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Cytotoxic drug sensitivity of Epstein-Barr virus transformed lymphoblastoid B-cells

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BMC Cancer20066:265

https://doi.org/10.1186/1471-2407-6-265

©  Markasz et al; licensee BioMed Central Ltd. 2006

Received: 30 August 2006

Accepted: 13 November 2006

Published: 13 November 2006

Open Peer Review reports

Abstract

Background

Epstein-Barr virus (EBV) is the causative agent of immunosuppression associated lymphoproliferations such as post-transplant lymphoproliferative disorder (PTLD), AIDS related immunoblastic lymphomas (ARL) and immunoblastic lymphomas in X-linked lymphoproliferative syndrome (XLP). The reported overall mortality for PTLD often exceeds 50%. Reducing the immunosuppression in recipients of solid organ transplants (SOT) or using highly active antiretroviral therapy in AIDS patients leads to complete remission in 23–50% of the PTLD/ARL cases but will not suffice for recipients of bone marrow grafts. An additional therapeutic alternative is the treatment with anti-CD20 antibodies (Rituximab) or EBV-specific cytotoxic T-cells. Chemotherapy is used for the non-responding cases only as the second or third line of treatment. The most frequently used chemotherapy regimens originate from the non-Hodgkin lymphoma protocols and there are no cytotoxic drugs that have been specifically selected against EBV induced lymphoproliferative disorders.

Methods

As lymphoblastoid cell lines (LCLs) are well established in vitro models for PTLD, we have assessed 17 LCLs for cytotoxic drug sensitivity. After three days of incubation, live and dead cells were differentially stained using fluorescent dyes. The precise numbers of live and dead cells were determined using a custom designed automated laser confocal fluorescent microscope.

Results

Independently of their origin, LCLs showed very similar drug sensitivity patterns against 29 frequently used cytostatic drugs. LCLs were highly sensitive for vincristine, methotrexate, epirubicin and paclitaxel.

Conclusion

Our data shows that the inclusion of epirubicin and paclitaxel into chemotherapy protocols against PTLD may be justified.

Keywords

  • Bortezomib
  • Epirubicin
  • Topotecan
  • Area Under Curve
  • Cell Survival Curve

Background

Development of malignant B-cell lymphomas after organ transplantation is a significant complication arising as a side effect of the immunosuppression required for successful graft survival. The oncogenic Epstein-Barr virus (EBV) is the etiologic agent in the posttransplant lymphoproliferative disorder (PTLD) and AIDS related immunoblastic lymphomas (ARL) [1]. The reported overall mortality for PTLD often exceeds 50% [2, 3]. The prognosis for PTLDs occurring after bone marrow transplantation is even worse [4, 5]. Male patients with the rare inherited X-linked lymphoproliferative syndrome, showing specific immune defect against EBV infection, also often succumb to EBV induced malignant lymphomas [6].

EBV is a ubiquitous human herpesvirus that persists for life. Primary EBV infection can lead to mononucleosis (IM) in adolescence and in adults, manifested by a massive expansion of B cells. EBV-encoded transformation-associated proteins drive the proliferation of B lymphoblasts in IM, in PTLDs and in immunodeficiency syndrome-associated immunoblastic lymphomas. The EBV transformed cells express nine latency-associated viral proteins: EBNA1-6, LMP-1, -2A and -2B. This latency program is referred to as the type III latency. The same latency program is present in the in vitro proliferating lymphoblastoid cell lines (LCLs), generated by infection of normal human B cells with EBV. The fraction of B cells that is susceptible to in vitro transformation can be anything between 10% and 100% [7].

EBV drives the proliferation of human B cells in vitro and during primary infection in vivo. Strong T cell-mediated immune responses have been documented against EBV encoded latent proteins and a wide range of HLA class I molecules with EBV originated peptide epitopes have been identified [8–10]. EBV associated lymphoproliferative disease can develop only in the absence of a competent cytotoxic T cell immune surveillance. EBV associated lymphoproliferative disease may disappear upon treatment restoring the immune response against EBV-infected B cells.

Historically LCLs were often regarded as non-tumorigenic in immunosupressed mice upon subcutaneous inoculation, especially in comparison with highly tumorigenic Burkitt's lymphomas. However intraperitoneal inoculation regularly leads to development of generalized lymphomas with multiorgan involvement. SCID mice inoculated intraperitoneally with peripheral blood lymphocytes (PBL) from EBV-seropositive donors or with human LCLs, develop EBV-induced human lymphoproliferations within a few weeks. These lymphomas are classified as immunoblastic lymphomas, often with plasmacytoid features [11]. Histologically the PBL derived human-SCID tumors very much resemble the EBV positive large cell lymphomas of immunosuppressed patients [12]. The tumors of the immunocompromised patients or the experimental tumors growing in immunodefective mice as well as the in vitro growing LCLs show very similar phenotypes. All three express the same spectrum of cell surface markers, B cell activation antigens and adhesion molecules. All three have normal karyotype and show identical viral gene expression patterns.

The risk of PTLD has been found to depend upon the type of the transplanted organ, the immunosuppressive regimen, the age, the underlying illness and the EBV status of the recipient at the time of transplantation. The estimated incidence of PTLD ranges from 1–4% after renal transplantation to 19% after intestinal transplantation. In bone marrow allograft recipients PTLD is relatively uncommon (1%) [13, 14] except for when certain high risk regimes, such as in vitro T-cell depletion (TCD) are used, when the risk may rise to 30%[4, 15] PTLD following allogenic stem cell transplantation usually derives from donor lymphocytes. The risk of PTLD is greater if the host is EBV-seronegative at the time of transplantation and/or if there is a mismatch between the donor and recipient HLA types [1].

No controlled studies have been performed in the management of PTLD and most of the recommendations for therapy come from small cohorts at single institutions [1]. The relative importance of T cell impairment, EBV and clonal proliferation has led to the following strategies: reduction of immunosuppression or prophylactic restoration of T-cell immunity [16], antiviral therapy and chemotherapy. Reducing the immunosuppression leads to complete and durable remission of PTLD [17] for 23–50% of patients after organ transplantation (SOD) but will not be efficient in the BMT setting. Reduction of immunosuppression is frequently the first therapeutic step, and patients who have had organ rejection have a much poorer prognosis.

For secondary EBV lymphomas post BMT none of the above regimens will suffice, except when specifically restoring EBV specific immunity [16]. Anti-B-cell monoclonal antibodies are an effective therapy for PTLD. A combination of anti CD21 and anti-CD24 antibodies were used. However these antibodies are not commercially available and interest has therefore recently turned towards Rituximab, a humanized monoclonal antibody against the pan-B cell marker CD20. The response rate of Rituximab treatment is 65% with a relapse rate of 18% [18, 19].

In cases that are not responding to the above mentioned therapy, chemotherapy is used as the second or third line of option.

The most frequently used chemotherapy protocols are the anthracycline based CHOP (cyclophosphamide, doxorubicin, vincristine and prednisolone) and VAPEC-B (doxorubicin, etoposide, cyclophosphamide, methotrexate, bleomycin, and vincristine) [20]. In the study of Muti et al. 17 of 40 PTLD patients were treated with a combination of reduced immunosuppression and chemotherapy (CHOP, VACOP-B – cyclophosphamide, vincristine, bleomycin, prednisolone, with increasing doses of doxorubicin and etoposide- or DHAP -cisplatinum, cytosine-arabinoside, dexamethasone) [21]. Remission rate for anthracycline-based combination therapy is 69%.

PTLD patients are exposed to a high mortality risk due to chemotherapy treatment related toxicity [1].

The side effects of a drug are the limiting factor in determining the dose. Increasing the dose of a drug leads to a more frequent appearance of side effects. Chemotherapeutic agents can also compromise the survival of the graft. Drugs that are effective even at low doses could therefore, not only give fewer side effects, but also provide a better graft survival.

The aim of this study was to find the most effective cytotoxic drugs against EBV-induced lymphoproliferations. We carried out over 6500 cell survival and proliferation assays, on single cell level, in order to establish the pattern of in vitro efficacy of the most commonly used cytotoxic drugs against EBV-transformed lymphoblastoid cells.

Methods

Cell lines and culture conditions

17 lymphoproliferative cell lines (LCLs) were used in the present study. 980215, 031016, 040113, 051018, JAK, LP, MIN, AF, GK, FUR, HA, VMB were established by in vitro infection of normal B lymphocytes, from different healthy donors, with the B95.8 strain of EBV. These cell lines were expanded in IMDM (Sigma) medium supplemented with 10% fetal calf serum (FCS). LSspontan is a spontaneous LCL established from a healthy donor. IARC171 was established using B95.8 virus infection of normal lymphocytes from a patient with Burkitt's lymphoma. TR was established from B cells of an XLP patient, with deletion in the SAP gene. The cell line IB4 contains an integrated EBV genome.

During the time of experiment the LCLs were cultured in IMDM (Sigma) supplemented with 20% FCS (Sigma), 100 mmol L-glutamine (Sigma) and 80 μg/ml gentamicin (Sigma). Cell suspensions were grown in a humidified incubator at 37°C in an atmosphere containing 5% CO2. Cell counts were adjusted to an optimal concentration of 1 × 106 cells/ml and the cells were fed twice a week. The absence of mycoplasma contamination was assured by regular monitoring with Hoechst 33258 staining.

Drugs

For the in vitro drug sensitivity test 29 drugs were used (summarized in Table 1). All the drugs were dissolved in 50% dimethyl sulfoxide (DMSO) and printed on 384 well plates, using a high density metal pin array (with 50 nl replica volumes) in Biomek 2000 fluid dispenser robot (Beckman). The same robot was used to generate the drug masterplates containing the triplicates of four different drug dilutions using a single tip automatic dispenser head.
Table 1

Used drugs, Cmax, AUC levels

Drug groups

Drug name

Brand name, company

In vitroused concentrations (μg/ml)

Cmax Value (μg/ml)

In vivodose (Cmax)

AUC (μg × h/ml)

In vivodose (AUC)

Reference

anthracyclines

epirubicin

Epirubicin Meda, Meda

0.026–1.66

9

120 mg/m2

2.412

90 mg/m2

(Fogli et al. 2002) [23]

 

daunorubicin

Cerubidin®, Aventis Pharma

0.065–4.166

0.49

0.95 mg/kg in 45 min

1.2786

1.5 mg/kg

(Andersson et al. 1979) [6]

 

doxorubicin

Doxorubicin Teva, Teva

0.026–1.66

0.93

50 mg/m2

0.82464

50 mg/m2

(Toffoli et al. 2004) [24]

epipodophyllotoxin

etoposide

Sigma

0.325–20.833

2.5

53 mg/m2/day

5.06

100 mg/m2/day

(Minami et al. 1995) [25] (Gruber et al.1995) [26]

camptothecins

topotecan

Hycamtin®, GlaxoSmithKline

0.052–3.33

0.0084

2.3 mg/m2/day

0.0196

1.2 mg/m2/day

(Gerrits et al. 1999) [27]

taxanes

paclitaxel

Taxol, Orifarm

0.078–5

3.38

175 mg/m2 by 3 h

13.49

175 mg/m2

(Fogli et al. 2002) [23]

 

docetaxel

Taxotere®, Aventis Pharma

0.52–33.33

2

60 mg/m2

3.326

85 mg/m2

(Rischin et al. 2002) [28]

vinca alkaloids

vincristine

Vincristine Mayne, Mayne Pharma

0.0065–0.416

0.37

1.4 mg/m2

0.182

1.32 mg/m2

(Terashi et al. 2000) [29] (Desai et al. 1982) [30]

 

vinblastine

Velbe®, STADApharm

0.013–0.833

0.005

1.5 mg/m2 by 24 h

0.218

1.7 mg/m2

(Stewart et al. 1983) [31] (Bates et al.) [32]

 

vinorelbine

Navelbine®, Pierre Fabre

0.13–8.33

0.83

200 mg/week

0.899

80 mg/m2/week

(Zhou et al. 1991) [33] (Freyer et al. 2003) [34]

platinum analogs

carboplatin

Carboplatin Mayne, Mayne Pharma

0.13–8.33

0.046

360 mg/m2

348000

360 mg/m2

(Ghazal-Aswad et al. 1996) [35]

 

oxaliplatin

Eloxatin, Sanofi-Synthelabo

0.065–4.166

3.2

130 mg/m2

71.5

130 mg/m2

(Gamelin et al. 1997) [36] (Graham et al. 2000) [37]

antifolate

methotrexate

Methotrexate Pharmacia, Pfizer

0.325–20.833

363

8–12 g/m2

13200000

12 g/m2

(Bacci et al. 2006) [38] (Crews et al. 2004) [39]

purin antagonists

6-mercaptopurine

Sigma

1.085–69.44

2

2.5 mg/kg oral dose

0.2587

85 mg/m2

(Chan et al. 1989) [26]

 

cladribine

Leustatin, Janssen-Cilag

0.013–0.833

0.0356

5 mg/m2

0.1541

5 mg/m2

(Albertioni et al. 1998) [40]

pyrimidine antagonists

fluorouracil

Fluorouracil Mayne, Mayne Pharma

0.65–41.66

55.4

400 mg/m2

11.59

400 mg/m2

(Casale et al. 2004) [41]

 

cytarabine

Cytarabine Pfizer, Pfizer

1.302–83.33

10.8

3 g/m2

523.4

1 g/m2

(DeAngelis et al. 1992) [42] (Gruber et al. 1995) [26]

 

gemcitabine

Gemzar, Orifarm

0.781–50

22.3

1000 mg/m2

9.3

1000 mg/m2

(Fogli et al. 2002) [23]

antitumor antibiotics

bleomycin

Bleomycin Baxter, Baxter

0.39–25*

0.19*

30 IU/day

0.089

8 IU/kg/day

(Broughton et al. 1977) [43] (Peng et al.1980) [44]

 

dactinomycin

Cosmegen®, MSD

0.006–0.416

0.1

1.5 mg/m2

300

1.5 mg/m2

(Veal et al. 2005) [45]

protease inhibitors

bortezomib

Velcade®, Janssen-Cilag

0.013–0.833

0.08

1.45 mg/m2

0.0438

1.45 mg/m2

(Papandreou et al. 2004) [46]

 

MG132

Sigma

0.13–8.33

#

    

alkylating agents

cyclophosphamide

Sendoxan, Baxter

0.52–33.33

37.2

50 mg/kg

367

50 mg/kg

(Xie et al. 2006) [47]

 

ifosphamide

Holoxan®, Baxter

0.52–33.33

56.63

16 g/m2 in 96 h

1827.7

3 g/m2/day

(Wright et al. 1995) [48] (Boddy et al. 1996) [45]

 

chlorambucil

Sigma

1.302–83.33

0.49

0.2 mg/m2

0.883

0.2 mg/m2

(GlaxoSmithKline Research Triangle Park) [49]

 

streptozotocin

Sigma

0.65–41.66

¤

    

miscellaneous

asparaginase

Asparaginase Medac, Medac

0.065–4.166*

4.48*

10000 IU/m2

0.943

30000 IU/m2

(Ho et al. 1981) [50] (Ylikangas et al. 2002) [51]

 

hydroxyurea

Sigma

0.65–41.66

21

18 mg/kg

82.49

15 mg/kg

(Gwilt et al. 2003) [52] (Yan et al. 2005) [46]

 

prednisolone

Di-Adreson F Aquosum, Organon

1.56–100

0.325

1 mg/kg/day

1.33

1 mg/kg/day

(Rostin et al. 1990) [53]

Cmax: maximum plasma level after administration of the clinical dose of the drug

*In case of bleomycin and asparaginase concentrations are in IU/ml

AUC: area under curve

#: not used in the clinical practice

¤: no data is available

The highest drug concentration was selected as the physicochemical maximally achievable drug concentration at 600 times dilution (50 nl drug in 30 μl suspension assay volume)

The Ratio of Maximum Achieved Plasma Concentration (RMAPC) was determined for each drug concentration in order to compare the in vitro tested concentrations to the in vivo maximally achieved plasma concentration (Cmax) levels.

RMAPC was calculated according to the following equation:

RMAPC = in vitro tested concentration/Cmax

In vitro drug sensitivity assay

In vitro drug sensitivity of LCLs was assessed using a 3-day cell culture on microtiter plates. 28 drugs were tested, each at 4 different concentrations in triplicates on 384-well plates (Greiner). Each well was loaded with 30 μl cell suspension containing 3000 cells. After three days of incubation the live and dead cells were differentially stained using fluorescent VitalDye (Biomarker, Hungary). The exact number of live and dead cells was determined using a custom designed automated laser confocal fluorescent microscope (a modified Perkin-Elmer UltraView LCI system) at the Karolinska Institute visualization core facility (KIVIF). The images were captured using the computer program QuantCapture 4.0 and the live and dead cells were identified and individually counted using the program QuantCount 3.0. Both programs were developed at the KIVIF using OpenLab Automator programming environment (Improvision). 15 control wells, that were used to determine the control cell survival (CCS), contained cells with only culture medium and 50 nl DMSO without drugs, 5 wells contained cells with culture medium alone. Comparing the two types of control wells no toxic effect of DMSO could be seen. Mean cell survival (MCS) was determined from the average of cell survival of all 17 LCLs.

Results

Comparison of the drug sensitivity pattern of the different LCLs

The 17 different LCLs that were tested in the present study represent a large variety of cells with different origins and in vitro history. The investigation included cell lines with several years of continuous in vitro culturing along with freshly established transformed B-cell cultures of only 3 weeks of age. Many of the lines were transformed by the B95-8 strain of EBV and some of them were spontaneous outgrowths driven by the donors own virus. Among the lines, we had LCLs from healthy donors, from XLP patients or lines established from the normal B-cells of Burkitt's lymphoma patients. We tested lines with both episomal and integrated EBV genome.

Remarkably, the LCLs of different origins showed a very similar sensitivity pattern against the different drugs. This phenomenon is illustrated in Figure 1, which summarizes the survival curves of all 17 LCLs against the four different concentrations of epirubicin. Each individual thin curve represents the average of three independent measurements. The thick line is the mean of all curves, the Mean Cell Survival (MCS). The grey shaded area marks the ± standard deviation (SD). Figure 2 summarizes the Mean Cell Survival curve along with the standard deviations for 28 drugs again emphasizing the very similar response of the different cell lines. The values for MG132 are represented only in Table 2.
Figure 1
Figure 1

Drug sensitivity pattern of 17 lymphoblastoid cell lines for epirubicin. The mean value of survival of LCLs is represented by the black curve, ± SD value is marked with grey. 1× : highest concentration, 16×: 16 times dilution of the highest concentration etc.

Figure 2
Figure 2

Mean values and standard deviations of drug sensitivity of 17 lymphoblastoid cell lines for 28 different cytostatic drugs. y axis: fraction of surviving cells 0–100% x axis: drug dilutions (1× represents the highest concentration).

Table 2

The average Mean Cell Survival (MCS) of the 17 LCLs at different drug concentrations, expressed as the Ratio of Maximum Achieved Plasma Concentration (RMAPC)

Group 1

Vincristine

Epirubicin

  

64× dilution

16× dilution

4× dilution

1× no dilution

 

64× dilution

16× dilution

4× dilution

1× no dilution

 

RMAPC

0.018

0.071

0.282

1.128

RMAPC

0.003

0.012

0.046

0.184

 

MCS

81.498

46.541

20.776

18.995

MCS

85.206

65.736

29.435

16.306

 

SD

27.995

25.737

15.258

12.209

SD

15.548

23.394

13.593

11.314

 

Paclitaxel

Methotrexate

 

RMAPC

0.020

0.081

0.326

1.303

RMAPC

0.001

0.004

0.014

0.057

 

MCS

48.119

29.999

24.653

23.148

MCS

76.618

44.824

32.924

29.314

 

SD

28.435

17.418

12.869

13.364

SD

22.796

25.843

15.590

16.455

Group 2

Gemcitabin

Dactinomycin

 

RMAPC

0.035

0.140

0.561

2.242

RMAPC

0.066

0.262

1.050

4.200

 

MCS

49.354

38.411

27.808

23.784

MCS

86.206

54.700

20.520

16.465

 

SD

34.718

30.034

16.945

12.153

SD

16.701

22.386

13.642

8.370

 

5-Flurouracil

Vinorelbine

 

RMAPC

0.012

0.047

0.188

0.752

RMAPC

0.156

0.625

2.501

10.005

 

MCS

74.861

58.001

42.337

30.505

MCS

82.833

42.823

25.176

24.683

 

SD

23.686

22.987

21.370

20.645

SD

18.131

23.930

16.506

14.634

 

Doxorubicin

Daunorubicin

 

RMAPC

0.028

0.112

0.447

1.789

RMAPC

0.133

0.531

2.126

8.502

 

MCS

82.503

52.477

28.292

11.499

MCS

83.171

61.159

25.940

20.439

 

SD

21.753

24.867

22.314

10.301

SD

21.886

25.402

23.933

17.961

 

Etoposide

Docetaxel

 

RMAPC

0.130

0.521

2.083

8.333

RMAPC

0.260

1.042

4.166

16.665

 

MCS

56.281

35.375

25.315

16.778

MCS

32.990

23.036

23.866

26.331

 

SD

21.045

19.983

15.497

11.166

SD

22.690

17.587

16.810

19.810

Group 3

Cytarabine

6-Mercaptopurine

 

RMAPC

0.121

0.482

1.929

7.716

RMAPC

0.543

2.170

8.680

34.720

 

MCS

87.321

79.450

48.255

40.124

MCS

84.450

78.834

62.325

55.419

 

SD

17.396

22.850

26.423

26.315

SD

22.147

16.514

29.820

32.858

 

Oxaliplatin

Cladribine

 

RMAPC

0.020

0.081

0.325

1.301

RMAPC

0.366

1.462

5.850

23.399

 

MCS

87.951

84.477

83.331

73.511

MCS

102.832

101.241

72.497

52.237

 

SD

21.010

26.545

21.839

30.744

SD

8.130

11.160

26.804

29.545

 

Asparaginase

Chlorambucil

 

RMAPC

0.015

0.058

0.232

0.930

RMAPC

2.646

10.586

42.342

169.370

 

MCS

92.021

91.570

90.371

82.978

MCS

89.903

71.879

13.225

11.099

 

SD

13.718

13.222

18.153

15.919

SD

17.578

26.506

10.994

7.527

 

Cyclophosphamide

Topotecan

 

RMAPC

0.014

0.056

0.224

0.896

RMAPC

6.194

24.777

99.107

396.429

 

MCS

86.670

93.412

89.498

84.041

MCS

93.897

72.802

23.250

24.784

 

SD

21.910

18.833

17.832

17.920

SD

19.406

21.275

16.659

21.380

 

Ifosphamide

Carboplatin

 

RMAPC

0.009

0.037

0.147

0.588

RMAPC

2.814

11.257

45.027

180.108

 

MCS

92.729

95.906

90.101

88.518

MCS

91.805

79.175

77.962

52.322

 

SD

16.694

14.965

15.299

16.677

SD

16.670

30.927

22.065

31.295

 

Hydroxyurea

Bleomycin

 

RMAPC

0.031

0.124

0.496

1.984

RMAPC

2.078

8.311

33.245

132.979

 

MCS

95.118

96.489

86.340

68.134

MCS

90.007

88.553

82.168

69.803

 

SD

19.595

13.933

19.759

24.782

SD

19.294

17.678

19.720

16.686

 

Vinblastine

Streptozotocin

 

RMAPC

2.603

10.413

41.650

166.600

RMAPC

no Cmax data was found

 

MCS

81.507

53.331

28.885

21.323

MCS

95.430

92.335

89.919

87.805

 

SD

25.921

25.678

17.941

15.889

SD

15.828

18.710

14.094

22.637

 

Bortezomib

MG-132

 

RMAPC

0.162

0.648

2.590

10.361

RMAPC

not used in clinical practice

 

MCS

93.119

81.671

75.498

28.700

MCS

87.345

96.374

88.097

27.045

 

SD

13.779

21.572

19.617

26.948

SD

13.980

17.493

16.974

24.310

 

Prednisolone

     
 

RMAPC

4.8

19.23077

76.92308

307.6923

     
 

MCS

75.55877

76.25595

62.46537

37.23379

     
 

SD

4.647172

11.09091

13.97021

11.65414

     

Group 1. Highly effective drugs: RMAPC < 0.3; MCS < 30%

Group 2. Partially effective drugs: RMAPC between 0.3 and 1, MCS < 60%

Group 3. Ineffective drugs: RMAPC > 1 or MCS > 60%

SD: standard deviation in mean cell survival

Identification of highly effective and non-effective drugs

The starting concentrations of the dilution series (1×, 4×, 16×, 64×) for the individual drugs were initially determined based on the solubility of the different agents. To make the cell survival data comparable with each other, we first compiled the known Maximum Achieved Plasma Concentration data (Cmax) for all 28 drugs stated from the literature (Table 1-column 5). Dividing the actual drug concentrations in the dilution series with the Cmax of the particular drug yielded the Ratio of Maximum Achieved Plasma Concentration (RMAPC). The calculated values of RMAPC for all the drugs are summarized in Table 2 along with MCS and ± SD values. Plotting the cell survival against the RMAPC values allowed a direct comparison of the effectiveness of different drugs. Figure 3 shows the comparison of the effectiveness of the members of three different drug families: the anthracyclines, vinca alcaloids and taxans. Figure 4 summarizes the mean cell survival curves for all the drugs along a common RMAPC axis. Based on their effectiveness on LCLs, we have divided the drugs into three different groups:
Figure 3
Figure 3

Drug sensitivity of LCLs for anthracyclines, vinca alkaloids and taxans.

Figure 4
Figure 4

Drug sensitivity mean values of 17 lymphoblastoid cell lines plotted against the Ratio of Maximum Achieved Plasma Concentration (RMAPC) values. The different drug families are labelled with different colours. The highly effective (Group 1) and partially effective (Group 2) drugs are identified.

Group 1: The drugs were considered to be highly effective if the mean cell survival (MCS) was below 30% at RMAPC 0.3 or below that.

Group 2: The drug was partially effective if MCS was under 60% and RMAPC was between 0.3 and 1.

Group 3: The drug was ineffective, e.g. the LCLs were resistant to the drug, if MCS was above 60% or RMAPC was above 1.

We found that the four most effective drugs against LCLs were: vincristine, paclitaxel, methotrexate and epirubicin (Group 1).

Gemcitabin, cytosine-arabinoside, doxorubicin, fluorouracil, dactinomycin, docetaxel, daunorubicin, etoposide, vinorelbine was rated as partially effective (Group 2.)

Most LCLs were resistant to cyclophosphamide, asparaginase, topotecan, oxaliplatin, bleomycin, 6-mercaptopurin, hydroxyurea, cladribine, chlorambucil, carboplatin, bortezomib, cytarabine, prednisolone and vinblastine (Group 3). Almost no drug response could be seen with oxaliplatin, bleomycin, cyclophosphamide, asparaginase, hydroxyurea and ifosphamide whereas vinblastine, chlorambucil, prednisolone and topotecan were effective, but only at very high concentrations, well above the maximum achievable plasma concentrations.

Although the Group 3 drugs were not effective against LCLs, these drugs show concentration dependent growth inhibitory effects on other cell lines or primary tumors (data not shown).

No RMAPC could be determined for streptozocin because no pharmacokinetical trials with established Cmax plasma levels were found. RMAPC was also not available for MG132 because it has not been used clinically. Streptozocin had no effect on survival at the concentrations used in the study. Although at the highest concentrations the proteasome inhibitor MG132 effectively decreased the survival of the cells, its clinically licensed functional homologue, bortezomib, was not effective.

An alternative way to calculate relationship between the in vitro drug concentrations and the in vivo used values is to use the area under curve (AUC) values of the individual drugs. To compare AUC values with the RMAPC data the following formula was used:

in vitro used concentration (μg/ml) × 72 h/AUC (μgxh/ml) in vivo.

In vivo AUC levels from the literature are summarized in Table 1. Using the formula for representing the mean cell survival curves for all the drugs along a common "ratio of AUC" axis, carboplatin, methotrexate and dactinomycin showed higher efficacy in comparison to RMAPC figures whereas the sensitivity order for the other drugs or for the group classifications did not change.

Discussion

The presented data suggest that many EBV transformed B-cell lines share a common cytotoxic drug sensitivity profile independent of their origin. This profile does not change even after many years of in vitro culturing. EBV appears to be the necessary and sufficient etiological agent behind the malignant immunoblastic B-cell lymphoproliferations in immunosuppressed patients. In all these cases the EBV encoded, latency associated viral proteins drive the cell proliferation without any obvious need for additional genetic changes. The phenotype of these tumors closely resembles the in vitro growing LCLs and the experimentally induced tumors that appeared upon intraperitoneal implantation of LCLs into SCID mice [11]. Considering the phenotypic and karyotypic stability of EBV transformed B-cells, our data raises the hope that PTLDs, AIDS associated CNS lymphomas and XLP associated lymphoproliferations may show similar patterns of drug sensitivity as the ones that we have established in the present study on a cohort of diverse LCLs.

Sugimoto et al. suggested that EBV mediated transformation is a two step process where, after prolonged passage, the cells may become aneuploid, accumulate p53 mutations, down regulate the p16/retinoblastoma protein pathway and become tumorigenic upon subcutaneous inoculation into nude mice [7]. Some of the cell lines that we have examined were kept in continuous culture over five years (IARC171, LSspontan, 980215). These cells are still euploid and show low soft agar clonability. The oldest line IARC171, has wild type p53, is non-tumorigenic upon subcutan inoculation but produces generalized immunoblastic lymphomas in SCID mice after intraperitoneal inoculation. The findings that PTLD can arise very rapidly in post-transplant patient together with the data that freshly EBV infected B-cells can grow into generalized immunoblastic lymphomas within a few weeks, implies that the development of PTLD does not require aneuploidy. Sawada et al. reported that LCLs with negative or low telomerase activity and normal karyotypes are more sensitive against certain drugs, than LCLs with a high telomerase activity and abnormal karyotypes [22]. This data together with our present findings may suggest that rapidly emerging PTLDs may show different drug sensitivity pattern from EBV positive aneuploid diffuse large cell B-cell lymphomas that arise for example in AIDS patients in sub-Saharan Africa.

Our data shows that euploid LCLs are particularly sensitive for anti-microtubule drugs and anthracyclines. Although all LCLs showed a dose dependent increase of cytotoxicity when treated with different members of these two drug families, only vincristine and paclitaxel as well as epirubicin and doxorubicin were considered to be effective when the used in vitro drug concentrations were compared to the maximum achievable plasma concentrations.

Alkylating agents, such as cyclophosphamide and ifosphamide were not effective on LCLs. This might be explained by the fact that both of these compounds are pro-drugs that have to be converted into active metabolites by the liver in vivo. Prednisolone was active but only in very high concentrations.

Conclusion

Vincristine and methotrexate are included in the frequently used CHOP and VAPEC-regimes, but no data could be found for the clinical use of epirubicin and paclitaxel for the treatment of PTLD or other EBV induced lymphoproliferations. Our results suggest that the inclusion of epirubicin and paclitaxel into chemotherapy protocols against PTLD may be justified.

Declarations

Acknowledgements

We thank the Swedish Cancer Society, the Swedish Research Council, Child Cancer Foundation and the IRIS center for economic support. We thank Doctor Noemi Nagy for the TR cell line.

Authors’ Affiliations

(1)
Department of Microbiology, Tumor and Cell Biology (MTC) and Center for Integrative Recognition in the Immune System (IRIS), Karolinska Institute, Stockholm, Sweden
(2)
Department of Pediatrics University of Debrecen, Medical and Health Science Center, Debrecen, Hungary
(3)
Department of Pediatrics, Karolinska Institutet, Karolinska University Hospital, Huddinge, Sweden
(4)
Karolinska Pharmacy, and Department of Woman and Child Health, Childhood Cancer Research Unit, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden

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    54. Pre-publication history

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