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Impact of Egr1 knockout on in vitro lung cancer proliferation, in vivo <t>T</t> <t>cell</t> infiltration, and T cell <t>exhaustion</t> in the tumor microenvironment. (A) The immune network and top 12 hub genes are visualized. From the top 30 most significantly up-regulated pathway clusters, 18 immunity-related terms and their associated genes were selected for Maximal Clique Centrality analysis using the CytoHubba plugin in Cytoscape. Gene interactions within the network indicate their participation in shared pathways. The background color of each gene box represents its centrality ranking: four genes co-ranked 1st (red), five genes co-ranked 5th (orange), and three genes co-ranked 10th (yellow). The 16 pathways associated with these 12 hub genes were further consolidated into 8 primary categories, represented by blue rectangular boxes. (B) Analysis of the DepMap CRISPR–Cas9 cancer dataset, evaluating the effect of Egr1 knockout in 342 human cancer cell lines, including independent assessments in KRAS -driven lung cancer lines, showed no significant impact on cell proliferation in either case. (C) Immunohistochemical staining of Cd4, Cd8, Cd3, Cd19, and F4/80 in Egr1 -deficient lung tumors compared with control tumors. Scale bars are provided for each image. (D) The heatmap illustrates the expression patterns of 55 curated T-cell exhaustion markers (CellMarker 2.0 and 10X Genomics) in control and Egr1 -deficient tumors. Differential expression analysis reveals that most exhaustion markers are up-regulated in Egr1 -deficient samples. The color scale represents relative expression levels, ranging from red (high expression) to blue (low expression).
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Impact of Egr1 knockout on in vitro lung cancer proliferation, in vivo <t>T</t> <t>cell</t> infiltration, and T cell <t>exhaustion</t> in the tumor microenvironment. (A) The immune network and top 12 hub genes are visualized. From the top 30 most significantly up-regulated pathway clusters, 18 immunity-related terms and their associated genes were selected for Maximal Clique Centrality analysis using the CytoHubba plugin in Cytoscape. Gene interactions within the network indicate their participation in shared pathways. The background color of each gene box represents its centrality ranking: four genes co-ranked 1st (red), five genes co-ranked 5th (orange), and three genes co-ranked 10th (yellow). The 16 pathways associated with these 12 hub genes were further consolidated into 8 primary categories, represented by blue rectangular boxes. (B) Analysis of the DepMap CRISPR–Cas9 cancer dataset, evaluating the effect of Egr1 knockout in 342 human cancer cell lines, including independent assessments in KRAS -driven lung cancer lines, showed no significant impact on cell proliferation in either case. (C) Immunohistochemical staining of Cd4, Cd8, Cd3, Cd19, and F4/80 in Egr1 -deficient lung tumors compared with control tumors. Scale bars are provided for each image. (D) The heatmap illustrates the expression patterns of 55 curated T-cell exhaustion markers (CellMarker 2.0 and 10X Genomics) in control and Egr1 -deficient tumors. Differential expression analysis reveals that most exhaustion markers are up-regulated in Egr1 -deficient samples. The color scale represents relative expression levels, ranging from red (high expression) to blue (low expression).
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Impact of Egr1 knockout on in vitro lung cancer proliferation, in vivo T cell infiltration, and T cell exhaustion in the tumor microenvironment. (A) The immune network and top 12 hub genes are visualized. From the top 30 most significantly up-regulated pathway clusters, 18 immunity-related terms and their associated genes were selected for Maximal Clique Centrality analysis using the CytoHubba plugin in Cytoscape. Gene interactions within the network indicate their participation in shared pathways. The background color of each gene box represents its centrality ranking: four genes co-ranked 1st (red), five genes co-ranked 5th (orange), and three genes co-ranked 10th (yellow). The 16 pathways associated with these 12 hub genes were further consolidated into 8 primary categories, represented by blue rectangular boxes. (B) Analysis of the DepMap CRISPR–Cas9 cancer dataset, evaluating the effect of Egr1 knockout in 342 human cancer cell lines, including independent assessments in KRAS -driven lung cancer lines, showed no significant impact on cell proliferation in either case. (C) Immunohistochemical staining of Cd4, Cd8, Cd3, Cd19, and F4/80 in Egr1 -deficient lung tumors compared with control tumors. Scale bars are provided for each image. (D) The heatmap illustrates the expression patterns of 55 curated T-cell exhaustion markers (CellMarker 2.0 and 10X Genomics) in control and Egr1 -deficient tumors. Differential expression analysis reveals that most exhaustion markers are up-regulated in Egr1 -deficient samples. The color scale represents relative expression levels, ranging from red (high expression) to blue (low expression).

Journal: Genes & Diseases

Article Title: In vivo multiplexed modeling reveals diverse roles of the TBX2 subfamily and Egr1 in Kr as -driven lung adenocarcinoma

doi: 10.1016/j.gendis.2025.101840

Figure Lengend Snippet: Impact of Egr1 knockout on in vitro lung cancer proliferation, in vivo T cell infiltration, and T cell exhaustion in the tumor microenvironment. (A) The immune network and top 12 hub genes are visualized. From the top 30 most significantly up-regulated pathway clusters, 18 immunity-related terms and their associated genes were selected for Maximal Clique Centrality analysis using the CytoHubba plugin in Cytoscape. Gene interactions within the network indicate their participation in shared pathways. The background color of each gene box represents its centrality ranking: four genes co-ranked 1st (red), five genes co-ranked 5th (orange), and three genes co-ranked 10th (yellow). The 16 pathways associated with these 12 hub genes were further consolidated into 8 primary categories, represented by blue rectangular boxes. (B) Analysis of the DepMap CRISPR–Cas9 cancer dataset, evaluating the effect of Egr1 knockout in 342 human cancer cell lines, including independent assessments in KRAS -driven lung cancer lines, showed no significant impact on cell proliferation in either case. (C) Immunohistochemical staining of Cd4, Cd8, Cd3, Cd19, and F4/80 in Egr1 -deficient lung tumors compared with control tumors. Scale bars are provided for each image. (D) The heatmap illustrates the expression patterns of 55 curated T-cell exhaustion markers (CellMarker 2.0 and 10X Genomics) in control and Egr1 -deficient tumors. Differential expression analysis reveals that most exhaustion markers are up-regulated in Egr1 -deficient samples. The color scale represents relative expression levels, ranging from red (high expression) to blue (low expression).

Article Snippet: Scale bars are provided for each image. (D) The heatmap illustrates the expression patterns of 55 curated T-cell exhaustion markers (CellMarker 2.0 and 10X Genomics) in control and Egr1 -deficient tumors.

Techniques: Knock-Out, In Vitro, In Vivo, CRISPR, Immunohistochemical staining, Staining, Control, Expressing, Quantitative Proteomics