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A Simple Flow Cytometry-Based Barcode for
Routine Authentication of Multiple Myeloma
and Mantle Cell Lymphoma Cell Lines
To the Editor:
CELL lines are widely used in laboratories for in vitro experi-
ments, especially for investigating abnormal hallmarks in can-
cer cells and identifying therapeutic targets. Human cell lines
are typically derived in academic laboratories from a wide
range of cancer samples. To achieve a representation of intra-
cancer heterogeneity, several laboratories, including ours, have
established cell line collections. However, the establishment
and maintenance of such collections significantly increase the
risk of cross-contaminations and misidentification of cell
lines, leading to the publication of false data/interpretation
(1). In addition to the risk of cross-contamination, widely
used cell lines can be described in contrasting manners for a
particular feature (e.g., the JJN3 myeloma cell line appears
either TP53
wt
or TP53
KO
, depending on the article), suggest-
ing that cell lines may have been misidentified. ICLAC, the
international cell line authentication committee, recommends
cell lines authentication using single tandem repeat (STR)
profiles that are usually performed by suppliers (2). Neverthe-
less, while cell lines are frozen and thawed at least four times
per year, STR profile is assessed upon receipt of cell lines but
not for routine assessment of cell lines identity. Because cross-
contaminations might happen, a rapid and low-cost method
for re-identification after each thawing of cells is required, as
it is for mycoplasma detection.
In this letter, we describe a simple and low cost method
involving human leukocyte antigen (HLA) typing and pheno-
typing that could be used for routine re-authentication using
flow cytometry. HLA typing is an international worldwide
nomenclature dedicated to blood transfusion and organ trans-
plant that identifies the HLA alleles carried by an individual
(3,4). Initially performed for research projects in immunology,
HLA Class I typing appears to be very useful for identification
of cell lines (5,6). The genomic typing is performed at the
generic (e.g., HLA-A*02) or specific (e.g., HLA-A*02:01) level
with the generic typing usually being sufficient to identify cell
lines within a dedicated collection. This genomic identifica-
tion is particularly useful upon the inclusion of new cell lines
within a collection and also for the establishment of deriva-
tives such as drug-resistant cell lines, which could indicate the
emergence of cryptic contaminating resistant cells within the
parental cell lines. Our laboratory currently uses a large num-
ber of both human multiple myeloma cell lines (HMCLs,
n517) and mantle cell lymphoma cell lines (MCLCLs, n58)
that we have collected from ATCC, DSMZ, or from academic
laboratories (7–9). Multiple myeloma (MM) and mantle cell
lymphoma (MCL) are plasma cell and B cell malignancies,
respectively. Independently of the global characterization of
cell lines (karyotype, gene expression profile, characterization
of TP53, and RAS mutations), the HLA Class I typing shown
in Supporting Information Table S1 confirms that the cell
lines examined were derived from independent individuals
(7). To routinely check their identity using flow cytometry, we
generated an algorithm that is based on HLA-A*02 expression
and on the mutually exclusive expression of the kappa or
lambda light chain of immunoglobulin. We used HLA-A*02
expression because HLA-A*02 is the most frequent allele in
the population and because a specific mAb is commercially
available. Expression of HLA-A*02, either positive or negative,
segregated cell lines into two groups: kappa or lambda expres-
sion then segregated the cell lines into 2–3 subgroups (Tables
1 and 2). A minimum of markers with a global, stable, and
selective expression (absent/present or low/bright expression)
was then defined within each subgroup. As shown in Table 1
Grant sponsor: Actions Cancer 44.
Additional Supporting Information may be found in the online version
of this article.
*Correspondence to: Catherine Pellat-Deceunynck, INSERM,
UMR892, Nantes, F-44000, France.
E-mail: catherine.pellat-deceunynck@univ-nantes.fr
Sophie Ma
ıga, Carole Brosseau, G
eraldine Descamps, Christelle Dousset,
and Patricia Gomez-Bougie contributed equally to this work.
Published online 00 Month 2015 in Wiley Online Library
(wileyonlinelibrary.com)
DOI: 10.1002/cyto.a.22643
V
C2015 International Society for Advancement of Cytometry
Cytometry Part A 00: 0000, 2015
Communication to the Editor
and Figure 1A, the HLA-A*02-cytoplasmic kappa/lambda
algorithm segregates HMCLs into five groups of 1–7 cell lines.
To further identify HMCLs within each group, we looked for
surface markers differentially expressed across cell lines. We
used gene expression profile to select molecules either
acquired or lost by malignant plasma cells and thus heteroge-
neously expressed by myeloma cells across both patients and
cell lines (7,10,11). We found nine markers (CD9, CD27,
CD33, CD45, CD81, CD106, CD117, CD137, FGFR3) that
were usually absent or present in an entire HMCL population
and efficient in segregating cell lines within the groups (Fig.
1A). Of note, some of them (CD27, CD33, CD45, CD117, or
FGFR3) are well-known myeloma-related deregulated
markers. The use of clonally related markers, such as HLA-
A*02 and kappa/lambda, may also help to identify cross-
contaminations that may occur after initial genomic authenti-
cation. As shown in Table 2 and Figure 1B, the HLA-A*02-
surface kappa/lambda algorithm in association with the differ-
ential expression of CD28, CD40, or CD5 discriminates the
eight MCLCLs (the MAVER-1 and MINO cell lines are discri-
minated using the differential levels in lambda and CD5
expression). Thus, HMCLs and MCLCLs are identified using
at least two (e.g., KARPAS620 or JEKO-1) and at most five
markers (ANBL-6).
Our authentication procedure of cell lines can be per-
formed in one half-day and does not require DNA. Moreover,
flow cytometry is powerful for the detection of very low cross-
contamination, which might increase during culture time and
repetitive freezing and thawing of cells. This algorithm can
also be used for STR-certified cell lines for which HLA Class I
Table 1. Algorithm for HMCLs.
HMCL HLA-A*02 c-KAPPA c-LAMBDA CD81 CD45 CD137 FGFR3 CD117 CD33 CD9 CD27 CD106 TOTAL
KARPAS620 111 11 2 11 2 2 2 1 2 11 2 2 2
JIM3 1112 11 2 22 2 2 2 2 22 3
U266 1112 11 1 12 2 2 2 2 22 3
KMM1 11 2 11 11 2 1 2 2 2 2 2 2 3
L363 111 2 11 11 2 2 2 2 2 2 2 2 4
KMS11 2 11 2 2 2 2 111 2 2 111 2 2 3
NCIH929 2112 1221221
a
22 3
AMO1 2 11 2 11 11 2 2 2 2 2 2 2 3
JJN3 2 11 2 111 2 2 2 1
a
2 111
a
22 3
SKMM2 2 11 2 111 2 2 2 2 11
a
2223
OPM2 2 2 11 111 2 2 111 2 2 2 2 2 3
LP1 2 2 11 2 2 2 1 2 2 2 2 2 3
RPMI8226 2 2 11 11 2 2 2 2 11 11 2 2 3
MM1S 2 2 11 2 2 2 2 2 2 111 2 2 3
ANBL6 221 2222221
a
22 5
KMS12BM 222
b
1 2 2 2 2 2 111 11 2 4
KMS12PE 222
b
11122 2 2 2 2 21 4
a
Expressed by a subpopulation.
b
KMS12BM and KMS12PE are non-secreting cell lines derived from the same patient and express no detectable level of lambda pro-
tein (both are weakly lambda positive at the mRNA level).
“Total” indicates the minimum number of markers required for cell line identification (the required markers are indicated by gray
shaded areas). Expression was determined using flow cytometry. The monoclonal antibodies (mAbs) used were PE-conjugated, except
for CD117 and FGFR3 mAbs (APC conjugated) and for CD45 mAb (FITC conjugated). The level of expression was defined by calculating
the ratio of fluorescence (specific staining over matched-conjugated isotype staining).
Ratio <2: 2.
2<ratio <10: 1.
10<ratio <50: 11.
Ratio>50: 111.
Table 2. Algorithm for MCLCLs
MCLCL HLA-A*02 KAPPA LAMBDA CD28 CD40 CD5 TOTAL
JEKO-1 11 11 2 2 1 1 2
GRANTA-519 111 2 11 1 1 2 3
JVM2 11 2 1 212 3
REC-1 2 112 212 3
UPN-1 2 111 2 2 2 2 3
Z138 2 2 111 2 1 2 3
MAVER-1 2 2 111 2 1 1 3
MINO 2 2 11 21113
“Total” indicates the minimum number of markers required
for cell line identification (the required markers are indicated by
gray shaded areas). Expression was determined using flow
cytometry. The monoclonal antibodies (mAbs) used were PE-
conjugated, except for CD40 mAb (FITC conjugated). The level of
expression was defined by calculating the ratio of fluorescence
(specific staining over matched-conjugated isotype staining).
Ratio <2: 2.
2<ratio <10: 1.
10<ratio <50: 11.
Ratio>50: 111.
Communication to the Editor
2
typing is unknown because flow cytometry directly assesses
HLA-A*02 expression. This HLA-A*02-based algorithm is
applicable not only to other types of B-cell malignancies but
also to other types of cell line collections if both type-specific
(such as kappa/lambda for B cells) and selective markers are
provided.
Figure 1. Histograms represent the overlay of specific staining (thick line) over control staining (thin line) in HMCLs (A) or MCLCLs (B).
The monoclonal antibodies (mAbs) used were purchased from Beckman Coulter or Becton Dickinson: they were PE-conjugated, except
for CD117 and FGFR3 mAbs (APC conjugated) and for CD40 and CD45 mAbs (FITC conjugated). Cytoplasmic kappa (c-kappa) and c-
lambda staining was performed after the permeabilization of cells using the Intraprep Permeabilization Reagent Kit (Beckman Coulter). A
single color staining was performed for all markers. Fluorescence acquisition (20,000 events were acquired) and analysis were performed
using FACsCalibur (Becton Dickinson) and Cell Quest software (PT Cytocell, SFR Bonamy, Nantes, France).
Communication to the Editor
Cytometry Part A 00: 0000, 2015 3
Sophie Ma
ıga,
1,2,3,4
Carole Brosseau,
1,2,3,4
G
eraldine Descamps,
1,2,3
Christelle Dousset,
1,2,3,5
Patricia Gomez-Bougie,
1,2,3,4
David Chiron,
1,2,3,4
Emmanuelle M
enoret,
6
Charlotte Kervoelen,
1,2,3,6
Henri Vi
e,
1,2,3,4
Anne Cesbron,
7
Agne
`s Moreau-Aubry,
1,2,3
Martine Amiot,
1,2,3,4
Catherine Pellat-Deceunynck
1,2,3,4*
1
INSERM, UMR892, Nantes F-44000, France
2
Universit
e de Nantes, Nantes F-44000, France
3
CNRS, UMR 6299, Nantes F-44000, France
4
CHU Nantes, Nantes
F-44000, France
5
Centre d’investigation Clinique, CHU de
Nantes, Nantes F-44000, France
6
Myelomax SAS, Nantes, France
7
Laboratoire d’Histocompatibiliteet
d’Immunog
en
etique, Etablissement Franc¸ais du
Sang Pays de la Loire, Nantes F-44000, France
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Communication to the Editor
4
... Granta-519 cells express high levels of cyclin D1 due to the chromosomal translocation of t(11;14)(q13;q32), but are deficient for ATM. 11,[13][14][15] In contrast to Granta-519 cells, the cell line Z-138 was derived from the bone marrow of a blastoid mantle cell lymphoma patient 16 Z-138 cells express normal levels of ATM and relatively higher levels of cyclin D. 16 In terms of cell surface markers, Granta-519 and Z-138 cell lines both lack CD5 expression and express lambda light chain and CD19 surface proteins. 14-16 Unlike Granta-519, Z-138 cells do not express HLA-A2 on their surface. ...
... 14-16 Unlike Granta-519, Z-138 cells do not express HLA-A2 on their surface. Thus, this marker can serve to distinguish between the two cell lines 14,16 We confirmed these differences by flow cytometry in our cultures (Data not shown). ...
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... HMCLs were previously characterized [1,6,7]. HMCLs were cultured in RPMI-5% fetal calf serum with or without 3 ng/ml of IL6 [1,6,7]. ...
... HMCLs were previously characterized [1,6,7]. HMCLs were cultured in RPMI-5% fetal calf serum with or without 3 ng/ml of IL6 [1,6,7]. Gene expression profile of HMCLs has been previously published [1]. ...
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... Human myeloma cell lines (HMCLs) (n = 26) and MM1S Dexamethasone resistant cell line (MM1SDR) were characterized as previously described 27,28 ...
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... Методы определения подлинности КЛ постоянно совершенствуются. На протяжении многих лет для аутентификации клеток применялись такие методы, как изоферментный анализ, кариотипирование, HLA-типирование и иммунофенотипирование [5,6]. Однако в последнее десятилетие наиболее широкое распространение получили молекулярно-биологические методы определения подлинности КЛ. ...
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... All cell lines used in this study have been extensively characterized. [27][28][29][30][31] TP53 and RAS mutations were performed by whole-exon sequencing 32 and confirmed by direct sequencing of reverse transcription polymerase chain reaction (RT-PCR) products. 29 p53 deficiency was confirmed by resistance to nutlin3a. ...
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Dear Sir, Recent reports 1–4 demonstrate the growing perception in the scientific community that cross contamination (CC) of mammalian cell lines represents a major risk for generating false scientific data. The level to which research has been compromised by the use of contaminated or misidentified cell lines has become a major concern for scientists, granting agencies, and, increasingly, scientific journals. In 2007, a group of cell biologists led by Roland M. Nardone petitioned the United States Secretary of Health and Human Services to develop an active program for cell line authentication. 5 They stressed that research and teaching tools in diverse fields of science and industry would be unimaginable without cell cultures. Despite the key importance of cell cultures, only little consensus exists regarding the technical means by which cell line identity can be controlled and how to follow through the results of any such testing. The key problems of CC are known and chronic in nature: neglecting guidelines for quality control and disregarding adequate cell culture techniques are the main reasons why cell lines have been misidentified or cross contaminated. The incidence of CC in directly and indirectly provenanced cell lines alike 1,3 implies that the majority of false cell lines are perpetrated in originators’ own laboratories, presumably by failures during the establishment of new cell lines. A plethora of reports unmasking bogus cancer cell lines, including members of the NCI-60 panel used to generate reference baseline transcriptional drug responses has triggered calls for remedial action. 5,6 Nevertheless, standard authentication procedures for testing cell line identity have yet to be defined. Short tandem repeat (STR) microsatellite sequences are highly polymorphic in human populations, and their stability throughout the lifespan of individuals renders STR profiling (typing) ideal for forensic use. STR typing has served as a reference technique for identity control of human cell lines at Biological Resource Centers (BRCs) since the turn of the millennium. 7 Ideally, authentication involves coincident STR