the mean. (E) Normalised scaled phosphorylation levels of ETV3 S139 and S29 across BRAFV600E-mutant cell lines (A2058, MNT-1, COLO-201) treated with Dabrafenib versus DMSO. Black lines indicate the mean. ETV3 dephosphorylation is significant in all cell lines (moderated t-test, adj. p-value < 0.05, exact p-values in Supplementary Table S2). (F) PCA of normalized phosphopeptides of three BRAFVE600E-mutant (red) and three other cell lines (grey). The PCA was calculated based on the top 10% most variable phosphopeptides across samples. (G) Volcano plot of differential phosphopeptide abundance in BRAFV600E-mutant (A2058, MNT-1, COLO-201) relative to cells without the mutation (HelaK, HEK293T, MDA-MB-231). Significantly upregulated (red) and downregulated (blue) phosphopeptides are highlighted (moderated t-test, adj. p-value < 0.05, |log₂ fold-change| > log₂(1.5) as indicated by dashed line). (H) Expression levels of phosphorylated ETV3 in steady state across all quantified sites, replicates and cell lines for BRAFV600E-mutant cells and cells without the mutation. Black lines indicate the mean. Significance was assessed using unpaired, two-sided t-test.
Article Snippet:
Techniques: Activity Assay, Solubility, Phospho-proteomics, Mutagenesis, De-Phosphorylation Assay, Expressing
Journal: bioRxiv
Article Title: Multi-omics and biophysical phosphoproteomics upon BRAF inhibition uncover functional networks of BRAFV600E-driven signaling
doi: 10.64898/2026.02.09.704793
Figure Lengend Snippet: (A) MAPK1-centred transcriptional subnetwork aggregated across all generated network models. Nodes represent transcription factors, kinases, and target proteins; edges show inferred regulatory relationships. Phosphosites with solubility or localization evidence are highlighted. ETV3 exhibits two MAPK1-regulated, potentially functional sites (S29 and S139). (B) Temporal phosphorylation dynamics of ETV3 following Dabrafenib treatment (100 nM, 4 h) in A2058 cells. Significance was assessed using limma’s moderated t-test. (C) Predicted transcription factor (TF) activity of ETV3 across three BRAFV600E-mutant cell lines (A2058, MNT-1, COLO-201). (D) log₂ solubility ratios for the average ETV3 protein and the S29 phosphoproteoform across six replicates. Significance was assessed using limma’s moderated t-test. (E) Thermal stability profiles for the S139 peptide (unmodified counterpart of the phosphopeptide) versus other ETV3 peptides. Significance was assessed using an unpaired, two-sided t-test. (F) Schematic of the ETV3 structure. Indicated are two prioritized phosphosites (S29 and S139) as well as the DNA binding domain (DBD) of ETV3 which is the only structured part of the protein. (G) log₂ ETV3 protein intensity in total or NP40-soluble lysis conditions for three replicates for DMSO and Dabrafenib (100 nM, 4 hours) treated cells. Significance was assessed with an unpaired, two-sided t-test. (H) log₂ ETV3 protein intensity in total, NP40-soluble and NP40-soluble combined with DNAse digestion lysis conditions for three replicates for Dabrafenib (100 nM, 4 hours) treated cells. Significance was assessed using limma’s moderated t-test.
Article Snippet:
Techniques: Generated, Solubility, Functional Assay, Phospho-proteomics, Activity Assay, Mutagenesis, Binding Assay, Lysis
Journal: bioRxiv
Article Title: Multi-omics and biophysical phosphoproteomics upon BRAF inhibition uncover functional networks of BRAFV600E-driven signaling
doi: 10.64898/2026.02.09.704793
Figure Lengend Snippet: (A) Validation of ETV3 knockdown using three independent siRNAs. All siRNAs efficiently reduce ETV3 protein levels compared with non-targeting control (ntctl). siETV3#2 was chosen for further experiments. Central lines indicate the mean. (B) Temporal profile of ETV3 protein abundance upon Dabrafenib treatment and knockdown in A2058 cells. After 24 hours of treatment, ETV3 expression cannot be detected anymore. Fit lines indicate mean protein intensities (loess fit). (C) Volcano plots of differential protein abundance in siETV3 and control A2058 cells at 0, 8, 24, and 48 hours of Dabrafenib treatment. Significantly upregulated (red) and downregulated (blue) phosphopeptides are highlighted (moderated t-test, adj. p-value < 0.05, |log₂ fold-change| > log₂(1.5) as indicated by dashed line). (D) Transcript expression changes of glucose transporters GLUT1 and GLUT3 across three BRAFV600E-mutant cell lines in response to Dabrafenib. (E) Heatmap of quantified metabolite levels in cellular supernatant of A208 cells after Dabrafenib treatment in control versus siETV3 A2058 cells. Central lines indicate the mean. (F) Cell viability after 48 hours in COLO-201 and MNT-1 cells treated with Dabrafenib (100 nM) alone, Telaglenastat (1 μM) alone or the combination (unpaired, two-sided t-test). The experiment was performed in three biological replicates (points), 56 data points were generated per replicate and condition (violin shape).Central lines indicate the mean. (G) Standardized scores indicating significant ETV3 single-nucleotide polymorphisms (SNPs) to phenotypes or diseases associations in the GWASdb. Colours show phenotype/disease group.
Article Snippet:
Techniques: Biomarker Discovery, Knockdown, Control, Quantitative Proteomics, Expressing, Mutagenesis, Generated