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human lung cancer 95c cells  (ATCC)


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    ATCC human lung cancer 95c cells
    Human Lung Cancer 95c Cells, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 19088 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    human lung cancer 95c cells - by Bioz Stars, 2026-06
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    ATCC human lung cancer a549 cells
    A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing <t>A549</t> cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.
    Human Lung Cancer A549 Cells, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ATCC human lung tumor cells a549
    A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing <t>A549</t> cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.
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    ATCC a549 human lung cancer cells
    A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing <t>A549</t> cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.
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    A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing <t>A549</t> cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.
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    ATCC non tumor human lung cells
    A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing <t>A549</t> cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.
    Non Tumor Human Lung Cells, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ATCC cell cultures human lung cancer cell line a549
    A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing <t>A549</t> cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.
    Cell Cultures Human Lung Cancer Cell Line A549, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ATCC human lung cancer cell line calu 3
    A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing <t>A549</t> cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.
    Human Lung Cancer Cell Line Calu 3, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing A549 cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.

    Journal: bioRxiv

    Article Title: Scalable longitudinal imaging and transcriptomics of cells in dynamic enclosures

    doi: 10.64898/2026.05.05.723030

    Figure Lengend Snippet: A: classification of CCEs in different phenotypes based on the analysis of longitudinal imaging data. Red: CellTrace™ Far Red, blue: Annexin V, green: EGFR. B: UMAP based on the transcriptomic data from 10,604 CCEs containing A549 cells treated with 10 µM Olmutinib. The colors represent different transcriptomic clusters. C: UMAP based on the transcriptomic data (same as panel B) colored according to the imaging-derived CCE classification in panel A. 2,328 CCEs that could not be accurately classified were excluded from the analysis. D: proportion of CCEs (y axis) belonging to each imaging-based phenotype (indicated by the color) within each gene expression cluster (x axis). E: Upset plot showing overlap of significant GSEA pathway enrichments across three classification strategies. The combination of transcriptomic clustering with imaging classification identified 15 unique pathways not found in either single-modality strategy. F: significant interaction effects (p_adj < 0.05) between RNA clusters and imaging phenotypes on the prediction of drug resistance pathway modules (G2M checkpoint, E2F targets, MYC targets, DNA repair, EMT) (see Methods). The daughter cell resistant phenotype showed 7 out of 14 total significant interactions, indicating that pathway activities are maximally explained by the combination of transcript state and the daughter cell resistant phenotypic classification. G: Confusion matrix for elastic net prediction of imaging phenotypes from gene expression. H: STRING PPI network for top 50 positive coefficient genes (associated with daughter cell resistance). I: STRING PPI network for top 50 negative coefficient genes (inversely associated with daughter cell resistance). J: Selected differentially expressed genes between expression-defined clusters (x axis). The color represents the average expression (scaled per gene) and the size of the circle indicates the percentage of CCEs expressing the gene. Cluster 2 showed strong enrichment for cell division pathways and overexpressed the proliferation marker TOP2A. Cluster 3 exhibited activation of multiple EGFR bypass pathways with overexpression of EPHA7 (64), HGF (65), ERBB2 (66), and AXL(67), all capable of activating MAPK signaling independently of EGFR. Cluster 5 displayed enrichment of p53 targets, including upregulation of quiescence-associated genes such as GADD45A, REDD1, ATF3, SFN, and BTG2.

    Article Snippet: Human lung cancer A549 cells were purchased from ATCC (CCL-185), and cultured in DMEM supplemented with 10% FBS and 1% Pen-Strep.

    Techniques: Imaging, Derivative Assay, Gene Expression, Expressing, Marker, Activation Assay, Over Expression