SNU-1076Homo sapiens (Human)Cancer cell line
Also known as: NCI-SNU-1076, SNU1076
AI Summary
No AI-generated summary available for this cell line.
Basic Information
| Database ID | CVCL_5006 |
|---|---|
| Species | Homo sapiens (Human) |
| Tissue Source | Larynx[UBERON:UBERON_0001737] |
Donor Information
| Age | 60 |
|---|---|
| Age Category | Adult |
| Sex | Male |
| Race | asian |
Disease Information
| Disease | Squamous cell carcinoma of the larynx |
|---|---|
| Lineage | Head and Neck |
| Subtype | Larynx Squamous Cell Carcinoma |
| OncoTree Code | LXSC |
DepMap Information
| Source Type | KCLB |
|---|---|
| Source ID | ACH-000549_source |
Known Sequence Variations
| Type | Gene/Protein | Description | Zygosity | Note | Source |
|---|---|---|---|---|---|
| MutationSimple | PIK3CA | p.His1047Arg (c.3140A>G) | Unspecified | - | PubMed=25926053, PubMed=20570890 |
| MutationSimple | CDKN2A | p.Pro114His (c.341C>A) (p.Ala128Ala, c.384C>A) | Homozygous | - | Unknown, PubMed=10369293 |
Haplotype Information (STR Profile)
Short Tandem Repeat (STR) profile for cell line authentication.
Amelogenin
X,Y
CSF1PO
11,12
D10S1248
13
D12S391
19,20
D13S317
8,10
D16S539
13
D18S51
14
D19S433
15.2
D1S1656
15
D21S11
30
D22S1045
15,17
D2S1338
19,24
D2S441
11
D3S1358
15
D5S818
9,12
D7S820
11,12
D8S1179
10,15
DYS391
11
FGA
24,25
Penta D
9,10
Penta E
12,22
TH01
6
TPOX
8,11
vWA
15,16
Gene Expression Profile
Gene expression levels and statistical distribution
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Full DepMap dataset with combined data across cell lines
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Publications
Next-generation characterization of the Cancer Cell Line Encyclopedia.
Sellers W.R.
Nature 569:503-508(2019).
An interactive resource to probe genetic diversity and estimated ancestry in cancer cell lines.
Dutil J., Chen Z.-H., Monteiro A.N.A., Teer J.K., Eschrich S.A.
Cancer Res. 79:1263-1273(2019).
TCLP: an online cancer cell line catalogue integrating HLA type, predicted neo-epitopes, virus and gene expression.
Loewer M., Sahin U., Castle J.C.
Genome Med. 7:118.1-118.7(2015).
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.
Morrissey M.P., Sellers W.R., Schlegel R., Garraway L.A.
Nature 483:603-607(2012).