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mouse cxcl10/ip-10 elisa kit  (Multi Sciences (Lianke) Biotech Co Ltd)


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    Structured Review

    Multi Sciences (Lianke) Biotech Co Ltd mouse cxcl10/ip-10 elisa kit
    Mouse Cxcl10/Ip 10 Elisa Kit, supplied by Multi Sciences (Lianke) Biotech Co Ltd, used in various techniques. Bioz Stars score: 94/100, based on 58 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/cxcl10/Mouse+CXCL10%2FIP-10+ELISA+Kit/custom%40ek268%4042031161
    Average 94 stars, based on 58 article reviews
    mouse cxcl10/ip-10 elisa kit - by Bioz Stars, 2026-10
    94/100 stars

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    Related Articles

    Enzyme-linked Immunosorbent Assay:

    Article Title: Trigger inducible tertiary lymphoid structure formation using covalent organic frameworks for cancer immunotherapy.
    Article Snippet: The relative expression of different immune biomarkers across samples was analyzed using the Vectra Polaris system (PerkinElmer). .. The cytokine levels were measured using Mouse TNFα and IFNγ ELISA Kit (Servicebio), Mouse IL13, IL17, IL22, CXCL10, and IFN-β ELISA Kit (MULTI SCIENCES). .. For cell supernatant, the cytokine levels were measured using mouse CCL19 and CCL21 ELISA Kit (RUIXIN BIOTECH).

    Article Title: Cryptochrome 2 stabilization alleviates psoriasis by inhibiting keratinocyte hyperproliferation and inflammation.
    Article Snippet: Psoriasis, a chronic inflammatory skin disorder, is characterized by aberrant keratinocyte proliferation and immune dysregulation.. Although cryptochrome 2 (CRY2), a circadian rhythm regulator, has been implicated in inflammatory conditions, its role in the psoriasis pathogenesis remains elusive.. Here, we report a marked downregulation of CRY2 expression in psoriasis, which was reversed upon biological therapy, suggesting its pivotal involvement in disease progression.

    Article Title: Trigger inducible tertiary lymphoid structure formation using covalent organic frameworks for cancer immunotherapy
    Article Snippet: .. The cytokine levels were measured using Mouse TNFα and IFNγ ELISA Kit (Servicebio), Mouse IL13, IL17, IL22, CXCL10, and IFN-β ELISA Kit (MULTI SCIENCES). .. For cell supernatant, the cytokine levels were measured using mouse CCL19 and CCL21 ELISA Kit (RUIXIN BIOTECH).

    Article Title: Reconstituted CD74 + NK cells trigger chronic graft versus host disease after allogeneic bone marrow transplantation.
    Article Snippet: .. The following ELISA kits were used: GM-CSF, TGF-β, and CXCL10 (Multisciences); IFNγ and TNF-α (Dakewe). ..

    Article Title: Manganese improves CD8 + T cell recruitment via cGAS-STING in hepatocellular carcinoma.
    Article Snippet: Hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths worldwide.. Chemotherapy using cisplatin, a drug that damages deoxyribonucleic acid (DNA), is not very effective in treating HCC due to its side effects and drug resistance.. Manganese (Mn2+), a trace element, has been shown to enhance immune responses, but its ability to improve cisplatin-induced antitumor immunity in HCC remains unclear.

    Article Title: The TOPK inhibitor HI-TOPK-032 enhances CAR T-cell therapy of hepatocellular carcinoma by upregulating memory T cells
    Article Snippet: Chimeric antigen receptor (CAR) T cells are emerging as an effective antitumoral therapy.. However, their therapeutic effects on solid tumors are limited because of their short survival time and the immunosuppressive tumor microenvironment.. Memory T cells respond more vigorously and persist longer than their na€ ve/effector counterparts.

    Article Title: Immunostimulant Hydrogel-Guided Tumor Microenvironment Reprogramming to Efficiently Potentiate Macrophage-Mediated Cellular Phagocytosis for Systemic Cancer Immunotherapy.
    Article Snippet: Macrophage-mediated cellular phagocytosis (MMCP) plays a critical role in conducting antitumor immunotherapy but is usually impaired by the intrinsic phagocytosis evading ability of tumor cells and the immunosuppressive tumor microenvironment (TME).. Herein, a MMCP-boosting hydrogel (TCCaGM) was elaborately engineered by encapsulating granulocyte-macrophage colony-stimulating factor (GM-CSF) and a therapeutic nanoplatform (TCCaN) that preloaded with the tunicamycin (Tuni) and catalase (CAT) with the assistance of CaCO3 nanoparticles (NPs).. Strikingly, the hypoxic/acidic TME was efficiently alleviated by the engineered hydrogel, “eat me” signal calreticulin (CRT) was upregulated, while the “don’t eat me” signal CD47 was downregulated on tumor cells, and the infiltrated DCs were recruited and activated, all of which contributed to boosting the macrophage-mediated phagocytosis and initiating tumor-specific CD8+ T cells responses.

    other:

    Article Title: Trigger inducible tertiary lymphoid structure formation using covalent organic frameworks for cancer immunotherapy.
    Article Snippet: For cell supernatant, the cytokine levels were measured using mouse CCL19 and CCL21 ELISA Kit (RUIXIN BIOTECH).

    Cell Culture:

    Article Title: Manganese improves CD8 + T cell recruitment via cGAS-STING in hepatocellular carcinoma.
    Article Snippet: Hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths worldwide.. Chemotherapy using cisplatin, a drug that damages deoxyribonucleic acid (DNA), is not very effective in treating HCC due to its side effects and drug resistance.. Manganese (Mn2+), a trace element, has been shown to enhance immune responses, but its ability to improve cisplatin-induced antitumor immunity in HCC remains unclear.

    Concentration Assay:

    Article Title: The TOPK inhibitor HI-TOPK-032 enhances CAR T-cell therapy of hepatocellular carcinoma by upregulating memory T cells
    Article Snippet: Chimeric antigen receptor (CAR) T cells are emerging as an effective antitumoral therapy.. However, their therapeutic effects on solid tumors are limited because of their short survival time and the immunosuppressive tumor microenvironment.. Memory T cells respond more vigorously and persist longer than their na€ ve/effector counterparts.

    Bicinchoninic Acid Protein Assay:

    Article Title: The TOPK inhibitor HI-TOPK-032 enhances CAR T-cell therapy of hepatocellular carcinoma by upregulating memory T cells
    Article Snippet: Chimeric antigen receptor (CAR) T cells are emerging as an effective antitumoral therapy.. However, their therapeutic effects on solid tumors are limited because of their short survival time and the immunosuppressive tumor microenvironment.. Memory T cells respond more vigorously and persist longer than their na€ ve/effector counterparts.



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    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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    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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    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 <t>CXCL10</t> 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.
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    Image Search Results


    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