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recombinant human gdf15 protein  (R&D Systems)


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    Structured Review

    R&D Systems recombinant human gdf15 protein
    Recombinant Human Gdf15 Protein, supplied by R&D Systems, used in various techniques. Bioz Stars score: 95/100, based on 51 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/recombinant+human+gdf+15/Recombinant+Human+GDF-15+Protein%2C+CF/pm41713960-30-0-5
    Average 95 stars, based on 51 article reviews
    recombinant human gdf15 protein - by Bioz Stars, 2026-09
    95/100 stars

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    Recombinant:

    Article Title: Growth Differentiation Factor 15 Protects SH-SY5Y Cells From Rotenone-Induced Toxicity by Suppressing Mitochondrial Apoptosis
    Article Snippet: .. Next, cells were treated with vehicle, rotenone (1 μM), and 0–100 ng/ml recombinant human GDF-15 (57-GD-025, R&D Systems, United States). .. Cell viability was detected using a Cell Counting Kit (CCK) 8 assay (A311-02, Vazyme, Nanjing, China).

    Article Title: Deficiency of liver sinusoidal scavenger receptors stabilin-1 and -2 in mice causes glomerulofibrotic nephropathy via impaired hepatic clearance of noxious blood factors
    Article Snippet: .. A total of 5 μg recombinant human GDF-15 (carrier free variant; R&D Systems) in 200 μl PBS was injected intravenously in age-matched 12- to 15-week-old Balb/c WT and Balb/c Stab1 –/– Stab2 –/– mice. ..

    Article Title: GDF-15 contributes to proliferation and immune escape of malignant gliomas.
    Article Snippet: The color reaction was stopped by the addition of 1 mol/L H2SO4, and absorbance was recorded in an ELISA reader (Tecan) at 450 nm. .. Using recombinant human GDF-15 as standard (R&D Systems), the assay was linear for GDF-15 concentrations between 0.1 ng/mL and 4 ng/mL. ..

    Article Title: Growth Differentiation Factor 15 Protects SH-SY5Y Cells From Rotenone-Induced Toxicity by Suppressing Mitochondrial Apoptosis.
    Article Snippet: .. Next, cells were treated with vehicle, rotenone (1 μM), and 0–100 ng/ml recombinant human GDF-15 (57-GD-025, R&D Systems, United States). .. Cell viability was detected using a Cell Counting Kit (CCK) 8 assay (A311-02, Vazyme, Nanjing, China).

    Article Title: GDF15 serves as a coactivator to enhance KISS-1 gene transcription through interacting with Sp1.
    Article Snippet: Ac ce pte d M an us cri pt © The Author(s) 2020.. Published by Oxford University Press.. All rights reserved.

    Article Title: Effect of growth differentiation factor-15 secreted by human umbilical cord blood-derived mesenchymal stem cells on amyloid beta levels in in vitro and in vivo models of Alzheimer's disease.
    Article Snippet: Alzheimer's disease (AD), which is the most common progressive neurodegenerative disease, causes learning and memory impairment.. The pathological progress of AD can derive from imbalanced homeostasis of amyloid beta (Ab) in the brain.. In such cases, microglia play important roles in regulating the brain Ab levels.

    Variant Assay:

    Article Title: Deficiency of liver sinusoidal scavenger receptors stabilin-1 and -2 in mice causes glomerulofibrotic nephropathy via impaired hepatic clearance of noxious blood factors
    Article Snippet: .. A total of 5 μg recombinant human GDF-15 (carrier free variant; R&D Systems) in 200 μl PBS was injected intravenously in age-matched 12- to 15-week-old Balb/c WT and Balb/c Stab1 –/– Stab2 –/– mice. ..

    Injection:

    Article Title: Deficiency of liver sinusoidal scavenger receptors stabilin-1 and -2 in mice causes glomerulofibrotic nephropathy via impaired hepatic clearance of noxious blood factors
    Article Snippet: .. A total of 5 μg recombinant human GDF-15 (carrier free variant; R&D Systems) in 200 μl PBS was injected intravenously in age-matched 12- to 15-week-old Balb/c WT and Balb/c Stab1 –/– Stab2 –/– mice. ..



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    a. Cryo-EM structure of the extracellular <t>GDF15–GFRAL–RET</t> complex (PDB: 6Q2J) showing a 2:2:2 stoichiometry, wherein the dimeric GDF15 bridges two GFRAL co-receptors and two RET receptors. b. Binding interfaces of GDF15 with GFRAL (top) and RET (bottom). Key interacting residues are shown as sticks. Hydrophobic hotspot residues used for binder design are highlighted in pink. c. Target sites for GDF15 binder design. The convex surface engaging GFRAL (site A, red) and the concave surface contacting RET (site B, light blue) are highlighted. Insets show electrostatic surface potentials of each site (white, hydrophobic; blue, positive charge; red, negative charge). d. Workflow of binder design using three scaffold generation strategies: Scaffold Grafting (SG), Diffusion-based de novo Design, and Scaffold-Search and Grafting (SSG).
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    a. Cryo-EM structure of the extracellular <t>GDF15–GFRAL–RET</t> complex (PDB: 6Q2J) showing a 2:2:2 stoichiometry, wherein the dimeric GDF15 bridges two GFRAL co-receptors and two RET receptors. b. Binding interfaces of GDF15 with GFRAL (top) and RET (bottom). Key interacting residues are shown as sticks. Hydrophobic hotspot residues used for binder design are highlighted in pink. c. Target sites for GDF15 binder design. The convex surface engaging GFRAL (site A, red) and the concave surface contacting RET (site B, light blue) are highlighted. Insets show electrostatic surface potentials of each site (white, hydrophobic; blue, positive charge; red, negative charge). d. Workflow of binder design using three scaffold generation strategies: Scaffold Grafting (SG), Diffusion-based de novo Design, and Scaffold-Search and Grafting (SSG).
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    a. Cryo-EM structure of the extracellular <t>GDF15–GFRAL–RET</t> complex (PDB: 6Q2J) showing a 2:2:2 stoichiometry, wherein the dimeric GDF15 bridges two GFRAL co-receptors and two RET receptors. b. Binding interfaces of GDF15 with GFRAL (top) and RET (bottom). Key interacting residues are shown as sticks. Hydrophobic hotspot residues used for binder design are highlighted in pink. c. Target sites for GDF15 binder design. The convex surface engaging GFRAL (site A, red) and the concave surface contacting RET (site B, light blue) are highlighted. Insets show electrostatic surface potentials of each site (white, hydrophobic; blue, positive charge; red, negative charge). d. Workflow of binder design using three scaffold generation strategies: Scaffold Grafting (SG), Diffusion-based de novo Design, and Scaffold-Search and Grafting (SSG).
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    Functional enrichment analysis of the GDF subfamily. A Proteins related to the GDF subfamily. B – E GO/KEGG analysis of related proteins. F Differential genes between patients with high and low <t>GDF15</t> expression. G – H GO/KEGG enrichment of upregulated genes in patients with high GDF15 expression. I , J GO/KEGG enrichment of upregulated genes in patients with low GDF15 expression. K , M GDF15 expression and GSEA enrichment analysis. (N-R) Correlation of GDF15 expression with cancer-related pathways
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    a. Cryo-EM structure of the extracellular GDF15–GFRAL–RET complex (PDB: 6Q2J) showing a 2:2:2 stoichiometry, wherein the dimeric GDF15 bridges two GFRAL co-receptors and two RET receptors. b. Binding interfaces of GDF15 with GFRAL (top) and RET (bottom). Key interacting residues are shown as sticks. Hydrophobic hotspot residues used for binder design are highlighted in pink. c. Target sites for GDF15 binder design. The convex surface engaging GFRAL (site A, red) and the concave surface contacting RET (site B, light blue) are highlighted. Insets show electrostatic surface potentials of each site (white, hydrophobic; blue, positive charge; red, negative charge). d. Workflow of binder design using three scaffold generation strategies: Scaffold Grafting (SG), Diffusion-based de novo Design, and Scaffold-Search and Grafting (SSG).

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. Cryo-EM structure of the extracellular GDF15–GFRAL–RET complex (PDB: 6Q2J) showing a 2:2:2 stoichiometry, wherein the dimeric GDF15 bridges two GFRAL co-receptors and two RET receptors. b. Binding interfaces of GDF15 with GFRAL (top) and RET (bottom). Key interacting residues are shown as sticks. Hydrophobic hotspot residues used for binder design are highlighted in pink. c. Target sites for GDF15 binder design. The convex surface engaging GFRAL (site A, red) and the concave surface contacting RET (site B, light blue) are highlighted. Insets show electrostatic surface potentials of each site (white, hydrophobic; blue, positive charge; red, negative charge). d. Workflow of binder design using three scaffold generation strategies: Scaffold Grafting (SG), Diffusion-based de novo Design, and Scaffold-Search and Grafting (SSG).

    Article Snippet: Recombinant human or mouse GDF15 (#9279-GD or #8944-GD, R&D Systems) was prepared at a stock concentration of 250 μg/mL and subsequently diluted in pooled human serum (Sigma #H6914) or mouse serum (Abbkine #BMS0070), resulting in a final concentration of up to 5 μg/mL (≤500 nM).

    Techniques: Cryo-EM Sample Prep, Binding Assay, Diffusion-based Assay

    a. Workflow of binder design via scaffold grafting. The GFRAL D2 domain was extracted as the initial scaffold to generate SG A 1 and SG A 2. SG A 2 was further optimized by scaffold-guided partial diffusion, resulting in five variants (SG A 2-1 to SG A 2-5). b. Extracted GFRAL D2 scaffold (residues 129∼211) from the GFRAL extracellular domain. The N- and C-termini, helices, and disulfide bonds are indicated. c. Backbone RMSD distribution of 100 ProteinMPNN-designed variants relative to the parental GFRAL D2 scaffold (mean RMSD = 0.85 Å). d. Structural alignment of the initial scaffold GFRAL D2 with SG A 1 (left) and SG A 2 (right). RMSD with AF3-predicted structure and AF3 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated, with the N- and C-termini labeled. e. Structural comparison of GFRAL-D2, SG A 1, and SG A 2 at the binding interface. Residues that enhance binding, commonly observed in both SG A 1 and SG A 2, are indicated. The rightmost panel shows the superposition of three scaffolds, highlighting α5 displacement. f. Superposition of SG A 1 and SG A 2, showing a unique electrostatic interaction in SG A 2. g. Structural alignment of SG A 2 with its partial diffusion-derived variants. RMSD with AF2-predicted structure and AF2 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated, with the N- and C-termini labeled. h. Backbone RMSD distribution of partial diffusion–derived variants relative to the SG A 2 scaffold (mean RMSD = 4.6 Å). i. Structural model of SG A 2-4 at the binding interface. Conserved binding residues in α5 (D69, Q72, L73, Q76), retained in SG A 2-4 variants compared to SG A 2, are highlighted. j. Binding interface comparison of SG A 2 and SG A 2-4, highlighting the shifted α1 position and distinct interacting residues on this helix.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. Workflow of binder design via scaffold grafting. The GFRAL D2 domain was extracted as the initial scaffold to generate SG A 1 and SG A 2. SG A 2 was further optimized by scaffold-guided partial diffusion, resulting in five variants (SG A 2-1 to SG A 2-5). b. Extracted GFRAL D2 scaffold (residues 129∼211) from the GFRAL extracellular domain. The N- and C-termini, helices, and disulfide bonds are indicated. c. Backbone RMSD distribution of 100 ProteinMPNN-designed variants relative to the parental GFRAL D2 scaffold (mean RMSD = 0.85 Å). d. Structural alignment of the initial scaffold GFRAL D2 with SG A 1 (left) and SG A 2 (right). RMSD with AF3-predicted structure and AF3 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated, with the N- and C-termini labeled. e. Structural comparison of GFRAL-D2, SG A 1, and SG A 2 at the binding interface. Residues that enhance binding, commonly observed in both SG A 1 and SG A 2, are indicated. The rightmost panel shows the superposition of three scaffolds, highlighting α5 displacement. f. Superposition of SG A 1 and SG A 2, showing a unique electrostatic interaction in SG A 2. g. Structural alignment of SG A 2 with its partial diffusion-derived variants. RMSD with AF2-predicted structure and AF2 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated, with the N- and C-termini labeled. h. Backbone RMSD distribution of partial diffusion–derived variants relative to the SG A 2 scaffold (mean RMSD = 4.6 Å). i. Structural model of SG A 2-4 at the binding interface. Conserved binding residues in α5 (D69, Q72, L73, Q76), retained in SG A 2-4 variants compared to SG A 2, are highlighted. j. Binding interface comparison of SG A 2 and SG A 2-4, highlighting the shifted α1 position and distinct interacting residues on this helix.

    Article Snippet: Recombinant human or mouse GDF15 (#9279-GD or #8944-GD, R&D Systems) was prepared at a stock concentration of 250 μg/mL and subsequently diluted in pooled human serum (Sigma #H6914) or mouse serum (Abbkine #BMS0070), resulting in a final concentration of up to 5 μg/mL (≤500 nM).

    Techniques: Diffusion-based Assay, Labeling, Comparison, Binding Assay, Derivative Assay

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet:

    Article Snippet: Recombinant human or mouse GDF15 (#9279-GD or #8944-GD, R&D Systems) was prepared at a stock concentration of 250 μg/mL and subsequently diluted in pooled human serum (Sigma #H6914) or mouse serum (Abbkine #BMS0070), resulting in a final concentration of up to 5 μg/mL (≤500 nM).

    Techniques: Binding Assay

    a. Workflow of de novo binder design using RF diffusion. A total of 1,728 initial scaffolds (50∼90 a.a) were generated, sequence-designed (three sequences per each backbone), and computationally filtered using in silico evaluation metrics. The top five binders (DE A 1–DE A 5) were structurally analyzed and experimentally validated by expression, purification, and binding analysis. The best-performing DE A 3 was further optimized by scaffold-guided partial diffusion, resulting in seven variants (DE A 3-1 to DE A 3-7). b. Distribution of helix counts in RFdiffusion-generated scaffolds to analyze structural diversity. c. AF2-predicted structural models of the five selected de novo binder candidates in complex with the GDF15 dimer. Binder lengths, pAE_interaction, and pLDDT values are indicated, with the N- and C-termini labeled. d. SDS-PAGE analysis of binders (DE A 1–5, left; DE A 3-1 to DE A 3-7, right) after E. coli expression and affinity purification. e. Binding interface comparison of DE A 3 (left) and DE A 3-5 (right) with GDF15. Key interacting residues are shown as sticks and labeled.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. Workflow of de novo binder design using RF diffusion. A total of 1,728 initial scaffolds (50∼90 a.a) were generated, sequence-designed (three sequences per each backbone), and computationally filtered using in silico evaluation metrics. The top five binders (DE A 1–DE A 5) were structurally analyzed and experimentally validated by expression, purification, and binding analysis. The best-performing DE A 3 was further optimized by scaffold-guided partial diffusion, resulting in seven variants (DE A 3-1 to DE A 3-7). b. Distribution of helix counts in RFdiffusion-generated scaffolds to analyze structural diversity. c. AF2-predicted structural models of the five selected de novo binder candidates in complex with the GDF15 dimer. Binder lengths, pAE_interaction, and pLDDT values are indicated, with the N- and C-termini labeled. d. SDS-PAGE analysis of binders (DE A 1–5, left; DE A 3-1 to DE A 3-7, right) after E. coli expression and affinity purification. e. Binding interface comparison of DE A 3 (left) and DE A 3-5 (right) with GDF15. Key interacting residues are shown as sticks and labeled.

    Article Snippet: Recombinant human or mouse GDF15 (#9279-GD or #8944-GD, R&D Systems) was prepared at a stock concentration of 250 μg/mL and subsequently diluted in pooled human serum (Sigma #H6914) or mouse serum (Abbkine #BMS0070), resulting in a final concentration of up to 5 μg/mL (≤500 nM).

    Techniques: Diffusion-based Assay, Generated, Sequencing, In Silico, Expressing, Purification, Binding Assay, Labeling, SDS Page, Affinity Purification, Comparison

    a. The RET domain segment (residues 586–622) was tested as an initial scaffold for site B binders design. b. AF2-predicted structures of 100 RET-derived variants by sequence design. Only disulfide-constrained β-strands remained folded. c. In silico filtering of 500 de novo backbones generated by RFdiffusion with site B hotspot constraints (W225, W228, M253, and Y297). No candidates satisfied filtering thresholds (pLDDT > 85 and pAE_interaction < 10; red box). d. Workflow of the scaffold search and grafting (SSG) strategy. The GDF15 structure was used as a query in the DALI server to search the Protein Data Bank (PDB) for natural scaffolds with similar topology and surface geometry. Candidate scaffolds were then subjected to scaffold-guided partial diffusion and sequence design. e. Representative scaffold candidates identified from the DALI server search: Follistatin/Activin A (PDB 2B0U), BMP9 pro-complex (mature domain + prodomain) (PDB 4YCI), BMP2/RGMA (PDB 4UHY), TGF-β3/GC-1008 antibody (PDB 3EO1), and BMP2/BMP2 receptor A (PDB 1ES7). RMSD relative to GDF15 is indicated. f. Structural comparison of GDF15/RET (green/pink) and BMP2/RGMA (olive/purple) complexes. GDF15 and BMP2 show overall similarity (RMSD = 2.5 Å), but interacting partners differ topologically. g. Structural alignment of RGMA with RGMA-derived binder variants (SSG B 1 to SSG B 5). RMSD with AF2-predicted structures and AF2 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated. h. SDS-PAGE analysis of binders (SSG B 1-SSG B 5) after E. coli expression and affinity purification.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. The RET domain segment (residues 586–622) was tested as an initial scaffold for site B binders design. b. AF2-predicted structures of 100 RET-derived variants by sequence design. Only disulfide-constrained β-strands remained folded. c. In silico filtering of 500 de novo backbones generated by RFdiffusion with site B hotspot constraints (W225, W228, M253, and Y297). No candidates satisfied filtering thresholds (pLDDT > 85 and pAE_interaction < 10; red box). d. Workflow of the scaffold search and grafting (SSG) strategy. The GDF15 structure was used as a query in the DALI server to search the Protein Data Bank (PDB) for natural scaffolds with similar topology and surface geometry. Candidate scaffolds were then subjected to scaffold-guided partial diffusion and sequence design. e. Representative scaffold candidates identified from the DALI server search: Follistatin/Activin A (PDB 2B0U), BMP9 pro-complex (mature domain + prodomain) (PDB 4YCI), BMP2/RGMA (PDB 4UHY), TGF-β3/GC-1008 antibody (PDB 3EO1), and BMP2/BMP2 receptor A (PDB 1ES7). RMSD relative to GDF15 is indicated. f. Structural comparison of GDF15/RET (green/pink) and BMP2/RGMA (olive/purple) complexes. GDF15 and BMP2 show overall similarity (RMSD = 2.5 Å), but interacting partners differ topologically. g. Structural alignment of RGMA with RGMA-derived binder variants (SSG B 1 to SSG B 5). RMSD with AF2-predicted structures and AF2 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated. h. SDS-PAGE analysis of binders (SSG B 1-SSG B 5) after E. coli expression and affinity purification.

    Article Snippet: Recombinant human or mouse GDF15 (#9279-GD or #8944-GD, R&D Systems) was prepared at a stock concentration of 250 μg/mL and subsequently diluted in pooled human serum (Sigma #H6914) or mouse serum (Abbkine #BMS0070), resulting in a final concentration of up to 5 μg/mL (≤500 nM).

    Techniques: Derivative Assay, Sequencing, In Silico, Generated, Diffusion-based Assay, Comparison, SDS Page, Expressing, Affinity Purification

    a, b. Schematic illustration (a) and structural model (b) of the BAT biosensor (SmBiT-GDF15 binder-LgBiT) for GDF15 detection in the “OFF” and “ON” states. The BAT biosensor consists of a designed GDF15 binder (red) flanked by SmBiT at the N-terminus (cyan, 1, SmBiT) and LgBiT at the C-terminus (blue, 2, LgBiT). In the absence of GDF15, two split luciferase fragments remain apart (“OFF” state with only background activity). Upon GDF15 binding, steric constraints bring two split luciferase fragments into proximity, enabling fragment complementation and restoring NanoLuc activity (“ON” state). The lengths of linker1 and linker2 (b, left) are key determinants for background signals in the absence of GDF15. c. SDS-PAGE analysis of SmBiT-DE A 3-LgBiT with various linker combinations after E.coli expression and affinity purification. d. Screening of linker combinations for SmBiT-DE A 3-LgBiT using a luminescence assay. Signal-to-noise ratios (luminescence intensity of each construct divided by that of the control without GDF15) are shown, with optimal linker combinations highlighted in red. e, g. Luminescent signals of SmBiT-DE A 3-LgBiT with 0-10 linkers (e) and of SmBiT-DE A 3-5-LgBiT with 5-5 linkers (g). Luminescence (arbitrary units, AU) is plotted against various concentrations of human or mouse GDF15 (n = 3). The linear detection range is indicated with a red box (0–10 nM). f. Sequence alignment of human and mouse GDF15. Conserved residues at site A are marked with black circles; species-specific substitutions at the interface are highlighted with green circles. h. AF3-predicted structures of DE A 3 or DE A 3-5 bound to human or mouse GDF15. Per-residue pLDDT values are color-coded according to the scale bar.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a, b. Schematic illustration (a) and structural model (b) of the BAT biosensor (SmBiT-GDF15 binder-LgBiT) for GDF15 detection in the “OFF” and “ON” states. The BAT biosensor consists of a designed GDF15 binder (red) flanked by SmBiT at the N-terminus (cyan, 1, SmBiT) and LgBiT at the C-terminus (blue, 2, LgBiT). In the absence of GDF15, two split luciferase fragments remain apart (“OFF” state with only background activity). Upon GDF15 binding, steric constraints bring two split luciferase fragments into proximity, enabling fragment complementation and restoring NanoLuc activity (“ON” state). The lengths of linker1 and linker2 (b, left) are key determinants for background signals in the absence of GDF15. c. SDS-PAGE analysis of SmBiT-DE A 3-LgBiT with various linker combinations after E.coli expression and affinity purification. d. Screening of linker combinations for SmBiT-DE A 3-LgBiT using a luminescence assay. Signal-to-noise ratios (luminescence intensity of each construct divided by that of the control without GDF15) are shown, with optimal linker combinations highlighted in red. e, g. Luminescent signals of SmBiT-DE A 3-LgBiT with 0-10 linkers (e) and of SmBiT-DE A 3-5-LgBiT with 5-5 linkers (g). Luminescence (arbitrary units, AU) is plotted against various concentrations of human or mouse GDF15 (n = 3). The linear detection range is indicated with a red box (0–10 nM). f. Sequence alignment of human and mouse GDF15. Conserved residues at site A are marked with black circles; species-specific substitutions at the interface are highlighted with green circles. h. AF3-predicted structures of DE A 3 or DE A 3-5 bound to human or mouse GDF15. Per-residue pLDDT values are color-coded according to the scale bar.

    Article Snippet: Recombinant human or mouse GDF15 (#9279-GD or #8944-GD, R&D Systems) was prepared at a stock concentration of 250 μg/mL and subsequently diluted in pooled human serum (Sigma #H6914) or mouse serum (Abbkine #BMS0070), resulting in a final concentration of up to 5 μg/mL (≤500 nM).

    Techniques: Luciferase, Activity Assay, Binding Assay, SDS Page, Expressing, Affinity Purification, Luminescence Assay, Construct, Control, Sequencing, Residue

    a. Schematic diagram of Fc-fused SG A 2-4 binder (SG A 2-4-Fc). b. SEC profile of SG A 2-4-Fc on a Superdex® 200 Increase 10/300 GL column (left) and SDS-PAGE analysis of elution fractions (right). c. SPR analysis of SG A 2-4-Fc and ponsegromab binding to immobilized GDF15. Sensorgrams are shown for analytes ranging from 5 to 50 nM (SG A 2-4-Fc or ponsegromab). d. Inhibition of GDF15-induced RET, AKT, and ERK phosphorylation in HEK293T cells stably expressing GFRAL and RET. Cells were co-treated with GDF15 (10 nM, 246 ng/ml) and either SG A 2-4-Fc or ponsegromab (100 nM; 7.8 μg/ml for SG A 2-4-Fc or 14.6 μg/ml for ponsegromab) for 30 mins. Phosphorylation was quantified relative to total protein (RET, AKT, and ERK each), normalized to the GDF15-only condition (n = 3). Statistical significance was determined using unpaired t-test (****P < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05; ns, not significant). e. Dose-dependent inhibition of GDF15-induced SRE-luciferase activity by SG A 2-4-Fc or ponsegromab in HEK293T cells co-expressing GFRAL, RET, and an SRE-Luc2 reporter. Data were normalized to GDF15-induced luminescence (100%), and IC 50 values were determined by non-linear regression fitting in GraphPad Prism.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. Schematic diagram of Fc-fused SG A 2-4 binder (SG A 2-4-Fc). b. SEC profile of SG A 2-4-Fc on a Superdex® 200 Increase 10/300 GL column (left) and SDS-PAGE analysis of elution fractions (right). c. SPR analysis of SG A 2-4-Fc and ponsegromab binding to immobilized GDF15. Sensorgrams are shown for analytes ranging from 5 to 50 nM (SG A 2-4-Fc or ponsegromab). d. Inhibition of GDF15-induced RET, AKT, and ERK phosphorylation in HEK293T cells stably expressing GFRAL and RET. Cells were co-treated with GDF15 (10 nM, 246 ng/ml) and either SG A 2-4-Fc or ponsegromab (100 nM; 7.8 μg/ml for SG A 2-4-Fc or 14.6 μg/ml for ponsegromab) for 30 mins. Phosphorylation was quantified relative to total protein (RET, AKT, and ERK each), normalized to the GDF15-only condition (n = 3). Statistical significance was determined using unpaired t-test (****P < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05; ns, not significant). e. Dose-dependent inhibition of GDF15-induced SRE-luciferase activity by SG A 2-4-Fc or ponsegromab in HEK293T cells co-expressing GFRAL, RET, and an SRE-Luc2 reporter. Data were normalized to GDF15-induced luminescence (100%), and IC 50 values were determined by non-linear regression fitting in GraphPad Prism.

    Article Snippet: Recombinant human or mouse GDF15 (#9279-GD or #8944-GD, R&D Systems) was prepared at a stock concentration of 250 μg/mL and subsequently diluted in pooled human serum (Sigma #H6914) or mouse serum (Abbkine #BMS0070), resulting in a final concentration of up to 5 μg/mL (≤500 nM).

    Techniques: SDS Page, Binding Assay, Inhibition, Phospho-proteomics, Stable Transfection, Expressing, Luciferase, Activity Assay

    a. Cryo-EM structure of the extracellular GDF15–GFRAL–RET complex (PDB: 6Q2J) showing a 2:2:2 stoichiometry, wherein the dimeric GDF15 bridges two GFRAL co-receptors and two RET receptors. b. Binding interfaces of GDF15 with GFRAL (top) and RET (bottom). Key interacting residues are shown as sticks. Hydrophobic hotspot residues used for binder design are highlighted in pink. c. Target sites for GDF15 binder design. The convex surface engaging GFRAL (site A, red) and the concave surface contacting RET (site B, light blue) are highlighted. Insets show electrostatic surface potentials of each site (white, hydrophobic; blue, positive charge; red, negative charge). d. Workflow of binder design using three scaffold generation strategies: Scaffold Grafting (SG), Diffusion-based de novo Design, and Scaffold-Search and Grafting (SSG).

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. Cryo-EM structure of the extracellular GDF15–GFRAL–RET complex (PDB: 6Q2J) showing a 2:2:2 stoichiometry, wherein the dimeric GDF15 bridges two GFRAL co-receptors and two RET receptors. b. Binding interfaces of GDF15 with GFRAL (top) and RET (bottom). Key interacting residues are shown as sticks. Hydrophobic hotspot residues used for binder design are highlighted in pink. c. Target sites for GDF15 binder design. The convex surface engaging GFRAL (site A, red) and the concave surface contacting RET (site B, light blue) are highlighted. Insets show electrostatic surface potentials of each site (white, hydrophobic; blue, positive charge; red, negative charge). d. Workflow of binder design using three scaffold generation strategies: Scaffold Grafting (SG), Diffusion-based de novo Design, and Scaffold-Search and Grafting (SSG).

    Article Snippet: Cells were treated with recombinant human GDF15 (10 nM; #9279-GD, R&D Systems) in the presence or absence of SG A 2-4-Fc or ponsegromab (100 nM) for 30 min. After washing with cold PBS, cells were lysed in RIPA buffer (#RC2002-050-00, Biosesang) supplemented with phosphatase inhibitor (#4906845001, Roche) and protease inhibitor cocktail (#11836170001, Roche) for 60 min at 4°C.

    Techniques: Cryo-EM Sample Prep, Binding Assay, Diffusion-based Assay

    a. Workflow of binder design via scaffold grafting. The GFRAL D2 domain was extracted as the initial scaffold to generate SG A 1 and SG A 2. SG A 2 was further optimized by scaffold-guided partial diffusion, resulting in five variants (SG A 2-1 to SG A 2-5). b. Extracted GFRAL D2 scaffold (residues 129∼211) from the GFRAL extracellular domain. The N- and C-termini, helices, and disulfide bonds are indicated. c. Backbone RMSD distribution of 100 ProteinMPNN-designed variants relative to the parental GFRAL D2 scaffold (mean RMSD = 0.85 Å). d. Structural alignment of the initial scaffold GFRAL D2 with SG A 1 (left) and SG A 2 (right). RMSD with AF3-predicted structure and AF3 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated, with the N- and C-termini labeled. e. Structural comparison of GFRAL-D2, SG A 1, and SG A 2 at the binding interface. Residues that enhance binding, commonly observed in both SG A 1 and SG A 2, are indicated. The rightmost panel shows the superposition of three scaffolds, highlighting α5 displacement. f. Superposition of SG A 1 and SG A 2, showing a unique electrostatic interaction in SG A 2. g. Structural alignment of SG A 2 with its partial diffusion-derived variants. RMSD with AF2-predicted structure and AF2 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated, with the N- and C-termini labeled. h. Backbone RMSD distribution of partial diffusion–derived variants relative to the SG A 2 scaffold (mean RMSD = 4.6 Å). i. Structural model of SG A 2-4 at the binding interface. Conserved binding residues in α5 (D69, Q72, L73, Q76), retained in SG A 2-4 variants compared to SG A 2, are highlighted. j. Binding interface comparison of SG A 2 and SG A 2-4, highlighting the shifted α1 position and distinct interacting residues on this helix.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. Workflow of binder design via scaffold grafting. The GFRAL D2 domain was extracted as the initial scaffold to generate SG A 1 and SG A 2. SG A 2 was further optimized by scaffold-guided partial diffusion, resulting in five variants (SG A 2-1 to SG A 2-5). b. Extracted GFRAL D2 scaffold (residues 129∼211) from the GFRAL extracellular domain. The N- and C-termini, helices, and disulfide bonds are indicated. c. Backbone RMSD distribution of 100 ProteinMPNN-designed variants relative to the parental GFRAL D2 scaffold (mean RMSD = 0.85 Å). d. Structural alignment of the initial scaffold GFRAL D2 with SG A 1 (left) and SG A 2 (right). RMSD with AF3-predicted structure and AF3 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated, with the N- and C-termini labeled. e. Structural comparison of GFRAL-D2, SG A 1, and SG A 2 at the binding interface. Residues that enhance binding, commonly observed in both SG A 1 and SG A 2, are indicated. The rightmost panel shows the superposition of three scaffolds, highlighting α5 displacement. f. Superposition of SG A 1 and SG A 2, showing a unique electrostatic interaction in SG A 2. g. Structural alignment of SG A 2 with its partial diffusion-derived variants. RMSD with AF2-predicted structure and AF2 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated, with the N- and C-termini labeled. h. Backbone RMSD distribution of partial diffusion–derived variants relative to the SG A 2 scaffold (mean RMSD = 4.6 Å). i. Structural model of SG A 2-4 at the binding interface. Conserved binding residues in α5 (D69, Q72, L73, Q76), retained in SG A 2-4 variants compared to SG A 2, are highlighted. j. Binding interface comparison of SG A 2 and SG A 2-4, highlighting the shifted α1 position and distinct interacting residues on this helix.

    Article Snippet: Cells were treated with recombinant human GDF15 (10 nM; #9279-GD, R&D Systems) in the presence or absence of SG A 2-4-Fc or ponsegromab (100 nM) for 30 min. After washing with cold PBS, cells were lysed in RIPA buffer (#RC2002-050-00, Biosesang) supplemented with phosphatase inhibitor (#4906845001, Roche) and protease inhibitor cocktail (#11836170001, Roche) for 60 min at 4°C.

    Techniques: Diffusion-based Assay, Labeling, Comparison, Binding Assay, Derivative Assay

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet:

    Article Snippet: Cells were treated with recombinant human GDF15 (10 nM; #9279-GD, R&D Systems) in the presence or absence of SG A 2-4-Fc or ponsegromab (100 nM) for 30 min. After washing with cold PBS, cells were lysed in RIPA buffer (#RC2002-050-00, Biosesang) supplemented with phosphatase inhibitor (#4906845001, Roche) and protease inhibitor cocktail (#11836170001, Roche) for 60 min at 4°C.

    Techniques: Binding Assay

    a. Workflow of de novo binder design using RF diffusion. A total of 1,728 initial scaffolds (50∼90 a.a) were generated, sequence-designed (three sequences per each backbone), and computationally filtered using in silico evaluation metrics. The top five binders (DE A 1–DE A 5) were structurally analyzed and experimentally validated by expression, purification, and binding analysis. The best-performing DE A 3 was further optimized by scaffold-guided partial diffusion, resulting in seven variants (DE A 3-1 to DE A 3-7). b. Distribution of helix counts in RFdiffusion-generated scaffolds to analyze structural diversity. c. AF2-predicted structural models of the five selected de novo binder candidates in complex with the GDF15 dimer. Binder lengths, pAE_interaction, and pLDDT values are indicated, with the N- and C-termini labeled. d. SDS-PAGE analysis of binders (DE A 1–5, left; DE A 3-1 to DE A 3-7, right) after E. coli expression and affinity purification. e. Binding interface comparison of DE A 3 (left) and DE A 3-5 (right) with GDF15. Key interacting residues are shown as sticks and labeled.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. Workflow of de novo binder design using RF diffusion. A total of 1,728 initial scaffolds (50∼90 a.a) were generated, sequence-designed (three sequences per each backbone), and computationally filtered using in silico evaluation metrics. The top five binders (DE A 1–DE A 5) were structurally analyzed and experimentally validated by expression, purification, and binding analysis. The best-performing DE A 3 was further optimized by scaffold-guided partial diffusion, resulting in seven variants (DE A 3-1 to DE A 3-7). b. Distribution of helix counts in RFdiffusion-generated scaffolds to analyze structural diversity. c. AF2-predicted structural models of the five selected de novo binder candidates in complex with the GDF15 dimer. Binder lengths, pAE_interaction, and pLDDT values are indicated, with the N- and C-termini labeled. d. SDS-PAGE analysis of binders (DE A 1–5, left; DE A 3-1 to DE A 3-7, right) after E. coli expression and affinity purification. e. Binding interface comparison of DE A 3 (left) and DE A 3-5 (right) with GDF15. Key interacting residues are shown as sticks and labeled.

    Article Snippet: Cells were treated with recombinant human GDF15 (10 nM; #9279-GD, R&D Systems) in the presence or absence of SG A 2-4-Fc or ponsegromab (100 nM) for 30 min. After washing with cold PBS, cells were lysed in RIPA buffer (#RC2002-050-00, Biosesang) supplemented with phosphatase inhibitor (#4906845001, Roche) and protease inhibitor cocktail (#11836170001, Roche) for 60 min at 4°C.

    Techniques: Diffusion-based Assay, Generated, Sequencing, In Silico, Expressing, Purification, Binding Assay, Labeling, SDS Page, Affinity Purification, Comparison

    a. The RET domain segment (residues 586–622) was tested as an initial scaffold for site B binders design. b. AF2-predicted structures of 100 RET-derived variants by sequence design. Only disulfide-constrained β-strands remained folded. c. In silico filtering of 500 de novo backbones generated by RFdiffusion with site B hotspot constraints (W225, W228, M253, and Y297). No candidates satisfied filtering thresholds (pLDDT > 85 and pAE_interaction < 10; red box). d. Workflow of the scaffold search and grafting (SSG) strategy. The GDF15 structure was used as a query in the DALI server to search the Protein Data Bank (PDB) for natural scaffolds with similar topology and surface geometry. Candidate scaffolds were then subjected to scaffold-guided partial diffusion and sequence design. e. Representative scaffold candidates identified from the DALI server search: Follistatin/Activin A (PDB 2B0U), BMP9 pro-complex (mature domain + prodomain) (PDB 4YCI), BMP2/RGMA (PDB 4UHY), TGF-β3/GC-1008 antibody (PDB 3EO1), and BMP2/BMP2 receptor A (PDB 1ES7). RMSD relative to GDF15 is indicated. f. Structural comparison of GDF15/RET (green/pink) and BMP2/RGMA (olive/purple) complexes. GDF15 and BMP2 show overall similarity (RMSD = 2.5 Å), but interacting partners differ topologically. g. Structural alignment of RGMA with RGMA-derived binder variants (SSG B 1 to SSG B 5). RMSD with AF2-predicted structures and AF2 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated. h. SDS-PAGE analysis of binders (SSG B 1-SSG B 5) after E. coli expression and affinity purification.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. The RET domain segment (residues 586–622) was tested as an initial scaffold for site B binders design. b. AF2-predicted structures of 100 RET-derived variants by sequence design. Only disulfide-constrained β-strands remained folded. c. In silico filtering of 500 de novo backbones generated by RFdiffusion with site B hotspot constraints (W225, W228, M253, and Y297). No candidates satisfied filtering thresholds (pLDDT > 85 and pAE_interaction < 10; red box). d. Workflow of the scaffold search and grafting (SSG) strategy. The GDF15 structure was used as a query in the DALI server to search the Protein Data Bank (PDB) for natural scaffolds with similar topology and surface geometry. Candidate scaffolds were then subjected to scaffold-guided partial diffusion and sequence design. e. Representative scaffold candidates identified from the DALI server search: Follistatin/Activin A (PDB 2B0U), BMP9 pro-complex (mature domain + prodomain) (PDB 4YCI), BMP2/RGMA (PDB 4UHY), TGF-β3/GC-1008 antibody (PDB 3EO1), and BMP2/BMP2 receptor A (PDB 1ES7). RMSD relative to GDF15 is indicated. f. Structural comparison of GDF15/RET (green/pink) and BMP2/RGMA (olive/purple) complexes. GDF15 and BMP2 show overall similarity (RMSD = 2.5 Å), but interacting partners differ topologically. g. Structural alignment of RGMA with RGMA-derived binder variants (SSG B 1 to SSG B 5). RMSD with AF2-predicted structures and AF2 scores (pAE_interaction and pLDDT) for the binder/GDF15 complex are indicated. h. SDS-PAGE analysis of binders (SSG B 1-SSG B 5) after E. coli expression and affinity purification.

    Article Snippet: Cells were treated with recombinant human GDF15 (10 nM; #9279-GD, R&D Systems) in the presence or absence of SG A 2-4-Fc or ponsegromab (100 nM) for 30 min. After washing with cold PBS, cells were lysed in RIPA buffer (#RC2002-050-00, Biosesang) supplemented with phosphatase inhibitor (#4906845001, Roche) and protease inhibitor cocktail (#11836170001, Roche) for 60 min at 4°C.

    Techniques: Derivative Assay, Sequencing, In Silico, Generated, Diffusion-based Assay, Comparison, SDS Page, Expressing, Affinity Purification

    a, b. Schematic illustration (a) and structural model (b) of the BAT biosensor (SmBiT-GDF15 binder-LgBiT) for GDF15 detection in the “OFF” and “ON” states. The BAT biosensor consists of a designed GDF15 binder (red) flanked by SmBiT at the N-terminus (cyan, 1, SmBiT) and LgBiT at the C-terminus (blue, 2, LgBiT). In the absence of GDF15, two split luciferase fragments remain apart (“OFF” state with only background activity). Upon GDF15 binding, steric constraints bring two split luciferase fragments into proximity, enabling fragment complementation and restoring NanoLuc activity (“ON” state). The lengths of linker1 and linker2 (b, left) are key determinants for background signals in the absence of GDF15. c. SDS-PAGE analysis of SmBiT-DE A 3-LgBiT with various linker combinations after E.coli expression and affinity purification. d. Screening of linker combinations for SmBiT-DE A 3-LgBiT using a luminescence assay. Signal-to-noise ratios (luminescence intensity of each construct divided by that of the control without GDF15) are shown, with optimal linker combinations highlighted in red. e, g. Luminescent signals of SmBiT-DE A 3-LgBiT with 0-10 linkers (e) and of SmBiT-DE A 3-5-LgBiT with 5-5 linkers (g). Luminescence (arbitrary units, AU) is plotted against various concentrations of human or mouse GDF15 (n = 3). The linear detection range is indicated with a red box (0–10 nM). f. Sequence alignment of human and mouse GDF15. Conserved residues at site A are marked with black circles; species-specific substitutions at the interface are highlighted with green circles. h. AF3-predicted structures of DE A 3 or DE A 3-5 bound to human or mouse GDF15. Per-residue pLDDT values are color-coded according to the scale bar.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a, b. Schematic illustration (a) and structural model (b) of the BAT biosensor (SmBiT-GDF15 binder-LgBiT) for GDF15 detection in the “OFF” and “ON” states. The BAT biosensor consists of a designed GDF15 binder (red) flanked by SmBiT at the N-terminus (cyan, 1, SmBiT) and LgBiT at the C-terminus (blue, 2, LgBiT). In the absence of GDF15, two split luciferase fragments remain apart (“OFF” state with only background activity). Upon GDF15 binding, steric constraints bring two split luciferase fragments into proximity, enabling fragment complementation and restoring NanoLuc activity (“ON” state). The lengths of linker1 and linker2 (b, left) are key determinants for background signals in the absence of GDF15. c. SDS-PAGE analysis of SmBiT-DE A 3-LgBiT with various linker combinations after E.coli expression and affinity purification. d. Screening of linker combinations for SmBiT-DE A 3-LgBiT using a luminescence assay. Signal-to-noise ratios (luminescence intensity of each construct divided by that of the control without GDF15) are shown, with optimal linker combinations highlighted in red. e, g. Luminescent signals of SmBiT-DE A 3-LgBiT with 0-10 linkers (e) and of SmBiT-DE A 3-5-LgBiT with 5-5 linkers (g). Luminescence (arbitrary units, AU) is plotted against various concentrations of human or mouse GDF15 (n = 3). The linear detection range is indicated with a red box (0–10 nM). f. Sequence alignment of human and mouse GDF15. Conserved residues at site A are marked with black circles; species-specific substitutions at the interface are highlighted with green circles. h. AF3-predicted structures of DE A 3 or DE A 3-5 bound to human or mouse GDF15. Per-residue pLDDT values are color-coded according to the scale bar.

    Article Snippet: Cells were treated with recombinant human GDF15 (10 nM; #9279-GD, R&D Systems) in the presence or absence of SG A 2-4-Fc or ponsegromab (100 nM) for 30 min. After washing with cold PBS, cells were lysed in RIPA buffer (#RC2002-050-00, Biosesang) supplemented with phosphatase inhibitor (#4906845001, Roche) and protease inhibitor cocktail (#11836170001, Roche) for 60 min at 4°C.

    Techniques: Luciferase, Activity Assay, Binding Assay, SDS Page, Expressing, Affinity Purification, Luminescence Assay, Construct, Control, Sequencing, Residue

    a. Schematic diagram of Fc-fused SG A 2-4 binder (SG A 2-4-Fc). b. SEC profile of SG A 2-4-Fc on a Superdex® 200 Increase 10/300 GL column (left) and SDS-PAGE analysis of elution fractions (right). c. SPR analysis of SG A 2-4-Fc and ponsegromab binding to immobilized GDF15. Sensorgrams are shown for analytes ranging from 5 to 50 nM (SG A 2-4-Fc or ponsegromab). d. Inhibition of GDF15-induced RET, AKT, and ERK phosphorylation in HEK293T cells stably expressing GFRAL and RET. Cells were co-treated with GDF15 (10 nM, 246 ng/ml) and either SG A 2-4-Fc or ponsegromab (100 nM; 7.8 μg/ml for SG A 2-4-Fc or 14.6 μg/ml for ponsegromab) for 30 mins. Phosphorylation was quantified relative to total protein (RET, AKT, and ERK each), normalized to the GDF15-only condition (n = 3). Statistical significance was determined using unpaired t-test (****P < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05; ns, not significant). e. Dose-dependent inhibition of GDF15-induced SRE-luciferase activity by SG A 2-4-Fc or ponsegromab in HEK293T cells co-expressing GFRAL, RET, and an SRE-Luc2 reporter. Data were normalized to GDF15-induced luminescence (100%), and IC 50 values were determined by non-linear regression fitting in GraphPad Prism.

    Journal: bioRxiv

    Article Title: De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics

    doi: 10.1101/2025.09.03.673894

    Figure Lengend Snippet: a. Schematic diagram of Fc-fused SG A 2-4 binder (SG A 2-4-Fc). b. SEC profile of SG A 2-4-Fc on a Superdex® 200 Increase 10/300 GL column (left) and SDS-PAGE analysis of elution fractions (right). c. SPR analysis of SG A 2-4-Fc and ponsegromab binding to immobilized GDF15. Sensorgrams are shown for analytes ranging from 5 to 50 nM (SG A 2-4-Fc or ponsegromab). d. Inhibition of GDF15-induced RET, AKT, and ERK phosphorylation in HEK293T cells stably expressing GFRAL and RET. Cells were co-treated with GDF15 (10 nM, 246 ng/ml) and either SG A 2-4-Fc or ponsegromab (100 nM; 7.8 μg/ml for SG A 2-4-Fc or 14.6 μg/ml for ponsegromab) for 30 mins. Phosphorylation was quantified relative to total protein (RET, AKT, and ERK each), normalized to the GDF15-only condition (n = 3). Statistical significance was determined using unpaired t-test (****P < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05; ns, not significant). e. Dose-dependent inhibition of GDF15-induced SRE-luciferase activity by SG A 2-4-Fc or ponsegromab in HEK293T cells co-expressing GFRAL, RET, and an SRE-Luc2 reporter. Data were normalized to GDF15-induced luminescence (100%), and IC 50 values were determined by non-linear regression fitting in GraphPad Prism.

    Article Snippet: Cells were treated with recombinant human GDF15 (10 nM; #9279-GD, R&D Systems) in the presence or absence of SG A 2-4-Fc or ponsegromab (100 nM) for 30 min. After washing with cold PBS, cells were lysed in RIPA buffer (#RC2002-050-00, Biosesang) supplemented with phosphatase inhibitor (#4906845001, Roche) and protease inhibitor cocktail (#11836170001, Roche) for 60 min at 4°C.

    Techniques: SDS Page, Binding Assay, Inhibition, Phospho-proteomics, Stable Transfection, Expressing, Luciferase, Activity Assay

    Functional enrichment analysis of the GDF subfamily. A Proteins related to the GDF subfamily. B – E GO/KEGG analysis of related proteins. F Differential genes between patients with high and low GDF15 expression. G – H GO/KEGG enrichment of upregulated genes in patients with high GDF15 expression. I , J GO/KEGG enrichment of upregulated genes in patients with low GDF15 expression. K , M GDF15 expression and GSEA enrichment analysis. (N-R) Correlation of GDF15 expression with cancer-related pathways

    Journal: Cell & Bioscience

    Article Title: Single-cell and spatial analyses of the GDF family in tumors, with a focus on the prognostic and biological role of GDF15 in hepatocellular carcinoma

    doi: 10.1186/s13578-025-01431-9

    Figure Lengend Snippet: Functional enrichment analysis of the GDF subfamily. A Proteins related to the GDF subfamily. B – E GO/KEGG analysis of related proteins. F Differential genes between patients with high and low GDF15 expression. G – H GO/KEGG enrichment of upregulated genes in patients with high GDF15 expression. I , J GO/KEGG enrichment of upregulated genes in patients with low GDF15 expression. K , M GDF15 expression and GSEA enrichment analysis. (N-R) Correlation of GDF15 expression with cancer-related pathways

    Article Snippet: For GDF15 treatment, recombinant human GDF15 (R&D Systems, Minneapolis, MN) were prepared in distilled water and added into the culture medium of liver cancer cells at a concentration of 100 ng/ml.

    Techniques: Functional Assay, Expressing

    Single-cell RNA sequencing analysis of liver samples from HCC patients. A The UMAP plots of 9 cell types identified in 90.444 cells, each dot represented a cell(left). The UMAP plots of cells clustered by article sources(right). B Bubble plots show gene expression in each cell subpopulation, with the size of the bubbles indicating the proportion of cells in the population expressing a particular gene, and the colours representing the average expression of each gene. C The number of each cell subpopulation in the entire single-cell dataset. D The UMAP plot shows the expression levels of the GDF family in cell subpopulations. E Average proportion of assigned cell types in different groups. F Monocle 2 trajectory analyses of GDF15_Hepatocytes and nonGDF15_Hepatocytes, which sequentially display cell states, changes in GDF15 expression levels, pseudotime and cell subgroups. G Predicting the stemness of cell subpopulations according to CytoTRACE, with darker colors indicating lower cell differentiation. It can be observed that GDF15_Hepatocytes are moving towards non-GDF15_Hepatocytes. H The heatmap shows the differentially expressed genes in tumor cells based on the pseudotime trajectory, The color key ranges from blue to red, indicating the relative expression levels from low to high. I GO analysis of differential genes between GDF15_Hepatocytes and non- GDF15_Hepatocytes. J The expression dynamics of representative genes show different expression in different cell types. K , L The communication heatmap/network of intercellular interactions (The red lines/squares indicate that the interaction weight/intensity between tumor group cells is higher than that of the normal group, while the blue lines/squares indicate that the interaction weight/intensity between normal group cells is higher than that of the tumor group). M , N Histograms showing the strength of afferent and efferent signals from different cell types in tumor tissue and normal tissue. O , P Heatmap showing afferent and efferent signal strengths of different pathways in tumor tissue and normal tissue for different cell types. Q Hierarchical diagram visually illustrates the interactions of the aforementioned signaling pathways in tumor tissue. The PERIOSTIN signaling pathway is exclusively received by GDF15_hepatocytes. R A z-score scatterplot of the samples is shown, with each scatter representing one sample and different colours indicating different subgroups. S Kaplan–Meier survival analysis charts

    Journal: Cell & Bioscience

    Article Title: Single-cell and spatial analyses of the GDF family in tumors, with a focus on the prognostic and biological role of GDF15 in hepatocellular carcinoma

    doi: 10.1186/s13578-025-01431-9

    Figure Lengend Snippet: Single-cell RNA sequencing analysis of liver samples from HCC patients. A The UMAP plots of 9 cell types identified in 90.444 cells, each dot represented a cell(left). The UMAP plots of cells clustered by article sources(right). B Bubble plots show gene expression in each cell subpopulation, with the size of the bubbles indicating the proportion of cells in the population expressing a particular gene, and the colours representing the average expression of each gene. C The number of each cell subpopulation in the entire single-cell dataset. D The UMAP plot shows the expression levels of the GDF family in cell subpopulations. E Average proportion of assigned cell types in different groups. F Monocle 2 trajectory analyses of GDF15_Hepatocytes and nonGDF15_Hepatocytes, which sequentially display cell states, changes in GDF15 expression levels, pseudotime and cell subgroups. G Predicting the stemness of cell subpopulations according to CytoTRACE, with darker colors indicating lower cell differentiation. It can be observed that GDF15_Hepatocytes are moving towards non-GDF15_Hepatocytes. H The heatmap shows the differentially expressed genes in tumor cells based on the pseudotime trajectory, The color key ranges from blue to red, indicating the relative expression levels from low to high. I GO analysis of differential genes between GDF15_Hepatocytes and non- GDF15_Hepatocytes. J The expression dynamics of representative genes show different expression in different cell types. K , L The communication heatmap/network of intercellular interactions (The red lines/squares indicate that the interaction weight/intensity between tumor group cells is higher than that of the normal group, while the blue lines/squares indicate that the interaction weight/intensity between normal group cells is higher than that of the tumor group). M , N Histograms showing the strength of afferent and efferent signals from different cell types in tumor tissue and normal tissue. O , P Heatmap showing afferent and efferent signal strengths of different pathways in tumor tissue and normal tissue for different cell types. Q Hierarchical diagram visually illustrates the interactions of the aforementioned signaling pathways in tumor tissue. The PERIOSTIN signaling pathway is exclusively received by GDF15_hepatocytes. R A z-score scatterplot of the samples is shown, with each scatter representing one sample and different colours indicating different subgroups. S Kaplan–Meier survival analysis charts

    Article Snippet: For GDF15 treatment, recombinant human GDF15 (R&D Systems, Minneapolis, MN) were prepared in distilled water and added into the culture medium of liver cancer cells at a concentration of 100 ng/ml.

    Techniques: RNA Sequencing, Gene Expression, Expressing, Cell Differentiation, Protein-Protein interactions

    Single-cell mapping, trajectory analysis and cellular communication in BRCA and PDAC. A UMAP showing BRCA subpopulation numbers (left) and annotated cell populations (right). B Bubble plots showing gene expression in each cell subpopulation, with the size of the bubbles indicating the proportion of cells in the population expressing a particular gene, and the colours representing the average expression of each gene. C UMAP plot showing the density of GDF15 gene expression per cell subpopulation. D – F Monocle2 trajectory analyses of GDF15_Malignant and non-GDF15_Malignant by cell subpopulation ( D ), pseudotime ( E ) and cell state ( F ). G Predicting the stemness of cell subpopulations according to CytoTRACE, with darker colors indicating lower cell differentiation. It can be observed that GDF15_Malignant are moving towards non-GDF15_Malignant. H Circle diagram showing potential cellular interactions between nine cell types by cellular communication. Node sizes indicate interactions; line widths indicate the number of significant ligand-receptor pairs. I Afferent and efferent signal intensity across cell subpopulations. J Heatmap of efferent and afferent patterns of different pathways across cells. K Important ligand receptors between Fibroblasts and GDF15_Malignant/non-GDF15_Malignant in the FN1, LAMININ and COLLAGEN pathways. L UMAP showing PDAC subpopulation numbers (left) and annotated cell populations (right). M Bubble map showing gene expression in each cell subpopulation. N UMAP plot showing the density of GDF15 gene expression per cell subpopulation. O , P , Q Monocle2 trajectory analyses of GDF15_ Ductal and non-GDF15_ Ductal by cell subpopulation ( O ), pseudotime ( P ) and cell state ( Q ). R Predicting the stemness of cell subpopulations according to CytoTRACE, with darker colors indicating lower cell differentiation. It can be observed that GDF15_ Ductal are moving towards non-GDF15_ Ductal. S Circle diagram showing potential cellular interactions between 11 cell types via cellular communication. T Afferent and efferent signal strength of each cell subpopulation. U Heatmap of efferent and afferent patterns of different pathways across cells. V The chordal graph demonstrates the presence of stronger cellular communication between Fibroblasts and GDF15_ Ductal in the COLLAGEN pathway

    Journal: Cell & Bioscience

    Article Title: Single-cell and spatial analyses of the GDF family in tumors, with a focus on the prognostic and biological role of GDF15 in hepatocellular carcinoma

    doi: 10.1186/s13578-025-01431-9

    Figure Lengend Snippet: Single-cell mapping, trajectory analysis and cellular communication in BRCA and PDAC. A UMAP showing BRCA subpopulation numbers (left) and annotated cell populations (right). B Bubble plots showing gene expression in each cell subpopulation, with the size of the bubbles indicating the proportion of cells in the population expressing a particular gene, and the colours representing the average expression of each gene. C UMAP plot showing the density of GDF15 gene expression per cell subpopulation. D – F Monocle2 trajectory analyses of GDF15_Malignant and non-GDF15_Malignant by cell subpopulation ( D ), pseudotime ( E ) and cell state ( F ). G Predicting the stemness of cell subpopulations according to CytoTRACE, with darker colors indicating lower cell differentiation. It can be observed that GDF15_Malignant are moving towards non-GDF15_Malignant. H Circle diagram showing potential cellular interactions between nine cell types by cellular communication. Node sizes indicate interactions; line widths indicate the number of significant ligand-receptor pairs. I Afferent and efferent signal intensity across cell subpopulations. J Heatmap of efferent and afferent patterns of different pathways across cells. K Important ligand receptors between Fibroblasts and GDF15_Malignant/non-GDF15_Malignant in the FN1, LAMININ and COLLAGEN pathways. L UMAP showing PDAC subpopulation numbers (left) and annotated cell populations (right). M Bubble map showing gene expression in each cell subpopulation. N UMAP plot showing the density of GDF15 gene expression per cell subpopulation. O , P , Q Monocle2 trajectory analyses of GDF15_ Ductal and non-GDF15_ Ductal by cell subpopulation ( O ), pseudotime ( P ) and cell state ( Q ). R Predicting the stemness of cell subpopulations according to CytoTRACE, with darker colors indicating lower cell differentiation. It can be observed that GDF15_ Ductal are moving towards non-GDF15_ Ductal. S Circle diagram showing potential cellular interactions between 11 cell types via cellular communication. T Afferent and efferent signal strength of each cell subpopulation. U Heatmap of efferent and afferent patterns of different pathways across cells. V The chordal graph demonstrates the presence of stronger cellular communication between Fibroblasts and GDF15_ Ductal in the COLLAGEN pathway

    Article Snippet: For GDF15 treatment, recombinant human GDF15 (R&D Systems, Minneapolis, MN) were prepared in distilled water and added into the culture medium of liver cancer cells at a concentration of 100 ng/ml.

    Techniques: Gene Expression, Expressing, Cell Differentiation

    Single-cell mapping and cellular communication in CRC,LSCC,NSCLC,OV and PRAD. A UMAP showing CRC annotated cell populations (left) and densitometry of GDF15 gene expression by cell subpopulation (right). B Afferent and efferent signal intensity across cell subpopulations in CRC. C Heatmap of efferent and afferent patterns of different pathways across cells in CRC. D Heatmap of the MIF signalling pathway in CRC, with GDF15_Malignant as the main ligand cell acting on CD74/CXCR4 on the surface of immune cells by secreting MIF. E UMAP showing LSCC annotated cell populations (left) and densitometry of GDF15 gene expression in each cell subpopulation (right). F Afferent and efferent signal intensity of each cell subpopulation in LSCC. G Heatmap of efferent and afferent patterns of different pathways across cells in LSCC. H Heatmap of ANNEXIN signalling pathway in LSCC with GDF15_Malignant acting through ANXA1-FPR1 ligand receptor in M1 and M2 cells. I UMAP showing annotated cell populations in NSCLC (left) and densitometry of GDF15 gene expression in each cell subpopulation (right). J Afferent and efferent signalling intensity of each cell subpopulation in NSCLC. K Heatmap of efferent and afferent patterns of different pathways across cells in NSCLC. L Heatmap of the MIF signalling pathway in NSCLC, with GDF15_Malignant as the main ligand cell acting on CD74/CD44 on the surface of immune cells by secreting MIF. M UMAP showing OV annotated cell populations (left) and densitometry of GDF15 gene expression in each cell subpopulation (right). N Afferent and efferent signal intensity of each cell subpopulation in OV. O Heatmap of efferent and afferent patterns of different pathways across cells in OV. P Heatmap of MK signalling pathway in OV, GDF15_Malignant acts on immune cells via MDK—NCL ligand receptor. Q UMAP showing PRAD annotated cell populations (left) and densitometry of GDF15 gene expression in each cell subpopulation (right). R Afferent and efferent signal intensities in each cell subpopulation in PRAD. S Heatmap of efferent and afferent patterns of different pathways across cells in PRAD. T Heatmap of MIF signalling pathway in PRAD, GDF15_Malignant acts on CD74/CD44 on the surface of immune cells by secreting MIF

    Journal: Cell & Bioscience

    Article Title: Single-cell and spatial analyses of the GDF family in tumors, with a focus on the prognostic and biological role of GDF15 in hepatocellular carcinoma

    doi: 10.1186/s13578-025-01431-9

    Figure Lengend Snippet: Single-cell mapping and cellular communication in CRC,LSCC,NSCLC,OV and PRAD. A UMAP showing CRC annotated cell populations (left) and densitometry of GDF15 gene expression by cell subpopulation (right). B Afferent and efferent signal intensity across cell subpopulations in CRC. C Heatmap of efferent and afferent patterns of different pathways across cells in CRC. D Heatmap of the MIF signalling pathway in CRC, with GDF15_Malignant as the main ligand cell acting on CD74/CXCR4 on the surface of immune cells by secreting MIF. E UMAP showing LSCC annotated cell populations (left) and densitometry of GDF15 gene expression in each cell subpopulation (right). F Afferent and efferent signal intensity of each cell subpopulation in LSCC. G Heatmap of efferent and afferent patterns of different pathways across cells in LSCC. H Heatmap of ANNEXIN signalling pathway in LSCC with GDF15_Malignant acting through ANXA1-FPR1 ligand receptor in M1 and M2 cells. I UMAP showing annotated cell populations in NSCLC (left) and densitometry of GDF15 gene expression in each cell subpopulation (right). J Afferent and efferent signalling intensity of each cell subpopulation in NSCLC. K Heatmap of efferent and afferent patterns of different pathways across cells in NSCLC. L Heatmap of the MIF signalling pathway in NSCLC, with GDF15_Malignant as the main ligand cell acting on CD74/CD44 on the surface of immune cells by secreting MIF. M UMAP showing OV annotated cell populations (left) and densitometry of GDF15 gene expression in each cell subpopulation (right). N Afferent and efferent signal intensity of each cell subpopulation in OV. O Heatmap of efferent and afferent patterns of different pathways across cells in OV. P Heatmap of MK signalling pathway in OV, GDF15_Malignant acts on immune cells via MDK—NCL ligand receptor. Q UMAP showing PRAD annotated cell populations (left) and densitometry of GDF15 gene expression in each cell subpopulation (right). R Afferent and efferent signal intensities in each cell subpopulation in PRAD. S Heatmap of efferent and afferent patterns of different pathways across cells in PRAD. T Heatmap of MIF signalling pathway in PRAD, GDF15_Malignant acts on CD74/CD44 on the surface of immune cells by secreting MIF

    Article Snippet: For GDF15 treatment, recombinant human GDF15 (R&D Systems, Minneapolis, MN) were prepared in distilled water and added into the culture medium of liver cancer cells at a concentration of 100 ng/ml.

    Techniques: Gene Expression

    Relationship between GDF subfamily members with immune infiltration. A , B Spearman correlation of GDF family AUC scores with microenvironmental components at spatial transcriptome resolution (P3T, P9T). C – J Spearman correlation of GDF15 with microenvironmental components at spatial transcriptome resolution. K Heatmap of immune infiltration in GDF15 high and low expression groups. L Differences in immune infiltration between high and low GDF15 expression samples (CIBERSORT). M Difference in Immunoinhibitor expression between GDF15 high and low expression groups. N Differences in TIDE scores between GDF15 high and low expression groups

    Journal: Cell & Bioscience

    Article Title: Single-cell and spatial analyses of the GDF family in tumors, with a focus on the prognostic and biological role of GDF15 in hepatocellular carcinoma

    doi: 10.1186/s13578-025-01431-9

    Figure Lengend Snippet: Relationship between GDF subfamily members with immune infiltration. A , B Spearman correlation of GDF family AUC scores with microenvironmental components at spatial transcriptome resolution (P3T, P9T). C – J Spearman correlation of GDF15 with microenvironmental components at spatial transcriptome resolution. K Heatmap of immune infiltration in GDF15 high and low expression groups. L Differences in immune infiltration between high and low GDF15 expression samples (CIBERSORT). M Difference in Immunoinhibitor expression between GDF15 high and low expression groups. N Differences in TIDE scores between GDF15 high and low expression groups

    Article Snippet: For GDF15 treatment, recombinant human GDF15 (R&D Systems, Minneapolis, MN) were prepared in distilled water and added into the culture medium of liver cancer cells at a concentration of 100 ng/ml.

    Techniques: Expressing

    GDF15 expression is elevated in HCC cells and promotes HCC cells proliferation and invasion. A GDF15 expression in human HCC cell lines analyzed by qRT-PCR. B Differential expression of GDF15 IHC score in normal liver and HCC. C Recombinant GDF15 promotes Lo2 cells proliferation and invasion. D The representative pictures (left) and quantification (right) of colony numbers of indicated cells as determined by an anchorage-independent growth assay. E MTT assays were subjected to detect the proliferation capacity of HCC cells. F The representative pictures (left) and quantification (right) of invaded cells were analyzed using the transwell matrix penetration assay. G Wound-healing assays were subjected to detect the migration capacity of HCC cells

    Journal: Cell & Bioscience

    Article Title: Single-cell and spatial analyses of the GDF family in tumors, with a focus on the prognostic and biological role of GDF15 in hepatocellular carcinoma

    doi: 10.1186/s13578-025-01431-9

    Figure Lengend Snippet: GDF15 expression is elevated in HCC cells and promotes HCC cells proliferation and invasion. A GDF15 expression in human HCC cell lines analyzed by qRT-PCR. B Differential expression of GDF15 IHC score in normal liver and HCC. C Recombinant GDF15 promotes Lo2 cells proliferation and invasion. D The representative pictures (left) and quantification (right) of colony numbers of indicated cells as determined by an anchorage-independent growth assay. E MTT assays were subjected to detect the proliferation capacity of HCC cells. F The representative pictures (left) and quantification (right) of invaded cells were analyzed using the transwell matrix penetration assay. G Wound-healing assays were subjected to detect the migration capacity of HCC cells

    Article Snippet: For GDF15 treatment, recombinant human GDF15 (R&D Systems, Minneapolis, MN) were prepared in distilled water and added into the culture medium of liver cancer cells at a concentration of 100 ng/ml.

    Techniques: Expressing, Quantitative RT-PCR, Quantitative Proteomics, Recombinant, Growth Assay, Migration

    The function of GDF15 in tumor growth and macrophage polarization. A Representative images of the migration ability of the liver cancer cell line after silencing GDF15. B Representative images of the invasion ability of the liver cancer cell line after silencing GDF15. C Validation of GDF15 knockout efficiency by qRT-PCR. D , E In vivo representative bioluminescent images demonstrate the growth of luciferase-labeled tumor cells. F–I Provided are representative images and qRT-PCR quantitative analyses of M1-like (F4/80-positive, CD86-positive) and M2-like (F4/80-positive, CD206-positive) macrophages in the tumor context. J , L Moreover, BMDMs from wild-type (WT) mice were either control or stimulated with LPS + IFN-γ, IL-4 + IL-13, or recombinant mouse GDF15 protein. Immunofluorescence (IF) analysis revealed representative images and quantitative data of macrophages exhibiting M1-like (iNOS positive) and M2-like (CD206 positive) phenotypes under GDF15 stimulation. K BMDMs after different inductions were stained and analyzed by flow cytometry

    Journal: Cell & Bioscience

    Article Title: Single-cell and spatial analyses of the GDF family in tumors, with a focus on the prognostic and biological role of GDF15 in hepatocellular carcinoma

    doi: 10.1186/s13578-025-01431-9

    Figure Lengend Snippet: The function of GDF15 in tumor growth and macrophage polarization. A Representative images of the migration ability of the liver cancer cell line after silencing GDF15. B Representative images of the invasion ability of the liver cancer cell line after silencing GDF15. C Validation of GDF15 knockout efficiency by qRT-PCR. D , E In vivo representative bioluminescent images demonstrate the growth of luciferase-labeled tumor cells. F–I Provided are representative images and qRT-PCR quantitative analyses of M1-like (F4/80-positive, CD86-positive) and M2-like (F4/80-positive, CD206-positive) macrophages in the tumor context. J , L Moreover, BMDMs from wild-type (WT) mice were either control or stimulated with LPS + IFN-γ, IL-4 + IL-13, or recombinant mouse GDF15 protein. Immunofluorescence (IF) analysis revealed representative images and quantitative data of macrophages exhibiting M1-like (iNOS positive) and M2-like (CD206 positive) phenotypes under GDF15 stimulation. K BMDMs after different inductions were stained and analyzed by flow cytometry

    Article Snippet: For GDF15 treatment, recombinant human GDF15 (R&D Systems, Minneapolis, MN) were prepared in distilled water and added into the culture medium of liver cancer cells at a concentration of 100 ng/ml.

    Techniques: Migration, Biomarker Discovery, Knock-Out, Quantitative RT-PCR, In Vivo, Luciferase, Labeling, Control, Recombinant, Immunofluorescence, Staining, Flow Cytometry

    Analysis of each member of the GDF subfamily with drug sensitivity. A Correlation of GDSC drug sensitivity with mRNA expression of each member of the GDF subfamily. B Correlation of CTRP drug sensitivity with mRNA expression of each member of the GDF subfamily. C Heat map of drugs associated with GDF15 in HCC. D Difference in IC50 of drugs in GDF high and low expression groups. E , F Molecular docking pattern of GDF11 with 17-AAG, teniposide. G , H Molecular docking pattern of GDF5 with topotecan, YM201636

    Journal: Cell & Bioscience

    Article Title: Single-cell and spatial analyses of the GDF family in tumors, with a focus on the prognostic and biological role of GDF15 in hepatocellular carcinoma

    doi: 10.1186/s13578-025-01431-9

    Figure Lengend Snippet: Analysis of each member of the GDF subfamily with drug sensitivity. A Correlation of GDSC drug sensitivity with mRNA expression of each member of the GDF subfamily. B Correlation of CTRP drug sensitivity with mRNA expression of each member of the GDF subfamily. C Heat map of drugs associated with GDF15 in HCC. D Difference in IC50 of drugs in GDF high and low expression groups. E , F Molecular docking pattern of GDF11 with 17-AAG, teniposide. G , H Molecular docking pattern of GDF5 with topotecan, YM201636

    Article Snippet: For GDF15 treatment, recombinant human GDF15 (R&D Systems, Minneapolis, MN) were prepared in distilled water and added into the culture medium of liver cancer cells at a concentration of 100 ng/ml.

    Techniques: Expressing