timp 1 anti human mab rabbit (Cell Signaling Technology Inc)
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Timp 1 Anti Human Mab Rabbit, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 95/100, based on 96 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/timp+1+anti+human+mab+rabbit/TIMP1+Rabbit+mAb/pmc12866174-2-0-5
Average 95 stars, based on 96 article reviews
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1) Product Images from "Multimodal profiling of pancreatic cancer reveals a TIMP-1-dominated secretory profile determining pro-tumor immunoinstruction in human cancers"
Article Title: Multimodal profiling of pancreatic cancer reveals a TIMP-1-dominated secretory profile determining pro-tumor immunoinstruction in human cancers
Journal: Cell Reports Medicine
doi: 10.1016/j.xcrm.2025.102546
Figure Legend Snippet: snRNA-seq identifies epithelial-subtype-specific CISS upregulation toward TIMP-1 hi basal-like PDAC (A) UMAP embedding of PDAC patient tumor ( n = 17) snRNA-seq and post-hoc cell-type annotation. CAF, cancer-associated fibroblasts; VSMC, vascular smooth muscle cells. (B) Selected marker genes ( Z scores) and proportion of positive cells in indicated cell types. (C) Non-epithelial cell UMAP embeddings and post-hoc cell-type annotation (see B–S3F). (D) Epithelial cell UMAP embeddings and post-hoc cell-type annotation. (E) Selected marker genes ( Z scores) and proportion of positive cells in epithelial subsets. (F and G) RNA velocity analysis to infer transcriptional dynamics in acinar/ductal cells (F) and cell state progression across neoplastic/malignant cells (G). Statistics (G) by Kruskal-Wallis and Dunn’s test compared to PanIN. (H) CISS expression in epithelial subsets and induction compared to acinar cells by Kruskal-Wallis and Dunn’s test. (I) (Left) CISS factor expression in epithelial subsets normalized to acinar (mean ±95% CI). (Right) Heatmap and statistics of CISS factors by Kruskal-Wallis and Dunn’s test. (J) Normalized TIMP1 expression on the UMAP embedding. (K) (Left) TIMP1 prevalence within the CISS by comparing norm. CISS expression with TIMP1 (red) or without TIMP1 (black) (mean ±95% CI). Statistics by Mann-Whitney tests. (Right) Volcano plot of TIMP1 prevalence across epithelial clusters identified TIMP1 lo classical, TIMP1 int basal-like, and TIMP1 hi basal-like cancer cells. Groups identified by log2 fold-changes and significance of TIMP1 prevalences within CISS pattern (left). (L) TIMP1 expression and proportion of individual cell subtypes within epithelial compartment across patient tumors. For all statistics: n.s., non-significant; ∗ p < 0.05, ∗∗ p < 0.01; ∗∗∗ p < 0.001; ∗∗∗∗ p < 0.0001.
Techniques Used: Marker, Expressing, MANN-WHITNEY
Figure Legend Snippet: CISS-prevalent TIMP-1 is causal for PDAC-cell-induced NK cell suppression (A) PCA integrating epithelial (red) and immune (blue) cell fractions, fractions of CISS-expressing epithelial cells, and epithelial TIMP1 . (B) Pearson correlation between PCA-standardized variables (A) (∗ p < 0.05, ∗∗ p < 0.01; ∗∗∗ p < 0.001; ∗∗∗∗ p < 0.0001). (C) Comparison of correlations between epithelial and immune subtypes (A and B) by paired Student’s t test between indicated groups. (D–F) Workflow (D) to identify canonical pathways [GSEA; (E)] and immune cell profiles [CIBERSORTx; (F)] correlated with TIMP1 expression (TCGA-PAAD). For GSEA, genes were ranked by correlation coefficients (Spearman) with TIMP1 expression. Reference gene set: C2:CP. (G–I) Workflow (G) for MIA PaCa-2-cell-derived secreted factors suppressing NK cell killing of K562 targets (H) and degranulation (I) at indicated effector-to-target ratios (E:T). Comparison to control media [no cancer conditioning; shared with (O,P)] by unpaired Student’s t tests. (J) Workflow for CRISPR-Cas9-based TIMP-1 knockout in MIA PaCa-2 cells and RNA-seq. (K) PCA of RNA-seq data [ n = 3 per cell line; (J)]. (L) TIMP-1-dependent DEGs (DESeq2) in MIA PaCa-2 cells. Intersection shows DEGs between TIMP-1 WT and TIMP-1 KO (1 and 2) cells, independent of CRISPR-Cas9 (CRISPR Control). (M) GSEA of TIMP-1-dependent biological processes in MIA PaCa-2 cells. log2 fold-changes of DEGs (L) between means of TIMP-1-competent (“TIMP-1 WT”/“ CRISPR Control”) cells and TIMP-1-deficient (“TIMP-1 KO 1/2”) cells. Reference gene set: GO:BP. Enriched gene sets (FDR q < 0.05) were categorized (see G). (N–P) Workflow (N) of TIMP-1-dependent NK cell suppression of CRISPR-Cas9-derived MIA PaCa-2 cell lines (J) on K562 target cell killing (O) and degranulation (P) at indicated E:T. Statistics by one-way ANOVA and Tukey test for indicated groups. Data in (H, I, K, O, and P) showing biological replicates as box and whiskers plots (H, I, O, and P). (D, G, J, and N) Created with BioRender.com .
Techniques Used: Expressing, Comparison, Derivative Assay, Control, CRISPR, Knock-Out, RNA Sequencing
Figure Legend Snippet: CISS-prevalent TIMP-1 is sufficient to suppress cytotoxic capacity in NK cells via CD74 signaling (A–F) Workflow (A) to identify NK cell clusters in TUM Cohort (B, C, and F) and Steele Cohort (D and E). (B and D) NK cell UMAP embeddings, post-hoc annotations, and selected marker genes ( Z scores) (C and D, bottom). ctx, cytotoxicity. KLRC, killer cell lectin like receptor C gene family. (E and F, right) GZMB and PRF1 expression on the UMAP (B and D). (F, left) RNA velocity to infer transcriptional dynamics in NK cell clusters. (G–I) NK cell granzyme B and perforin levels upon exposure to (G) rhWT-TIMP-1 (granzyme B: UNT, n = 17; 50 ng/mL, n = 6; 100 ng/mL, n = 6; 250 ng/mL, n = 10; 500 ng/mL, n = 14; perforin: UNT, n = 12; 50 ng/mL, n = 6; 100 ng/mL, n = 6; 250 ng/mL, n = 6; 500 ng/mL, n = 11). (H) 500 ng/mL WT-TIMP-1 vs. equimolar N-TIMP-1 (granzyme B: UNT, n = 32; WT-TIMP-1, n = 30; N-TIMP-1, n = 24; perforin: UNT, n = 27; WT-TIMP-1, n = 27; N-TIMP-1, n = 24); (I) 500 ng/mL WT-TIMP-1 vs. equimolar N-TIMP-1 with or without α-CD74 antibody milatuzumab or immunoglobulin G (IgG) control (granzyme B: IgG alone, n = 23; IgG + WT-TIMP-1, n = 25; IgG + N-TIMP-1, n = 20; α-CD74 alone, n = 26; α-CD74 + WT-TIMP-1, n = 24; α-CD74 + N-TIMP-1, n = 20; perforin: IgG alone, n = 19; IgG + WT-TIMP-1, n = 20; IgG + N-TIMP-1, n = 20; α-CD74 alone, n = 19; α-CD74 + WT-TIMP-1, n = 20; α-CD74 + N-TIMP-1, n = 20). Data (G–I) pooled from four independent experiments show biological replicates (box and whiskers plots) derived from six healthy donors. Statistics by one-way ANOVA and Dunnett test (G) or one-way ANOVA and Tukey test (H and I) across indicated groups. (J and K) Proportions of NK (J) and epithelial (K) subsets within samples (TUM Cohort). (L) PCA of NK and epithelial subsets (J and K), NK cell CD74 , and cancer cell TIMP1 expression (small dots) across patients (large dots). Exp., expression. (M) Spearman correlation between TIMP1 hi basal-like cancer cells and ctx hi NK cells. (N) Inferred cancer cell-to-NK cell signaling by CellChat in tumors (J and K) (also see H). (A) Created with BioRender.com .
Techniques Used: Marker, Expressing, Control, Derivative Assay
Figure Legend Snippet: TIMP-1-dependent suppression of NK cell mTOR signaling links PDAC immunosuppression to clinical risk profiles (A–C) Workflow (A) to identify enriched pathways in NK_ctx hi C1 cluster vs. all other NK clusters in TUM Cohort (B) and Steele Cohort (C). DEGs (adj. p < 0.05) by Wilcoxon rank-sum test and auROC analysis. Mean odds ratios by pathway enrichment using Enrichr (Hallmark reference gene sets; see A and S6B , ). AKT, protein kinase B; IL-2, interleukin-2; mTORC1, mechanistic target of rapamycin complex 1; PI3K, phosphoinositide 3-kinase; STAT5, signal transducer and activator of transcription 5; UV, ultraviolet. (D–K) Workflow (D) to identify TIMP-1-dependent MIA PaCa-2-cell-mediated suppression of mTOR-signaling and IL-2 responses in NK cells, using co-culture [3 h (F); 24h (E and G)] or cancer-cell-conditioned media [24 h (H and I); 72 h (J and K)]. NK cell suppression with or without IL-2 activation assessed by (E) K562 killing (E:T 1:3; killing for 3 h); (F–H) p-mTOR(Ser2448)/p-S6(Ser235/236) signaling; (I) intracellular NK cell IFN-γ and TNF-α; (J) cell growth; (K) neutral lipid content; norm. to IL-2-free controls (H–J). Statistics between indicated groups: one-way ANOVA and Dunnett test (E–G, upper), one-way ANOVA and Tukey test (H, J, and K), unpaired Student’s t tests (E–G, lower; I). (L and M) NK cell (L) p-mTOR and (M) p-S6 levels upon exposure to rhWT-TIMP-1. Statistics by two-way ANOVA and Dunnett test. Data (E–M) shown as biological replicates [box and whiskers plots (E–I, and K–M) or mean ± SEM (J)]. (N–P) Cox-regression-based TIMP1 /NK risk score for recurrence-free (RFS) or metastasis-free survival (MFS) (TCGA-PAAD, n = 137), (N) For MFS, patient hazard ratios (HRs), and risk groups separated by quartiles. Statistics between linear predictors of TIMP1 expression and NK cell activity by Spearman correlation. (O) For MFS, survival probabilities by Kaplan-Meier curves (±95% CI). Statistics: global differences by KONP test, restricted mean survival time (RMST; τ = 0.9) between high (H) and low (L) risk groups by Wald test. (P) Heatmaps showing HRs (upper) and significance (lower) for the TIMP1 /NK score, both factors individually, and CISS by Cox regression analyses and G squared log likelihood ratio (∗ p < 0.05; ∗∗ p < 0.01). (A and D) Created with BioRender.com .
Techniques Used: Co-Culture Assay, Activation Assay, Expressing, Activity Assay
Figure Legend Snippet: Multikinase inhibition targets TIMP-1 and CISS and enhances NK cell cytotoxicity in TIMP1 hi /CISS hi basal-like PDAC in vivo (A) TIMP1 hi /CISS hi basal-like PDAC in patients based on TIMP1/CISS expression (see ). Statistics by Mann-Whitney tests. (B) Transcription factor targets (TFTs) and kinase perturbations correlated with TIMP1/CISS in basal-like PDAC. (Left) Genes correlating (Spearman; p < 0.05) with TIMP1 expression were ranked by coefficients for GSEA (reference: C3:TFT). DEGs (Wilcoxon rank-sum test and auROC analysis) between TIMP1 hi /CISS hi basal-like cancer and other epithelial cells tested for pathway enrichment by Enrichr (“Kinase perturbations from GEO UP” and “DOWN”). (C) UMAP embedding of TIMP1 expression (see J), ERK activity, and FGFR signaling. ERK activity (TFT:MAPK3_Target_Genes) and FGFR signaling (Reactome_Signaling_by_FGFR) calculated by UCell and correlated to TIMP1 expression (Spearman). (D) Western blot ( n = 3; biological replicates) of intracellular TIMP-1 in MIA PaCa-2 cells upon treatment with trametinib (T) and nintedanib (N). Statistics by one-way ANOVA and Dunnett test. (E) ZIP synergy map of TIMP-1 inhibition (intracellular TIMP-1) in MIA PaCa-2 cells using trametinib or nintedanib (see A). (F) Workflow to assess in vivo effect of trametinib, nintedanib, and a -PDL1 treatment on TIMP1/CISS and NK cells in orthotopic classical and basal-like PDAC transplantation mouse models. (G–J) UMAP embedding of all cells (G) or cancer cells (H) from scRNA-seq of PDAC tumors derived from (F) and post-hoc cell-type annotations (G), cancer cell type (H, upper), or Timp1 expression (H, lower). (I) Timp1 and (J) CISS expression in cancer cells. Statistics by Mann-Whitney tests. (K) CISS factors in PDAC cells upon indicated treatments vs. controls from snRNA-seq data (F–J). Changes in CISS factors calculated by pseudobulk limma-voom workflow. Statistics: one-way ANOVA for matched data (genes) and Dunnett test between indicated groups. (L and M) UMAP embedding of NK cell clusters (M) and proportions across treatments (F,G), assessed by frequencies (M, upper) and PCA (M, lower). (N and O) Pathways enriched (N; Enrichr using Hallmark reference gene set) and cytotoxicity gene expression (O) between treatment- enriched and - reduced NK clusters. Changes in cytotoxicity genes (O) calculated by Wilcoxon rank-sum test and auROC analysis. Statistics by paired Student’s t test. (F) Created with BioRender.com .
Techniques Used: Inhibition, In Vivo, Expressing, MANN-WHITNEY, Activity Assay, Western Blot, Transplantation Assay, Derivative Assay, Gene Expression