Journal: bioRxiv

Article Title: Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

doi: 10.64898/2025.12.01.691211

Figure Lengend Snippet: (A, B, and C) For each PDO model, the left panels show bright-field micrographs of 3D organoid cultures (“Bright Field”), the middle panels show histological images of the corresponding patient tumor section (“Tumor”), and the right panels show histology of the PDO model (“Organoid”). (A) Well-differentiated PDAC samples. (B) Moderately differentiated PDAC samples. (C) Poorly differentiated PDAC samples. (D) Representative fluorescence images of the PANC-03 organoid model stained with fluorescently labeled antibodies for cell-cell adhesion protein E-cadherin (green) and epithelial cell marker EpCAM (red), with DAPI nuclear counterstain. (E) The same analysis applies to the PANC-13 PDO line. The arrows indicate cells displaying scattered cytoplasmic or patchy membrane staining.

Article Snippet: To our knowledge, this represents the first application of the full Targetmol library in PDAC PDOs, providing an unbiased, broad pharmacologic landscape of pancreatic tumor vulnerabilities.

Techniques: Fluorescence, Staining, Labeling, Marker, Membrane

Journal: bioRxiv

Article Title: Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

doi: 10.64898/2025.12.01.691211

Figure Lengend Snippet: (A) Bar plots showing, for each individual PDAC case, the percentage of mutated genes found exclusively in the tumor (T), exclusively in the matching PDO model (O), or in both (shared, S). (B) Scatter plots of variant allele frequencies for each somatic mutation detected in an individual PDAC tumor versus matching mutations in the matched PDO model. Each point represents one variant; the close correlation (points near the diagonal) indicates that PDOs retain the mutational spectrum of the original tumors. (C) Heatmap displaying the mutational landscape of core PDAC driver genes across the PDO cohort. The conserved driver mutation signatures reinforce the genomic fidelity of PDOs and support their use as functional avatars for pharmacologic interrogation.

Article Snippet: To our knowledge, this represents the first application of the full Targetmol library in PDAC PDOs, providing an unbiased, broad pharmacologic landscape of pancreatic tumor vulnerabilities.

Techniques: Variant Assay, Mutagenesis, Functional Assay

Journal: bioRxiv

Article Title: Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

doi: 10.64898/2025.12.01.691211

Figure Lengend Snippet: (A) Schematic overview of the organoid-based drug screening strategy. Patient-derived organoids (PDOs) were exposed to a library of 1,813 clinically approved small molecules. Viability was measured after 7 days of treatment to identify compounds that preferentially suppressed growth of individual organoid models. (B) Confocal imaging of PDO spheroid formation in 384-well format. Representative confocal DAPI-stained z-stack images (5-µm intervals) demonstrate that pancreatic PDOs form uniform, lumen-containing epithelial spheres under miniaturized screening conditions. Nuclear organization and spheroid morphology remain intact across the full z-axis, confirming that PDO structural integrity is preserved during high-throughput assay plating. Numbers represent the sequence of z-axis images. (C) Images show the stainless-steel pin-tool array used for nanoliter-scale compound transfer into 384-well PDO plates. The system deposits 200 nL of each drug with high positional accuracy, enabling reproducible and cost-efficient screening of 1,813 compounds in parallel. Insets illustrate the pin geometry and contact-based delivery mechanism. (D) Drug sensitivity profiles for each PDO model based on normalized B-scores. Each dot represents a single compound; the major drug families among the top hits are highlighted: proteasome inhibitors (green), microtubule poisons (blue), topoisomerase inhibitors (red), epigenetic modulators (purple), and cardiac glycosides (brown). Compounds with more negative B-scores exhibit higher cytotoxicity than those with a full drug distribution. The two dotted horizontal lines denote statistical thresholds used to identify outlier compounds. Points below these cutoffs represent drugs with responses that exceed expected assay variability and are considered significant hits.

Article Snippet: To our knowledge, this represents the first application of the full Targetmol library in PDAC PDOs, providing an unbiased, broad pharmacologic landscape of pancreatic tumor vulnerabilities.

Techniques: Drug discovery, Derivative Assay, Imaging, Staining, High Throughput Screening Assay, Sequencing

Journal: bioRxiv

Article Title: Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

doi: 10.64898/2025.12.01.691211

Figure Lengend Snippet: (A) Enrichment analysis of drugs’ sensitivities by pharmacologic class combined for all tested PDO models. Drug families were ranked by weighted enrichment ratio (bars, left y-axis), with statistical significance indicated by the −log10(p-value) (line, right y-axis). Proteasome inhibitors, epigenetic modulators, microtubule poisons, cardiac glycosides, and topoisomerase inhibitors emerged as the most enriched classes across the PDO cohort. The dashed horizontal line denotes the neutral enrichment threshold (WER = 1.0), corresponding to the expected frequency of hits if compounds were randomly distributed across drug families. Drug classes exceeding this threshold are considered significantly enriched for high-activity compounds, indicating preferential sensitivity in the PDO cohort. Classes falling below the line show no enrichment. (B) Radar plot summarizing mean sensitivity across drug families for all ten PDO models. Each line represents one model, colored by model ID. Axes correspond to drug-family categories, and radial distance from the center reflects the normalized mean B-score for all compounds within that family, where higher values indicate greater sensitivity and values near the center indicate lower or minimal activity. Classes with the largest outward displacement, such as proteasome inhibitors, epigenetic modulators, and cardiac glycosides, represent drug families with the strongest shared activity across PDOs. In contrast, inward-pointing values reflect variable or limited sensitivity. (C) A drug–PDO interaction network generated using Cytoscape connecting each of the ten pancreatic ductal adenocarcinoma (PDAC) organoid models to their top five most active compounds, grouped by pharmacologic classes. Nodes are colored based on organoid differentiation state: well-differentiated (green), moderately differentiated (blue), and poorly differentiated (red). Drug nodes are labeled and clustered by functional class: proteasome inhibitors, epigenetic modulators, topoisomerase inhibitors, microtubule poisons, and cardiac glycosides. This visualization demonstrates that proteasome inhibitors exhibit broad activity across all PDOs, whereas topoisomerase inhibitors and microtubule poisons are more strongly associated with well-differentiated models (PANC-03, PANC-06). Moderately differentiated PDOs (e.g., PANC-04, PANC-15, PANC-17) are enriched for epigenetic modulators, while poorly differentiated PDOs (PANC-13, PANC-14) uniquely associate with cardiac glycosides. These patterns illustrate how histologic differentiation correlates with specific drug class sensitivities. (D) Volcano plot illustrating differential drug responses between classical (n=7) and basal (n=3) PDOs. For each compound, the x-axis shows the difference in mean B-scores (ΔB = mean(classical) – mean(basal), where negative values (blue) indicate preferential cytotoxicity in classical PDOs and positive values (red) indicate stronger cytotoxicity in basal PDOs. The y-axis represents –log10(p-value) from Welch’s t-test. Dashed lines denote ΔB = 0 and p = 0.05. This representation captures the broad asymmetry in response patterns and visually separates compounds with preferential activity toward classical versus basal PDO models.

Article Snippet: To our knowledge, this represents the first application of the full Targetmol library in PDAC PDOs, providing an unbiased, broad pharmacologic landscape of pancreatic tumor vulnerabilities.

Techniques: Activity Assay, Generated, Labeling, Functional Assay

Journal: bioRxiv

Article Title: Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

doi: 10.64898/2025.12.01.691211

Figure Lengend Snippet: Bubble plot showing relative drug sensitivity of each PDO model to a panel of 12 clinically relevant agents, including standard chemotherapies (e.g., gemcitabine, paclitaxel, irinotecan), targeted agents (e.g., PARP inhibitors, trametinib, erlotinib), and repurposed compounds (e.g., cardiac glycosides). Each column represents individual drugs, and each row corresponds to a PDO model. The size of each bubble reflects the magnitude of the response, and the color indicates the response classification: green (sensitive), yellow (intermediate), or red (resistant), based on normalized B-score thresholds. While several PDOs showed broad sensitivity to agents like paclitaxel and gemcitabine, others exhibited selective resistance, highlighting intertumoral heterogeneity and the potential clinical value of PDO-guided therapy prioritization.

Article Snippet: To our knowledge, this represents the first application of the full Targetmol library in PDAC PDOs, providing an unbiased, broad pharmacologic landscape of pancreatic tumor vulnerabilities.

Techniques:

Journal: bioRxiv

Article Title: Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

doi: 10.64898/2025.12.01.691211

Figure Lengend Snippet: (A) Heatmaps showing mutations in genes associated with DNA repair and replication stress (left), microtubule structure and mitotic regulation (upper middle), and chromatin remodeling/epigenetic control (lower middle) across ten PDO models. Columns are grouped by classical PDOs shown on the left (green/blue) and basal PDOs on the right (red). Dark squares indicate detected somatic mutations; light squares indicate wild-type status; gray shading demarcates subtype groupings. (B) Heatmaps illustrating mutations in genes involved in mitochondrial function and lipid/sterol metabolism (green), vesicle trafficking and Golgi/endo-lysosomal machinery (red), and ubiquitin–proteasome/ERAD/ligase and deubiquitinase pathways (blue).

Article Snippet: To our knowledge, this represents the first application of the full Targetmol library in PDAC PDOs, providing an unbiased, broad pharmacologic landscape of pancreatic tumor vulnerabilities.

Techniques: Control, Ubiquitin Proteomics

Journal: bioRxiv

Article Title: Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

doi: 10.64898/2025.12.01.691211

Figure Lengend Snippet: Heatmaps displaying the presence or absence of somatic mutations across multiple DNA repair and chromatin-remodeling pathways in all ten PDAC PDO models. Each column represents a PDO, and each row corresponds to a gene within a specific functional category. Dark squares indicate detected mutations; pale squares indicate wild-type status.

Article Snippet: To our knowledge, this represents the first application of the full Targetmol library in PDAC PDOs, providing an unbiased, broad pharmacologic landscape of pancreatic tumor vulnerabilities.

Techniques: Functional Assay

Journal: Neural Regeneration Research

Article Title: Hypoxia-preconditioned bone marrow–derived mesenchymal stem cells protect neurons from cardiac arrest–induced pyroptosis

doi: 10.4103/NRR.NRR-D-23-01922

Figure Lengend Snippet: PFKL mediates the neuroprotective and antioxidant effects of HP-BMSCs in CPR rats. (A) Neurological deficit scores (NDS) in four group (CPR + PBS, CPR + HP-BMSCs, CPR + si NC HP-BMSCs, CPR + si-PFKL HP-BMSCs, n = 8). The black line represents the NDS levels in the sham group. (B) Serum S100B levels after treatment as indicated ( n = 8). (C) Nissl staining of rat brains after CPR in different group (sham, CPR + PBS, CPR + HP-BMSCs, CPR + si NC HP-BMSCs, CPR + si-PFKL HP-BMSCs, n = 8). After 24 hours of resuscitation, the number of Nissl bodies in the rat cortex significantly decreased, and transplantation of HP-BMSCs could alleviate the reduction of Nissl bodies. However, this effect of HP-BMSCs was reversed after knocking down PFKL. Scale bars: 100 μm (upper) or 50 μm (lower). (D) The AOD of cortical neurons by Nissl staining. (E, F) Representative immunohistochemical staining of 4-HNE (E) and 8-OHdG (F) in cortex following ROSC. After transplantation of HP-BMSCs, the expression of 4-HNE and 8-OHdG in the cortex of CA/CPR rats significantly decreased, whereas this effect was attenuated after knocking down PFKL. The selected areas (black frame) were displayed at a higher magnification level. Scale bars: 70 μm (upper) or 50 μm (lower). (G, H) Percentage of 4-HNE-positive cells (G) and 8-OHdG-positive cells (H) in immunohistochemical images ( n = 8). (I–K) Histograms show the expression of SOD (I), GSH-Px (J) and MDA (K). n = 6 rats per group. (L) Representative images show iNOS (green, Alexa Fluor 488) immunostaining with NeuN (red, CY3) and DAPI (blue) in the cotex ( n = 8). The white boxed areas are shown magnified. HP-BMSCs significantly reduced the expression of iNOS in the neurons of CA-induced rats, while knocking down the expression of PFKL in HP-BMSCs did not lead to significant changes in the expression of iNOS. Scale bars: 50 μm (lower) or 1000 μm (upper). (M) Percentage of iNOS-positive neurons in immunofluorescence images. (N) ROS generation in cortex post-resuscitation was assayed by ROS assay kit. Compared with the si-NC HP-BMSCs group, the reduction effect of si-PFKL HP-BMSCs on post-resuscitation cortical ROS is significantly weakened. The fluorescence was detected by the fluorescence microplate reader ( n = 3). Scale bars: 100 μm. (O) The fluorescent intensity of ROS shown in N. Results expressed as median and interquartile range (A and D) or means ± SD (G–K, M and O). * P < 0.05, vs . sham group; # P < 0.05, vs . CPR + PBS group; & P < 0.05, vs . CPR + si-NC-BMSCs group (Kruskal–Wallis test followed by Dunn’s multiple comparisons test in A and D; one-way analysis of variance followed by Tukey’s multiple comparisons test in G–K, M and O). 4-HNE: 4-Hydroxynonenal; 8-OHdG: 8-hydroxy-2′-deoxyguanosine; AOD: average optical density; CPR: cardiopulmonary resuscitation; HP-BMSCs: hypoxia preconditioned bone marrow mesenchymal stem cells; iNOS: inducible nitric oxide synthase; MDA: malondialdehyde; PBS: phosphate-buffered saline; PFKL: liver isoform of phosphofructokinase; ROI: region of interest; ROS: reactive oxygen species; ROSC: return of spontaneous circulation; SOD: superoxide dismutase.

Article Snippet: For the second experiment, the cells were divided into five groups that were left untreated or treated with siRNAs, left untreated or treated with 10 μM mitochondria-targeted antioxidant (Mito-TEMPO, TargetMol, Shanghai.

Techniques: Staining, Transplantation Assay, Immunohistochemical staining, Expressing, Immunostaining, Immunofluorescence, ROS Assay, Fluorescence, Analysis, Saline, Immunohistochemistry, Knockdown

Journal: Viruses

Article Title: Targeting Human Proteins for Antiviral Drug Discovery and Repurposing Efforts: A Focus on Protein Kinases

doi: 10.3390/v15020568

Figure Lengend Snippet: Important antiviral kinase inhibitors reported in the biomedical literature.

Article Snippet: FDA- Approved Anticancer Drug, AstraZeneca, 2015.

Techniques: Virus, Activity Assay, Reverse Transcription, DNA Synthesis, Infection

Journal: Viruses

Article Title: Targeting Human Proteins for Antiviral Drug Discovery and Repurposing Efforts: A Focus on Protein Kinases

doi: 10.3390/v15020568

Figure Lengend Snippet: Important antiviral kinase inhibitors reported in the biomedical literature.

Article Snippet: FDA- Approved Anticancer Drug, Genentech, 2004.

Techniques: Virus, Activity Assay, Reverse Transcription, DNA Synthesis, Infection

Journal: Viruses

Article Title: Targeting Human Proteins for Antiviral Drug Discovery and Repurposing Efforts: A Focus on Protein Kinases

doi: 10.3390/v15020568

Figure Lengend Snippet: Important antiviral kinase inhibitors reported in the biomedical literature.

Article Snippet: FDA- Approved Anticancer Drug, Ariad, 2012.

Techniques: Virus, Activity Assay, Reverse Transcription, DNA Synthesis, Infection