Review




Structured Review

Proteintech grap
Identification of candidate genes. (A) Differences in survival between the high and low neutrophil group. (B) RSF analysis and expression levels of genes related to prognosis. (C) Expression levels and distributions of RASGRP4, COX20, <t>CD47,</t> <t>TIMM10B,</t> LY86, <t>GRAP,</t> TNFRSF13C and ATP6V0D1 in different tumor subtypes. (D-G) Kaplan–Meier graphs displaying the survival potential of patients with TNBC, grouped by the expression levels of significant genes.
Grap, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 2 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Images

1) Product Images from "Identification of tumor associated neutrophils-related genes in triple-negative breast cancer for predicting prognosis and therapeutic response through integrated single-cell analysis"

Article Title: Identification of tumor associated neutrophils-related genes in triple-negative breast cancer for predicting prognosis and therapeutic response through integrated single-cell analysis

Journal: Frontiers in Immunology

doi: 10.3389/fimmu.2025.1613529

Identification of candidate genes. (A) Differences in survival between the high and low neutrophil group. (B) RSF analysis and expression levels of genes related to prognosis. (C) Expression levels and distributions of RASGRP4, COX20, CD47, TIMM10B, LY86, GRAP, TNFRSF13C and ATP6V0D1 in different tumor subtypes. (D-G) Kaplan–Meier graphs displaying the survival potential of patients with TNBC, grouped by the expression levels of significant genes.
Figure Legend Snippet: Identification of candidate genes. (A) Differences in survival between the high and low neutrophil group. (B) RSF analysis and expression levels of genes related to prognosis. (C) Expression levels and distributions of RASGRP4, COX20, CD47, TIMM10B, LY86, GRAP, TNFRSF13C and ATP6V0D1 in different tumor subtypes. (D-G) Kaplan–Meier graphs displaying the survival potential of patients with TNBC, grouped by the expression levels of significant genes.

Techniques Used: Expressing

Correlations between TIMM10B, GRAP, TNFRSF13C and RASGRP4 and drug sensitivity. (A-D) Correlations between key genes and the IC50 of chemotherapeutic agents.
Figure Legend Snippet: Correlations between TIMM10B, GRAP, TNFRSF13C and RASGRP4 and drug sensitivity. (A-D) Correlations between key genes and the IC50 of chemotherapeutic agents.

Techniques Used:

GSEA and GSVA of the four genes. (A-D) . GSEA revealed the enriched signaling pathways associated with TIMM10B, GRAP, TNFRSF13C and RASGRP4. (E-H) . Analysis of key genes using GSVA. The x-axis illustrates the t value of the GSVA score, and the y-axis depicts KEGG pathways; blue highlights upregulated pathways, whereas green highlights downregulated pathways. |NES| ≥ 1 and FDR < 0.25.
Figure Legend Snippet: GSEA and GSVA of the four genes. (A-D) . GSEA revealed the enriched signaling pathways associated with TIMM10B, GRAP, TNFRSF13C and RASGRP4. (E-H) . Analysis of key genes using GSVA. The x-axis illustrates the t value of the GSVA score, and the y-axis depicts KEGG pathways; blue highlights upregulated pathways, whereas green highlights downregulated pathways. |NES| ≥ 1 and FDR < 0.25.

Techniques Used: Protein-Protein interactions

Cell communication and quasitemporal analysis. (A) Circus plot illustrating the greater total number of significantly interacting pairs between neutrophils and immune cells as estimated by CellPhoneDB (P<0.05). (B) Bubble diagram of the cell communication network between ligands and neutrophils and other cell subtypes as well as with neutrophil itself themselves. (C-E) Trajectory analysis of the potential relatedness between the two groups according to pseudotime, cell type and group. (F-H) Changes in the expression of TIMM10B, GRAP, TNFRSF13C and RASGRP4 over pseudotime.
Figure Legend Snippet: Cell communication and quasitemporal analysis. (A) Circus plot illustrating the greater total number of significantly interacting pairs between neutrophils and immune cells as estimated by CellPhoneDB (P<0.05). (B) Bubble diagram of the cell communication network between ligands and neutrophils and other cell subtypes as well as with neutrophil itself themselves. (C-E) Trajectory analysis of the potential relatedness between the two groups according to pseudotime, cell type and group. (F-H) Changes in the expression of TIMM10B, GRAP, TNFRSF13C and RASGRP4 over pseudotime.

Techniques Used: Expressing

Clinical relevance of TIMM10B, GRAP, TNFRSF13C and RASGRP4. (A) Polychromatic immunofluorescence staining showing the distribution of MPO, TIMM10B, GRAP, TNFRSF13C and RASGRP4 expression. Scale bar (upper panel), 200 µm. Scale bar (bottom panel), 50 µm. (B) IHC scores of MPO, TIMM10B, GRAP, TNFRSF13C and RASGRP4 in adjacent tissue (AT), stage I-II (I-II) and III TNBC. (C) Correlations between MPO and the four candidate genes in stage I-II (I-II) TNBC. (D) Correlations between MPO and the four candidate genes in stage III (III) TNBC. (E) Representative images of coimmunostaining for MPO and four target genes in adjacent tissue from the stage I-II and III TNBC groups. Scale bar, 20 µm. (F) Percentage of TIMM10B-, GRAP-, TNFRSF13C- and RASGRP4-positive cells in AT and stage I-II and III TNBC. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. ns, not significant.
Figure Legend Snippet: Clinical relevance of TIMM10B, GRAP, TNFRSF13C and RASGRP4. (A) Polychromatic immunofluorescence staining showing the distribution of MPO, TIMM10B, GRAP, TNFRSF13C and RASGRP4 expression. Scale bar (upper panel), 200 µm. Scale bar (bottom panel), 50 µm. (B) IHC scores of MPO, TIMM10B, GRAP, TNFRSF13C and RASGRP4 in adjacent tissue (AT), stage I-II (I-II) and III TNBC. (C) Correlations between MPO and the four candidate genes in stage I-II (I-II) TNBC. (D) Correlations between MPO and the four candidate genes in stage III (III) TNBC. (E) Representative images of coimmunostaining for MPO and four target genes in adjacent tissue from the stage I-II and III TNBC groups. Scale bar, 20 µm. (F) Percentage of TIMM10B-, GRAP-, TNFRSF13C- and RASGRP4-positive cells in AT and stage I-II and III TNBC. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. ns, not significant.

Techniques Used: Immunofluorescence, Staining, Expressing

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Image Search Results


Identification of candidate genes. (A) Differences in survival between the high and low neutrophil group. (B) RSF analysis and expression levels of genes related to prognosis. (C) Expression levels and distributions of RASGRP4, COX20, CD47, TIMM10B, LY86, GRAP, TNFRSF13C and ATP6V0D1 in different tumor subtypes. (D-G) Kaplan–Meier graphs displaying the survival potential of patients with TNBC, grouped by the expression levels of significant genes.

Journal: Frontiers in Immunology

Article Title: Identification of tumor associated neutrophils-related genes in triple-negative breast cancer for predicting prognosis and therapeutic response through integrated single-cell analysis

doi: 10.3389/fimmu.2025.1613529

Figure Lengend Snippet: Identification of candidate genes. (A) Differences in survival between the high and low neutrophil group. (B) RSF analysis and expression levels of genes related to prognosis. (C) Expression levels and distributions of RASGRP4, COX20, CD47, TIMM10B, LY86, GRAP, TNFRSF13C and ATP6V0D1 in different tumor subtypes. (D-G) Kaplan–Meier graphs displaying the survival potential of patients with TNBC, grouped by the expression levels of significant genes.

Article Snippet: The primary antibodies used in the experiment included antibodies against MPO (ZSGB-Bio, ZA-0197, diluted1:200), TIMM10B (Proteintech, 10907-1, diluted 1:200), GRAP (Proteintech, 14505-1, diluted 1:200), and TNFRSF13C (Proteintech, 22582-1, diluted 1:200), RASGRP4 (Abcam, 96293, diluted 1:100).

Techniques: Expressing

Correlations between TIMM10B, GRAP, TNFRSF13C and RASGRP4 and drug sensitivity. (A-D) Correlations between key genes and the IC50 of chemotherapeutic agents.

Journal: Frontiers in Immunology

Article Title: Identification of tumor associated neutrophils-related genes in triple-negative breast cancer for predicting prognosis and therapeutic response through integrated single-cell analysis

doi: 10.3389/fimmu.2025.1613529

Figure Lengend Snippet: Correlations between TIMM10B, GRAP, TNFRSF13C and RASGRP4 and drug sensitivity. (A-D) Correlations between key genes and the IC50 of chemotherapeutic agents.

Article Snippet: The primary antibodies used in the experiment included antibodies against MPO (ZSGB-Bio, ZA-0197, diluted1:200), TIMM10B (Proteintech, 10907-1, diluted 1:200), GRAP (Proteintech, 14505-1, diluted 1:200), and TNFRSF13C (Proteintech, 22582-1, diluted 1:200), RASGRP4 (Abcam, 96293, diluted 1:100).

Techniques:

GSEA and GSVA of the four genes. (A-D) . GSEA revealed the enriched signaling pathways associated with TIMM10B, GRAP, TNFRSF13C and RASGRP4. (E-H) . Analysis of key genes using GSVA. The x-axis illustrates the t value of the GSVA score, and the y-axis depicts KEGG pathways; blue highlights upregulated pathways, whereas green highlights downregulated pathways. |NES| ≥ 1 and FDR < 0.25.

Journal: Frontiers in Immunology

Article Title: Identification of tumor associated neutrophils-related genes in triple-negative breast cancer for predicting prognosis and therapeutic response through integrated single-cell analysis

doi: 10.3389/fimmu.2025.1613529

Figure Lengend Snippet: GSEA and GSVA of the four genes. (A-D) . GSEA revealed the enriched signaling pathways associated with TIMM10B, GRAP, TNFRSF13C and RASGRP4. (E-H) . Analysis of key genes using GSVA. The x-axis illustrates the t value of the GSVA score, and the y-axis depicts KEGG pathways; blue highlights upregulated pathways, whereas green highlights downregulated pathways. |NES| ≥ 1 and FDR < 0.25.

Article Snippet: The primary antibodies used in the experiment included antibodies against MPO (ZSGB-Bio, ZA-0197, diluted1:200), TIMM10B (Proteintech, 10907-1, diluted 1:200), GRAP (Proteintech, 14505-1, diluted 1:200), and TNFRSF13C (Proteintech, 22582-1, diluted 1:200), RASGRP4 (Abcam, 96293, diluted 1:100).

Techniques: Protein-Protein interactions

Cell communication and quasitemporal analysis. (A) Circus plot illustrating the greater total number of significantly interacting pairs between neutrophils and immune cells as estimated by CellPhoneDB (P<0.05). (B) Bubble diagram of the cell communication network between ligands and neutrophils and other cell subtypes as well as with neutrophil itself themselves. (C-E) Trajectory analysis of the potential relatedness between the two groups according to pseudotime, cell type and group. (F-H) Changes in the expression of TIMM10B, GRAP, TNFRSF13C and RASGRP4 over pseudotime.

Journal: Frontiers in Immunology

Article Title: Identification of tumor associated neutrophils-related genes in triple-negative breast cancer for predicting prognosis and therapeutic response through integrated single-cell analysis

doi: 10.3389/fimmu.2025.1613529

Figure Lengend Snippet: Cell communication and quasitemporal analysis. (A) Circus plot illustrating the greater total number of significantly interacting pairs between neutrophils and immune cells as estimated by CellPhoneDB (P<0.05). (B) Bubble diagram of the cell communication network between ligands and neutrophils and other cell subtypes as well as with neutrophil itself themselves. (C-E) Trajectory analysis of the potential relatedness between the two groups according to pseudotime, cell type and group. (F-H) Changes in the expression of TIMM10B, GRAP, TNFRSF13C and RASGRP4 over pseudotime.

Article Snippet: The primary antibodies used in the experiment included antibodies against MPO (ZSGB-Bio, ZA-0197, diluted1:200), TIMM10B (Proteintech, 10907-1, diluted 1:200), GRAP (Proteintech, 14505-1, diluted 1:200), and TNFRSF13C (Proteintech, 22582-1, diluted 1:200), RASGRP4 (Abcam, 96293, diluted 1:100).

Techniques: Expressing

Clinical relevance of TIMM10B, GRAP, TNFRSF13C and RASGRP4. (A) Polychromatic immunofluorescence staining showing the distribution of MPO, TIMM10B, GRAP, TNFRSF13C and RASGRP4 expression. Scale bar (upper panel), 200 µm. Scale bar (bottom panel), 50 µm. (B) IHC scores of MPO, TIMM10B, GRAP, TNFRSF13C and RASGRP4 in adjacent tissue (AT), stage I-II (I-II) and III TNBC. (C) Correlations between MPO and the four candidate genes in stage I-II (I-II) TNBC. (D) Correlations between MPO and the four candidate genes in stage III (III) TNBC. (E) Representative images of coimmunostaining for MPO and four target genes in adjacent tissue from the stage I-II and III TNBC groups. Scale bar, 20 µm. (F) Percentage of TIMM10B-, GRAP-, TNFRSF13C- and RASGRP4-positive cells in AT and stage I-II and III TNBC. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. ns, not significant.

Journal: Frontiers in Immunology

Article Title: Identification of tumor associated neutrophils-related genes in triple-negative breast cancer for predicting prognosis and therapeutic response through integrated single-cell analysis

doi: 10.3389/fimmu.2025.1613529

Figure Lengend Snippet: Clinical relevance of TIMM10B, GRAP, TNFRSF13C and RASGRP4. (A) Polychromatic immunofluorescence staining showing the distribution of MPO, TIMM10B, GRAP, TNFRSF13C and RASGRP4 expression. Scale bar (upper panel), 200 µm. Scale bar (bottom panel), 50 µm. (B) IHC scores of MPO, TIMM10B, GRAP, TNFRSF13C and RASGRP4 in adjacent tissue (AT), stage I-II (I-II) and III TNBC. (C) Correlations between MPO and the four candidate genes in stage I-II (I-II) TNBC. (D) Correlations between MPO and the four candidate genes in stage III (III) TNBC. (E) Representative images of coimmunostaining for MPO and four target genes in adjacent tissue from the stage I-II and III TNBC groups. Scale bar, 20 µm. (F) Percentage of TIMM10B-, GRAP-, TNFRSF13C- and RASGRP4-positive cells in AT and stage I-II and III TNBC. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. ns, not significant.

Article Snippet: The primary antibodies used in the experiment included antibodies against MPO (ZSGB-Bio, ZA-0197, diluted1:200), TIMM10B (Proteintech, 10907-1, diluted 1:200), GRAP (Proteintech, 14505-1, diluted 1:200), and TNFRSF13C (Proteintech, 22582-1, diluted 1:200), RASGRP4 (Abcam, 96293, diluted 1:100).

Techniques: Immunofluorescence, Staining, Expressing

Figure 2. The ITT of mIgE-BCRs employs Grb2 and GRAP for signal amplification. DG75 cells deficient for Grb2 and GRAP were retrovirally transduced to express either wild type (wt) or ITT-mutant (YA) mIgE. Surface expression of mIgE variants is shown in (A), their Ca2+ mobilization profiles on stimulation with 10 µg/ml anti- IgE antibodies are shown in (B). (C) Ca2+ mobilization kinetics of wild type mIgE-BCRs in parental DG75 cells (blue curve) and Grb2/GRAP double-deficient cells (Grb2/GRAP-dko, red curve). (D) Grb2/GRAP double- deficient cells expressing wild type or ITT-mutant mIgE (from (A) and (B)) were additionally transduced to express both Grb2 along with EFGP and GRAP together with tagRFP. Ca2+ mobilization kinetics of the cells on stimulation of mIgE-BCRs was analyzed as before. (E) DG75 B cells (wt) and Grb2/GRAP double-deficient cells (dko) expressing wild type mIgE-BCRs were stimulated with the indicated concentrations of anti-IgE antibodies for five minutes. Phosphorylation of Erk proteins was analyzed by immunoblotting and relative band intensities were determined as before. (F) IgE-BCR-induced time course of Erk phosphorylation in DG75 (wt), Grb2/GRAP double-deficient cells (dko) and double-deficient cells reconstituted to express Grb2 and GRAP (dko + Grb2 + GRAP). Data are representative of three independent experiments.

Journal: Scientific reports

Article Title: Grb2 and GRAP connect the B cell antigen receptor to Erk MAP kinase activation in human B cells.

doi: 10.1038/s41598-018-22544-x

Figure Lengend Snippet: Figure 2. The ITT of mIgE-BCRs employs Grb2 and GRAP for signal amplification. DG75 cells deficient for Grb2 and GRAP were retrovirally transduced to express either wild type (wt) or ITT-mutant (YA) mIgE. Surface expression of mIgE variants is shown in (A), their Ca2+ mobilization profiles on stimulation with 10 µg/ml anti- IgE antibodies are shown in (B). (C) Ca2+ mobilization kinetics of wild type mIgE-BCRs in parental DG75 cells (blue curve) and Grb2/GRAP double-deficient cells (Grb2/GRAP-dko, red curve). (D) Grb2/GRAP double- deficient cells expressing wild type or ITT-mutant mIgE (from (A) and (B)) were additionally transduced to express both Grb2 along with EFGP and GRAP together with tagRFP. Ca2+ mobilization kinetics of the cells on stimulation of mIgE-BCRs was analyzed as before. (E) DG75 B cells (wt) and Grb2/GRAP double-deficient cells (dko) expressing wild type mIgE-BCRs were stimulated with the indicated concentrations of anti-IgE antibodies for five minutes. Phosphorylation of Erk proteins was analyzed by immunoblotting and relative band intensities were determined as before. (F) IgE-BCR-induced time course of Erk phosphorylation in DG75 (wt), Grb2/GRAP double-deficient cells (dko) and double-deficient cells reconstituted to express Grb2 and GRAP (dko + Grb2 + GRAP). Data are representative of three independent experiments.

Article Snippet: The anti-Grb2 antibody (3F2) was from Millipore, the anti-SLP65 antibody (2C9) from BAbCo, the polyclonal anti-GRAP antibody (raised against the C-terminus of GRAP) from Atlas Antibodies and the anti-GST antibody from MoBiTec.

Techniques: Amplification, Mutagenesis, Expressing, Phospho-proteomics, Western Blot

Figure 3. Grb2 and GRAP are essential for activation of Erk by the mIgM-BCR in DG75 B cells. (A) Activation of Erk in DG75 cells (wt), and variants lacking either Grb2 (Grb2-ko) or GRAP (GRAP-ko) or both (dko) following stimulation with 20 µg/ml anti-IgM F(ab’)2 fragments for the indicated times. Cleared cellular lysates were analyzed as before. In addition the expression of Grb2 and GRAP in the different DG75 sublines was tested with the indicated antibodies. (B) Quantitative analysis of Erk phosphorylation in the same cells using intracellular staining of phospho-Erk followed by flow cytometric analysis of mean fluorescence intensities (MFIs). The average changes in MFIs of three independent experiments are shown in (C). Basal signal intensities of unstimulated parental DG75 cells (wt) were defined as 1.0 and all other intensities were normalized accordingly. Error bars represent standard deviation of the mean of three independent experiments. (D) Parental DG75 cells (wt) and Grb2/GRAP double-deficient cells (dko) were stimulated for the indicated times with 20 µg/ml anti-IgM F(ab’)2 fragments. Cleared cellular lysates were analyzed for phosphorylated Mek (α-p-Mek) and total Mek (α-Mek) as loading control. Data are representative of three independent experiments.

Journal: Scientific reports

Article Title: Grb2 and GRAP connect the B cell antigen receptor to Erk MAP kinase activation in human B cells.

doi: 10.1038/s41598-018-22544-x

Figure Lengend Snippet: Figure 3. Grb2 and GRAP are essential for activation of Erk by the mIgM-BCR in DG75 B cells. (A) Activation of Erk in DG75 cells (wt), and variants lacking either Grb2 (Grb2-ko) or GRAP (GRAP-ko) or both (dko) following stimulation with 20 µg/ml anti-IgM F(ab’)2 fragments for the indicated times. Cleared cellular lysates were analyzed as before. In addition the expression of Grb2 and GRAP in the different DG75 sublines was tested with the indicated antibodies. (B) Quantitative analysis of Erk phosphorylation in the same cells using intracellular staining of phospho-Erk followed by flow cytometric analysis of mean fluorescence intensities (MFIs). The average changes in MFIs of three independent experiments are shown in (C). Basal signal intensities of unstimulated parental DG75 cells (wt) were defined as 1.0 and all other intensities were normalized accordingly. Error bars represent standard deviation of the mean of three independent experiments. (D) Parental DG75 cells (wt) and Grb2/GRAP double-deficient cells (dko) were stimulated for the indicated times with 20 µg/ml anti-IgM F(ab’)2 fragments. Cleared cellular lysates were analyzed for phosphorylated Mek (α-p-Mek) and total Mek (α-Mek) as loading control. Data are representative of three independent experiments.

Article Snippet: The anti-Grb2 antibody (3F2) was from Millipore, the anti-SLP65 antibody (2C9) from BAbCo, the polyclonal anti-GRAP antibody (raised against the C-terminus of GRAP) from Atlas Antibodies and the anti-GST antibody from MoBiTec.

Techniques: Activation Assay, Expressing, Phospho-proteomics, Staining, Fluorescence, Standard Deviation, Control

Figure 6. DAG-responsive RasGRP isoforms are poorly expressed in human B cells. (A) Primary human B cells isolated from peripheral blood of a healthy donor were stained with anti-CD19 antibodies to verify the purity of the used cells. (B) Cleared cellular lysates of primary human B cells, the Burkitt lymphoma lines Ramos and DG75 and the human T cell line Jurkat were prepared. In addition, Grb2/GRAP double-deficient DG75 cells (Grb2/GRAP-dko) were retrovirally transduced to express RasGRP2 or RasGRP3, respectively, along with IRES-driven EFGP and sorted for EGFP expression. Lysates of all cell types were loaded onto two gels and blotted simultaneously. One membrane was probed with antibodies to RasGRP isoforms 1 and 2, Grb2 and GRAP, the second membrane was probed with antibodies to RasGRP3. Both blots were probed with anti-β- Actin as loading control. The relative band intensities for RasGRP isoforms normalized to the respective Actin signals are shown below the blots. Data are representative of three independent experiments. (C) Quantification of Erk phosphorylation in the same cells was measured by phos-flow analysis as before. Basal signal intensities of unstimulated parental DG75 cells (wt) were defined as 1.0 and all other intensities were normalized accordingly. Error bars represent standard deviation of the mean of three independent experiments.

Journal: Scientific reports

Article Title: Grb2 and GRAP connect the B cell antigen receptor to Erk MAP kinase activation in human B cells.

doi: 10.1038/s41598-018-22544-x

Figure Lengend Snippet: Figure 6. DAG-responsive RasGRP isoforms are poorly expressed in human B cells. (A) Primary human B cells isolated from peripheral blood of a healthy donor were stained with anti-CD19 antibodies to verify the purity of the used cells. (B) Cleared cellular lysates of primary human B cells, the Burkitt lymphoma lines Ramos and DG75 and the human T cell line Jurkat were prepared. In addition, Grb2/GRAP double-deficient DG75 cells (Grb2/GRAP-dko) were retrovirally transduced to express RasGRP2 or RasGRP3, respectively, along with IRES-driven EFGP and sorted for EGFP expression. Lysates of all cell types were loaded onto two gels and blotted simultaneously. One membrane was probed with antibodies to RasGRP isoforms 1 and 2, Grb2 and GRAP, the second membrane was probed with antibodies to RasGRP3. Both blots were probed with anti-β- Actin as loading control. The relative band intensities for RasGRP isoforms normalized to the respective Actin signals are shown below the blots. Data are representative of three independent experiments. (C) Quantification of Erk phosphorylation in the same cells was measured by phos-flow analysis as before. Basal signal intensities of unstimulated parental DG75 cells (wt) were defined as 1.0 and all other intensities were normalized accordingly. Error bars represent standard deviation of the mean of three independent experiments.

Article Snippet: The anti-Grb2 antibody (3F2) was from Millipore, the anti-SLP65 antibody (2C9) from BAbCo, the polyclonal anti-GRAP antibody (raised against the C-terminus of GRAP) from Atlas Antibodies and the anti-GST antibody from MoBiTec.

Techniques: Isolation, Staining, Expressing, Membrane, Control, Phospho-proteomics, Standard Deviation