Cellosaurus HuP-T3 (CVCL_1299)

Cell line name HuP-T3
Synonyms HUP-T3; HuPT3; HupT3; HUPT3
Accession CVCL_1299
Resource Identification Initiative To cite this cell line use: HuP-T3 (RRID:CVCL_1299)
Comments Part of: Cancer Cell Line Encyclopedia (CCLE) project.
Doubling time: ~40-50 hours (DSMZ).
Microsatellite instability: Stable (MSS) (Sanger).
Omics: Array-based CGH.
Omics: Deep exome analysis.
Omics: Deep RNAseq analysis.
Omics: DNA methylation analysis.
Omics: Metabolome analysis.
Omics: SNP array analysis.
Omics: Transcriptome analysis.
Disease Pancreatic adenocarcinoma (NCIt: C8294)
Species of origin Homo sapiens (Human) (NCBI Taxonomy: 9606)
Hierarchy Children: CVCL_2258 (1.2B4)
Sex of cell Male
Category Cancer cell line
STR profile Source(s): Cosmic-CLP; DSMZ; ECACC; PubMed=25877200

Markers:
AmelogeninX,Y
CSF1PO10
D13S3179,11
D16S53910,13
D18S5116,17
D21S1128,30
D3S135815,16
D5S81810,14
D7S82012
D8S117915
FGA21,22
Penta D9,10
Penta E16,17
TH019
TPOX8,12
vWA18
Publications

PubMed=8454916; DOI=10.1007/BF02795197
Nishimura N., Saito S., Kubota Y., Moto-o N., Taguchi K., Yamazaki K., Watanabe A., Sasaki H.
Newly established human pancreatic carcinoma cell lines and their lectin binding properties.
Int. J. Pancreatol. 13:31-41(1993)

PubMed=15126341; DOI=10.1158/0008-5472.CAN-03-3159
Heidenblad M., Schoenmakers E.F.P.M., Jonson T., Gorunova L., Veltman J.A., van Kessel A.G., Hoglund M.
Genome-wide array-based comparative genomic hybridization reveals multiple amplification targets and novel homozygous deletions in pancreatic carcinoma cell lines.
Cancer Res. 64:3052-3059(2004)

PubMed=15688027; DOI=10.1038/sj.onc.1208383
Heidenblad M., Lindgren D., Veltman J.A., Jonson T., Mahlamaki E.H., Gorunova L., van Kessel A.G., Schoenmakers E.F.P.M., Hoglund M.
Microarray analyses reveal strong influence of DNA copy number alterations on the transcriptional patterns in pancreatic cancer: implications for the interpretation of genomic amplifications.
Oncogene 24:1794-1801(2005)

PubMed=22460905; DOI=10.1038/nature11003
Barretina J.G., Caponigro G., Stransky N., Venkatesan K., Margolin A.A., Kim S., Wilson C.J., Lehar J., Kryukov G.V., Sonkin D., Reddy A., Liu M., Murray L., Berger M.F., Monahan J.E., Morais P., Meltzer J., Korejwa A., Jane-Valbuena J., Mapa F.A., Thibault J., Bric-Furlong E., Raman P., Shipway A., Engels I.H., Cheng J., Yu G.K., Yu J., Aspesi P. Jr., de Silva M., Jagtap K., Jones M.D., Wang L., Hatton C., Palescandolo E., Gupta S., Mahan S., Sougnez C., Onofrio R.C., Liefeld T., MacConaill L., Winckler W., Reich M., Li N., Mesirov J.P., Gabriel S.B., Getz G., Ardlie K., Chan V., Myer V.E., Weber B.L., Porter J., Warmuth M., Finan P., Harris J.L., Meyerson M., Golub T.R., Morrissey M.P., Sellers W.R., Schlegel R., Garraway L.A.
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.
Nature 483:603-607(2012)

PubMed=25167228; DOI=10.1038/bjc.2014.475
Hamidi H., Lu M., Chau K., Anderson L., Fejzo M., Ginther C., Linnartz R., Zubel A., Slamon D.J., Finn R.S.
KRAS mutational subtype and copy number predict in vitro response of human pancreatic cancer cell lines to MEK inhibition.
Br. J. Cancer 111:1788-1801(2014)

PubMed=25485619; DOI=10.1038/nbt.3080
Klijn C., Durinck S., Stawiski E.W., Haverty P.M., Jiang Z., Liu H., Degenhardt J., Mayba O., Gnad F., Liu J., Pau G., Reeder J., Cao Y., Mukhyala K., Selvaraj S.K., Yu M., Zynda G.J., Brauer M.J., Wu T.D., Gentleman R.C., Manning G., Yauch R.L., Bourgon R., Stokoe D., Modrusan Z., Neve R.M., de Sauvage F.J., Settleman J., Seshagiri S., Zhang Z.
A comprehensive transcriptional portrait of human cancer cell lines.
Nat. Biotechnol. 33:306-312(2015)

PubMed=26216984; DOI=10.1073/pnas.1501605112
Daemen A., Peterson D., Sahu N., McCord R., Du X., Liu B., Kowanetz K., Hong R., Moffat J., Gao M., Boudreau A., Mroue R., Corson L., O'Brien T., Qing J., Sampath D., Merchant M., Yauch R., Manning G., Settleman J., Hatzivassiliou G., Evangelista M.
Metabolite profiling stratifies pancreatic ductal adenocarcinomas into subtypes with distinct sensitivities to metabolic inhibitors.
Proc. Natl. Acad. Sci. U.S.A. 112:E4410-E4417(2015)

PubMed=27397505; DOI=10.1016/j.cell.2016.06.017
Iorio F., Knijnenburg T.A., Vis D.J., Bignell G.R., Menden M.P., Schubert M., Aben N., Goncalves E., Barthorpe S., Lightfoot H., Cokelaer T., Greninger P., van Dyk E., Chang H., de Silva H., Heyn H., Deng X., Egan R.K., Liu Q., Mironenko T., Mitropoulos X., Richardson L., Wang J., Zhang T., Moran S., Sayols S., Soleimani M., Tamborero D., Lopez-Bigas N., Ross-Macdonald P., Esteller M., Gray N.S., Haber D.A., Stratton M.R., Benes C.H., Wessels L.F.A., Saez-Rodriguez J., McDermott U., Garnett M.J.
A landscape of pharmacogenomic interactions in cancer.
Cell 166:740-754(2016)

Cross-references
Cell line collections DSMZ; ACC-259
ECACC; 93121055
ICLC; HTL96006
Cell line databases/resources CLDB; cl1769
CLDB; cl1770
CLDB; cl1771
CCLE; HUPT3_PANCREAS
Cosmic-CLP; 907285
GDSC; 907285
LINCS_LDP; LCL-1790
Ontologies CLO; CLO_0004299
CLO; CLO_0004300
EFO; EFO_0006596
Biological sample resources BioSample; SAMN03472116
Chemistry resources ChEMBL-Cells; CHEMBL3308399
ChEMBL-Targets; CHEMBL1075477
Gene expression databases GEO; GSM206515
GEO; GSM827205
GEO; GSM887151
GEO; GSM888223
GEO; GSM1374567
GEO; GSM1669922
Polymorphism and mutation databases Cosmic; 907285
Cosmic; 1995451
Cosmic; 2434096