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cd8a ly 2 microbeads  (Miltenyi Biotec)


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    Miltenyi Biotec cd8a ly 2 microbeads
    scRNA-seq reveals differential immune infiltration in αOX40-treated tumors based on response (A) Schematic of the bilateral MC38 tumor model assessing αOX40 response. Humanized OX40 mice received three doses of αOX40, followed by resection of the left tumor for scRNA-seq and flow cytometry analysis. Contralateral tumor dynamics and survival were monitored longitudinally. (B) UMAP visualization of scRNA-seq data from immune cells in MC38-bearing mice following αOX40 treatment. Cells are color-coded by annotated cell type. (C) Heatmap depicting nine transcriptionally distinct immune cell subpopulations. (D) Pie chart shows the relative abundance of nine immune cell clusters in αOX40 responders and nonresponders. (E) Flow cytometry analysis of tumor-infiltrating immune cell frequencies in αOX40-treated MC38-bearing mice. Frequencies of CD4 + T cells, <t>CD8</t> + T cells, and macrophages were quantified after the third αOX40 dose (control, n = 5 mice; mice with a robust therapeutic response named as responder, n = 4 mice; mice with minimal to no response named as nonresponder, n = 4 mice). Data represent mean ± SD from one of two independent experiments (E). Statistical significance was determined using one-way ANOVA with multiple comparisons. ∗∗ p < 0.01.
    Cd8a Ly 2 Microbeads, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 96/100, based on 268 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/cd8a/CD8a+(Ly-2)+MicroBeads%2C+mouse/pmc13130681-53-0-5
    Average 96 stars, based on 268 article reviews
    cd8a ly 2 microbeads - by Bioz Stars, 2026-10
    96/100 stars

    Images

    1) Product Images from "Immunogenic tumor cell death and T-cell-derived IFN-γ elicit tumoricidal macrophages to potentiate OX40 immunotherapy"

    Article Title: Immunogenic tumor cell death and T-cell-derived IFN-γ elicit tumoricidal macrophages to potentiate OX40 immunotherapy

    Journal: Cell Reports Medicine

    doi: 10.1016/j.xcrm.2026.102699

    scRNA-seq reveals differential immune infiltration in αOX40-treated tumors based on response (A) Schematic of the bilateral MC38 tumor model assessing αOX40 response. Humanized OX40 mice received three doses of αOX40, followed by resection of the left tumor for scRNA-seq and flow cytometry analysis. Contralateral tumor dynamics and survival were monitored longitudinally. (B) UMAP visualization of scRNA-seq data from immune cells in MC38-bearing mice following αOX40 treatment. Cells are color-coded by annotated cell type. (C) Heatmap depicting nine transcriptionally distinct immune cell subpopulations. (D) Pie chart shows the relative abundance of nine immune cell clusters in αOX40 responders and nonresponders. (E) Flow cytometry analysis of tumor-infiltrating immune cell frequencies in αOX40-treated MC38-bearing mice. Frequencies of CD4 + T cells, CD8 + T cells, and macrophages were quantified after the third αOX40 dose (control, n = 5 mice; mice with a robust therapeutic response named as responder, n = 4 mice; mice with minimal to no response named as nonresponder, n = 4 mice). Data represent mean ± SD from one of two independent experiments (E). Statistical significance was determined using one-way ANOVA with multiple comparisons. ∗∗ p < 0.01.
    Figure Legend Snippet: scRNA-seq reveals differential immune infiltration in αOX40-treated tumors based on response (A) Schematic of the bilateral MC38 tumor model assessing αOX40 response. Humanized OX40 mice received three doses of αOX40, followed by resection of the left tumor for scRNA-seq and flow cytometry analysis. Contralateral tumor dynamics and survival were monitored longitudinally. (B) UMAP visualization of scRNA-seq data from immune cells in MC38-bearing mice following αOX40 treatment. Cells are color-coded by annotated cell type. (C) Heatmap depicting nine transcriptionally distinct immune cell subpopulations. (D) Pie chart shows the relative abundance of nine immune cell clusters in αOX40 responders and nonresponders. (E) Flow cytometry analysis of tumor-infiltrating immune cell frequencies in αOX40-treated MC38-bearing mice. Frequencies of CD4 + T cells, CD8 + T cells, and macrophages were quantified after the third αOX40 dose (control, n = 5 mice; mice with a robust therapeutic response named as responder, n = 4 mice; mice with minimal to no response named as nonresponder, n = 4 mice). Data represent mean ± SD from one of two independent experiments (E). Statistical significance was determined using one-way ANOVA with multiple comparisons. ∗∗ p < 0.01.

    Techniques Used: Flow Cytometry, Control, Clinical Proteomics

    NOS2-expressing macrophages is associated with response to αOX40 therapy (A) UMAP of monocytes/macrophages subclusters from scRNA-seq data in αOX40-treated MC38-bearing mice. (B) Representative marker genes in the monocyte/macrophage subclusters. (C) Pie chart showing the proportional distribution of monocyte/macrophage subsets of responders and nonresponders. (D) QuSAGE pathway analysis demonstrated enrichment of innate immune and phagocytic signaling pathways in distinct monocyte/macrophage subsets. (E) UMAP showing Mac_C1 signature genes and a heatmap of immune-related gene expression across TAM subclusters ( Z score normalized). (F) Violin plots comparing Nos2 expression levels in Mac_C1 subset between responsive and nonresponsive. (G) Flow cytometry analysis shows the percentage of M1-like (F4/80 + NOS2 + ) and M2-like (F4/80 + CD206 + ) macrophages in tumor tissues of control ( n = 5 mice), nonresponders (with minimal to no response, n = 4 mice), and responders (with a robust therapeutic response, n = 4 mice). (H and I) Comparison of Nos2 expression levels in responders versus nonresponders pre- or post-αOX40 treatment. Bilateral-MC38-bearing mice were treated with αOX40, and tumors from one side were analyzed by RNA-seq prior to (H) or following αOX40 treatment (I). The Nos2 expression was analyzed from RNA-seq data (left) and validated by RT-qPCR (right) ( n = 5 biological replicates). (J) NOS2 expression in tumor biopsies post-treatment determined by RNA-seq. Patients with advanced solid tumors and >1 prior therapy received HFB301001 monotherapy. Tumor biopsy samples were obtained on day 8 of cycle 2 for subsequent RNA-seq analysis. NOS2 expression were compared between patients achieving stable disease (SD, n = 3) and those with progressive disease (PD, n = 3). (K) GO enrichment analysis of upregulated genes in Mac_C1 of responders. (L) Calreticulin expression was quantified by flow cytometry in different response groups following αOX40 treatment ( n = 3 mice per group). (M) NOS2 expression in BMDMs was analyzed by flow cytometry after stimulation with CD8 + T cell supernatant and MC38 lysate, combined with TLR inhibition and IFN-γ blockade ( n = 5 biological replicates). (N) Quantification of Nos2 expression in BMDM by RT-qPCR after 24-h stimulation with MPLA (TLR4 agonist, 100 ng/mL), IFN-γ (20 ng/mL), or both. Data normalized to Gapdh and presented as fold-change relative to unstimulated controls ( n = 4 biological replicates). Data are shown as means ± SD from one of two independent experiments (G, H, I, L, M, and N). Statistical significance was determined using one-way ANOVA with multiple comparisons (G, L, M, and N) or using an unpaired two-tailed t test (H, I, and J). n.s., not significant; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; VST, variance stabilized transformation; sup., supernatant; lys., tumor lysate; inh., inhibitor.
    Figure Legend Snippet: NOS2-expressing macrophages is associated with response to αOX40 therapy (A) UMAP of monocytes/macrophages subclusters from scRNA-seq data in αOX40-treated MC38-bearing mice. (B) Representative marker genes in the monocyte/macrophage subclusters. (C) Pie chart showing the proportional distribution of monocyte/macrophage subsets of responders and nonresponders. (D) QuSAGE pathway analysis demonstrated enrichment of innate immune and phagocytic signaling pathways in distinct monocyte/macrophage subsets. (E) UMAP showing Mac_C1 signature genes and a heatmap of immune-related gene expression across TAM subclusters ( Z score normalized). (F) Violin plots comparing Nos2 expression levels in Mac_C1 subset between responsive and nonresponsive. (G) Flow cytometry analysis shows the percentage of M1-like (F4/80 + NOS2 + ) and M2-like (F4/80 + CD206 + ) macrophages in tumor tissues of control ( n = 5 mice), nonresponders (with minimal to no response, n = 4 mice), and responders (with a robust therapeutic response, n = 4 mice). (H and I) Comparison of Nos2 expression levels in responders versus nonresponders pre- or post-αOX40 treatment. Bilateral-MC38-bearing mice were treated with αOX40, and tumors from one side were analyzed by RNA-seq prior to (H) or following αOX40 treatment (I). The Nos2 expression was analyzed from RNA-seq data (left) and validated by RT-qPCR (right) ( n = 5 biological replicates). (J) NOS2 expression in tumor biopsies post-treatment determined by RNA-seq. Patients with advanced solid tumors and >1 prior therapy received HFB301001 monotherapy. Tumor biopsy samples were obtained on day 8 of cycle 2 for subsequent RNA-seq analysis. NOS2 expression were compared between patients achieving stable disease (SD, n = 3) and those with progressive disease (PD, n = 3). (K) GO enrichment analysis of upregulated genes in Mac_C1 of responders. (L) Calreticulin expression was quantified by flow cytometry in different response groups following αOX40 treatment ( n = 3 mice per group). (M) NOS2 expression in BMDMs was analyzed by flow cytometry after stimulation with CD8 + T cell supernatant and MC38 lysate, combined with TLR inhibition and IFN-γ blockade ( n = 5 biological replicates). (N) Quantification of Nos2 expression in BMDM by RT-qPCR after 24-h stimulation with MPLA (TLR4 agonist, 100 ng/mL), IFN-γ (20 ng/mL), or both. Data normalized to Gapdh and presented as fold-change relative to unstimulated controls ( n = 4 biological replicates). Data are shown as means ± SD from one of two independent experiments (G, H, I, L, M, and N). Statistical significance was determined using one-way ANOVA with multiple comparisons (G, L, M, and N) or using an unpaired two-tailed t test (H, I, and J). n.s., not significant; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001; VST, variance stabilized transformation; sup., supernatant; lys., tumor lysate; inh., inhibitor.

    Techniques Used: Expressing, Marker, Protein-Protein interactions, Gene Expression, Flow Cytometry, Control, Clinical Proteomics, Comparison, RNA Sequencing, Quantitative RT-PCR, Inhibition, Two Tailed Test, Transformation Assay

    The antitumor efficacy of the Combo therapy is contingent upon CD8 + T cells and macrophages (A) UMAP of scRNA-seq data from tumor-infiltrating immune cells in OX40-humanized MC38-bearing mice treated with MPLA, IFN-γ, αOX40, or Combo. Cells are color-coded by annotated cell type. (B) Bubble chart showing the top variable marker genes for identified immune cell types. (C) Pie chart shows the relative abundance of 11 immune cell clusters in control, αOX40, MPLA+IFN-γ, or Combo. (D) Macrophage frequency and absolute count in tumors of MC38-bearing mice after two and three treatment cycles with MPLA, IFN-γ, αOX40, or Combo, analyzed by flow cytometry ( n = 5 mice per group). (E) Schematic of CD8 + T cell depletion assay. (F) Tumor volume and survival were monitored. Kaplan-Meier survival analysis corresponding to the depletion study of CD8 + T cell ( n = 6 mice per group). (G) Schematic of macrophage depletion assay in early and late stage. (H and I) Tumor volume and survival were monitored. Kaplan-Meier survival analysis corresponding to the depletion study in (G) ( n = 6–10 mice per group). Data are shown as means ± SD from one of two independent experiments (D, F, H, and I). Statistical significance was determined using one-way ANOVA with Tukey’s multiple comparisons test (D). Log rank test was used (F, H, and I) for statistical comparison. n.s., not significant; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001.
    Figure Legend Snippet: The antitumor efficacy of the Combo therapy is contingent upon CD8 + T cells and macrophages (A) UMAP of scRNA-seq data from tumor-infiltrating immune cells in OX40-humanized MC38-bearing mice treated with MPLA, IFN-γ, αOX40, or Combo. Cells are color-coded by annotated cell type. (B) Bubble chart showing the top variable marker genes for identified immune cell types. (C) Pie chart shows the relative abundance of 11 immune cell clusters in control, αOX40, MPLA+IFN-γ, or Combo. (D) Macrophage frequency and absolute count in tumors of MC38-bearing mice after two and three treatment cycles with MPLA, IFN-γ, αOX40, or Combo, analyzed by flow cytometry ( n = 5 mice per group). (E) Schematic of CD8 + T cell depletion assay. (F) Tumor volume and survival were monitored. Kaplan-Meier survival analysis corresponding to the depletion study of CD8 + T cell ( n = 6 mice per group). (G) Schematic of macrophage depletion assay in early and late stage. (H and I) Tumor volume and survival were monitored. Kaplan-Meier survival analysis corresponding to the depletion study in (G) ( n = 6–10 mice per group). Data are shown as means ± SD from one of two independent experiments (D, F, H, and I). Statistical significance was determined using one-way ANOVA with Tukey’s multiple comparisons test (D). Log rank test was used (F, H, and I) for statistical comparison. n.s., not significant; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001.

    Techniques Used: Marker, Control, Flow Cytometry, Depletion Assay, Comparison

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    Cell Isolation:

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    Staining:

    Article Title: Stem-like precursors of exhausted Th cells upheld by a Tox-Myb-Eomes transcriptional hierarchy propagate Th cell responses in chronic infection.
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    Single Cell:

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    Amplification:

    Article Title: Stem-like precursors of exhausted Th cells upheld by a Tox-Myb-Eomes transcriptional hierarchy propagate Th cell responses in chronic infection.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Anti-Biotin microbeads Miltenyi Biotec Cat# 130-090-485; RRID: AB_244365 Anti-mouse CD4 Microbead Miltenyi Biotec Cat# 130-117-043 Anti-mouse CD8 Microbead Miltenyi Biotec Cat# 130-117-044 Anti-mouse CD19 Microbead Miltenyi Biotec Cat# 130-121-301 Percoll GE Healthcare Bioscience Cat# 17089101 Peroxidase-conjugated AffiniPure Goat Anti-Rat IgG Jackson ImmunoResearch Laboratories Cat# 112-035-003 Anti-VL-4 antibody BioXcell Cat# BE0106; RRID: AB_10949017 Triton X-100 Ajax Finechem Cat# AJA1552 O-phenylenediamine dihydrochloride Thermo Fisher Scientific Cat# P7288 H2O2 Perhydrol Sigma-Aldrich Cat# 7722-84-1 Na2HPO4 Sigma-Aldrich Cat# 7558-79-4 Citric Acid Sigma-Aldrich Cat# 251275 Critical commercial assays Naı̈ve CD4 T cell isolation kit Miltenyi Biotec Cat# 130-104-453 FOXP3 transcription factor staining buffer set ebioscience Cat# 00-5523-00 Chromium NEXT GEM Single Cell 5’ Kit v2 10x Genomics Cat# PN-1000263 Library Construction Kit 10x Genomics Cat# PN-1000190 Chromium Single Cell Mouse TCR Amplification Kit 10x Genomics Cat# PN-1000254 Dual Index Kit TN Set 10x Genomics Cat# PN-1000215 Dual Index Kit TT Set 10x Genomics Cat# PN-1000250 High Sensitivity D5000 Reagents Agilent Technologies Cat# 5067-5593 Deposited data Single cell-RNA sequencing raw data This paper GEO: GSE283820 Experimental models: Organisms/strains MybGFP Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Foxp3RFP Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Mybfl/flCd4Cre Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Mybfl/flCd4Cre SMARTA Axel Kallies lab, The Peter Doherty Institute, University of Melbourne N/A Mybfl/flERT2Cre Axel Kallies lab, The Peter Doherty Institute, University of Melbourne N/A Eomesfl/flCd4Cre Laura Mackay lab, The Peter Doherty Institute, University of Melbourne N/A ERT2Cre The Jackson laboratory N/A Cd4Cre The Jackson laboratory N/A SMARTA The Jackson laboratory N/A C57BL/6 The Peter Doherty Institute, University of Melbourne N/A Ly5.1 Australian Bio Resources/ Ozgene Animal Resources Centre N/A Oligonucleotides TOX sgRNA Synthego 1.CGAAGATTGTGGCATCAATG 2.AGCGGCCTGCCTCTGATATG Software and algorithms Flowjo 10.10.0 Flowjo, LLC RRID:SCR_008520 (Continued on next page) ll OPEN ACCESSArticle Immunity 59, 1–17.e1–e5, July 14, 2026 e2 ..

    Sequencing:

    Article Title: Stem-like precursors of exhausted Th cells upheld by a Tox-Myb-Eomes transcriptional hierarchy propagate Th cell responses in chronic infection.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Anti-Biotin microbeads Miltenyi Biotec Cat# 130-090-485; RRID: AB_244365 Anti-mouse CD4 Microbead Miltenyi Biotec Cat# 130-117-043 Anti-mouse CD8 Microbead Miltenyi Biotec Cat# 130-117-044 Anti-mouse CD19 Microbead Miltenyi Biotec Cat# 130-121-301 Percoll GE Healthcare Bioscience Cat# 17089101 Peroxidase-conjugated AffiniPure Goat Anti-Rat IgG Jackson ImmunoResearch Laboratories Cat# 112-035-003 Anti-VL-4 antibody BioXcell Cat# BE0106; RRID: AB_10949017 Triton X-100 Ajax Finechem Cat# AJA1552 O-phenylenediamine dihydrochloride Thermo Fisher Scientific Cat# P7288 H2O2 Perhydrol Sigma-Aldrich Cat# 7722-84-1 Na2HPO4 Sigma-Aldrich Cat# 7558-79-4 Citric Acid Sigma-Aldrich Cat# 251275 Critical commercial assays Naı̈ve CD4 T cell isolation kit Miltenyi Biotec Cat# 130-104-453 FOXP3 transcription factor staining buffer set ebioscience Cat# 00-5523-00 Chromium NEXT GEM Single Cell 5’ Kit v2 10x Genomics Cat# PN-1000263 Library Construction Kit 10x Genomics Cat# PN-1000190 Chromium Single Cell Mouse TCR Amplification Kit 10x Genomics Cat# PN-1000254 Dual Index Kit TN Set 10x Genomics Cat# PN-1000215 Dual Index Kit TT Set 10x Genomics Cat# PN-1000250 High Sensitivity D5000 Reagents Agilent Technologies Cat# 5067-5593 Deposited data Single cell-RNA sequencing raw data This paper GEO: GSE283820 Experimental models: Organisms/strains MybGFP Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Foxp3RFP Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Mybfl/flCd4Cre Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Mybfl/flCd4Cre SMARTA Axel Kallies lab, The Peter Doherty Institute, University of Melbourne N/A Mybfl/flERT2Cre Axel Kallies lab, The Peter Doherty Institute, University of Melbourne N/A Eomesfl/flCd4Cre Laura Mackay lab, The Peter Doherty Institute, University of Melbourne N/A ERT2Cre The Jackson laboratory N/A Cd4Cre The Jackson laboratory N/A SMARTA The Jackson laboratory N/A C57BL/6 The Peter Doherty Institute, University of Melbourne N/A Ly5.1 Australian Bio Resources/ Ozgene Animal Resources Centre N/A Oligonucleotides TOX sgRNA Synthego 1.CGAAGATTGTGGCATCAATG 2.AGCGGCCTGCCTCTGATATG Software and algorithms Flowjo 10.10.0 Flowjo, LLC RRID:SCR_008520 (Continued on next page) ll OPEN ACCESSArticle Immunity 59, 1–17.e1–e5, July 14, 2026 e2 ..

    Software:

    Article Title: Stem-like precursors of exhausted Th cells upheld by a Tox-Myb-Eomes transcriptional hierarchy propagate Th cell responses in chronic infection.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Anti-Biotin microbeads Miltenyi Biotec Cat# 130-090-485; RRID: AB_244365 Anti-mouse CD4 Microbead Miltenyi Biotec Cat# 130-117-043 Anti-mouse CD8 Microbead Miltenyi Biotec Cat# 130-117-044 Anti-mouse CD19 Microbead Miltenyi Biotec Cat# 130-121-301 Percoll GE Healthcare Bioscience Cat# 17089101 Peroxidase-conjugated AffiniPure Goat Anti-Rat IgG Jackson ImmunoResearch Laboratories Cat# 112-035-003 Anti-VL-4 antibody BioXcell Cat# BE0106; RRID: AB_10949017 Triton X-100 Ajax Finechem Cat# AJA1552 O-phenylenediamine dihydrochloride Thermo Fisher Scientific Cat# P7288 H2O2 Perhydrol Sigma-Aldrich Cat# 7722-84-1 Na2HPO4 Sigma-Aldrich Cat# 7558-79-4 Citric Acid Sigma-Aldrich Cat# 251275 Critical commercial assays Naı̈ve CD4 T cell isolation kit Miltenyi Biotec Cat# 130-104-453 FOXP3 transcription factor staining buffer set ebioscience Cat# 00-5523-00 Chromium NEXT GEM Single Cell 5’ Kit v2 10x Genomics Cat# PN-1000263 Library Construction Kit 10x Genomics Cat# PN-1000190 Chromium Single Cell Mouse TCR Amplification Kit 10x Genomics Cat# PN-1000254 Dual Index Kit TN Set 10x Genomics Cat# PN-1000215 Dual Index Kit TT Set 10x Genomics Cat# PN-1000250 High Sensitivity D5000 Reagents Agilent Technologies Cat# 5067-5593 Deposited data Single cell-RNA sequencing raw data This paper GEO: GSE283820 Experimental models: Organisms/strains MybGFP Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Foxp3RFP Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Mybfl/flCd4Cre Stephen L. Nutt lab, Walter and Eliza Hall Institute of Medical Research N/A Mybfl/flCd4Cre SMARTA Axel Kallies lab, The Peter Doherty Institute, University of Melbourne N/A Mybfl/flERT2Cre Axel Kallies lab, The Peter Doherty Institute, University of Melbourne N/A Eomesfl/flCd4Cre Laura Mackay lab, The Peter Doherty Institute, University of Melbourne N/A ERT2Cre The Jackson laboratory N/A Cd4Cre The Jackson laboratory N/A SMARTA The Jackson laboratory N/A C57BL/6 The Peter Doherty Institute, University of Melbourne N/A Ly5.1 Australian Bio Resources/ Ozgene Animal Resources Centre N/A Oligonucleotides TOX sgRNA Synthego 1.CGAAGATTGTGGCATCAATG 2.AGCGGCCTGCCTCTGATATG Software and algorithms Flowjo 10.10.0 Flowjo, LLC RRID:SCR_008520 (Continued on next page) ll OPEN ACCESSArticle Immunity 59, 1–17.e1–e5, July 14, 2026 e2 ..

    Isolation:

    Article Title: Synergistic immunotherapy of NSCLC enabled by a biomimetic nanodelivery system for autophagy-mediated MDSC reprogramming and metabolic modulation.
    Article Snippet: The immunosuppressive tumor microenvironment (TME) in non-small cell lung cancer (NSCLC), particularly the dominance of myeloid-derived suppressor cells (MDSCs), remains a major barrier to effective immunotherapy.. Here, we developed a bioengineered nanoplatform (PD-L1-SSD@NPs) by conjugating an anti-PD-L1 antibody to hollow mesoporous silica nanoparticles for the targeted delivery of saikosaponin D (SSD) to PD-L1-high MDSCs.. This strategy nanoplatform enhanced SSD delivery and activated autophagic flux in MDSCs, thereby reprogramming them from an immunosuppressive phenotype toward an immune-activating state.

    Activation Assay:

    Article Title: Synergistic immunotherapy of NSCLC enabled by a biomimetic nanodelivery system for autophagy-mediated MDSC reprogramming and metabolic modulation.
    Article Snippet: The immunosuppressive tumor microenvironment (TME) in non-small cell lung cancer (NSCLC), particularly the dominance of myeloid-derived suppressor cells (MDSCs), remains a major barrier to effective immunotherapy.. Here, we developed a bioengineered nanoplatform (PD-L1-SSD@NPs) by conjugating an anti-PD-L1 antibody to hollow mesoporous silica nanoparticles for the targeted delivery of saikosaponin D (SSD) to PD-L1-high MDSCs.. This strategy nanoplatform enhanced SSD delivery and activated autophagic flux in MDSCs, thereby reprogramming them from an immunosuppressive phenotype toward an immune-activating state.

    Selection:

    Article Title: Synergistic immunotherapy of NSCLC enabled by a biomimetic nanodelivery system for autophagy-mediated MDSC reprogramming and metabolic modulation.
    Article Snippet: The immunosuppressive tumor microenvironment (TME) in non-small cell lung cancer (NSCLC), particularly the dominance of myeloid-derived suppressor cells (MDSCs), remains a major barrier to effective immunotherapy.. Here, we developed a bioengineered nanoplatform (PD-L1-SSD@NPs) by conjugating an anti-PD-L1 antibody to hollow mesoporous silica nanoparticles for the targeted delivery of saikosaponin D (SSD) to PD-L1-high MDSCs.. This strategy nanoplatform enhanced SSD delivery and activated autophagic flux in MDSCs, thereby reprogramming them from an immunosuppressive phenotype toward an immune-activating state.

    Magnetic Cell Separation:

    Article Title: Synergistic immunotherapy of NSCLC enabled by a biomimetic nanodelivery system for autophagy-mediated MDSC reprogramming and metabolic modulation.
    Article Snippet: The immunosuppressive tumor microenvironment (TME) in non-small cell lung cancer (NSCLC), particularly the dominance of myeloid-derived suppressor cells (MDSCs), remains a major barrier to effective immunotherapy.. Here, we developed a bioengineered nanoplatform (PD-L1-SSD@NPs) by conjugating an anti-PD-L1 antibody to hollow mesoporous silica nanoparticles for the targeted delivery of saikosaponin D (SSD) to PD-L1-high MDSCs.. This strategy nanoplatform enhanced SSD delivery and activated autophagic flux in MDSCs, thereby reprogramming them from an immunosuppressive phenotype toward an immune-activating state.



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    Figure Lengend Snippet: Proangiogenic and immunosuppression phenotype of TANs in the CRLM microenvironment. A, Heatmap showing signature scores for angiogenesis, myeloid cell recruitment, neutrophil cytotoxicity, MDSC, and NET across each TAN and PMN subset. B, Comparison of angiogenesis, myeloid cell recruitment, MDSC, and NET signature scores among TAN and PMN subsets. C, Dot plot illustrating expression levels of major cytokines and chemokines in each TAN and PMN subset. D, Representative IHC images of CD31 staining in CRLM tissues. Scale bars, 50 µm. E, Correlation analysis between CD31 and TAN1 density using Spearman’s rank correlation ( n = 102). F, Representative images and quantification of tube formation in HUVECs when cocultured with conditioned medium from human LGALS3 − neutrophils or LGALS3 + neutrophils ( n = 6). G, UMAP plot showing six monocyte/macrophage subsets across colorectal cancer, adjacent liver tissues, CRLM, and PB samples. H, Shell-like plot depicting ligand–receptor interaction strength between TAN1_LGASL3 and neutrophil/monocyte/macrophage subset in CRLM. I, Selected ligand–receptor interactions between TAN1_LGASL3 and neutrophil/monocyte/macrophage subset in CRLM. J, Representative mIHC images of CD68, CCL3L1, CD66b, CCR1, and BHLHE40 in CRLM. Scale bars, 50 µm. K, Representative images of macrophage migration assays and effects of conditioned medium from human LGALS3 + neutrophils on migration of macrophages (induced from THP-1 cells) in the presence of CCR1 inhibitor (BX471) or anti-CCL3 antibody ( n = 6). L, Comparison of immunosuppressive macrophage signature scores between colorectal cancer and CRLM. M, Schematic of the CRLM mouse model. C57BL/6 mice received intrasplenic injections of mouse colorectal cancer cells (MC38). Mice were subsequently treated with IgG control (IgG; n = 6), anti-Ly6G antibody (anti-Ly6G; n = 6), or anti-Ly6G plus anti-CD8a antibodies (anti-Ly6G + anti-CD8a; n = 6). Livers were harvested on day 14. N, Representative images of liver metastases from IgG, anti-Ly6G, and anti-Ly6G + anti-CD8a groups. O, Comparison of liver weights among the three groups. P values were calculated by the Wilcoxon rank-sum test ( B and L ) and unpaired Student t test ( F , K , and O ). *, P < 0.05; **, P < 0.01; ***, P < 0.001. CRC, colorectal cancer; Ctrl, control.

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