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BT-474

RRID:CVCL_0179

Organism

Homo sapiens

Comments

Part of: AKT genetic alteration cell panel (ATCC TCP-1029). Part of: Cancer Cell Line Encyclopedia (CCLE) project. Part of: COSMIC cell lines project. Part of: EGFR genetic alteration cell panel (ATCC TCP-1027). Part of: ERK genetic alteration cell panel (ATCC TCP-1033). Part of: ICBP43 breast cancer cell line panel. Part of: KuDOS 95 cell line panel. Part of: MD Anderson Cell Lines Project. Part of: Naval Biosciences Laboratory (NBL) collection (transferred to ATCC in 1982). Doubling time: 3.5 days (PubMed=9671407); 78 hours (PubMed=25984343); ~100 hours (DSMZ). Microsatellite instability: Stable (MSS) (PubMed=23671654; Sanger). Sequence variation: Heterozygous for MAPK1 p.His61Gln (ATCC). Omics: Array-based CGH. Omics: CNV analysis. Omics: Deep exome analysis. Omics: Deep phosphoproteome analysis. Omics: Deep proteome analysis. Omics: Deep RNAseq analysis. Omics: DNA methylation analysis. Omics: Genome sequenced. Omics: Metabolome analysis. Omics: miRNA expression profiling. Omics: Protein expression by reverse-phase protein arrays. Omics: shRNA library screening. Omics: SNP array analysis. Omics: Transcriptome analysis. Discontinued: ATCC; CRL-7913.

Proper Citation

KCB Cat# KCB 2011115YJ, RRID:CVCL_0179

Category

Cancer cell line

Sex

Female

Synonyms

Bt-474, BT474

Vendor

KCB

Cat Num

KCB 2011115YJ

Cross References

BTO; BTO:0001932 CLO; CLO_0002042 EFO; EFO_0001093 MCCL; MCC:0000070 CLDB; cl497 CLDB; cl498 CLDB; cl4997 AddexBio; C0006012/4902 ATCC; CRL-7913 ATCC; HTB-20 BCRC; 60359 BCRJ; 0353 BioSample; SAMN01821539 BioSample; SAMN01821618 BioSample; SAMN03473029 BioSamples; SAMEA3516847 BioSamples; SAMEA3516848 BioSamples; SAMEA3516849 CCLE; BT474_BREAST CCRID; 3111C0001CCC000129 CCRID; 3111C0002000000023 CCRID; 3131C0001000700143 ChEMBL-Cells; CHEMBL3307636 ChEMBL-Targets; CHEMBL614529 CLS; 300131/p705_BT-474 Cosmic; 687464 Cosmic; 871138 Cosmic; 904351 Cosmic; 923058 Cosmic; 934520 Cosmic; 946359 Cosmic; 970088 Cosmic; 979721 Cosmic; 1000122 Cosmic; 1017168 Cosmic; 1018460 Cosmic; 1046934 Cosmic; 1047699 Cosmic; 1071903 Cosmic; 1129654 Cosmic; 1136353 Cosmic; 1176605 Cosmic; 1287890 Cosmic; 1289383 Cosmic; 1308996 Cosmic; 1434947 Cosmic; 1523771 Cosmic; 1603191 Cosmic; 1609475 Cosmic; 1945863 Cosmic; 2165003 Cosmic; 2301523 Cosmic; 2318376 Cosmic; 2361356 Cosmic-CLP; 946359 DSMZ; ACC-64 GDSC; 946359 GEO; GSM1716 GEO; GSM1725 GEO; GSM69198 GEO; GSM73557 GEO; GSM73702 GEO; GSM115110 GEO; GSM147888 GEO; GSM147957 GEO; GSM149981 GEO; GSM149989 GEO; GSM149997 GEO; GSM155210 GEO; GSM184392 GEO; GSM184393 GEO; GSM213707 GEO; GSM213717 GEO; GSM213718 GEO; GSM213719 GEO; GSM213737 GEO; GSM213740 GEO; GSM213743 GEO; GSM213745 GEO; GSM217615 GEO; GSM274657 GEO; GSM276780 GEO; GSM320173 GEO; GSM344341 GEO; GSM344391 GEO; GSM350504 GEO; GSM388211 GEO; GSM533397 GEO; GSM533412 GEO; GSM590105 GEO; GSM679677 GEO; GSM679678 GEO; GSM679679 GEO; GSM679680 GEO; GSM679681 GEO; GSM679682 GEO; GSM679683 GEO; GSM679684 GEO; GSM679685 GEO; GSM679686 GEO; GSM679687 GEO; GSM679688 GEO; GSM679689 GEO; GSM679690 GEO; GSM679691 GEO; GSM783958 GEO; GSM847198 GEO; GSM847453 GEO; GSM843476 GEO; GSM886892 GEO; GSM887957 GEO; GSM903063 GEO; GSM903064 GEO; GSM903065 GEO; GSM903066 GEO; GSM903067 GEO; GSM903068 GEO; GSM903069 GEO; GSM967821 GEO; GSM1008891 GEO; GSM1053692 GEO; GSM1172941 GEO; GSM1172853 GEO; GSM1214587 GEO; GSM1264068 GEO; GSM1264073 GEO; GSM1264110 GEO; GSM1264115 GEO; GSM1374408 GEO; GSM1374409 GEO; GSM1374410 GEO; GSM1401649 GEO; GSM1669630 GEO; GSM2176271 GEO; GSM2176272 ICLC; HTL00008 IGRhCellID; BT474 KCB; KCB 2011115YJ KCLB; 60062 LINCS_HMS; 50106 LINCS_LDP; LCL-1308 NCBI_Iran; C435 PRIDE; PXD002281 PRIDE; PXD004357 TOKU-E; 694

lncRNA Epigenetic Landscape Analysis Identifies EPIC1 as an Oncogenic lncRNA that Interacts with MYC and Promotes Cell-Cycle Progression in Cancer.

  • Wang Z
  • Cancer Cell
  • 2018 Apr 9

Literature context: BT-474 ATCC Cat# HTB-20; RRID:CVCL_0179 HCC1937 ATCC Cat# CRL-2336; RRI


Abstract:

We characterized the epigenetic landscape of genes encoding long noncoding RNAs (lncRNAs) across 6,475 tumors and 455 cancer cell lines. In stark contrast to the CpG island hypermethylation phenotype in cancer, we observed a recurrent hypomethylation of 1,006 lncRNA genes in cancer, including EPIC1 (epigenetically-induced lncRNA1). Overexpression of EPIC1 is associated with poor prognosis in luminal B breast cancer patients and enhances tumor growth in vitro and in vivo. Mechanistically, EPIC1 promotes cell-cycle progression by interacting with MYC through EPIC1's 129-283 nt region. EPIC1 knockdown reduces the occupancy of MYC to its target genes (e.g., CDKN1A, CCNA2, CDC20, and CDC45). MYC depletion abolishes EPIC1's regulation of MYC target and luminal breast cancer tumorigenesis in vitro and in vivo.

Funding information:
  • Intramural NIH HHS - Z01 ES100485(United States)

Microenvironment-Mediated Mechanisms of Resistance to HER2 Inhibitors Differ between HER2+ Breast Cancer Subtypes.

  • Watson SS
  • Cell Syst
  • 2018 Mar 28

Literature context: Human: BT474 ATCC RRID:CVCL_0179 Human: BT474-TRgf Robert Kerbel


Abstract:

Extrinsic signals are implicated in breast cancer resistance to HER2-targeted tyrosine kinase inhibitors (TKIs). To examine how microenvironmental signals influence resistance, we monitored TKI-treated breast cancer cell lines grown on microenvironment microarrays composed of printed extracellular matrix proteins supplemented with soluble proteins. We tested ∼2,500 combinations of 56 soluble and 46 matrix microenvironmental proteins on basal-like HER2+ (HER2E) or luminal-like HER2+ (L-HER2+) cells treated with the TKIs lapatinib or neratinib. In HER2E cells, hepatocyte growth factor, a ligand for MET, induced resistance that could be reversed with crizotinib, an inhibitor of MET. In L-HER2+ cells, neuregulin1-β1 (NRG1β), a ligand for HER3, induced resistance that could be reversed with pertuzumab, an inhibitor of HER2-HER3 heterodimerization. The subtype-specific responses were also observed in 3D cultures and murine xenografts. These results, along with bioinformatic pathway analysis and siRNA knockdown experiments, suggest different mechanisms of resistance specific to each HER2+ subtype: MET signaling for HER2E and HER2-HER3 heterodimerization for L-HER2+ cells.

Funding information:
  • Intramural NIH HHS - (United States)

A Predictive Model for Selective Targeting of the Warburg Effect through GAPDH Inhibition with a Natural Product.

  • Liberti MV
  • Cell Metab.
  • 2017 Oct 3

Literature context: CCRL-5826Human: BT-474 cellsATCCHTB-20Human: MDA-MB-231 cellsATCCHTB-2


Abstract:

Targeted cancer therapies that use genetics are successful, but principles for selectively targeting tumor metabolism that is also dependent on the environment remain unknown. We now show that differences in rate-controlling enzymes during the Warburg effect (WE), the most prominent hallmark of cancer cell metabolism, can be used to predict a response to targeting glucose metabolism. We establish a natural product, koningic acid (KA), to be a selective inhibitor of GAPDH, an enzyme we characterize to have differential control properties over metabolism during the WE. With machine learning and integrated pharmacogenomics and metabolomics, we demonstrate that KA efficacy is not determined by the status of individual genes, but by the quantitative extent of the WE, leading to a therapeutic window in vivo. Thus, the basis of targeting the WE can be encoded by molecular principles that extend beyond the status of individual genes.

Funding information:
  • NCI NIH HHS - R00 CA168997()
  • NCI NIH HHS - R01 CA174643()
  • NCI NIH HHS - R01 CA193256()
  • NIDDK NIH HHS - R01 DK105550()
  • NIGMS NIH HHS - T32 GM007273()
  • NIGMS NIH HHS - T32 GM008500()

Mitotic Spindle Assembly and Genomic Stability in Breast Cancer Require PI3K-C2α Scaffolding Function.

  • Gulluni F
  • Cancer Cell
  • 2017 Oct 9

Literature context: VCL_0031BT474ATCCCat. # HTB-20; RRID:CVCL_0179SKBR3ATCCCat. # HTB-30; RRID:CVC


Abstract:

Proper organization of the mitotic spindle is key to genetic stability, but molecular components of inter-microtubule bridges that crosslink kinetochore fibers (K-fibers) are still largely unknown. Here we identify a kinase-independent function of class II phosphoinositide 3-OH kinase α (PI3K-C2α) acting as limiting scaffold protein organizing clathrin and TACC3 complex crosslinking K-fibers. Downregulation of PI3K-C2α causes spindle alterations, delayed anaphase onset, and aneuploidy, indicating that PI3K-C2α expression is required for genomic stability. Reduced abundance of PI3K-C2α in breast cancer models initially impairs tumor growth but later leads to the convergent evolution of fast-growing clones with mitotic checkpoint defects. As a consequence of altered spindle, loss of PI3K-C2α increases sensitivity to taxane-based therapy in pre-clinical models and in neoadjuvant settings.

Calmodulin-like protein 3 is an estrogen receptor alpha coregulator for gene expression and drug response in a SNP, estrogen, and SERM-dependent fashion.

  • Qin S
  • Breast Cancer Res.
  • 2017 Aug 18

Literature context:  breast cancer cell lines T47D, BT474, ZR75-1 and CAMA-1 were obtaine


Abstract:

BACKGROUND: We previously performed a case-control genome-wide association study in women treated with selective estrogen receptor modulators (SERMs) for breast cancer prevention and identified single nucleotide polymorphisms (SNPs) in ZNF423 as potential biomarkers for response to SERM therapy. The ZNF423rs9940645 SNP, which is approximately 200 bp away from the estrogen response elements, resulted in the SNP, estrogen, and SERM-dependent regulation of ZNF423 expression and, "downstream", that of BRCA1. METHODS: Electrophoretic mobility shift assay-mass spectrometry was performed to identify proteins binding to the ZNF423 SNP and coordinating with estrogen receptor alpha (ERα). Clustered, regularly interspaced short palindromic repeats (CRISPR)/Cas9 genome editing was applied to generate ZR75-1 breast cancer cells with different ZNF423 SNP genotypes. Both cultured cells and mouse xenograft models with different ZNF423 SNP genotypes were used to study the cellular responses to SERMs and poly(ADP-ribose) polymerase (PARP) inhibitors. RESULTS: We identified calmodulin-like protein 3 (CALML3) as a key sensor of this SNP and a coregulator of ERα, which contributes to differential gene transcription regulation in an estrogen and SERM-dependent fashion. Furthermore, using CRISPR/Cas9-engineered ZR75-1 breast cancer cells with different ZNF423 SNP genotypes, striking differences in cellular responses to SERMs and PARP inhibitors, alone or in combination, were observed not only in cells but also in a mouse xenograft model. CONCLUSIONS: Our results have demonstrated the mechanism by which the ZNF423 rs9940645 SNP might regulate gene expression and drug response as well as its potential role in achieving more highly individualized breast cancer therapy.

Funding information:
  • NCI NIH HHS - P50 CA116201()
  • NCI NIH HHS - R01 CA196648()
  • NCI NIH HHS - U10 CA180868()
  • NIGMS NIH HHS - R01 GM028157()
  • NIGMS NIH HHS - U19 GM061388()

Environmental cystine drives glutamine anaplerosis and sensitizes cancer cells to glutaminase inhibition.

  • Muir A
  • Elife
  • 2017 Aug 15

Literature context: D:CVCL_0179; MCF7: ATCC Cat# HTB-22, RRID:C


Abstract:

Many mammalian cancer cell lines depend on glutamine as a major tri-carboxylic acid (TCA) cycle anaplerotic substrate to support proliferation. However, some cell lines that depend on glutamine anaplerosis in culture rely less on glutamine catabolism to proliferate in vivo. We sought to understand the environmental differences that cause differential dependence on glutamine for anaplerosis. We find that cells cultured in adult bovine serum, which better reflects nutrients available to cells in vivo, exhibit decreased glutamine catabolism and reduced reliance on glutamine anaplerosis compared to cells cultured in standard tissue culture conditions. We find that levels of a single nutrient, cystine, accounts for the differential dependence on glutamine in these different environmental contexts. Further, we show that cystine levels dictate glutamine dependence via the cystine/glutamate antiporter xCT/SLC7A11. Thus, xCT/SLC7A11 expression, in conjunction with environmental cystine, is necessary and sufficient to increase glutamine catabolism, defining important determinants of glutamine anaplerosis and glutaminase dependence in cancer.

TGF-β reduces DNA ds-break repair mechanisms to heighten genetic diversity and adaptability of CD44+/CD24- cancer cells.

  • Pal D
  • Elife
  • 2017 Jan 16

Literature context: , BT-474 (RRID:CVCL_0179), MDA-MB-2


Abstract:

Many lines of evidence have indicated that both genetic and non-genetic determinants can contribute to intra-tumor heterogeneity and influence cancer outcomes. Among the best described sub-population of cancer cells generated by non-genetic mechanisms are cells characterized by a CD44+/CD24- cell surface marker profile. Here, we report that human CD44+/CD24- cancer cells are genetically highly unstable because of intrinsic defects in their DNA-repair capabilities. In fact, in CD44+/CD24- cells, constitutive activation of the TGF-beta axis was both necessary and sufficient to reduce the expression of genes that are crucial in coordinating DNA damage repair mechanisms. Consequently, we observed that cancer cells that reside in a CD44+/CD24- state are characterized by increased accumulation of DNA copy number alterations, greater genetic diversity and improved adaptability to drug treatment. Together, these data suggest that the transition into a CD44+/CD24- cell state can promote intra-tumor genetic heterogeneity, spur tumor evolution and increase tumor fitness.

Funding information:
  • NCI NIH HHS - P01 CA129243()
  • NCI NIH HHS - P30 CA045508()