KMS-26Homo sapiens (Human)Cancer cell line

Also known as: Kawasaki Medical School-26, KMS26

🤖 AI SummaryBased on 14 publications

Quick Overview

Human multiple myeloma cell line with known genetic alterations and drug resistance profiles.

Detailed Summary

KMS-26 is a human multiple myeloma cell line derived from a patient with plasma cell leukemia. It is characterized by specific genetic alterations, including translocations and mutations that contribute to its malignant phenotype. This cell line has been used in studies to investigate the mechanisms of drug resistance and the role of various signaling pathways in myeloma progression. Research on KMS-26 has provided insights into the molecular characteristics of multiple myeloma and has been instrumental in understanding the disease's response to therapeutic interventions.

Research Applications

Investigation of drug resistance mechanismsStudy of genetic alterations in multiple myelomaAnalysis of signaling pathways in myeloma progression

Key Characteristics

Translocations and mutations associated with malignant transformationDrug resistance profilesRelevance to multiple myeloma research
Generated on 6/19/2025

Basic Information

Database IDCVCL_2992
SpeciesHomo sapiens (Human)
Tissue SourcePleural effusion[UBERON:UBERON_0000175]

Donor Information

Age50
Age CategoryAdult
SexMale
Raceasian

Disease Information

DiseaseMultiple myeloma
LineageLymphoid
SubtypePlasma Cell Myeloma
OncoTree CodePCM

DepMap Information

Source TypeHSRRB
Source IDACH-000588_source

Known Sequence Variations

TypeGene/ProteinDescriptionZygosityNoteSource
MutationSimpleTP53p.Arg175His (c.524G>A)UnspecifiedSomatic mutation acquired during proliferationfrom parent cell line YCC-3

Haplotype Information (STR Profile)

Short Tandem Repeat (STR) profile for cell line authentication.

Amelogenin
X,Y
CSF1PO
10
D13S317
12
D16S539
10
D18S51
13,20
D21S11
30,31.2
D3S1358
16
D5S818
13
D7S820
8,12
D8S1179
14,15
FGA
24
Penta D
11
Penta E
12
TH01
7,8
TPOX
11,12
vWA
17,20
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

Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis.

Sirota M., Wiita A.P.

Leukemia 34:2754-2765(2020).

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).

Profiling the B/T cell receptor repertoire of lymphocyte derived cell lines.

Yang H.H., Koeffler H.P.

BMC Cancer 18:940.1-940.13(2018).

Characterization of human cancer cell lines by reverse-phase protein arrays.

Liang H.

Cancer Cell 31:225-239(2017).

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).

Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies.

Golub T.R., Root D.E., Hahn W.C.

Sci. Data 1:140035-140035(2014).

A resource for cell line authentication, annotation and quality control.

Neve R.M.

Nature 520:307-311(2015).

A comprehensive transcriptional portrait of human cancer cell lines.

Settleman J., Seshagiri S., Zhang Z.-M.

Nat. Biotechnol. 33:306-312(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).

Integrative high-resolution microarray analysis of human myeloma cell lines reveals deregulated miRNA expression associated with allelic imbalances and gene expression profiles.

Todoerti K., Ronchetti D., Lambertenghi-Deliliers G., Neri A.

Genes Chromosomes Cancer 48:521-531(2009).

Characterization of MYC translocations in multiple myeloma cell lines.

Dib A., Gabrea A., Glebov O.K., Bergsagel P.L., Kuehl W.M.

J. Natl. Cancer Inst. Monogr. 39:25-31(2008).

An integrative genomic approach reveals coordinated expression of intronic miR-335, miR-342, and miR-561 with deregulated host genes in multiple myeloma.

Fabris S., Lambertenghi-Deliliers G., Neri A.

BMC Med. Genomics 1:37.1-37.9(2008).

Promiscuous mutations activate the noncanonical NF-kappaB pathway in multiple myeloma.

Stewart A.K., Carpten J.D., Bergsagel P.L.

Cancer Cell 12:131-144(2007).

Molecular characterization of human multiple myeloma cell lines by integrative genomics: insights into the biology of the disease.

Lambertenghi-Deliliers G., Bertoni F., Neri A.

Genes Chromosomes Cancer 46:226-238(2007).

Expression of protein gene product 9.5 (PGP9.5)/ubiquitin-C-terminal hydrolase 1 (UCHL-1) in human myeloma cells.

Murakami H., Sadahira Y., Sugihara T.

Br. J. Haematol. 127:292-298(2004).

Overexpression of PDZK1 within the 1q12-q22 amplicon is likely to be associated with drug-resistance phenotype in multiple myeloma.

Taniwaki M., Inazawa J.

Am. J. Pathol. 165:71-81(2004).