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human normal gastric mucosal epithelial cells ges 1  (Procell Inc)

 
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    Procell Inc human normal gastric mucosal epithelial cells ges 1
    A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in <t>GES-1,</t> SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.
    Human Normal Gastric Mucosal Epithelial Cells Ges 1, supplied by Procell Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Average 86 stars, based on 1 article reviews
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    Images

    1) Product Images from "ALDH3A2 negatively orchestrates gastric cancer progression through a synergistic induction of ferroptosis and ferroptosis-driven macrophage reprogramming"

    Article Title: ALDH3A2 negatively orchestrates gastric cancer progression through a synergistic induction of ferroptosis and ferroptosis-driven macrophage reprogramming

    Journal: Cell Death & Disease

    doi: 10.1038/s41419-025-08364-8

    A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.
    Figure Legend Snippet: A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.

    Techniques Used: Immunohistochemistry, Expressing, Quantitative RT-PCR, Western Blot



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    A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in <t>GES-1,</t> SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.
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    A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in <t>GES-1,</t> SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.
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    A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in <t>GES-1,</t> SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.
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    A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in <t>GES-1,</t> SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.
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    A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in <t>GES-1,</t> SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.
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    Expression of interleukin-34 in gastric cancer tissues and cell lines, and construction of AGS cell lines with stable knockdown or overexpression of interleukin-34. A: Representative immunohistochemistry (IHC) staining of interleukin (IL)-34 in adjacent normal tissue, gastric cancer (GC) tissues, (scale bar = 25 μm); B: IHC staining scores were used to evaluate IL-34 expression in GC tissues and adjacent normal tissue; C: Western blotting was used to detect IL-34 protein expression in gastric normal <t>epithelial</t> cells (GES-1) and GC cell lines (AGS, HGC-27, and MKN-45); D: The relative densitometric analysis of protein bands was calculated; E: IL-34 mRNA expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR); F and G: Western blotting was used to verify the downregulation of IL-34 in AGS cell lines; H: qRT-PCR was used to verify the downregulation of IL-34 in AGS cell lines; I and J: Western blotting was used to verify the overexpression of IL-34 in AGS cell lines; K: qRT-PCR was used to verify the overexpression of IL-34 in AGS cell lines. b P < 0.01, c P < 0.001.
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    Expression of interleukin-34 in gastric cancer tissues and cell lines, and construction of AGS cell lines with stable knockdown or overexpression of interleukin-34. A: Representative immunohistochemistry (IHC) staining of interleukin (IL)-34 in adjacent normal tissue, gastric cancer (GC) tissues, (scale bar = 25 μm); B: IHC staining scores were used to evaluate IL-34 expression in GC tissues and adjacent normal tissue; C: Western blotting was used to detect IL-34 protein expression in gastric normal <t>epithelial</t> cells (GES-1) and GC cell lines (AGS, HGC-27, and MKN-45); D: The relative densitometric analysis of protein bands was calculated; E: IL-34 mRNA expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR); F and G: Western blotting was used to verify the downregulation of IL-34 in AGS cell lines; H: qRT-PCR was used to verify the downregulation of IL-34 in AGS cell lines; I and J: Western blotting was used to verify the overexpression of IL-34 in AGS cell lines; K: qRT-PCR was used to verify the overexpression of IL-34 in AGS cell lines. b P < 0.01, c P < 0.001.
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    Expression of interleukin-34 in gastric cancer tissues and cell lines, and construction of AGS cell lines with stable knockdown or overexpression of interleukin-34. A: Representative immunohistochemistry (IHC) staining of interleukin (IL)-34 in adjacent normal tissue, gastric cancer (GC) tissues, (scale bar = 25 μm); B: IHC staining scores were used to evaluate IL-34 expression in GC tissues and adjacent normal tissue; C: Western blotting was used to detect IL-34 protein expression in gastric normal <t>epithelial</t> cells (GES-1) and GC cell lines (AGS, HGC-27, and MKN-45); D: The relative densitometric analysis of protein bands was calculated; E: IL-34 mRNA expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR); F and G: Western blotting was used to verify the downregulation of IL-34 in AGS cell lines; H: qRT-PCR was used to verify the downregulation of IL-34 in AGS cell lines; I and J: Western blotting was used to verify the overexpression of IL-34 in AGS cell lines; K: qRT-PCR was used to verify the overexpression of IL-34 in AGS cell lines. b P < 0.01, c P < 0.001.
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    Image Search Results


    A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.

    Journal: Cell Death & Disease

    Article Title: ALDH3A2 negatively orchestrates gastric cancer progression through a synergistic induction of ferroptosis and ferroptosis-driven macrophage reprogramming

    doi: 10.1038/s41419-025-08364-8

    Figure Lengend Snippet: A Volcano plot of differentially expressed genes between gastric cancer and adjacent non-tumor tissues. B Venn diagram showing the overlap of GC-related differentially expressed genes (DEGs) with ferroptosis-related genes (FerrDb) and mitochondrial dysfunction-related genes (MitoProteome). Prognostic gene screening based on overall survival using Univariate Cox regression ( C ), LASSO Cox analysis ( D , E ), Boruta ( F ), and Random Forest ( G ). H Upset plot showing ALDH3A2, PDK4, and GJA1 as common candidate genes identified across all machine learning methods. I Immunohistochemistry images of ALDH3A2, PDK4, and GJA1 proteins from the Human Protein Atlas. J Relative mRNA expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells assessed by qRT-PCR (n = 4). K Protein expression of ALDH3A2 in GES-1, SGC7901, MGC803, HGC27, and MKN45 cells were assessed by immunoblotting (n = 4). L Relative mRNA expression of PDK4 and GJA1 in GES-1, HGC27, and MGC803 cells assessed by qRT-PCR (n = 4). Statistical significance was determined by an unpaired Student’s t-test. Data are presented as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001; n.s., not significant.

    Article Snippet: Human normal gastric mucosal epithelial cells GES-1, gastric cancer cell lines MGC803, HGC27, SGC7901, MKN45, and human embryonic kidney cells (293 T) used in this study were all sourced from Procell (Wuhan, China).

    Techniques: Immunohistochemistry, Expressing, Quantitative RT-PCR, Western Blot

    Expression of interleukin-34 in gastric cancer tissues and cell lines, and construction of AGS cell lines with stable knockdown or overexpression of interleukin-34. A: Representative immunohistochemistry (IHC) staining of interleukin (IL)-34 in adjacent normal tissue, gastric cancer (GC) tissues, (scale bar = 25 μm); B: IHC staining scores were used to evaluate IL-34 expression in GC tissues and adjacent normal tissue; C: Western blotting was used to detect IL-34 protein expression in gastric normal epithelial cells (GES-1) and GC cell lines (AGS, HGC-27, and MKN-45); D: The relative densitometric analysis of protein bands was calculated; E: IL-34 mRNA expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR); F and G: Western blotting was used to verify the downregulation of IL-34 in AGS cell lines; H: qRT-PCR was used to verify the downregulation of IL-34 in AGS cell lines; I and J: Western blotting was used to verify the overexpression of IL-34 in AGS cell lines; K: qRT-PCR was used to verify the overexpression of IL-34 in AGS cell lines. b P < 0.01, c P < 0.001.

    Journal: World Journal of Gastrointestinal Oncology

    Article Title: Interleukin-34 promotes the proliferation and epithelial-mesenchymal transition of gastric cancer cells

    doi: 10.4251/wjgo.v14.i10.1968

    Figure Lengend Snippet: Expression of interleukin-34 in gastric cancer tissues and cell lines, and construction of AGS cell lines with stable knockdown or overexpression of interleukin-34. A: Representative immunohistochemistry (IHC) staining of interleukin (IL)-34 in adjacent normal tissue, gastric cancer (GC) tissues, (scale bar = 25 μm); B: IHC staining scores were used to evaluate IL-34 expression in GC tissues and adjacent normal tissue; C: Western blotting was used to detect IL-34 protein expression in gastric normal epithelial cells (GES-1) and GC cell lines (AGS, HGC-27, and MKN-45); D: The relative densitometric analysis of protein bands was calculated; E: IL-34 mRNA expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR); F and G: Western blotting was used to verify the downregulation of IL-34 in AGS cell lines; H: qRT-PCR was used to verify the downregulation of IL-34 in AGS cell lines; I and J: Western blotting was used to verify the overexpression of IL-34 in AGS cell lines; K: qRT-PCR was used to verify the overexpression of IL-34 in AGS cell lines. b P < 0.01, c P < 0.001.

    Article Snippet: The human normal gastric mucosal epithelial cell line (GES-1) and human GC cell lines (AGS, MKN-45 and HGC-27) were provided by Prof. Aman Xu (The First Affiliated Hospital of Anhui Medical University).

    Techniques: Expressing, Knockdown, Over Expression, Immunohistochemistry, Western Blot, Real-time Polymerase Chain Reaction, Quantitative RT-PCR

    Interleukin-34 regulates the expression of epithelial-mesenchymal transition-related proteins in AGS cells. A-D: Downregulation of endogenous interleukin (IL)-34 increases E-cadherin expression, and reduces the expression of N-cadherin and vimentin in AGS cells; E-H: Upregulation of endogenous IL-34 reduces the E-cadherin expression, but increases the expression of N-cadherin and vimentin in AGS cells. Data was experiments performed in triplicate and expressed as mean ± standard deviation. b P < 0.01.

    Journal: World Journal of Gastrointestinal Oncology

    Article Title: Interleukin-34 promotes the proliferation and epithelial-mesenchymal transition of gastric cancer cells

    doi: 10.4251/wjgo.v14.i10.1968

    Figure Lengend Snippet: Interleukin-34 regulates the expression of epithelial-mesenchymal transition-related proteins in AGS cells. A-D: Downregulation of endogenous interleukin (IL)-34 increases E-cadherin expression, and reduces the expression of N-cadherin and vimentin in AGS cells; E-H: Upregulation of endogenous IL-34 reduces the E-cadherin expression, but increases the expression of N-cadherin and vimentin in AGS cells. Data was experiments performed in triplicate and expressed as mean ± standard deviation. b P < 0.01.

    Article Snippet: The human normal gastric mucosal epithelial cell line (GES-1) and human GC cell lines (AGS, MKN-45 and HGC-27) were provided by Prof. Aman Xu (The First Affiliated Hospital of Anhui Medical University).

    Techniques: Expressing, Standard Deviation