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incubation with anti igf1  (R&D Systems)


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    R&D Systems incubation with anti igf1
    Incubation With Anti Igf1, supplied by R&D Systems, used in various techniques. Bioz Stars score: 93/100, based on 107 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    R&D Systems incubation with anti igf1
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    Santa Cruz Biotechnology mouse monoclonal anti igf1
    <t>IGF1</t> promotes the secretion of AGR2, which in turn enhances the presentation of the IGF1R on the cell surface (A) The Venn diagram of the upper panel illustrates the count of genes down-regulated in Capan2 and Panc1 cells post AGR2 knockout. The Gene Ontology (GO) analysis of the lower panel identifies enriched biological processes, notably “regulation of IGF receptor signaling pathway” at transcriptional levels, after AGR2 knockout in these cell lines. (B) Western blot and quantitative reverse-transcription PCR (qRT-PCR) analyses assess IGF1R and AGR2 expression in Capan2 and Panc1 cells following AGR2 knockout via the CRISPR-Cas9 system (performed in triplicate). (C) Flow cytometry (FACS) quantifies cell membrane surface expression of IGF1R in Capan2 and Panc1 cells after AGR2 knockout (performed in triplicate). (D) Co-immunoprecipitation assays reveal AGR2’s interaction with pro-IGF1R in Capan2 and Panc1 cells (performed in triplicate). (E) Immunofluorescence imaging displays AGR2 and IGF1R distribution and ER labeling in Panc1 cells (scale bars: 50 μm). (F) Western blot analysis of IGF1R and AGR2 in Panc1 and Capan2 cells with controls (original cell lines), AGR2-knockout (AGR2 KO ) post-expression of AGR2 WT , AGR2 ΔNLS , AGR2 ΔSP , and AGR2 C81A mutation (performed in triplicate). (G) Western blot analysis of IGF1R expression in AGR2 in Panc1 and Capan2 cells with AGR2 knockout (KO) treated with 3-methyladenine (3-MA) (15 mM), bafilomycin A1 (30 nM), chloroquine (20 mM), MLN4929 (1 mM), or MG132 (5 mM) for 12 h (performed in triplicate). (H) Western blot analysis of IGF1R, phosphorylated IGF1R, c-JUN, phosphorylated c-JUN, and AGR2 following 12 h of serum starvation and subsequent IGF1 stimulation (50 ng/mL, performed in triplicate). (I) ELISA measures AGR2 secretion after serum starvation and treatment with PPP (1 μM) and IGF1 (50 ng/mL) over time (performed in triplicate). (J) Identification of potential c-JUN-binding sites within the AGR2 promoter region. (K) Western blot analysis of c-JUN, phosphorylated c-JUN, and AGR2 expression following c-JUN knockdown and IGF1 stimulation over time (performed in triplicate). (L) Western blot shows c-JUN, phosphorylated c-JUN, and AGR2 expression post anisomycin treatment over time (performed in triplicate). (M) Chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR) demonstrates c-JUN enrichment at AGR2’s transcription start sites (TSSs) before and after IGF1 treatment (performed in triplicate). (N) Integrative Genomics Viewer (IGV) tracks display c-JUN peaks in AGR2’s promoter region post IGF1 treatment. (O) Dual-luciferase reporter assays in Capan2 and Panc1 cells evaluate AGR2 promoter activity under various lengths and site-specific mutations after IGF1 treatment (performed in triplicate). Statistical analyses: (B) and (C) used a one-way ANOVA with multiple comparisons. (I), (M), (N), and (O) were analyzed using two-tailed, unpaired Student’s t tests. Data are presented as mean ± SD, with significance marked as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and “ns” indicates no significance.
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    OriGene igf1
    A Differences in cellular composition between the proliferative- ( n = 4) and secretory phases ( n = 3) of the menstrual cycle based on scRNA-seq data (two-sided t -test). Data are represented using a boxplot showing the median and first and third quantile. N describes the number of patients/ samples for each respective menstrual cycle phase. SE1 p-value < 0.0018, SE2 p -value < 0.0035. B Representative OVGP1 immunohistochemistry in the fallopian tube of patients in the proliferative phase ( n = 2) and in the secretory phase ( n = 2). C Scatter plot comparing gene expression levels of pre-menopausal SE1 (secretory phase) and SE2 cells (proliferative phase) using pseudo-bulk RNA analysis. D Volcano plot derived from pseudo bulk analysis. The volcano plot shows the differential gene expression analysis of genes expressed in SE cells (SE 1/2/3-pre) based on the proliferative and secretory phases. E Number of differentially expressed genes between the proliferative- and secretory phases of the menstrual cycle by cell clusters based on scRNA-seq data. F Dot plot showing normalized scRNA-seq derived gene expression levels of selected genes that differ in the proliferative and secretory phase in ST subtypes. G Representative immunofluorescence staining of <t>IGF1</t> and IGF2 in primary human stromal and epithelial fallopian cell co-culture of one patient ( n = 3). The co-culture was stimulated for 8 h with estrogen (E4) or progesterone (P4). IGF1 protein in green, IGF2 protein in red and nuclei/ DAPI in blue. White dotted lines mark epithelial cells while white stars mark stromal cells. H Ligand-receptor interactions, detected by CellPhoneDB, between SE and ST subtypes (left) and between SE cells (right) separated by the menstrual phase using scRNA-seq data. I RNA velocity analysis of SE1- and SE2-pre cells. Arrows indicate the location of the estimated future cell state. Long vectors mark rapid transition events (i.e., large changes in gene expression), while short arrows indicate homeostasis. J Median latent time for pre-menopausal SE cells during the proliferative- and secretory phase of the menstrual cycle, highlighting temporal positions for SE1- and SE2-pre.
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    Proteintech igf 1
    A Differences in cellular composition between the proliferative- ( n = 4) and secretory phases ( n = 3) of the menstrual cycle based on scRNA-seq data (two-sided t -test). Data are represented using a boxplot showing the median and first and third quantile. N describes the number of patients/ samples for each respective menstrual cycle phase. SE1 p-value < 0.0018, SE2 p -value < 0.0035. B Representative OVGP1 immunohistochemistry in the fallopian tube of patients in the proliferative phase ( n = 2) and in the secretory phase ( n = 2). C Scatter plot comparing gene expression levels of pre-menopausal SE1 (secretory phase) and SE2 cells (proliferative phase) using pseudo-bulk RNA analysis. D Volcano plot derived from pseudo bulk analysis. The volcano plot shows the differential gene expression analysis of genes expressed in SE cells (SE 1/2/3-pre) based on the proliferative and secretory phases. E Number of differentially expressed genes between the proliferative- and secretory phases of the menstrual cycle by cell clusters based on scRNA-seq data. F Dot plot showing normalized scRNA-seq derived gene expression levels of selected genes that differ in the proliferative and secretory phase in ST subtypes. G Representative immunofluorescence staining of <t>IGF1</t> and IGF2 in primary human stromal and epithelial fallopian cell co-culture of one patient ( n = 3). The co-culture was stimulated for 8 h with estrogen (E4) or progesterone (P4). IGF1 protein in green, IGF2 protein in red and nuclei/ DAPI in blue. White dotted lines mark epithelial cells while white stars mark stromal cells. H Ligand-receptor interactions, detected by CellPhoneDB, between SE and ST subtypes (left) and between SE cells (right) separated by the menstrual phase using scRNA-seq data. I RNA velocity analysis of SE1- and SE2-pre cells. Arrows indicate the location of the estimated future cell state. Long vectors mark rapid transition events (i.e., large changes in gene expression), while short arrows indicate homeostasis. J Median latent time for pre-menopausal SE cells during the proliferative- and secretory phase of the menstrual cycle, highlighting temporal positions for SE1- and SE2-pre.
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    A Differences in cellular composition between the proliferative- ( n = 4) and secretory phases ( n = 3) of the menstrual cycle based on scRNA-seq data (two-sided t -test). Data are represented using a boxplot showing the median and first and third quantile. N describes the number of patients/ samples for each respective menstrual cycle phase. SE1 p-value < 0.0018, SE2 p -value < 0.0035. B Representative OVGP1 immunohistochemistry in the fallopian tube of patients in the proliferative phase ( n = 2) and in the secretory phase ( n = 2). C Scatter plot comparing gene expression levels of pre-menopausal SE1 (secretory phase) and SE2 cells (proliferative phase) using pseudo-bulk RNA analysis. D Volcano plot derived from pseudo bulk analysis. The volcano plot shows the differential gene expression analysis of genes expressed in SE cells (SE 1/2/3-pre) based on the proliferative and secretory phases. E Number of differentially expressed genes between the proliferative- and secretory phases of the menstrual cycle by cell clusters based on scRNA-seq data. F Dot plot showing normalized scRNA-seq derived gene expression levels of selected genes that differ in the proliferative and secretory phase in ST subtypes. G Representative immunofluorescence staining of <t>IGF1</t> and IGF2 in primary human stromal and epithelial fallopian cell co-culture of one patient ( n = 3). The co-culture was stimulated for 8 h with estrogen (E4) or progesterone (P4). IGF1 protein in green, IGF2 protein in red and nuclei/ DAPI in blue. White dotted lines mark epithelial cells while white stars mark stromal cells. H Ligand-receptor interactions, detected by CellPhoneDB, between SE and ST subtypes (left) and between SE cells (right) separated by the menstrual phase using scRNA-seq data. I RNA velocity analysis of SE1- and SE2-pre cells. Arrows indicate the location of the estimated future cell state. Long vectors mark rapid transition events (i.e., large changes in gene expression), while short arrows indicate homeostasis. J Median latent time for pre-menopausal SE cells during the proliferative- and secretory phase of the menstrual cycle, highlighting temporal positions for SE1- and SE2-pre.
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    A Differences in cellular composition between the proliferative- ( n = 4) and secretory phases ( n = 3) of the menstrual cycle based on scRNA-seq data (two-sided t -test). Data are represented using a boxplot showing the median and first and third quantile. N describes the number of patients/ samples for each respective menstrual cycle phase. SE1 p-value < 0.0018, SE2 p -value < 0.0035. B Representative OVGP1 immunohistochemistry in the fallopian tube of patients in the proliferative phase ( n = 2) and in the secretory phase ( n = 2). C Scatter plot comparing gene expression levels of pre-menopausal SE1 (secretory phase) and SE2 cells (proliferative phase) using pseudo-bulk RNA analysis. D Volcano plot derived from pseudo bulk analysis. The volcano plot shows the differential gene expression analysis of genes expressed in SE cells (SE 1/2/3-pre) based on the proliferative and secretory phases. E Number of differentially expressed genes between the proliferative- and secretory phases of the menstrual cycle by cell clusters based on scRNA-seq data. F Dot plot showing normalized scRNA-seq derived gene expression levels of selected genes that differ in the proliferative and secretory phase in ST subtypes. G Representative immunofluorescence staining of <t>IGF1</t> and IGF2 in primary human stromal and epithelial fallopian cell co-culture of one patient ( n = 3). The co-culture was stimulated for 8 h with estrogen (E4) or progesterone (P4). IGF1 protein in green, IGF2 protein in red and nuclei/ DAPI in blue. White dotted lines mark epithelial cells while white stars mark stromal cells. H Ligand-receptor interactions, detected by CellPhoneDB, between SE and ST subtypes (left) and between SE cells (right) separated by the menstrual phase using scRNA-seq data. I RNA velocity analysis of SE1- and SE2-pre cells. Arrows indicate the location of the estimated future cell state. Long vectors mark rapid transition events (i.e., large changes in gene expression), while short arrows indicate homeostasis. J Median latent time for pre-menopausal SE cells during the proliferative- and secretory phase of the menstrual cycle, highlighting temporal positions for SE1- and SE2-pre.
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    A Differences in cellular composition between the proliferative- ( n = 4) and secretory phases ( n = 3) of the menstrual cycle based on scRNA-seq data (two-sided t -test). Data are represented using a boxplot showing the median and first and third quantile. N describes the number of patients/ samples for each respective menstrual cycle phase. SE1 p-value < 0.0018, SE2 p -value < 0.0035. B Representative OVGP1 immunohistochemistry in the fallopian tube of patients in the proliferative phase ( n = 2) and in the secretory phase ( n = 2). C Scatter plot comparing gene expression levels of pre-menopausal SE1 (secretory phase) and SE2 cells (proliferative phase) using pseudo-bulk RNA analysis. D Volcano plot derived from pseudo bulk analysis. The volcano plot shows the differential gene expression analysis of genes expressed in SE cells (SE 1/2/3-pre) based on the proliferative and secretory phases. E Number of differentially expressed genes between the proliferative- and secretory phases of the menstrual cycle by cell clusters based on scRNA-seq data. F Dot plot showing normalized scRNA-seq derived gene expression levels of selected genes that differ in the proliferative and secretory phase in ST subtypes. G Representative immunofluorescence staining of <t>IGF1</t> and IGF2 in primary human stromal and epithelial fallopian cell co-culture of one patient ( n = 3). The co-culture was stimulated for 8 h with estrogen (E4) or progesterone (P4). IGF1 protein in green, IGF2 protein in red and nuclei/ DAPI in blue. White dotted lines mark epithelial cells while white stars mark stromal cells. H Ligand-receptor interactions, detected by CellPhoneDB, between SE and ST subtypes (left) and between SE cells (right) separated by the menstrual phase using scRNA-seq data. I RNA velocity analysis of SE1- and SE2-pre cells. Arrows indicate the location of the estimated future cell state. Long vectors mark rapid transition events (i.e., large changes in gene expression), while short arrows indicate homeostasis. J Median latent time for pre-menopausal SE cells during the proliferative- and secretory phase of the menstrual cycle, highlighting temporal positions for SE1- and SE2-pre.
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    A Differences in cellular composition between the proliferative- ( n = 4) and secretory phases ( n = 3) of the menstrual cycle based on scRNA-seq data (two-sided t -test). Data are represented using a boxplot showing the median and first and third quantile. N describes the number of patients/ samples for each respective menstrual cycle phase. SE1 p-value < 0.0018, SE2 p -value < 0.0035. B Representative OVGP1 immunohistochemistry in the fallopian tube of patients in the proliferative phase ( n = 2) and in the secretory phase ( n = 2). C Scatter plot comparing gene expression levels of pre-menopausal SE1 (secretory phase) and SE2 cells (proliferative phase) using pseudo-bulk RNA analysis. D Volcano plot derived from pseudo bulk analysis. The volcano plot shows the differential gene expression analysis of genes expressed in SE cells (SE 1/2/3-pre) based on the proliferative and secretory phases. E Number of differentially expressed genes between the proliferative- and secretory phases of the menstrual cycle by cell clusters based on scRNA-seq data. F Dot plot showing normalized scRNA-seq derived gene expression levels of selected genes that differ in the proliferative and secretory phase in ST subtypes. G Representative immunofluorescence staining of <t>IGF1</t> and IGF2 in primary human stromal and epithelial fallopian cell co-culture of one patient ( n = 3). The co-culture was stimulated for 8 h with estrogen (E4) or progesterone (P4). IGF1 protein in green, IGF2 protein in red and nuclei/ DAPI in blue. White dotted lines mark epithelial cells while white stars mark stromal cells. H Ligand-receptor interactions, detected by CellPhoneDB, between SE and ST subtypes (left) and between SE cells (right) separated by the menstrual phase using scRNA-seq data. I RNA velocity analysis of SE1- and SE2-pre cells. Arrows indicate the location of the estimated future cell state. Long vectors mark rapid transition events (i.e., large changes in gene expression), while short arrows indicate homeostasis. J Median latent time for pre-menopausal SE cells during the proliferative- and secretory phase of the menstrual cycle, highlighting temporal positions for SE1- and SE2-pre.
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    IGF1 promotes the secretion of AGR2, which in turn enhances the presentation of the IGF1R on the cell surface (A) The Venn diagram of the upper panel illustrates the count of genes down-regulated in Capan2 and Panc1 cells post AGR2 knockout. The Gene Ontology (GO) analysis of the lower panel identifies enriched biological processes, notably “regulation of IGF receptor signaling pathway” at transcriptional levels, after AGR2 knockout in these cell lines. (B) Western blot and quantitative reverse-transcription PCR (qRT-PCR) analyses assess IGF1R and AGR2 expression in Capan2 and Panc1 cells following AGR2 knockout via the CRISPR-Cas9 system (performed in triplicate). (C) Flow cytometry (FACS) quantifies cell membrane surface expression of IGF1R in Capan2 and Panc1 cells after AGR2 knockout (performed in triplicate). (D) Co-immunoprecipitation assays reveal AGR2’s interaction with pro-IGF1R in Capan2 and Panc1 cells (performed in triplicate). (E) Immunofluorescence imaging displays AGR2 and IGF1R distribution and ER labeling in Panc1 cells (scale bars: 50 μm). (F) Western blot analysis of IGF1R and AGR2 in Panc1 and Capan2 cells with controls (original cell lines), AGR2-knockout (AGR2 KO ) post-expression of AGR2 WT , AGR2 ΔNLS , AGR2 ΔSP , and AGR2 C81A mutation (performed in triplicate). (G) Western blot analysis of IGF1R expression in AGR2 in Panc1 and Capan2 cells with AGR2 knockout (KO) treated with 3-methyladenine (3-MA) (15 mM), bafilomycin A1 (30 nM), chloroquine (20 mM), MLN4929 (1 mM), or MG132 (5 mM) for 12 h (performed in triplicate). (H) Western blot analysis of IGF1R, phosphorylated IGF1R, c-JUN, phosphorylated c-JUN, and AGR2 following 12 h of serum starvation and subsequent IGF1 stimulation (50 ng/mL, performed in triplicate). (I) ELISA measures AGR2 secretion after serum starvation and treatment with PPP (1 μM) and IGF1 (50 ng/mL) over time (performed in triplicate). (J) Identification of potential c-JUN-binding sites within the AGR2 promoter region. (K) Western blot analysis of c-JUN, phosphorylated c-JUN, and AGR2 expression following c-JUN knockdown and IGF1 stimulation over time (performed in triplicate). (L) Western blot shows c-JUN, phosphorylated c-JUN, and AGR2 expression post anisomycin treatment over time (performed in triplicate). (M) Chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR) demonstrates c-JUN enrichment at AGR2’s transcription start sites (TSSs) before and after IGF1 treatment (performed in triplicate). (N) Integrative Genomics Viewer (IGV) tracks display c-JUN peaks in AGR2’s promoter region post IGF1 treatment. (O) Dual-luciferase reporter assays in Capan2 and Panc1 cells evaluate AGR2 promoter activity under various lengths and site-specific mutations after IGF1 treatment (performed in triplicate). Statistical analyses: (B) and (C) used a one-way ANOVA with multiple comparisons. (I), (M), (N), and (O) were analyzed using two-tailed, unpaired Student’s t tests. Data are presented as mean ± SD, with significance marked as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and “ns” indicates no significance.

    Journal: Cell Reports Medicine

    Article Title: Disrupting AGR2/IGF1 paracrine and reciprocal signaling for pancreatic cancer therapy

    doi: 10.1016/j.xcrm.2024.101927

    Figure Lengend Snippet: IGF1 promotes the secretion of AGR2, which in turn enhances the presentation of the IGF1R on the cell surface (A) The Venn diagram of the upper panel illustrates the count of genes down-regulated in Capan2 and Panc1 cells post AGR2 knockout. The Gene Ontology (GO) analysis of the lower panel identifies enriched biological processes, notably “regulation of IGF receptor signaling pathway” at transcriptional levels, after AGR2 knockout in these cell lines. (B) Western blot and quantitative reverse-transcription PCR (qRT-PCR) analyses assess IGF1R and AGR2 expression in Capan2 and Panc1 cells following AGR2 knockout via the CRISPR-Cas9 system (performed in triplicate). (C) Flow cytometry (FACS) quantifies cell membrane surface expression of IGF1R in Capan2 and Panc1 cells after AGR2 knockout (performed in triplicate). (D) Co-immunoprecipitation assays reveal AGR2’s interaction with pro-IGF1R in Capan2 and Panc1 cells (performed in triplicate). (E) Immunofluorescence imaging displays AGR2 and IGF1R distribution and ER labeling in Panc1 cells (scale bars: 50 μm). (F) Western blot analysis of IGF1R and AGR2 in Panc1 and Capan2 cells with controls (original cell lines), AGR2-knockout (AGR2 KO ) post-expression of AGR2 WT , AGR2 ΔNLS , AGR2 ΔSP , and AGR2 C81A mutation (performed in triplicate). (G) Western blot analysis of IGF1R expression in AGR2 in Panc1 and Capan2 cells with AGR2 knockout (KO) treated with 3-methyladenine (3-MA) (15 mM), bafilomycin A1 (30 nM), chloroquine (20 mM), MLN4929 (1 mM), or MG132 (5 mM) for 12 h (performed in triplicate). (H) Western blot analysis of IGF1R, phosphorylated IGF1R, c-JUN, phosphorylated c-JUN, and AGR2 following 12 h of serum starvation and subsequent IGF1 stimulation (50 ng/mL, performed in triplicate). (I) ELISA measures AGR2 secretion after serum starvation and treatment with PPP (1 μM) and IGF1 (50 ng/mL) over time (performed in triplicate). (J) Identification of potential c-JUN-binding sites within the AGR2 promoter region. (K) Western blot analysis of c-JUN, phosphorylated c-JUN, and AGR2 expression following c-JUN knockdown and IGF1 stimulation over time (performed in triplicate). (L) Western blot shows c-JUN, phosphorylated c-JUN, and AGR2 expression post anisomycin treatment over time (performed in triplicate). (M) Chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR) demonstrates c-JUN enrichment at AGR2’s transcription start sites (TSSs) before and after IGF1 treatment (performed in triplicate). (N) Integrative Genomics Viewer (IGV) tracks display c-JUN peaks in AGR2’s promoter region post IGF1 treatment. (O) Dual-luciferase reporter assays in Capan2 and Panc1 cells evaluate AGR2 promoter activity under various lengths and site-specific mutations after IGF1 treatment (performed in triplicate). Statistical analyses: (B) and (C) used a one-way ANOVA with multiple comparisons. (I), (M), (N), and (O) were analyzed using two-tailed, unpaired Student’s t tests. Data are presented as mean ± SD, with significance marked as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and “ns” indicates no significance.

    Article Snippet: Mouse monoclonal anti-IGF1 , Santa Cruz Biotechnology , Cat# sc-518040;.

    Techniques: Knock-Out, Western Blot, Reverse Transcription, Quantitative RT-PCR, Expressing, CRISPR, Flow Cytometry, Membrane, Immunoprecipitation, Immunofluorescence, Imaging, Labeling, Mutagenesis, Enzyme-linked Immunosorbent Assay, Binding Assay, Knockdown, Chromatin Immunoprecipitation, Real-time Polymerase Chain Reaction, Luciferase, Activity Assay, Two Tailed Test

    Secreted AGR2 promotes IGF1 production from CAFs via the Wnt/β-catenin pathway (A) Western blot analysis evaluates AGR2 and IGF1 levels in three human PDAC-derived CAFs and three PDAC cell lines (Capan2, HPAC, and Panc1) across three independent experiments. (B) qRT-PCR analysis of IGF1 expression and supernatant ELISA analyses of IGF1 secretion in human PDAC-derived CAFs co-cultured with two human PDAC organoids and with or without treatment with Agr2-neutralizing antibody (5 μg/mL) for 48 h ( n = 3 independent experiments). (C) qRT-PCR assesses IGF1 expression in PDAC-derived CAFs co-cultured with AGR2-knockout Capan2 and Panc1 cells, following re-expression of AGR2 WT , AGR2 ΔNLS , and AGR2 ΔSP for 48 h (upper); Western blot analysis investigates IGF1R, phosphorylated IGF1R, c-JUN, phosphorylated c-JUN, and AGR2 levels in AGR2-knockout Capan2 and Panc1 cells after co-culture with PDAC-derived CAFs (lower, n = 3 independent experiments). (D) qRT-PCR explores IGF1 expression in two PDAC-derived CAFs after treatment with rAGR2 (500 ng/mL), rTGF-β1 (4 μg/mL), and rIL-1α (200 ng/mL) for 24 h ( n = 3 independent experiments). (E) Supernatant analysis quantifies collagen levels in two PDAC-derived CAFs following rAGR2 treatment (500 ng/mL) for 24 h ( n = 3 independent experiments). (F) Transwell assays examine cell migration in two PDAC-derived CAFs following rAGR2 treatment (500 ng/mL) for 24 h ( n = 3 independent experiments). (G) Left: scRNA-seq identifies iCAFs and myCAFs within 16 PDAC tissues (GEO: GSE155698), showing iCAFs with elevated IGF1 expression (>mean value). Right: volcano plot displays genes differentially expressed between IGF1 high and IGF1 low CAFs (FDR < 0.01; log 2 FC > 0.5), accompanied by KEGG pathway analysis of the IGF1-CAF signature. (H) Principal component analysis (PCA) of transcriptomic data from CAFs treated with rAGR2, rTGF-β1, and rIL-1α ( n = 3 per group). (I) A heatmap shows genes significantly upregulated in CAFs after treatment with rAGR2, rTGF-β1, and rIL-1α (FDR < 0.01; log2FC > 0.5; left). Bioplant pathway analysis elucidates upregulated gene pathways post rAGR2 treatment in CAFs (right). (J) Identification of potential lymphoid enhancer binding factor 1 (LEF1)-binding sites within the IGF1 promoter region. (K) Western blot analysis shows β-catenin expression in both nuclear and cytoplasmic fractions of PDAC-derived CAFs after AGR2 stimulation (500 ng/mL) for 0.5, 1, 3, and 6 h ( n = 3 independent experiments). (L) Western blot and qRT-PCR analyses evaluate β-catenin and IGF1 levels in PDAC-derived CAFs post β-catenin knockdown or following treatment with ICG-001 (Wnt pathway inhibitor) and rAGR2 (500 ng/mL) for 24 h (M) Luciferase reporter assays in three PDAC-derived CAFs transfected with wild-type and site-specific mutagenized IGF1 promoter sequences based on (J) predictions, post rAGR2 treatment (500 ng/mL) for 24 h ( n = 3 independent experiments). Statistical analysis: one-way ANOVA with multiple comparisons test was used for (B), (C), (D), and (L); two-tailed, unpaired Student’s t tests were employed for (E), (F), and (M). Data are presented as mean ± SD, with ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001 indicating levels of statistical significance.

    Journal: Cell Reports Medicine

    Article Title: Disrupting AGR2/IGF1 paracrine and reciprocal signaling for pancreatic cancer therapy

    doi: 10.1016/j.xcrm.2024.101927

    Figure Lengend Snippet: Secreted AGR2 promotes IGF1 production from CAFs via the Wnt/β-catenin pathway (A) Western blot analysis evaluates AGR2 and IGF1 levels in three human PDAC-derived CAFs and three PDAC cell lines (Capan2, HPAC, and Panc1) across three independent experiments. (B) qRT-PCR analysis of IGF1 expression and supernatant ELISA analyses of IGF1 secretion in human PDAC-derived CAFs co-cultured with two human PDAC organoids and with or without treatment with Agr2-neutralizing antibody (5 μg/mL) for 48 h ( n = 3 independent experiments). (C) qRT-PCR assesses IGF1 expression in PDAC-derived CAFs co-cultured with AGR2-knockout Capan2 and Panc1 cells, following re-expression of AGR2 WT , AGR2 ΔNLS , and AGR2 ΔSP for 48 h (upper); Western blot analysis investigates IGF1R, phosphorylated IGF1R, c-JUN, phosphorylated c-JUN, and AGR2 levels in AGR2-knockout Capan2 and Panc1 cells after co-culture with PDAC-derived CAFs (lower, n = 3 independent experiments). (D) qRT-PCR explores IGF1 expression in two PDAC-derived CAFs after treatment with rAGR2 (500 ng/mL), rTGF-β1 (4 μg/mL), and rIL-1α (200 ng/mL) for 24 h ( n = 3 independent experiments). (E) Supernatant analysis quantifies collagen levels in two PDAC-derived CAFs following rAGR2 treatment (500 ng/mL) for 24 h ( n = 3 independent experiments). (F) Transwell assays examine cell migration in two PDAC-derived CAFs following rAGR2 treatment (500 ng/mL) for 24 h ( n = 3 independent experiments). (G) Left: scRNA-seq identifies iCAFs and myCAFs within 16 PDAC tissues (GEO: GSE155698), showing iCAFs with elevated IGF1 expression (>mean value). Right: volcano plot displays genes differentially expressed between IGF1 high and IGF1 low CAFs (FDR < 0.01; log 2 FC > 0.5), accompanied by KEGG pathway analysis of the IGF1-CAF signature. (H) Principal component analysis (PCA) of transcriptomic data from CAFs treated with rAGR2, rTGF-β1, and rIL-1α ( n = 3 per group). (I) A heatmap shows genes significantly upregulated in CAFs after treatment with rAGR2, rTGF-β1, and rIL-1α (FDR < 0.01; log2FC > 0.5; left). Bioplant pathway analysis elucidates upregulated gene pathways post rAGR2 treatment in CAFs (right). (J) Identification of potential lymphoid enhancer binding factor 1 (LEF1)-binding sites within the IGF1 promoter region. (K) Western blot analysis shows β-catenin expression in both nuclear and cytoplasmic fractions of PDAC-derived CAFs after AGR2 stimulation (500 ng/mL) for 0.5, 1, 3, and 6 h ( n = 3 independent experiments). (L) Western blot and qRT-PCR analyses evaluate β-catenin and IGF1 levels in PDAC-derived CAFs post β-catenin knockdown or following treatment with ICG-001 (Wnt pathway inhibitor) and rAGR2 (500 ng/mL) for 24 h (M) Luciferase reporter assays in three PDAC-derived CAFs transfected with wild-type and site-specific mutagenized IGF1 promoter sequences based on (J) predictions, post rAGR2 treatment (500 ng/mL) for 24 h ( n = 3 independent experiments). Statistical analysis: one-way ANOVA with multiple comparisons test was used for (B), (C), (D), and (L); two-tailed, unpaired Student’s t tests were employed for (E), (F), and (M). Data are presented as mean ± SD, with ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001 indicating levels of statistical significance.

    Article Snippet: Mouse monoclonal anti-IGF1 , Santa Cruz Biotechnology , Cat# sc-518040;.

    Techniques: Western Blot, Derivative Assay, Quantitative RT-PCR, Expressing, Enzyme-linked Immunosorbent Assay, Cell Culture, Knock-Out, Co-Culture Assay, Migration, Binding Assay, Knockdown, Luciferase, Transfection, Two Tailed Test

    High serum levels of AGR2 and IGF1 are associated with enhanced desmoplastic reactions and immunosuppression in PDAC (A) ELISA analysis of Igf1 in serum from 8-week-old KC mice, KC; Agr2 −/− mice, and KC; Agr2 OE mice reveals a significant difference (left, n = 12 mice per group). Comparison between KC mice and KC; Agr2 −/− mice with PDAC also shows marked differences (right, n = 5 mice per group). (B) Serum levels of AGR2 and IGF1 exhibit a correlation in 145 human patients with PDAC, analyzed using Pearson’s correlation coefficient. (C) IHC images display α-SMA, podoplanin (PDPN), collagen, and IL-6 positivity in tumor areas, comparing AGR2 high ; IGF1 high samples with AGR2 low ; IGF1 low samples, demonstrating a difference in desmoplastic reaction. (D) IHC images illustrate the differential presence of CD3, CD8, CD4, FOXP3, CD68, CD206, and CD20-positive cells in tumors between AGR2 high ; IGF1 high samples and AGR2 low ; IGF1 low samples, indicating variations in immune cell infiltration (scale bars: 50 μm). (E) IHC imaging further reveals the distribution of Cd3, Cd8, Cd4, Foxp3, B220, F4/80, and Cd206-positive cells in tumors from KC mice versus KC; Agr2 −/− mice, emphasizing differences in immunological responses (scale bars: 50 μm). p values in left of (A) was calculated using a one-way ANOVA with a multiple comparisons test, p values in right of (A), (C), (D), and (E) were calculated using two-tailed, unpaired Student’s t tests, and correlation coefficient in (B) was calculated using Pearson’s correlation coefficient. Data are presented as mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. ns, no significance.

    Journal: Cell Reports Medicine

    Article Title: Disrupting AGR2/IGF1 paracrine and reciprocal signaling for pancreatic cancer therapy

    doi: 10.1016/j.xcrm.2024.101927

    Figure Lengend Snippet: High serum levels of AGR2 and IGF1 are associated with enhanced desmoplastic reactions and immunosuppression in PDAC (A) ELISA analysis of Igf1 in serum from 8-week-old KC mice, KC; Agr2 −/− mice, and KC; Agr2 OE mice reveals a significant difference (left, n = 12 mice per group). Comparison between KC mice and KC; Agr2 −/− mice with PDAC also shows marked differences (right, n = 5 mice per group). (B) Serum levels of AGR2 and IGF1 exhibit a correlation in 145 human patients with PDAC, analyzed using Pearson’s correlation coefficient. (C) IHC images display α-SMA, podoplanin (PDPN), collagen, and IL-6 positivity in tumor areas, comparing AGR2 high ; IGF1 high samples with AGR2 low ; IGF1 low samples, demonstrating a difference in desmoplastic reaction. (D) IHC images illustrate the differential presence of CD3, CD8, CD4, FOXP3, CD68, CD206, and CD20-positive cells in tumors between AGR2 high ; IGF1 high samples and AGR2 low ; IGF1 low samples, indicating variations in immune cell infiltration (scale bars: 50 μm). (E) IHC imaging further reveals the distribution of Cd3, Cd8, Cd4, Foxp3, B220, F4/80, and Cd206-positive cells in tumors from KC mice versus KC; Agr2 −/− mice, emphasizing differences in immunological responses (scale bars: 50 μm). p values in left of (A) was calculated using a one-way ANOVA with a multiple comparisons test, p values in right of (A), (C), (D), and (E) were calculated using two-tailed, unpaired Student’s t tests, and correlation coefficient in (B) was calculated using Pearson’s correlation coefficient. Data are presented as mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. ns, no significance.

    Article Snippet: Mouse monoclonal anti-IGF1 , Santa Cruz Biotechnology , Cat# sc-518040;.

    Techniques: Enzyme-linked Immunosorbent Assay, Comparison, Imaging, Two Tailed Test

    Combined targeting attenuates desmoplastic reaction and normalizes immunosuppressive microenvironment (A) Western blot analysis reveals Agr2 and Igf1 levels in PSCs isolated from wild-type mice and three mouse PDAC cell lines, highlighting the differential expression patterns. (B) Schematic diagram shows the therapeutic strategy of combining IGF1R inhibitor and AGR2-neutralizing antibody. (C) ELISA and qRT-PCR analyses demonstrate Igf1 levels in PSCs co-cultured with KPC PDAC-derived organoids. The impact of treatments with the IGF1R inhibitor (PPP; 1 μM), Agr2-neutralizing antibody (5 μg/mL) alone, or their combination for 48 h is shown ( n = 3 independent experiments). (D) Western blot results display the expression levels of p-Igf1r, Igf1r, c-Jun, p-c-Jun, Akt, p-Akt, Erk, p-Erk, and Agr2 in mouse PDAC-derived organoids after co-culture with PSC cells and subsequent treatments as mentioned in (C) ( n = 3 independent experiments). (E) Representative images and quantitative analyses show the growth dynamics of PDAC organoids co-cultured with PSC cells under various treatment conditions over 0, 24, 48, and 96 h (scale bars: 50 μm, n = 3 independent experiments). (F) Tumor volume comparisons in KPC mice post caerulein-induced acute pancreatitis and subsequent treatments with Agr2 antibody (4 mg/kg; intraperitoneally [i.p.], three times per week for 2 weeks), PPP (20 mg/kg; i.p., three times per week for 2 weeks), or their combination ( n = 5 for control group, n = 3 for single treatment groups, and n = 5 for combined treatment group). (G) ELISA quantification of Agr2, Igf1, Il-1α, Lif, GM-CSF, and Il-6 in serum samples from the four groups of KPC mice underscores the systemic effects of the treatment modalities on cytokine levels ( n = 5 for control group, n = 3 for single treatment groups, and n = 5 for combined treatment group). (H and I) Representative stained sections and quantitative statistics of H&E, Pdpn, α-SMA, collagen, Cd3, Cd4, Foxp3, B220, and Cd206-positive cells within PDAC tumors (scale bars: 50 μm, n = 5 mice per group). (J) Representative IHC highlights CD8-positive cells in lymph nodes adjacent to the tumors (scale bars: 50 μm). p values in (C), (F), and (G) were calculated using a one-way ANOVA with a multiple comparisons test, and p values in (H) and (I) were calculated using two-tailed, unpaired Student’s t tests. Data are presented as mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001.

    Journal: Cell Reports Medicine

    Article Title: Disrupting AGR2/IGF1 paracrine and reciprocal signaling for pancreatic cancer therapy

    doi: 10.1016/j.xcrm.2024.101927

    Figure Lengend Snippet: Combined targeting attenuates desmoplastic reaction and normalizes immunosuppressive microenvironment (A) Western blot analysis reveals Agr2 and Igf1 levels in PSCs isolated from wild-type mice and three mouse PDAC cell lines, highlighting the differential expression patterns. (B) Schematic diagram shows the therapeutic strategy of combining IGF1R inhibitor and AGR2-neutralizing antibody. (C) ELISA and qRT-PCR analyses demonstrate Igf1 levels in PSCs co-cultured with KPC PDAC-derived organoids. The impact of treatments with the IGF1R inhibitor (PPP; 1 μM), Agr2-neutralizing antibody (5 μg/mL) alone, or their combination for 48 h is shown ( n = 3 independent experiments). (D) Western blot results display the expression levels of p-Igf1r, Igf1r, c-Jun, p-c-Jun, Akt, p-Akt, Erk, p-Erk, and Agr2 in mouse PDAC-derived organoids after co-culture with PSC cells and subsequent treatments as mentioned in (C) ( n = 3 independent experiments). (E) Representative images and quantitative analyses show the growth dynamics of PDAC organoids co-cultured with PSC cells under various treatment conditions over 0, 24, 48, and 96 h (scale bars: 50 μm, n = 3 independent experiments). (F) Tumor volume comparisons in KPC mice post caerulein-induced acute pancreatitis and subsequent treatments with Agr2 antibody (4 mg/kg; intraperitoneally [i.p.], three times per week for 2 weeks), PPP (20 mg/kg; i.p., three times per week for 2 weeks), or their combination ( n = 5 for control group, n = 3 for single treatment groups, and n = 5 for combined treatment group). (G) ELISA quantification of Agr2, Igf1, Il-1α, Lif, GM-CSF, and Il-6 in serum samples from the four groups of KPC mice underscores the systemic effects of the treatment modalities on cytokine levels ( n = 5 for control group, n = 3 for single treatment groups, and n = 5 for combined treatment group). (H and I) Representative stained sections and quantitative statistics of H&E, Pdpn, α-SMA, collagen, Cd3, Cd4, Foxp3, B220, and Cd206-positive cells within PDAC tumors (scale bars: 50 μm, n = 5 mice per group). (J) Representative IHC highlights CD8-positive cells in lymph nodes adjacent to the tumors (scale bars: 50 μm). p values in (C), (F), and (G) were calculated using a one-way ANOVA with a multiple comparisons test, and p values in (H) and (I) were calculated using two-tailed, unpaired Student’s t tests. Data are presented as mean ± SD. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001.

    Article Snippet: Mouse monoclonal anti-IGF1 , Santa Cruz Biotechnology , Cat# sc-518040;.

    Techniques: Western Blot, Isolation, Expressing, Enzyme-linked Immunosorbent Assay, Quantitative RT-PCR, Cell Culture, Derivative Assay, Co-Culture Assay, Control, Staining, Two Tailed Test

    Journal: Cell Reports Medicine

    Article Title: Disrupting AGR2/IGF1 paracrine and reciprocal signaling for pancreatic cancer therapy

    doi: 10.1016/j.xcrm.2024.101927

    Figure Lengend Snippet:

    Article Snippet: Mouse monoclonal anti-IGF1 , Santa Cruz Biotechnology , Cat# sc-518040;.

    Techniques: Virus, Recombinant, Control, Enzyme-linked Immunosorbent Assay, Isolation, Membrane, Protein Extraction, Chromatin Immunoprecipitation, Bicinchoninic Acid Protein Assay, Sircol Collagen Assay, Luciferase, RNA Sequencing Assay, Sequencing, Expressing, Real-time Polymerase Chain Reaction, shRNA, Plasmid Preparation, Software, Flow Cytometry

    A Differences in cellular composition between the proliferative- ( n = 4) and secretory phases ( n = 3) of the menstrual cycle based on scRNA-seq data (two-sided t -test). Data are represented using a boxplot showing the median and first and third quantile. N describes the number of patients/ samples for each respective menstrual cycle phase. SE1 p-value < 0.0018, SE2 p -value < 0.0035. B Representative OVGP1 immunohistochemistry in the fallopian tube of patients in the proliferative phase ( n = 2) and in the secretory phase ( n = 2). C Scatter plot comparing gene expression levels of pre-menopausal SE1 (secretory phase) and SE2 cells (proliferative phase) using pseudo-bulk RNA analysis. D Volcano plot derived from pseudo bulk analysis. The volcano plot shows the differential gene expression analysis of genes expressed in SE cells (SE 1/2/3-pre) based on the proliferative and secretory phases. E Number of differentially expressed genes between the proliferative- and secretory phases of the menstrual cycle by cell clusters based on scRNA-seq data. F Dot plot showing normalized scRNA-seq derived gene expression levels of selected genes that differ in the proliferative and secretory phase in ST subtypes. G Representative immunofluorescence staining of IGF1 and IGF2 in primary human stromal and epithelial fallopian cell co-culture of one patient ( n = 3). The co-culture was stimulated for 8 h with estrogen (E4) or progesterone (P4). IGF1 protein in green, IGF2 protein in red and nuclei/ DAPI in blue. White dotted lines mark epithelial cells while white stars mark stromal cells. H Ligand-receptor interactions, detected by CellPhoneDB, between SE and ST subtypes (left) and between SE cells (right) separated by the menstrual phase using scRNA-seq data. I RNA velocity analysis of SE1- and SE2-pre cells. Arrows indicate the location of the estimated future cell state. Long vectors mark rapid transition events (i.e., large changes in gene expression), while short arrows indicate homeostasis. J Median latent time for pre-menopausal SE cells during the proliferative- and secretory phase of the menstrual cycle, highlighting temporal positions for SE1- and SE2-pre.

    Journal: Nature Communications

    Article Title: A cell atlas of the human fallopian tube throughout the menstrual cycle and menopause

    doi: 10.1038/s41467-024-55440-2

    Figure Lengend Snippet: A Differences in cellular composition between the proliferative- ( n = 4) and secretory phases ( n = 3) of the menstrual cycle based on scRNA-seq data (two-sided t -test). Data are represented using a boxplot showing the median and first and third quantile. N describes the number of patients/ samples for each respective menstrual cycle phase. SE1 p-value < 0.0018, SE2 p -value < 0.0035. B Representative OVGP1 immunohistochemistry in the fallopian tube of patients in the proliferative phase ( n = 2) and in the secretory phase ( n = 2). C Scatter plot comparing gene expression levels of pre-menopausal SE1 (secretory phase) and SE2 cells (proliferative phase) using pseudo-bulk RNA analysis. D Volcano plot derived from pseudo bulk analysis. The volcano plot shows the differential gene expression analysis of genes expressed in SE cells (SE 1/2/3-pre) based on the proliferative and secretory phases. E Number of differentially expressed genes between the proliferative- and secretory phases of the menstrual cycle by cell clusters based on scRNA-seq data. F Dot plot showing normalized scRNA-seq derived gene expression levels of selected genes that differ in the proliferative and secretory phase in ST subtypes. G Representative immunofluorescence staining of IGF1 and IGF2 in primary human stromal and epithelial fallopian cell co-culture of one patient ( n = 3). The co-culture was stimulated for 8 h with estrogen (E4) or progesterone (P4). IGF1 protein in green, IGF2 protein in red and nuclei/ DAPI in blue. White dotted lines mark epithelial cells while white stars mark stromal cells. H Ligand-receptor interactions, detected by CellPhoneDB, between SE and ST subtypes (left) and between SE cells (right) separated by the menstrual phase using scRNA-seq data. I RNA velocity analysis of SE1- and SE2-pre cells. Arrows indicate the location of the estimated future cell state. Long vectors mark rapid transition events (i.e., large changes in gene expression), while short arrows indicate homeostasis. J Median latent time for pre-menopausal SE cells during the proliferative- and secretory phase of the menstrual cycle, highlighting temporal positions for SE1- and SE2-pre.

    Article Snippet: Slides were stained overnight at 4 °C in goat serum (Thermo Fisher Scientific, Cat#16210064) using the following primary antibodies: IGF1 (1:200, OriGene Technologies, TA805748S) and IGF2 (1:200, ThermoFisher scientific, MA532485), followed by fluorescently labeled secondary antibodies (1:200, Alexa Fluor 488 and 568, Invitrogen) and Hoechst 33258 (1:200, Molecular probes, H-3569) for 1 h. We imaged slides on a Nikon Eclipse Ti2 microscope and processed images with NIS-Elements (Nikon).

    Techniques: Immunohistochemistry, Expressing, Derivative Assay, Immunofluorescence, Staining, Co-Culture Assay