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Preventing Culture Shocks: Fit-For-Purpose Cell Supply Jim Cooper ELRIG Drug Discovery, Manchester, 4th September 2013 ...

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Preventing Culture Shocks: Fit-For-Purpose Cell Supply Jim Cooper ELRIG Drug Discovery, Manchester, 4th September 2013

Organisational structure Since April 2013:

Culture Collections’ Scientific Development Group (SDG)

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Cell Lines are Key Reagents in the Drug Discovery Workflow

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Cell Lines are Critical Reagents

PSN1 – 94060601 Human pancreatic adenocarcinoma cell line

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They should be as physiologically relevant as possible



Their biology and relevance should be understood



They should be verified



The supply should be standard and consistent



Robust Quality Control is paramount



New technologies give new insights into cell QC

Factors Impacting Cell Supply  Inventory management  Mycoplasma and other microbial contamination  Maintenance of desired cell characteristics: • Finite / primary cell lines • Over-passaging • Sub-optimal cryopreservation and storage • Affect of cell environment on phenotype and selective pressure  Misidentified or cross contaminated cell lines: • Awareness • Consensus • Test Limitations

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Inventory Management: The Challenge of Managing Legacy in a Cell Repository What’s really in the freezer?

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?

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>95% Accuracy 24% Accuracy 8

2003 – 2008: ECACC LN2 StockCheck • >40 year’s worth of master, • • • •



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working, distribution and legacy stock >50,000 cell lines 2 x WTE for 5 years Over 1 million vial locations in 32 consolidated tanks Inventory software input by barcode, keyboard and voice activated interface. 2-3 operation verification of each location.

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Effect of Sub-optimal Storage Plating Profile of Cells Stored at Client’s Lab

Plating Profile of cells stored at ECACC

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Sub-optimal Cryopreservation and Storage Poor freezing may have a similar effect as re-cloning or extensive passage. Effective QC

• Apoptosis • Plating • Growth

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Mycoplasma Contamination

In 20% of cultures received by ECACC

Surface of a Vero Cell under scanning electron microscopy 16



Tests for Mycoplasma ECACC uses:    

Culture Isolation (Reference Method) PCR Indirect DNA Stain (Hoechst) Working towards MycoAlert

Regulatory authorities currently only recognise Culture Isolation and Indirect DNA Stain 17

% accuracy

Accuracy

to t3 t3 cells

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Culture Collections - a PHE Biological Resource

Nested PCR

assays

in house PCR 2

in house PCR 1

MycoAlert

hoechst stain

isolation

90 80 70 60 50 40 30 20 10 0

Over Passaging of Cells and Prolonged Culture

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Culture Collections - a PHE Biological Resource

A549 Lamellar bodies: 1976

MUC5A

2013 ABCA3

2D 21

MUC5B

3D

2D

3D

Impact of Cell Environment on Phenotype:

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A549 Human Lung Carcinoma - gene expression is significantly altered with different substrates.

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Misidentified Cell lines 1952 – HeLa Cell Line

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Cell Line

Claimed origin:

C16

Human foetal lung

Chang Liver

Human liver

Clone 1-5c-4

Human conjunctiva

D98/AH2 Clone B

Somatic cell hybrid (HeLa cells and mouse 3T3 cells)

FL

Human amnion

GIRARDI HEART

Human heart

Hep-2C

Human larynx

Hep2

Human larynx

HSG

Human sub-mandibular gland

INT 407

Human embryonic intestine

JIII

Human monocytic leukaemia

KB

Human oral epidermis

L-41

Human bone marrow

L132

Human embryonic lung

WISH

Human amnion

WKD

Human conjunctiva

WRL 68

Human embryonic liver

1970’s

Issue of HeLa contamination identified

Today:

It’s not just HeLa… The issue is getting worse Capes-Davies and Freshney - Comprehensive list of ~400 misidentified cell lines identified in peer reviewed literature

20% of human cancer research has been carried out on the wrong cell lines THOUSANDS of recent publications are invalid!

1. MacLeod et al., (1999)) 2. Drexler HG et al. (2003.

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GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA

2, 4

GATA-GATA GATA-GATA GATA-GATA

GATA-GATA

GATA-GATA GATA-GATA GATA-GATA

GATA-GATA GATA-GATA GATA-GATA

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1, 3

GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA GATA-GATA

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STR profiling 29

GATA-GATA GATA-GATA

GATA-GATA GATA-GATA GATA-GATA

2, 3

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International Cell Line Authentication Committee (ICLAC)

ICLAC International Cell Line Authentication Committee

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Primer Sets FSS

FSS SGM

SGM+

D8 D21

Powerplex 1.2

Codis set

Powerplex 16

identifiler+

D8

D8

D8

D8

D21

D21

D21

D21

D7

D7

D7

D7

CSF1PO

CSF1PO

CSF1PO

CSF1PO

D3

D3

D3

THO1

THO1

THO1

THO1

D13

D13

D13

D13

D16

D16

D3 THO1

THO1

THO1 D16

vWA

vWA

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D2

D2

D19

D19

vWA

D18

D18

Am

Am

FGA

D16

FGA

vWA

vWA

vWA

vWA

TPOX

TPOX

TPOX

TPOX

D18

D18

D18

Am

Am

Am

Am

D5

D5

D5

D5

FGA

FGA

FGA

FES

Penta D

F13A1

Penta E

Standardisation of results and guideline interpretation - STR Profile Match Criteria •Compare with “standard” profiles on online databases and profiles in your data set. •Focus on the 8 Core Alleles and Gender •Calculate the % match • • •

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ANSI/ATCC ASN-002 Standard (2011) International Cell Line Authentication Committee (ICLAC) Resources http://standards.atcc.org/kwspub/home/the_international_cell_line_authentication_committeeiclac_/

Categorisation •Unique cell line: STR profile “80% or more” unique – no matches can be found on public access databases •Authentic cell line: STR profile matches a cell line of the same designation (same donor) with 80% or more accuracy •Misidentified or cross contaminated cell line: matches a cell line of another designation (another donor) with 80% or more accuracy OR does not match the designated cell line profile (less than 55% match) •Cell line is genetically unstable (mutation) : between 56% and 80% match – requires more investigation. (Rare).

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Example: Locus D5S818 D13S317 D7S820 D16S539 vWA THO1 Amelogenin TPOX CSF1PO

Test Sample Score 12 12 10 8,9 15,16 8 X 10,12 12,13

10,13 9 10,12 11 17 7 X 11 12,14

Total Alleles in Test Sample

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Total Alleles in Reference Sample

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Shared Alleles in Test and Reference Samples

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Percent Match =

Number of Shared Alleles x 2 Total Alleles in Test Sample + Total alleles in the Reference Sample

= 32% Match

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Reference Sample

ICLAC maintains the database of ~400 misidentified cell lines

Freshney R. I. et al (2010) Int J Cancer. 126: 302-04

New cases since ICLAC inception (2012)

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Reference / cell line

Outcome (to date)

4 x Naso-pharangeal cell lines (CNE1, 2 & HNE 1, 2) fingerprinted as 60-80% match with HeLa

Discussion ongoing. Are they simple cross contaminations or hybrids?

NCI-H929 Human Myeloma. Breitkopf et al in PNAS (USA) 2012 claim the cell line expresses a rare BCRABL tyrosine kinase. Fingerprinting showed their NCIH929 cells were actually the leukaemeia cell line: K562.

Discussion followed up through letters to PNAS from Macleod et al (2012) and a reply from Breitkopf et al who still claim their NCI-H929 is genuine but has “chameleon characteristics”.

SLK human Kaposi sarcoma demonstrated to be Caki (renal cell carcinoma) by Sturzl et al In J Cancer 2012

Added to the database

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Reference / cell line

Outcome (to date)

KU7, used as a human bladder cell line for decades demonstrated as being Hela by Jager et al, J Urol 2013

Added to database

R06E – a new fruit bat cell line (2009) permissive to vaccinia Ankara shown by the originating authors (Jordan et al) to be Vero (African Green Monkey) (2012)

Added to database

1205Lu Melanoma. Claimed by Nair et al to be cross contaminated with mouse cells (cell line was grown as a xenograft).

Under investigation - the issue may only relate to one supplier.

Thyroid Medullary Carcinomas RO-H85-1 and RD-81-1 found to be 647-V bladder carcinoma and HT-29 colon carcinoma respectively

Added to database

Novel MAI cell line (MALT lymphoma), Kuo et al Genes, Chrom and Cancer 2011. The author published the STR profile as part of the cell line characterisation but did not check it against a database. The paper passed peer review but it is clear that the profile matches the already established lymphoma cell line “Pfeiffer”. A quick literature search demonstrated the author published work on Pfeiffer two years previously.

A letter from ICLAC has been submitted to Genes Chromosomes and Cancer.

T1 novel neural stem cell line, Wu et al 2011. The author published the STR profile as part of the cell line characterisation but did not check it against a database. The paper passed peer review but it is clear that the profile matches Hela.

Challenge ongoing

Residual Issues: Cell Lines with the same name

No. of Loci Cell Line Tumour Testing Lab Locus D5S818 D13S317 D7S820 D16S539 vWA THO1 Amelogenin TPOX CSF1PO D8S1179 D21S11 D3S1358 PentaE PentaD D18S51 FGA

9 loci T406* Oral SCC Zhao 2011 Score 12 12 10 8,9 15,16 8 X 10,12 12,13

16 loci T406 Glioblastoma CLS 10,13 9 10,12 11 17 7 X 11 12,14 14 28,30 14,16 7,10 11 13,18 23,26

* Reported identical to seven other SCC cell lines by Zhao in 2011. Entered into the database of misidentified cell lines 38

9 Loci aren’t always adequate… No. Loci Testing Lab Cell Line Tumour Locus D5S818 D13S317 D7S820 D16S539 vWA THO1 Amelogenin TPOX CSF1PO D8S1179 D21S11 D3S1358 PentaE PentaD D18S51 FGA

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9 loci ATCC Cess Lymphoma Score 11,12 12 10,12 12 16,17 7,9.3 X,Y 8,9 10,11

9 loci 16 loci 16 loci DSMZ ECACC ECACC IGR 37 / IGR 39 IGR 39 IGR 37 Melanoma (Same Patient)

16 loci Castella LN235 Glioma

11,12 12 10,11 11 17,21 9 X,Y 8,11 11,12

11,12 9 10,12 11 17 7,9 X,Y 8 11,12 14,15 29,32.2 15 14,15 11,12 13,16 22

11,12 12 10,11 11 17,21 9 X,Y 8,11 11,12 14,15 31.2,32.2 17,18 12,16 9 15 22

11,12 12 10,11 11 17,21 9 X,Y 8,11 11,12 14,15 31.2,32.2 17,18 12,16 9 14,15 22

In the absence of regulation it is up to all of us to ensure we’re working with verified materials and therefore carrying out valid research. 40

Uniquely Identifying Non-Human Cell Lines…

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Factors Impacting Cell Supply  Inventory management  Mycoplasma and other microbial contamination  Maintenance of desired cell characteristics: • Finite / primary cell lines • Over-passaging • Sub-optimal cryopreservation and storage • Affect of cell environment on phenotype and selective pressure  Misidentified or cross contaminated cell lines: • Awareness • Consensus • Test Limitations

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Thanks

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To you all for your attention

• • • • • • •

Steve Grigsby and the Culture Collections’ Logistics Team Dr Ed Burnett and Dr Liz Penn and rest of the SDG Team Dr Karen Kempsell and Muhammad Abdulatif, Diagnostic Technologies, PHE Porton Howard Tolley, Microbial Imaging, PHE Porton Dr Amanda Capes-Davis and the ICLAC Team Jamie Taylor and Claire Wilson, Culture Collections’ QC Diane Fellows, ECACC Operations



And…… to my Mother in Law for the frozen red cabbage.

Jim Cooper Cell Biology Applications Scientist

[email protected] www.phe-culturecollections.org.uk

ELRIG Drug Discovery, Manchester, 4th September 2013