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Structured Review

Proteintech cxcl10
Targeting Capability of D-EVs to Senescent NPCs is Mediated by the <t>CXCL10-CXCR3</t> Axis. (A) Schematic diagram of RNA sequencing for senescent NPCs treated with D-EVs or not. (B-C) Volcano plots and heatmaps displaying differential gene expression in senescent NPCs treated with D-EVs or not. (D) A Venn diagram illustrates overlap between DEGs identified in senescent NPCs treated with D-EVs and key gene databases for cytokine-cytokine receptor interactions. (E) A Venn diagram illustrates overlap between DEGs identified in D-MSCs and chemokine signaling pathway key gene databases. (F-G) Network analysis of the hub genes among the above total DEGs. A protein-protein interaction network was created in the STRING database, while the Cytoscape software was used to determine the hub genes in the network. (H) GO analysis confirming enrichment of terms related to senescent NPCs treated with D-EVs or not in the BP categories. (I) GSEA analysis of cytokine-cytokine receptor interactions in D-EVs group versus TBHP group. (J) Western blot analysis confirmed the expression of CXCR3 in Control and senescent NPCs, and (S) quantitative analysis. (K) Western blot analysis confirmed the expression of CXCL10 in N-EVs and D-EVs, and (R) quantitative analysis. (L) Protein binding analysis of CXCR3 and CXCL10 by PyMOL. (M) Confocal analysis of the uptake of pHrodo-labeled EVs in senescent NPCs following the treatments of N-EVs, D-EVs with CXCL10 knockout/anti-CXCR3, or not, and (Q) quantitative analysis. (N) In vivo tracking of PKH26-labeled CXCL10 knockout D-EVs. (O) Flow cytometry showing uptake of different EVs with CXCL10 knockout/anti-CXCR3 or not by senescent NPCs, and (P) quantitative analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.
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1) Product Images from "Microenvironment-educated MSC-EVs loaded injectable smart hydrogel for targeting senescent nucleus pulposus cells and inhibiting ferroptosis against intervertebral disc degeneration"

Article Title: Microenvironment-educated MSC-EVs loaded injectable smart hydrogel for targeting senescent nucleus pulposus cells and inhibiting ferroptosis against intervertebral disc degeneration

Journal: Bioactive Materials

doi: 10.1016/j.bioactmat.2026.02.030

Targeting Capability of D-EVs to Senescent NPCs is Mediated by the CXCL10-CXCR3 Axis. (A) Schematic diagram of RNA sequencing for senescent NPCs treated with D-EVs or not. (B-C) Volcano plots and heatmaps displaying differential gene expression in senescent NPCs treated with D-EVs or not. (D) A Venn diagram illustrates overlap between DEGs identified in senescent NPCs treated with D-EVs and key gene databases for cytokine-cytokine receptor interactions. (E) A Venn diagram illustrates overlap between DEGs identified in D-MSCs and chemokine signaling pathway key gene databases. (F-G) Network analysis of the hub genes among the above total DEGs. A protein-protein interaction network was created in the STRING database, while the Cytoscape software was used to determine the hub genes in the network. (H) GO analysis confirming enrichment of terms related to senescent NPCs treated with D-EVs or not in the BP categories. (I) GSEA analysis of cytokine-cytokine receptor interactions in D-EVs group versus TBHP group. (J) Western blot analysis confirmed the expression of CXCR3 in Control and senescent NPCs, and (S) quantitative analysis. (K) Western blot analysis confirmed the expression of CXCL10 in N-EVs and D-EVs, and (R) quantitative analysis. (L) Protein binding analysis of CXCR3 and CXCL10 by PyMOL. (M) Confocal analysis of the uptake of pHrodo-labeled EVs in senescent NPCs following the treatments of N-EVs, D-EVs with CXCL10 knockout/anti-CXCR3, or not, and (Q) quantitative analysis. (N) In vivo tracking of PKH26-labeled CXCL10 knockout D-EVs. (O) Flow cytometry showing uptake of different EVs with CXCL10 knockout/anti-CXCR3 or not by senescent NPCs, and (P) quantitative analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.
Figure Legend Snippet: Targeting Capability of D-EVs to Senescent NPCs is Mediated by the CXCL10-CXCR3 Axis. (A) Schematic diagram of RNA sequencing for senescent NPCs treated with D-EVs or not. (B-C) Volcano plots and heatmaps displaying differential gene expression in senescent NPCs treated with D-EVs or not. (D) A Venn diagram illustrates overlap between DEGs identified in senescent NPCs treated with D-EVs and key gene databases for cytokine-cytokine receptor interactions. (E) A Venn diagram illustrates overlap between DEGs identified in D-MSCs and chemokine signaling pathway key gene databases. (F-G) Network analysis of the hub genes among the above total DEGs. A protein-protein interaction network was created in the STRING database, while the Cytoscape software was used to determine the hub genes in the network. (H) GO analysis confirming enrichment of terms related to senescent NPCs treated with D-EVs or not in the BP categories. (I) GSEA analysis of cytokine-cytokine receptor interactions in D-EVs group versus TBHP group. (J) Western blot analysis confirmed the expression of CXCR3 in Control and senescent NPCs, and (S) quantitative analysis. (K) Western blot analysis confirmed the expression of CXCL10 in N-EVs and D-EVs, and (R) quantitative analysis. (L) Protein binding analysis of CXCR3 and CXCL10 by PyMOL. (M) Confocal analysis of the uptake of pHrodo-labeled EVs in senescent NPCs following the treatments of N-EVs, D-EVs with CXCL10 knockout/anti-CXCR3, or not, and (Q) quantitative analysis. (N) In vivo tracking of PKH26-labeled CXCL10 knockout D-EVs. (O) Flow cytometry showing uptake of different EVs with CXCL10 knockout/anti-CXCR3 or not by senescent NPCs, and (P) quantitative analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Techniques Used: RNA Sequencing, Gene Expression, Software, Western Blot, Expressing, Control, Protein Binding, Labeling, Knock-Out, In Vivo, Flow Cytometry

D-EVs Deliver GPX4 to Inhibit Ferroptosis in Senescent NPCs. (A) Representative Senescent-Tracker images of NPCs treated with N-EVs, D-EVs, Era, and D-Evs sh-CXCL10 . (B) Volcano plot of transcriptomic data comparing D-MSC and N-MSC. (C) KEGG pathway analysis of DEGs in D-MSCs versus N-MSCs. (D) Volcano plot of proteomic data comparing D-EVs and N-EVs. (E) KEGG pathway analysis of transcriptomic and proteomic data integration. (F) A Venn diagram illustrating the intersection of genes from the D-MSC transcriptome, the D-EVs proteome, and the ferroptosis-related gene set. (G) Bar graph showing the relative expression levels of core overlapping genes identified in (F). (H) MS analysis revealed that GPX4 is enriched in the D-EVs proteome. (I) Western blot analysis confirming GPX4 protein in D-EVs and N-EVs. (J) Western blot analysis of key senescence (p21, P16) markers in NPCs following treatment with PBS or N-EVs with CXCL10 or GPX4 knockout. (K) Representative images of EdU depicting cell proliferation ability in the control, TBHP, D-EVs, D-EVs sh-CXCL10 , D-EVs sh-GPX4 , and D-EVs sh-CXCL10+GPX4 groups. (L-M) Confocal images showing GPX4 delivery from different EVs to senescent NPCs at 12h and 24h co-culture, and (N) colocalization analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.
Figure Legend Snippet: D-EVs Deliver GPX4 to Inhibit Ferroptosis in Senescent NPCs. (A) Representative Senescent-Tracker images of NPCs treated with N-EVs, D-EVs, Era, and D-Evs sh-CXCL10 . (B) Volcano plot of transcriptomic data comparing D-MSC and N-MSC. (C) KEGG pathway analysis of DEGs in D-MSCs versus N-MSCs. (D) Volcano plot of proteomic data comparing D-EVs and N-EVs. (E) KEGG pathway analysis of transcriptomic and proteomic data integration. (F) A Venn diagram illustrating the intersection of genes from the D-MSC transcriptome, the D-EVs proteome, and the ferroptosis-related gene set. (G) Bar graph showing the relative expression levels of core overlapping genes identified in (F). (H) MS analysis revealed that GPX4 is enriched in the D-EVs proteome. (I) Western blot analysis confirming GPX4 protein in D-EVs and N-EVs. (J) Western blot analysis of key senescence (p21, P16) markers in NPCs following treatment with PBS or N-EVs with CXCL10 or GPX4 knockout. (K) Representative images of EdU depicting cell proliferation ability in the control, TBHP, D-EVs, D-EVs sh-CXCL10 , D-EVs sh-GPX4 , and D-EVs sh-CXCL10+GPX4 groups. (L-M) Confocal images showing GPX4 delivery from different EVs to senescent NPCs at 12h and 24h co-culture, and (N) colocalization analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Techniques Used: Expressing, Western Blot, Knock-Out, Control, Co-Culture Assay

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Western Blot:

Article Title: Microneedles combining delivery of hUMSC-derived exosomes and EGCG mitigate UV-induced skin damage.
Article Snippet: .. Western blot analysis was performed to assess the expression of IL-1β (Cat# 16806-1-AP, 1:2000, Proteintech), CXCL10 (Cat# 10937-1-AP, 1:1000, Proteintech), TGF-β1 (Cat# ab215715, 1:1000, Abcam), and SOD2 (Cat# ab13533, 1:5000, Abcam). ..

Article Title: Microneedles combining delivery of hUMSC-derived exosomes and EGCG mitigate UV-induced skin damage
Article Snippet: .. Western blot analysis was performed to assess the expression of IL-1β (Cat# 16806-1-AP, 1:2000, Proteintech), CXCL10 (Cat# 10937-1-AP, 1:1000, Proteintech), TGF-β1 (Cat# ab215715, 1:1000, Abcam), and SOD2 (Cat# ab13533, 1:5000, Abcam). ..

Expressing:

Article Title: Microneedles combining delivery of hUMSC-derived exosomes and EGCG mitigate UV-induced skin damage.
Article Snippet: .. Western blot analysis was performed to assess the expression of IL-1β (Cat# 16806-1-AP, 1:2000, Proteintech), CXCL10 (Cat# 10937-1-AP, 1:1000, Proteintech), TGF-β1 (Cat# ab215715, 1:1000, Abcam), and SOD2 (Cat# ab13533, 1:5000, Abcam). ..

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Blocking Assay:

Article Title: Integrative mendelian randomization and multi-omics analysis reveal a gut microbiota-metabolite-CXCL10 axis in breast cancer
Article Snippet: For Western blot analysis, proteins were separated by SDS-PAGE and transferred onto PVDF membranes (Millipore, USA). .. After blocking with 10% skim milk for 1 h, membranes were incubated overnight at 4°C with primary antibodies against CXCR3 (1:1000, 26,756–1-AP, Proteintech, USA) and CXCL10 (1:1000, 10,937–1-AP, Proteintech, USA), followed by HRP-conjugated Goat Anti-Rabbit secondary antibody (1:5000, Beyotime, A0208). .. Bands were visualized using an ECL kit (Thermo Scientific, USA) and quantified with ImageJ software.

Incubation:

Article Title: Integrative mendelian randomization and multi-omics analysis reveal a gut microbiota-metabolite-CXCL10 axis in breast cancer
Article Snippet: For Western blot analysis, proteins were separated by SDS-PAGE and transferred onto PVDF membranes (Millipore, USA). .. After blocking with 10% skim milk for 1 h, membranes were incubated overnight at 4°C with primary antibodies against CXCR3 (1:1000, 26,756–1-AP, Proteintech, USA) and CXCL10 (1:1000, 10,937–1-AP, Proteintech, USA), followed by HRP-conjugated Goat Anti-Rabbit secondary antibody (1:5000, Beyotime, A0208). .. Bands were visualized using an ECL kit (Thermo Scientific, USA) and quantified with ImageJ software.

Article Title: Sympathetic nerve aggravates autoimmune skin disease via NE–adrenergic receptor axis: Neuroimmune cross-talk insights from vitiligo
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Article Title: Microenvironment-educated MSC-EVs loaded injectable smart hydrogel for targeting senescent nucleus pulposus cells and inhibiting ferroptosis against intervertebral disc degeneration
Article Snippet: .. After blocked with 5% non-fat milk for 2 h at room temperature, the membranes were incubated with primary antibodies against GAPDH (1:5000, 104941-AP, Proteintech), TSG101 (1:1000, DF8427, Affinity), CD9 (1:1000, AF5139, Affinity), CD63 (1:2000, 25682-1-AP, Proteintech), Calnexin (1:5000, 10427-2-AP, Proteintech), GM130 (1:20000, 11308-1-AP, Proteintech), CXCR3 (1:5000, 26756-1-AP, Proteintech), CXCL10 (1:2000, 10937-1-AP, Proteintech), MMP3 (1:2000, 17873-1-AP, Proteintech), ADAMTS5 (DF13268, Affinity), P16 (AF5484, Affinity), P21 (10355-1-AP, Proteintech), GPX4 (1:1000, 381958, Zen-bio), SLC7A11 (1:1000, 26864-1-AP, Proteintech), ACSL4 (1:5000, 22401-1-AP, Proteintech) and Tubulin (1:10000, T40103 , Abmart) overnight at 4 °C. .. After washing three times with TBST (Tris-buffered saline and 0.1% Tween 20), the membranes were incubated with secondary antibodies (1:5000, SA00001-2, SA00001-1, Proteintech) for 2 h at room temperature.

Article Title: Sympathetic nerve aggravates autoimmune skin disease via NE-adrenergic receptor axis: Neuroimmune cross-talk insights from vitiligo.
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Targeting Capability of D-EVs to Senescent NPCs is Mediated by the CXCL10-CXCR3 Axis. (A) Schematic diagram of RNA sequencing for senescent NPCs treated with D-EVs or not. (B-C) Volcano plots and heatmaps displaying differential gene expression in senescent NPCs treated with D-EVs or not. (D) A Venn diagram illustrates overlap between DEGs identified in senescent NPCs treated with D-EVs and key gene databases for cytokine-cytokine receptor interactions. (E) A Venn diagram illustrates overlap between DEGs identified in D-MSCs and chemokine signaling pathway key gene databases. (F-G) Network analysis of the hub genes among the above total DEGs. A protein-protein interaction network was created in the STRING database, while the Cytoscape software was used to determine the hub genes in the network. (H) GO analysis confirming enrichment of terms related to senescent NPCs treated with D-EVs or not in the BP categories. (I) GSEA analysis of cytokine-cytokine receptor interactions in D-EVs group versus TBHP group. (J) Western blot analysis confirmed the expression of CXCR3 in Control and senescent NPCs, and (S) quantitative analysis. (K) Western blot analysis confirmed the expression of CXCL10 in N-EVs and D-EVs, and (R) quantitative analysis. (L) Protein binding analysis of CXCR3 and CXCL10 by PyMOL. (M) Confocal analysis of the uptake of pHrodo-labeled EVs in senescent NPCs following the treatments of N-EVs, D-EVs with CXCL10 knockout/anti-CXCR3, or not, and (Q) quantitative analysis. (N) In vivo tracking of PKH26-labeled CXCL10 knockout D-EVs. (O) Flow cytometry showing uptake of different EVs with CXCL10 knockout/anti-CXCR3 or not by senescent NPCs, and (P) quantitative analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Journal: Bioactive Materials

Article Title: Microenvironment-educated MSC-EVs loaded injectable smart hydrogel for targeting senescent nucleus pulposus cells and inhibiting ferroptosis against intervertebral disc degeneration

doi: 10.1016/j.bioactmat.2026.02.030

Figure Lengend Snippet: Targeting Capability of D-EVs to Senescent NPCs is Mediated by the CXCL10-CXCR3 Axis. (A) Schematic diagram of RNA sequencing for senescent NPCs treated with D-EVs or not. (B-C) Volcano plots and heatmaps displaying differential gene expression in senescent NPCs treated with D-EVs or not. (D) A Venn diagram illustrates overlap between DEGs identified in senescent NPCs treated with D-EVs and key gene databases for cytokine-cytokine receptor interactions. (E) A Venn diagram illustrates overlap between DEGs identified in D-MSCs and chemokine signaling pathway key gene databases. (F-G) Network analysis of the hub genes among the above total DEGs. A protein-protein interaction network was created in the STRING database, while the Cytoscape software was used to determine the hub genes in the network. (H) GO analysis confirming enrichment of terms related to senescent NPCs treated with D-EVs or not in the BP categories. (I) GSEA analysis of cytokine-cytokine receptor interactions in D-EVs group versus TBHP group. (J) Western blot analysis confirmed the expression of CXCR3 in Control and senescent NPCs, and (S) quantitative analysis. (K) Western blot analysis confirmed the expression of CXCL10 in N-EVs and D-EVs, and (R) quantitative analysis. (L) Protein binding analysis of CXCR3 and CXCL10 by PyMOL. (M) Confocal analysis of the uptake of pHrodo-labeled EVs in senescent NPCs following the treatments of N-EVs, D-EVs with CXCL10 knockout/anti-CXCR3, or not, and (Q) quantitative analysis. (N) In vivo tracking of PKH26-labeled CXCL10 knockout D-EVs. (O) Flow cytometry showing uptake of different EVs with CXCL10 knockout/anti-CXCR3 or not by senescent NPCs, and (P) quantitative analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Article Snippet: After blocked with 5% non-fat milk for 2 h at room temperature, the membranes were incubated with primary antibodies against GAPDH (1:5000, 104941-AP, Proteintech), TSG101 (1:1000, DF8427, Affinity), CD9 (1:1000, AF5139, Affinity), CD63 (1:2000, 25682-1-AP, Proteintech), Calnexin (1:5000, 10427-2-AP, Proteintech), GM130 (1:20000, 11308-1-AP, Proteintech), CXCR3 (1:5000, 26756-1-AP, Proteintech), CXCL10 (1:2000, 10937-1-AP, Proteintech), MMP3 (1:2000, 17873-1-AP, Proteintech), ADAMTS5 (DF13268, Affinity), P16 (AF5484, Affinity), P21 (10355-1-AP, Proteintech), GPX4 (1:1000, 381958, Zen-bio), SLC7A11 (1:1000, 26864-1-AP, Proteintech), ACSL4 (1:5000, 22401-1-AP, Proteintech) and Tubulin (1:10000, T40103 , Abmart) overnight at 4 °C.

Techniques: RNA Sequencing, Gene Expression, Software, Western Blot, Expressing, Control, Protein Binding, Labeling, Knock-Out, In Vivo, Flow Cytometry

D-EVs Deliver GPX4 to Inhibit Ferroptosis in Senescent NPCs. (A) Representative Senescent-Tracker images of NPCs treated with N-EVs, D-EVs, Era, and D-Evs sh-CXCL10 . (B) Volcano plot of transcriptomic data comparing D-MSC and N-MSC. (C) KEGG pathway analysis of DEGs in D-MSCs versus N-MSCs. (D) Volcano plot of proteomic data comparing D-EVs and N-EVs. (E) KEGG pathway analysis of transcriptomic and proteomic data integration. (F) A Venn diagram illustrating the intersection of genes from the D-MSC transcriptome, the D-EVs proteome, and the ferroptosis-related gene set. (G) Bar graph showing the relative expression levels of core overlapping genes identified in (F). (H) MS analysis revealed that GPX4 is enriched in the D-EVs proteome. (I) Western blot analysis confirming GPX4 protein in D-EVs and N-EVs. (J) Western blot analysis of key senescence (p21, P16) markers in NPCs following treatment with PBS or N-EVs with CXCL10 or GPX4 knockout. (K) Representative images of EdU depicting cell proliferation ability in the control, TBHP, D-EVs, D-EVs sh-CXCL10 , D-EVs sh-GPX4 , and D-EVs sh-CXCL10+GPX4 groups. (L-M) Confocal images showing GPX4 delivery from different EVs to senescent NPCs at 12h and 24h co-culture, and (N) colocalization analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Journal: Bioactive Materials

Article Title: Microenvironment-educated MSC-EVs loaded injectable smart hydrogel for targeting senescent nucleus pulposus cells and inhibiting ferroptosis against intervertebral disc degeneration

doi: 10.1016/j.bioactmat.2026.02.030

Figure Lengend Snippet: D-EVs Deliver GPX4 to Inhibit Ferroptosis in Senescent NPCs. (A) Representative Senescent-Tracker images of NPCs treated with N-EVs, D-EVs, Era, and D-Evs sh-CXCL10 . (B) Volcano plot of transcriptomic data comparing D-MSC and N-MSC. (C) KEGG pathway analysis of DEGs in D-MSCs versus N-MSCs. (D) Volcano plot of proteomic data comparing D-EVs and N-EVs. (E) KEGG pathway analysis of transcriptomic and proteomic data integration. (F) A Venn diagram illustrating the intersection of genes from the D-MSC transcriptome, the D-EVs proteome, and the ferroptosis-related gene set. (G) Bar graph showing the relative expression levels of core overlapping genes identified in (F). (H) MS analysis revealed that GPX4 is enriched in the D-EVs proteome. (I) Western blot analysis confirming GPX4 protein in D-EVs and N-EVs. (J) Western blot analysis of key senescence (p21, P16) markers in NPCs following treatment with PBS or N-EVs with CXCL10 or GPX4 knockout. (K) Representative images of EdU depicting cell proliferation ability in the control, TBHP, D-EVs, D-EVs sh-CXCL10 , D-EVs sh-GPX4 , and D-EVs sh-CXCL10+GPX4 groups. (L-M) Confocal images showing GPX4 delivery from different EVs to senescent NPCs at 12h and 24h co-culture, and (N) colocalization analysis. The data were presented as mean ± SD. n = 3, ns, not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Article Snippet: After blocked with 5% non-fat milk for 2 h at room temperature, the membranes were incubated with primary antibodies against GAPDH (1:5000, 104941-AP, Proteintech), TSG101 (1:1000, DF8427, Affinity), CD9 (1:1000, AF5139, Affinity), CD63 (1:2000, 25682-1-AP, Proteintech), Calnexin (1:5000, 10427-2-AP, Proteintech), GM130 (1:20000, 11308-1-AP, Proteintech), CXCR3 (1:5000, 26756-1-AP, Proteintech), CXCL10 (1:2000, 10937-1-AP, Proteintech), MMP3 (1:2000, 17873-1-AP, Proteintech), ADAMTS5 (DF13268, Affinity), P16 (AF5484, Affinity), P21 (10355-1-AP, Proteintech), GPX4 (1:1000, 381958, Zen-bio), SLC7A11 (1:1000, 26864-1-AP, Proteintech), ACSL4 (1:5000, 22401-1-AP, Proteintech) and Tubulin (1:10000, T40103 , Abmart) overnight at 4 °C.

Techniques: Expressing, Western Blot, Knock-Out, Control, Co-Culture Assay

METTL3 K513 dimethylation suppresses type I IFN response and antitumor immune responses. A, GSEA of differentially expressed genes between METTL3 WT and METTL3 K513R cells based on prior sequencing data. NES, normalized enrichment score. B, IF staining using the J2 antibody to detect dsRNA levels in METTL3 WT and METTL3 K513R LoVo cells. C, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. D, Heatmap showing differential expression of ISGs in METTL3 WT and METTL3 K513R LoVo cells. E, ELISA analysis of IFNβ and CXCL10 secretion in METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells. F, Flow cytometry analysis of MHC-I expression in METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells. MFI, mean fluorescence intensity. G, Subcutaneous implantation of METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells into BALB/c mice ( n = 5). Representative bioluminescent images and tumor bioluminescence intensity. H, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in tumor-infiltrating lymphocytes (TIL) from subcutaneous tumors ( G ). I, Subcutaneous implantation of METTL3 WT and METTL3 K513R CT26 cells into NOD/SCID/IL2Rγ null (NCG) mice ( n = 5). Tumor volumes were monitored. Data information: All immunoblots were performed independently three times with similar results. Data are presented as mean ± SD. In E , F , and G , statistical analysis was performed using one-way ANOVA with the Tukey test. In H , statistical analysis was performed using two-way ANOVA with Tukey test. In I , statistical analysis was performed using the Student two-tailed t test. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Journal: Cancer Research

Article Title: METTL3 Methylation Induces Decay of Endogenous Retroelement Transcripts to Promote Tumor Immune Evasion

doi: 10.1158/0008-5472.CAN-25-2893

Figure Lengend Snippet: METTL3 K513 dimethylation suppresses type I IFN response and antitumor immune responses. A, GSEA of differentially expressed genes between METTL3 WT and METTL3 K513R cells based on prior sequencing data. NES, normalized enrichment score. B, IF staining using the J2 antibody to detect dsRNA levels in METTL3 WT and METTL3 K513R LoVo cells. C, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. D, Heatmap showing differential expression of ISGs in METTL3 WT and METTL3 K513R LoVo cells. E, ELISA analysis of IFNβ and CXCL10 secretion in METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells. F, Flow cytometry analysis of MHC-I expression in METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells. MFI, mean fluorescence intensity. G, Subcutaneous implantation of METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells into BALB/c mice ( n = 5). Representative bioluminescent images and tumor bioluminescence intensity. H, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in tumor-infiltrating lymphocytes (TIL) from subcutaneous tumors ( G ). I, Subcutaneous implantation of METTL3 WT and METTL3 K513R CT26 cells into NOD/SCID/IL2Rγ null (NCG) mice ( n = 5). Tumor volumes were monitored. Data information: All immunoblots were performed independently three times with similar results. Data are presented as mean ± SD. In E , F , and G , statistical analysis was performed using one-way ANOVA with the Tukey test. In H , statistical analysis was performed using two-way ANOVA with Tukey test. In I , statistical analysis was performed using the Student two-tailed t test. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Article Snippet: IFNβ and CXCL10 levels in conditioned media were quantified using the Mouse IFNβ Enzyme-Linked Immunosorbent Assay (ELISA) Kit (RK00420, ABclonal) and the Mouse CXCL10 ELISA Kit (RK00056, ABclonal) according to the manufacturer’s protocol.

Techniques: Sequencing, Staining, Quantitative Proteomics, Enzyme-linked Immunosorbent Assay, Flow Cytometry, Expressing, Fluorescence, Western Blot, Two Tailed Test

SETD1A mediates colorectal cancer immune evasion via METTL3 K513 dimethylation. A, IF staining using J2 antibody to detect dsRNA levels in control and SETD1A knockdown LoVo cells. B, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. C, qRT-PCR analysis of ISGs in control and SETD1A knockdown LoVo cells. D, ELISA analysis of IFNβ and CXCL10 secretion in control and SETD1A knockdown CT26 cells. E, Flow cytometry analysis of MHC-I expression in control and SETD1A knockdown CT26 cells. F, Subcutaneous implantation of control and SETD1A knockdown CT26 cells into BALB/c mice ( n = 5). Tumor volumes were monitored. G, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in tumor-infiltrating lymphocytes (TIL) from subcutaneous tumors ( F ). H, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. I, qRT-PCR analysis of ISGs in METTL3 WT and METTL3 K513R LoVo cells with or without SETD1A knockdown. J, Subcutaneous implantation of METTL3 WT and METTL3 K513R CT26 cells with or without SETD1A knockdown into BALB/c mice ( n = 5). Tumor volumes were monitored. K, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in TILs from subcutaneous tumors ( J ). Data information: All immunoblots were performed independently three times with similar results. Data are presented as mean ± SD. In C–E , G , I , and K , statistical analysis was performed using one-way ANOVA with the Tukey test. In F and J , statistical analysis was performed using two-way ANOVA with Tukey test. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001. NC, negative control.

Journal: Cancer Research

Article Title: METTL3 Methylation Induces Decay of Endogenous Retroelement Transcripts to Promote Tumor Immune Evasion

doi: 10.1158/0008-5472.CAN-25-2893

Figure Lengend Snippet: SETD1A mediates colorectal cancer immune evasion via METTL3 K513 dimethylation. A, IF staining using J2 antibody to detect dsRNA levels in control and SETD1A knockdown LoVo cells. B, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. C, qRT-PCR analysis of ISGs in control and SETD1A knockdown LoVo cells. D, ELISA analysis of IFNβ and CXCL10 secretion in control and SETD1A knockdown CT26 cells. E, Flow cytometry analysis of MHC-I expression in control and SETD1A knockdown CT26 cells. F, Subcutaneous implantation of control and SETD1A knockdown CT26 cells into BALB/c mice ( n = 5). Tumor volumes were monitored. G, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in tumor-infiltrating lymphocytes (TIL) from subcutaneous tumors ( F ). H, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. I, qRT-PCR analysis of ISGs in METTL3 WT and METTL3 K513R LoVo cells with or without SETD1A knockdown. J, Subcutaneous implantation of METTL3 WT and METTL3 K513R CT26 cells with or without SETD1A knockdown into BALB/c mice ( n = 5). Tumor volumes were monitored. K, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in TILs from subcutaneous tumors ( J ). Data information: All immunoblots were performed independently three times with similar results. Data are presented as mean ± SD. In C–E , G , I , and K , statistical analysis was performed using one-way ANOVA with the Tukey test. In F and J , statistical analysis was performed using two-way ANOVA with Tukey test. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001. NC, negative control.

Article Snippet: IFNβ and CXCL10 levels in conditioned media were quantified using the Mouse IFNβ Enzyme-Linked Immunosorbent Assay (ELISA) Kit (RK00420, ABclonal) and the Mouse CXCL10 ELISA Kit (RK00056, ABclonal) according to the manufacturer’s protocol.

Techniques: Staining, Control, Knockdown, Quantitative RT-PCR, Enzyme-linked Immunosorbent Assay, Flow Cytometry, Expressing, Western Blot, Negative Control

METTL3 K513 dimethylation suppresses type I IFN response and antitumor immune responses. A, GSEA of differentially expressed genes between METTL3 WT and METTL3 K513R cells based on prior sequencing data. NES, normalized enrichment score. B, IF staining using the J2 antibody to detect dsRNA levels in METTL3 WT and METTL3 K513R LoVo cells. C, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. D, Heatmap showing differential expression of ISGs in METTL3 WT and METTL3 K513R LoVo cells. E, ELISA analysis of IFNβ and CXCL10 secretion in METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells. F, Flow cytometry analysis of MHC-I expression in METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells. MFI, mean fluorescence intensity. G, Subcutaneous implantation of METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells into BALB/c mice ( n = 5). Representative bioluminescent images and tumor bioluminescence intensity. H, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in tumor-infiltrating lymphocytes (TIL) from subcutaneous tumors ( G ). I, Subcutaneous implantation of METTL3 WT and METTL3 K513R CT26 cells into NOD/SCID/IL2Rγ null (NCG) mice ( n = 5). Tumor volumes were monitored. Data information: All immunoblots were performed independently three times with similar results. Data are presented as mean ± SD. In E , F , and G , statistical analysis was performed using one-way ANOVA with the Tukey test. In H , statistical analysis was performed using two-way ANOVA with Tukey test. In I , statistical analysis was performed using the Student two-tailed t test. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Journal: Cancer Research

Article Title: METTL3 Methylation Induces Decay of Endogenous Retroelement Transcripts to Promote Tumor Immune Evasion

doi: 10.1158/0008-5472.CAN-25-2893

Figure Lengend Snippet: METTL3 K513 dimethylation suppresses type I IFN response and antitumor immune responses. A, GSEA of differentially expressed genes between METTL3 WT and METTL3 K513R cells based on prior sequencing data. NES, normalized enrichment score. B, IF staining using the J2 antibody to detect dsRNA levels in METTL3 WT and METTL3 K513R LoVo cells. C, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. D, Heatmap showing differential expression of ISGs in METTL3 WT and METTL3 K513R LoVo cells. E, ELISA analysis of IFNβ and CXCL10 secretion in METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells. F, Flow cytometry analysis of MHC-I expression in METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells. MFI, mean fluorescence intensity. G, Subcutaneous implantation of METTL3 KO, METTL3 WT, and METTL3 K513R CT26 cells into BALB/c mice ( n = 5). Representative bioluminescent images and tumor bioluminescence intensity. H, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in tumor-infiltrating lymphocytes (TIL) from subcutaneous tumors ( G ). I, Subcutaneous implantation of METTL3 WT and METTL3 K513R CT26 cells into NOD/SCID/IL2Rγ null (NCG) mice ( n = 5). Tumor volumes were monitored. Data information: All immunoblots were performed independently three times with similar results. Data are presented as mean ± SD. In E , F , and G , statistical analysis was performed using one-way ANOVA with the Tukey test. In H , statistical analysis was performed using two-way ANOVA with Tukey test. In I , statistical analysis was performed using the Student two-tailed t test. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Article Snippet: IFNβ and CXCL10 levels in conditioned media were quantified using the Mouse IFNβ Enzyme-Linked Immunosorbent Assay (ELISA) Kit (RK00420, ABclonal) and the Mouse CXCL10 ELISA Kit (RK00056, ABclonal) according to the manufacturer’s protocol.

Techniques: Sequencing, Staining, Quantitative Proteomics, Enzyme-linked Immunosorbent Assay, Flow Cytometry, Expressing, Fluorescence, Western Blot, Two Tailed Test

SETD1A mediates colorectal cancer immune evasion via METTL3 K513 dimethylation. A, IF staining using J2 antibody to detect dsRNA levels in control and SETD1A knockdown LoVo cells. B, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. C, qRT-PCR analysis of ISGs in control and SETD1A knockdown LoVo cells. D, ELISA analysis of IFNβ and CXCL10 secretion in control and SETD1A knockdown CT26 cells. E, Flow cytometry analysis of MHC-I expression in control and SETD1A knockdown CT26 cells. F, Subcutaneous implantation of control and SETD1A knockdown CT26 cells into BALB/c mice ( n = 5). Tumor volumes were monitored. G, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in tumor-infiltrating lymphocytes (TIL) from subcutaneous tumors ( F ). H, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. I, qRT-PCR analysis of ISGs in METTL3 WT and METTL3 K513R LoVo cells with or without SETD1A knockdown. J, Subcutaneous implantation of METTL3 WT and METTL3 K513R CT26 cells with or without SETD1A knockdown into BALB/c mice ( n = 5). Tumor volumes were monitored. K, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in TILs from subcutaneous tumors ( J ). Data information: All immunoblots were performed independently three times with similar results. Data are presented as mean ± SD. In C–E , G , I , and K , statistical analysis was performed using one-way ANOVA with the Tukey test. In F and J , statistical analysis was performed using two-way ANOVA with Tukey test. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001. NC, negative control.

Journal: Cancer Research

Article Title: METTL3 Methylation Induces Decay of Endogenous Retroelement Transcripts to Promote Tumor Immune Evasion

doi: 10.1158/0008-5472.CAN-25-2893

Figure Lengend Snippet: SETD1A mediates colorectal cancer immune evasion via METTL3 K513 dimethylation. A, IF staining using J2 antibody to detect dsRNA levels in control and SETD1A knockdown LoVo cells. B, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. C, qRT-PCR analysis of ISGs in control and SETD1A knockdown LoVo cells. D, ELISA analysis of IFNβ and CXCL10 secretion in control and SETD1A knockdown CT26 cells. E, Flow cytometry analysis of MHC-I expression in control and SETD1A knockdown CT26 cells. F, Subcutaneous implantation of control and SETD1A knockdown CT26 cells into BALB/c mice ( n = 5). Tumor volumes were monitored. G, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in tumor-infiltrating lymphocytes (TIL) from subcutaneous tumors ( F ). H, IB analysis of DNA and RNA sensors, along with signaling proteins involved in the type I IFN pathway. I, qRT-PCR analysis of ISGs in METTL3 WT and METTL3 K513R LoVo cells with or without SETD1A knockdown. J, Subcutaneous implantation of METTL3 WT and METTL3 K513R CT26 cells with or without SETD1A knockdown into BALB/c mice ( n = 5). Tumor volumes were monitored. K, Flow cytometric analysis of the proportions of CD8 + T cells, NK cells, and M1 and M2 macrophages in TILs from subcutaneous tumors ( J ). Data information: All immunoblots were performed independently three times with similar results. Data are presented as mean ± SD. In C–E , G , I , and K , statistical analysis was performed using one-way ANOVA with the Tukey test. In F and J , statistical analysis was performed using two-way ANOVA with Tukey test. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001. NC, negative control.

Article Snippet: IFNβ and CXCL10 levels in conditioned media were quantified using the Mouse IFNβ Enzyme-Linked Immunosorbent Assay (ELISA) Kit (RK00420, ABclonal) and the Mouse CXCL10 ELISA Kit (RK00056, ABclonal) according to the manufacturer’s protocol.

Techniques: Staining, Control, Knockdown, Quantitative RT-PCR, Enzyme-linked Immunosorbent Assay, Flow Cytometry, Expressing, Western Blot, Negative Control