antibodies against cyclin a  (R&D Systems)

Journal: bioRxiv

Article Title: Targeting Distinct Cell Cycle Nodes Overcomes KRAS/RAS Inhibitor Resistance

doi: 10.64898/2026.03.10.710937

Figure Lengend Snippet: (A) GSEA analysis illustrating the differential effect of MRTX849 on the genes associated with E2F target pathway and the proteins associated with G2/M checkpoint in cell cycle machinery. (B) Heat map represents the differential effect of MRTX849 in downregulating the indicated genes and proteins that are involved in cell cycle from MiaPaCa-2-WT and MiaPaca-2-MR cells following 48-hour treatment. (C) Biochemical analysis on the indicated sensitive (WT) and resistance cell lines to compare the effect of MRTX849 on RB phosphorylation and cyclin A expression at different doses after treating the cells for 48 hours. (D) GSEA analysis highlighting pathways associated with genes and proteins that are differentially expressed between MiaPaCa-2-MR and MiaPaCa-2-WT cells. (E) Volcano plots of differentially expressed genes and proteins in MiaPaCa-2-MR versus MiaPaCa-2-WT cells. (F) Heat map illustrating the effects of indicated targeted therapeutic agents on normalized fold change in cell growth in combination with DMSO or mutant-selective KRAS inhibitors. (G) Synergistic interactions between KRAS inhibitors and erlotinib or AZD4547 in AsPC-1-MR, UM53, and MiaPaCa-2-MR cells. Heat maps depict normalized fold change in growth rate following treatment with increasing concentrations of KRAS inhibitors in combination with erlotinib or AZD4547. Bliss synergy scores were calculated using the SynergyFinder online platform.

Article Snippet: Antibodies against Cyclin A (Cat# AF5999) and β-actin (Cat# MAB8929) were purchased from R&D Systems (Minneapolis, MN).

Techniques: Phospho-proteomics, Expressing, Mutagenesis

Journal: bioRxiv

Article Title: Predictable clonal hierarchies from restricted progenitors provide a framework for cell type-specific therapies in glioblastoma

doi: 10.64898/2026.02.21.707071

Figure Lengend Snippet: Track-informed combination targeting of progenitor populations suppresses GBM growth a) LGALS1 expression across progenitor Tracks (left) and progenitor cell types (right) in the CellTag lineage-tracing dataset. b) FeaturePlot of LGALS1 expression in the GBM meta-atlas of primary tumor cells. c) Primary GBM meta-atlas cells were binned into LGALS1 -High (grey) and LGALS1 -Low (light blue) based on LGALS1 expression (STable6, Methods): cells were split by the median LGALS1 expression (High ≥ median, Low < median). Violin plot shows LGALS1 expression in each bin. Differential expression was then performed Low vs High (so positive avg_log2FC indicates genes enriched in LGALS1 -Low cells). Right, lollipop plot shows the top differentially expressed genes enriched in LGALS1-Low cells, highlighting CDK4 (dot size, −log10 adjusted P value; x-axis, avg_log2FC Low vs High). d) CDK4 expression across progenitor Tracks (left) and progenitor cell types (right) in the CellTag lineage-tracing dataset. e) FeaturePlot of CDK4 expression in the GBM meta-atlas of primary tumor cells. f) The combination of LGALS1 inhibition through OTX008 with CDK4 inhibition through Abemaciclib is predicted to target Track 3 progenitors (MES.Progenitor, NVP) and complementary Track 1-2 progenitors (IPC, Radial Glia). g) LGALS1 and CDK4 expression stratifies progenitor cells into complementary high-expression groups. (Top) Boxplots show LGALS1 and CDK4 expression in the CellTagging dataset comparing Progenitor vs Non-Progenitor cells. P-values are from two-sided Wilcoxon tests. (Bottom) Progenitor cells were additionally binned by global median splits of LGALS1 and CDK4 across all cells to define four mutually exclusive categories (Neither, LGALS1_high, CDK4_high, Both) and an OR category (Either_High = LGALS1_high OR CDK4_high). Lollipop plot reports the percent of progenitor cells in each category. h) Representative clones satisfying LGALS1_high or CDK4_high treatment categories across patients, as defined in panel g. Clone member cells are overlaid on the global UMAP (grey) and indicated by colored shapes, with each shape representing an individual cell within the clone. i) Representative clones multiple patients containing cells classified as Both (LGALS1_high and CDK4_high), as defined in panel g. j) Representative immunoblot of the patient-derived gliomasphere line GS187 treated for 7 days with Vehicle, Abemaciclib (CDK4/6 inhibitor), OTX008 (LGALS1 inhibitor), or the combination. Abemaciclib treatment reduced phosphorylation of RB at S780 (pRb) with corresponding effects on total RB, consistent with on-target CDK4/6 pathway inhibition. CCN2A and CDK4 levels are shown as additional markers in the CDK4/6 axis. OTX008 treatment targets LGALS1 and CYPB serves as a loading control. k) Quantification of immunoblot signals shown in panel 4j from GS187 gliomaspheres. Protein levels for pRB (S780), RB, CCN2A, CDK4, and LGALS1 were normalized to the loading control (CYPB) and expressed as fold change relative to Vehicle (dashed line at 1). l) Patient-derived gliomaspheres expressing a Gaussia luciferase construct are transplanted onto human cortical organoids, where tumor cells engraft and secrete luciferase into the surrounding media. Secreted luciferase activity in conditioned media provides a noninvasive readout of tumor cell burden over time. m) Schematic timeline of the treatment regimen used for growth assays in the HOTT system. Following a 7-day engraftment period, organoids transplanted with patient-derived gliomaspheres were treated with Vehicle, Abemaciclib, OTX008, or the combination of OTX008 and Abemaciclib. Conditioned media was collected every 48 hours for measurement of secreted Gaussia luciferase activity, with luminescence quantified to generate tumor growth curves. n) Patient-derived gliomasphere lines GS005 and GS025 (n = 2 independent lines) expressing Gaussia luciferase were transplanted onto human cortical organoids (n = 3 independent transplants per condition) and treated according to the scheme in . Conditioned media were collected every 48 hours and luciferase activity was normalized to the corresponding day 1 measurement for each transplant. Data are shown as mean ± s.d. across independent transplants. Statistical comparisons were performed between drug-treated and vehicle conditions at each time point.

Article Snippet: Membranes were incubated overnight with primary antibodies against pRb (S780; Cell Signaling Technology, 8180), Rb (Cell Signaling Technology, 9309), CCNA2 (Cell Signaling Technology, 4656), CDK4 (Cell Signaling Technology, 12790), CYPB (Cell Signaling Technology, 43603), and LGALS1 (Cell Signaling Technology, D608).

Techniques: Expressing, Quantitative Proteomics, Inhibition, Clone Assay, Western Blot, Derivative Assay, Phospho-proteomics, Control, Luciferase, Construct, Activity Assay

Journal: bioRxiv

Article Title: Predictable clonal hierarchies from restricted progenitors provide a framework for cell type-specific therapies in glioblastoma

doi: 10.64898/2026.02.21.707071

Figure Lengend Snippet: Identification of progenitor-associated drug targets with tumor-selective expression a) Strategy used to identify candidate therapeutic targets from lineage-informed progenitor programs. Progenitor signature genes (n = 1,855) were first defined from the CellTagging dataset based on differential expression between progenitor and non-progenitor malignant cells. These genes were queried against the Drug-Gene Interaction Database (DGIdb) to identify targets with known inhibitor interactions, yielding 326 druggable genes. Druggable candidates were then ranked by tumor selectivity using a composite score that integrates progenitor specificity from the CellTagging genescore together with relative expression in a primary GBM meta-atlas and depletion in a normal adult brain meta-atlas, enabling prioritization of progenitor targets with maximal therapeutic window. b) Scatter plot shows progenitor-associated druggable genes identified by querying the Drug-Gene Interaction Database (DGIdb) for inhibitor-linked interactions among progenitor signature genes. The x-axis shows the CellTagging progenitor genescore, a composite metric reflecting both specificity and enrichment in progenitor cells, calculated as the ratio of the fraction of progenitor cells expressing a gene to the fraction of non-progenitor cells expressing the gene, multiplied by the average log 2 fold change. The y-axis shows a tumor-normal score calculated as the difference between z-scored mean expression in a GBM meta-atlas and z-scored mean expression in a normal adult brain meta-atlas. Each point represents a gene. Genes with positive tumor-normal scores (red) are enriched in tumor relative to normal brain, whereas genes with negative scores (blue) show higher relative expression in normal tissue. c) Kaplan-Meier survival curves for proneural GBM patients in the TCGA dataset stratified by LGALS1 expression using a median cutoff. Patients with LGALS1 High tumors (red; n = 81, events = 77, median survival = 11.1 months) exhibit reduced overall survival compared to the LGALS1 Low group (blue; n = 81, events = 58, median survival = 19.8 months). Significance was assessed by log-rank test (p = 3e−04) and Wilcoxon test (p = 5e−04); hazard ratio (HR) = 0.53 (95% CI, 0.38-0.76). d) Volcano plot summarizing differential expression in the primary GBM meta-atlas comparing LGALS1-Low versus LGALS1-High cells. e) Differential expression in the primary GBM meta-atlas comparing LGALS1-Low vs LGALS1-High cells (Low vs High). Each point is a gene (x-axis, avg_log2FC Low vs High; y-axis, −log10 adjusted P value). Positive fold-change indicates genes enriched in LGALS1-Low cells; CDK4 is highlighted/labeled. Differential expression used a Wilcoxon test with min.pct = 0.5 and logFC threshold = 0.25. f) Representative immunoblots from two additional patient-derived gliomasphere lines (GS025 and GS225) treated for 7 days with Vehicle (DMSO), Abemaciclib (1 µM), OTX008 (2.5 µM), or the combination.

Article Snippet: Membranes were incubated overnight with primary antibodies against pRb (S780; Cell Signaling Technology, 8180), Rb (Cell Signaling Technology, 9309), CCNA2 (Cell Signaling Technology, 4656), CDK4 (Cell Signaling Technology, 12790), CYPB (Cell Signaling Technology, 43603), and LGALS1 (Cell Signaling Technology, D608).

Techniques: Expressing, Biomarker Discovery, Quantitative Proteomics, Labeling, Western Blot, Derivative Assay