Journal: Cell Communication and Signaling : CCS

Article Title: FOXM1 regulates platelet-induced anoikis resistance in pancreatic cancer cells

doi: 10.1186/s12964-025-02644-8

Figure Lengend Snippet: FOXM1 expression and the associated gene signature are upregulated in attached cells. A FOXM1 mRNA expression was significantly higher in attached (AT) versus low-attachment (LA) cultures in all tested cell lines except PA-TU-8988T cells. RPLP0 was used as a reference gene (BxPC-3: FC = 0.06 ± 0.005; Su.86.86: FC = 0.1 ± 0.032; IMIM-PC1: FC = 0.34 ± 0.021; CAPAN-1: FC = 0.28 ± 0.037; MIA Paca-2: FC = 0.34 ± 0.007; PANC-1: FC = 0.27 ± 0.007; PA-TU-8988 S: FC = 0.15 ± 0.009; PA-TU-8988T: FC = 0.83 ± 0.033). B Protein analysis and quantification of FOXM1 protein in attached and low-attachment cell cultures. GAPDH was used as a loading control. C Validation of RNA sequencing results of genes known to be regulated by FOXM1 in BxPC-3 cells using RT-qPCR. RPLP0 was used as a reference gene ( KIF20A : FC = 0.12 ± 0.04; KIF2C : FC = 0.05 ± 0.004; KIF4A : FC = 0.10 ± 0.008; CCNA2 : FC = 0.08 ± 0.012; CCNB2 : FC = 0.09 ± 0.006; CDC20 : FC = 0.06 ± 0.008; BIRC5 : FC = 0.08 ± 0.017; AURKB : FC = 0.07 ± 0.018). D Changes in the expression of FOXM1 mRNA (RPLP0 normalized) were correlated with the percentage of PI-positive (= dead) cells under low-attachment. Bars and error bars represent the mean values and the corresponding SEMs ( n = 3; * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, n.s. = non-significant).

Article Snippet: CAPAN-1 (ACC 244), MIA Paca-2 (ACC 733), PANC-1 (ACC 783), PA-TU-8988 S (ACC 204) and PA-TU-8988T (ACC 162) pancreatic cancer cells were obtained from the DSMZ.

Techniques: Expressing, Control, Biomarker Discovery, RNA Sequencing, Quantitative RT-PCR

Journal: bioRxiv

Article Title: Chemical proteomics decrypts the kinases that shape the dynamic human phosphoproteome

doi: 10.1101/2025.11.18.689017

Figure Lengend Snippet: DecryptM analysis of context-specific drug-perturbed phospho- proteomes at scale. (A) Schematic representation of the decryptM workflow used to measure 17 million dose- dependent phosphorylated peptidoform profiles in response to 133 kinase inhibitors in 5 cancer cell lines. (B) Heatmap summarizing the number of significant drug-perturbed peptidoforms across 665 decryptM experiments. Drugs were arranged by drug target class. Futibatinib (FGFRi) in A204 and Lapatinib (HERi) in A431 are highlighted with a turquoise box. (C) top panel: volcano plot summaries of the decryptM experiments marked in B. Each dot is a peptidoform dose-response curve. Colors denote different CurveCurator classifications (black: “up-” or “down-regulated”; dark gray: “not-regulated”, light gray: “unclear”). The yellow line represents CurveCurator’s relevance boundary (alpha=0.05, fc lim =0.45). Bottom right panel: Dose-response curves of one peptidoform of the transcription factor ETV3 highlighted in the volcano plots. Bottom right panel: Venn diagrams depicting the overlap of up- or down- regulated peptidoforms between both experiments. (D) Heatmap showing the degree of similarity (blue, top left triangle) and overlap (brown, bottom right triangle) between any pair of decryptM combinations. Hierarchical clustering was based on the degree of overlap. Prominent clusters are labeled by roman numerals and represent shared peptidoform perturbation signatures of common signaling axes. The decryptM comparison from panel C is indicated with an asterisk. The mathematical calculation of similarity and overlap is iconized on the left .

Article Snippet: A204 (DSMZ: #ACC-250, McCoy’s 5a medium, 10% v/v FBS), SK-ES-1 (DSMZ: #ACC 518, McCoy’s 5a medium, 15% v/v FBS), SK-LMS-1 (Hölzel: #CLS300125, DMEM:F12 medium, 2 mM L- glutamine, 5% v/v FBS), MES-SA (ATCC: #CRL-1976, McCoy’s 5a medium, 10% v/v FBS), A431 (ATCC: #CRL-1555, DMEM medium, 10% v/v FBS).

Techniques: Labeling, Comparison

Journal: bioRxiv

Article Title: Chemical proteomics decrypts the kinases that shape the dynamic human phosphoproteome

doi: 10.1101/2025.11.18.689017

Figure Lengend Snippet: Annotating the human phosphoproteome with potency-coherent and motif-plausible kinase::substrate relationships. (A) Potency coherence map akin to , but now correlating the activity change of a kinase group (here S6Ks) and one peptidoform (here RPS6_RLS(ph)S(ph)LRAS(ph)TSK) across all experiments (black dots). The inset shows the dose-response curve for this peptidoform in the Ridaforolimus-A204 experiment as an example (red dot in main panel). The vertical blue line indicates the estimated change in S6Ks activity from its seed peptidoforms in this experiment. (B) Volcano plot summarizing all 19,084 potency coherence maps for S6Ks::peptidoform combinations and highlighting several examples, including the map shown in A. Vertical dashed lines mark the chosen threshold of i corr >0.8, and the horizontal line marks the p- value adj. <0.05 threshold. (C) Volcano plot akin to B, but this time asking which of the 44 kinase groups best explains the potencies of a peptidoform. The inset shows the canonical PI3K/AKTs/MTOR/S6Ks pathway. The pathway hierarchy is reflected in the volcano plot through decreasing order of statistical significance, as several upstream inhibitors of S6Ks were used. (D) t-SNE projection of all confident (potency-coherence and motif-plausible) kinase::substrate relationships colored by kinase groups. The inset quantifies the gains and losses in kinase::substrate relationships relative to PSP resulting from the data analysis presented in this work .

Article Snippet: A204 (DSMZ: #ACC-250, McCoy’s 5a medium, 10% v/v FBS), SK-ES-1 (DSMZ: #ACC 518, McCoy’s 5a medium, 15% v/v FBS), SK-LMS-1 (Hölzel: #CLS300125, DMEM:F12 medium, 2 mM L- glutamine, 5% v/v FBS), MES-SA (ATCC: #CRL-1976, McCoy’s 5a medium, 10% v/v FBS), A431 (ATCC: #CRL-1555, DMEM medium, 10% v/v FBS).

Techniques: Activity Assay

Journal: bioRxiv

Article Title: Chemical proteomics decrypts the kinases that shape the dynamic human phosphoproteome

doi: 10.1101/2025.11.18.689017

Figure Lengend Snippet: Potency coherence connects genotypes to proteotypes to phenotypes. (A) Schematic representation of relating genotype (alteration data from DepMap Portal: AMP=amplification, MUT=mutation, DEL=deletion, and FUS=fusion), proteotype (decryptM: data from this study), and phenotype (viability data from Lee et al.) for five cell lines and using the ERK and MTOR axes as examples. Receptor to transducer kinase connectivity (red dotted arrow) was determined by potency-coherent perturbation patterns of the most upstream kinase (e.g. see CurveCurator dashboards for EGFR:Afatinib, FGFR:Futibatinib, PDGFR:Lenvatinib, MET:Tepotinib, IGFR:Linsitinib). The extent of kinase activity perturbation in each cell line (colored bars) is depicted by the number (and percentage of total) of confident ERK and MTOR substrates that were down-regulated (red), not-regulated (gray, barely visible), or absent/unclear (white). For phenotypic (cell viability) measurements, Trametinib was used as an ERK-axis proxy and Rapamycin as an MTOR-axis proxy. (B) Cell viability dose-response curves for Pemigatinib, Trametinib, Ponatinib, Lenvatinib, and Copanlisib in A204. Black bold arrows at the back plateaus indicate the contribution of each axis alone & or combined (1x2) to cell growth inhibition. The simplified pathway in the inset depicts the inhibitors, their targets, and kinase connectivity in A204. (C) Swarm plots showing growth inhibition of SKES1 and RDES in response to 144 inhibitors, notably insensitivity to Trametinib (MEKi; left panel) but hypersensitivity to Dinaciclib (CDK9i) and Dactinomycin (RNAPoli; right panel) .

Article Snippet: A204 (DSMZ: #ACC-250, McCoy’s 5a medium, 10% v/v FBS), SK-ES-1 (DSMZ: #ACC 518, McCoy’s 5a medium, 15% v/v FBS), SK-LMS-1 (Hölzel: #CLS300125, DMEM:F12 medium, 2 mM L- glutamine, 5% v/v FBS), MES-SA (ATCC: #CRL-1976, McCoy’s 5a medium, 10% v/v FBS), A431 (ATCC: #CRL-1555, DMEM medium, 10% v/v FBS).

Techniques: Amplification, Mutagenesis, Activity Assay, Inhibition