KMS-11Homo sapiens (Human)Cancer cell line

Also known as: Kawasaki Medical School-11, kms 11, kms11, KMS11

🤖 AI SummaryBased on 14 publications

Quick Overview

Human multiple myeloma cell line with B cell origin, used in cancer research.

Detailed Summary

The KMS-11 cell line is a human multiple myeloma cell line derived from a B cell lineage. It is widely used in cancer research, particularly in studies related to multiple myeloma. This cell line has been characterized in various genomic and transcriptomic studies, showing specific mutations and expression profiles that are relevant to myeloma biology. Research on KMS-11 has contributed to understanding the genetic and molecular mechanisms underlying multiple myeloma, including the role of MYC translocations and other genomic alterations. The cell line is also utilized in drug sensitivity and resistance studies, providing insights into potential therapeutic targets and treatment strategies.

Research Applications

Multiple myeloma researchGenomic and transcriptomic studiesDrug sensitivity and resistance studiesMYC translocation analysis

Key Characteristics

B cell originMYC translocationsGenomic instabilityDrug response profiling
Generated on 6/19/2025

Basic Information

Database IDCVCL_2989
SpeciesHomo sapiens (Human)
Tissue SourcePleural effusion[UBERON:UBERON_0000175]

Donor Information

Age67
Age CategoryAdult
SexFemale
Raceasian

Disease Information

DiseaseMultiple myeloma
LineageLymphoid
SubtypePlasma Cell Myeloma
OncoTree CodePCM

DepMap Information

Source TypeHSRRB
Source IDACH-000714_source

Known Sequence Variations

TypeGene/ProteinDescriptionZygosityNoteSource
MutationSimpleTRAF3p.Lys191Leufs*3Homozygous-from parent cell line KMS-11
MutationSimpleFGFR3p.Tyr373Cys (c.1118A>G)Unspecified-from parent cell line KMS-11
Gene fusionIGKJ5IGKV3-15-IGKJ5--from parent cell line KMS-11
Gene fusionIGKJ4IGKV1-37-IGKJ4--from parent cell line KMS-11

Haplotype Information (STR Profile)

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

Amelogenin
X
CSF1PO
13
D13S317
12
D16S539
9,13
D18S51
13,14
D21S11
28,30
D3S1358
15
D5S818
10,12
D7S820
11,12
D8S1179
13
FGA
22,24
Penta D
11,12
Penta E
15,16
TH01
6,9
TPOX
12
vWA
17,18
Gene Expression Profile
Gene expression levels and statistical distribution
Loading cohorts...
Full DepMap dataset with combined data across cell lines

Loading gene expression data...

Publications

Pan-cancer proteomic map of 949 human cell lines.";

Robinson P.J., Zhong Q., Garnett M.J., Reddel R.R.

Cancer Cell 40:835-849.e8(2022).

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).

Quantitative proteomics of the Cancer Cell Line Encyclopedia.";

Sellers W.R., Gygi S.P.

Cell 180:387-402.e16(2020).

Next-generation characterization of the Cancer Cell Line Encyclopedia.

Sellers W.R.

Nature 569:503-508(2019).

Prioritization of cancer therapeutic targets using CRISPR-Cas9 screens.

Stronach E.A., Saez-Rodriguez J., Yusa K., Garnett M.J.

Nature 568:511-516(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).

Whole-exon sequencing of human myeloma cell lines shows mutations related to myeloma patients at relapse with major hits in the DNA regulation and repair pathways.

Pellat-Deceunynck C.

J. Hematol. Oncol. 11:137.1-137.13(2018).

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).

A landscape of pharmacogenomic interactions in cancer.";

Wessels L.F.A., Saez-Rodriguez J., McDermott U., Garnett M.J.

Cell 166:740-754(2016).

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 simple flow cytometry-based barcode for routine authentication of multiple myeloma and mantle cell lymphoma cell lines.

Moreau-Aubry A., Amiot M., Pellat-Deceunynck C.

Cytometry A 87:285-288(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).

A high-risk signature for patients with multiple myeloma established from the molecular classification of human myeloma cell lines.

Pellat-Deceunynck C.

Haematologica 96:574-582(2011).

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).

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).

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).

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).

The phenotype of normal, reactive and malignant plasma cells. Identification of 'many and multiple myelomas' and of new targets for myeloma therapy.

Moreau P., Amiot M., Pellat-Deceunynck C.

Haematologica 91:1234-1240(2006).

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).

Activated fibroblast growth factor receptor 3 is an oncogene that contributes to tumor progression in multiple myeloma.

Kuehl W.M., Bergsagel P.L.

Blood 97:729-736(2001).

Malignant hematopoietic cell lines: in vitro models for the study of multiple myeloma and plasma cell leukemia.

Drexler H.G., Matsuo Y.

Leuk. Res. 24:681-703(2000).

PTEN gene alterations in lymphoid neoplasms.";

Sakai A., Thieblemont C., Wellmann A., Jaffe E.S., Raffeld M.

Blood 92:3410-3415(1998).

Promiscuous translocations into immunoglobulin heavy chain switch regions in multiple myeloma.

Kuehl W.M.

Proc. Natl. Acad. Sci. U.S.A. 93:13931-13936(1996).

Establishment of five human myeloma cell lines.";

Yawata Y., Kimoto T.

In Vitro Cell. Dev. Biol. 25:723-729(1989).

Establishment and characterization of five human myeloma cell lines.

Ohtsuki T., Yawata Y., Namba M.

Hum. Cell 2:297-303(1989).

The leukemia-lymphoma cell line factsbook.";

Drexler H.G.

(In book) ISBN 9780122219702; pp.1-733; Academic Press; London; United Kingdom (2001).

Multiple myeloma cell lines.";

Jernberg-Wiklund H., Nilsson K.

(In book chapter) Human cell culture. Vol. 3. Cancer cell lines part 3; Masters J.R.W., Palsson B.O. (eds.); pp.81-155; Kluwer Academic Publishers; New York; USA (2000).