Investigational New Drugs

, Volume 28, Issue 1, pp 49–60

Differential gene expression triggered by highly cytotoxic α-Emitter-immunoconjugates in gastric cancer cells

Authors

    • Department of Nuclear MedicineTechnische Universität München
  • Matthias Port
    • Department of Hematology and OncologyHannover Medical School
    • Bundeswehr Institute of Radiobiology, German Armed Forces
  • Christos Apostolidis
    • European Commission, Joint Research Centre, Institute for Transuranium Elements
  • Frank Bruchertseifer
    • European Commission, Joint Research Centre, Institute for Transuranium Elements
  • Markus Schwaiger
    • Department of Nuclear MedicineTechnische Universität München
  • Reingard Senekowitsch-Schmidtke
    • Department of Nuclear MedicineTechnische Universität München
  • Michael Abend
    • Bundeswehr Institute of Radiobiology, German Armed Forces
    • Department of RadiooncologyTechnische Universität München
PRECLINICAL STUDIES

DOI: 10.1007/s10637-008-9214-4

Cite this article as:
Seidl, C., Port, M., Apostolidis, C. et al. Invest New Drugs (2010) 28: 49. doi:10.1007/s10637-008-9214-4
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Summary

Immunoconjugates composed of the α-emitter 213Bi and the monoclonal antibody d9MAb specifically target HSC45-M2 gastric cancer cells expressing mutant d9-E-cadherin. These conjugates efficiently killed tumor cells in a nude mouse peritoneal carcinomatosis model. To elucidate the molecular responses of HSC45-M2 cells to α-emitter irradiation, whole genome gene expression profiling was performed. For that purpose HSC45-M2 cells were incubated with lethal doses of 213Bi-d9MAb. RNA was isolated at 6, 24 and 48 h after irradiation, transcribed into cDNA and hybridized to whole genome microarrays. Results of microarray analysis were validated using RTQ-PCR showing correspondence of approximately 90%. Following incubation with 213Bi-d9MAb, 682-1125 genes showed upregulation and 666-1278 genes showed downregulation at one time point, each. Eight genes appeared upregulated and 12 genes downregulated throughout. Molecular functions and biological processes of differentially expressed genes were categorized according to the PANTHER database. Following 213Bi-d9MAb irradiation also a time-dependent shift in terms of overrepresentation of biological processes was observed. Among the genes showing continuous upregulation, COL4A2, NEDD9 and C3 have not been associated with the cellular response to high LET radiation so far. The same holds true for WWP2, RFX3, HIST4H4 and JADE1 that showed continuous downregulation. According to PANTHER, three of the consistently upregulated (ITM2C, FLJ11000, MSMB) and downregulated (HCG9, GAS2L3, FLJ21439) genes, respectively, have not been associated with any biological process or molecular function so far. Thus, these findings revealed interesting new targets for selective elimination of tumor cells and new insights regarding response of tumor cells to α-emitter exposure.

Keywords

RadioimmunotherapyAlpha-emitter 213BiGastric cancerGene expression profilingWhole genome microarray

Abbreviations

DIG-POD

digoxigenin-phosphodiesterase

d9MAb

monoclonal antibody targeting mutant d9-E-cadherin

LET

linear energy transfer

MFC

micro fluidic card

PANTHER

Protein ANalysis THrough Evolutionary Relationships

RTQ-PCR

real time quantitative polymerase chain reaction

Introduction

Selective elimination of tumor cells can be achieved via radionuclide-labelled antibodies that specifically bind to cell surface antigens that show overexpression or exclusive expression in the tumor cells to be targeted. β-emitter-immunoconjugates applying 131I, 177Lu, 188Re/186Re or 90Y have been successfully used in experimental and clinical studies for the treatment of B-cell non-Hodgkin’s lymphoma, malignant glioma, ovarian cancer, melanoma and HER-2 expressing tumors [1]. With respect to relative biological effectiveness, α-emitters such as 225Ac, 211At, 213Bi and 212Pb are superior to β-emitters due to short ranges in tissue combined with a high linear energy transfer (LET). α-emitters cause severe DNA double-strand-breaks that are repaired inefficiently finally inducing cell death. Cells are irreversibly damaged by only four α-particles but approximately 1,000 β-particles traversing the nucleus [2]. Due to the short range of α-emitters on the one hand cells that are not targeted by α-emitter-immunoconjugates should not be affected, and on the other hand α-emitter radioimmunotherapy is promising in the elimination of disseminated tumor cells and the treatment of minimal residual disease [3, 4]. So far α-emitter-immunoconjugates have been successfully applied in treatment of leukaemia [5, 6], ovarian carcinoma [7, 8], melanoma [9], malignant glioma [10] and disseminated peritoneal disease showing HER-2 overexpression [11].

In diffuse-type gastric cancer radioimmunotherapy utilizes a mutant E-cadherin lacking exon 9 (d9-E-cadherin) as a tumor specific antigen. Mutant d9-E-cadherin, expressed by approximately 10% of patients suffering from diffuse-type gastric cancer, is selectively targeted by the monoclonal antibody d9MAb [12]. 213Bi-d9MAb immunoconjugates have been shown to destroy d9-E-cadherin expressing gastric cancer cells both in vitro and in vivo [1317]. The molecular mechanisms triggered by high LET α-particle-emitting nuclides such as 213Bi are just beginning to be elucidated. There is evidence that high LET α-emitters trigger processes different from that induced by low LET β- or γ-emitters or chemotherapeutics [18] and, accordingly, that limited DNA-damage induces signal cascades that are different from those of severe, lethal damages [19]. Detailed insight into α-emitter induced signal cascades could significantly improve strategies of radioimmunotherapy. In a first study on 213Bi-d9MAb induced differential expression of selected genes associated with damage response/cell death via real time quantitative (RTQ)-PCR, we could show that 213Bi activates death cascades different from apoptosis [20].

The aim of this study was to expand analysis of 213Bi-induced differential gene expression to the whole genome (29,098 genes) and to characterize 213Bi-induced changes of biological processes associated with cell death in gastric cancer cells. Differentially expressed genes were categorized according to the biological processes they are involved and molecular functions they code for using the PANTHER database. Also overrepresentation of biological processes as a consequence of 213Bi-incubation was determined. We could show that overrepresentation of definite biological processes changed with time after incubation of HSC45-M2 cells with 213Bi-d9MAb. Approximately 1,000 genes showed differential expression—upregulation or downregulation—at one time point, i.e. at 6, 24 or 48 h after irradiation. Eight genes appeared unregulated and 12 genes downregulated throughout. Among these genes are interesting new targets for selective elimination of tumor cells. Our findings reveal new insights with respect to response of tumor cells to α-emitter exposure inducing cell death.

Materials and methods

Labelling of antibody with 213Bi

The monoclonal antibody d9MAb (IgG2a, clone 6H8) specifically recognizes mutant E-cadherin lacking exon 9 (d9-E-cad). The α-emitter 213Bi (t1/2 = 46 min), eluted from a 225Ac/213Bi generator system (Institute for Transuranium Elements, Karlsruhe, Germany) [21] was coupled to the antibody via the chelate SCN-CHX-A”-DTPA as described [15]. Briefly, d9MAb conjugated to the chelate was incubated with BiI4-/BiI52- from the 225Ac/213-Bi generator system for 7 min in 0.4 M ammonium acetate at pH 5.3. The 213Bi-immunoconjugates were purified by size exclusion chromatography (PD-10 columns, GE Healthcare, Freiburg, Germany). Efficacy of 213Bi-d9Mab binding to HSC45-M2 cells was assayed as described [14].

Incubation of tumor cells with 213Bi-d9MAb

The human HSC45-M2 gastric cancer cell line established from ascites and pleural effusion of a patient, is efficiently targeted by d9MAb due to expression of approximately 3 × 105 d9-E-cad molecules per cell [15, 22]. The cells were grown in DMEM supplemented with 10% FCS at 37°C in a humidified atmosphere with 5% CO2.

Aliquots of 5 × 106 cells (1.7 × 105/ml) were seeded into 175-cm2 tissue culture flasks 24 h before treatment with 213Bi-immunoconjugates. The exponentially growing, adherent cells were incubated with 213Bi-d9Mab (1.5 MBq/ml) for 3 h in 10 ml culture medium. Finally, culture medium containing residual 213Bi-immunoconjugates was exchanged and the cells were grown over definite time intervals depending on the endpoints shown below. The controls did not receive any treatment, but were processed just as the 213Bi-d9MAb treated cells in terms of incubation times and changes of culture media. As we have shown previously, the cold antibody has no effect on survival of cells in vitro and therefore could be omitted in controls [15].

RNA isolation

Untreated controls and 213Bi-d9MAb treated cells were detached using 1 mM EDTA in PBS at 6, 24 and 48 h after start of incubation. Total RNA was isolated with the Prep Station 6100 (Applied Biosystems, Weiterstadt, Germany) according to the manufacturer’s instructions and stored at −80°C until usage for gene expression arrays and RTQ-PCR. Residual DNA was digested with RNase free DNase Set (Qiagen, Hilden, Germany).

To control quality and purity of isolated total RNA, spectralphotometry, agarose gel electrophoresis and PCR (using β-Actin primers for detection of DNA contamination) were performed. Only total RNA with a ratio A260/A280 > 1,9 (spectralphotometry), with 28S ribosomal bands being present at approximately twice the amounts of the 18S RNA (agarose gel electrophoresis) and without detectable contamination of DNA (PCR) were employed for gene expression arrays and RTQ-PCR. The methods chosen for validating RNA quality represent state of the art standards and methodology. Besides, quality measurements are performed in our laboratory accredited according to QM ISO 9001.

Microarray analysis (Human Genome Survey Microarray V2.0)

All materials and instruments used for microarray analysis were from Applied Biosystems (Weiterstadt, Germany). The RNA templates from three independent experiments isolated 6, 24 and 48 h after incubation of HSC45-M2 cells with 213Bi-d9MAb (1.5 MBq/ml) and from their corresponding controls were pooled separately. This resulted in 6 individually pooled template samples each containing 37–40 µg of total RNA. After RNA quality controls (see above) templates were transcribed into cDNA using the chemoluminescenct RT labelling kitTM. Briefly, mRNA was reversely transcribed using an oligo (dT) primer in the presence of dGTP, dCTP, dATP and DIG-dUTP. Following RNA degradation, the DIG-labeled cDNA was purified and hybridized overnight on the Human Genome Survey Microarray V2.0 covering 29,098 genes using the microarray platform AB1700. Subsequently microarrays were washed several times and the anti-DIG-POD mediated chemoluminescence reaction was performed using the chemoluminescence kitTM. Chemoluminescence was detected with the AB1700 microarray reader.

Differentially expressed genes were categorized according to the biological processes they are involved and the molecular functions they code for using the PANTHER database (available at: www.pantherdb.org). PANTHER was also used to calculate if the number of differentially expressed genes (Δ-genes) of a certain biological process corresponds to under- or overrepresentation of that biological process. For that, the code of all Δ-genes was transferred into PANTHER. According to the annotation of each gene (link of the gene with known biological functionality) stored in the software, the number of observed Δ-genes coding for a certain biological process is counted. Transferring the Δ-genes into PANTHER, also the microarray from where the data originate, is recognized. Hence, the total number of genes on the microarray (e.g. 30,000) and the number of genes coding for a certain biological process (e.g. 1,000 genes, corresponding to 3.3%, coding for cell proliferation) are registered by PANTHER. Thus, in this example, the expected number of Δ-genes involved in cell proliferation and detected by microarray analysis is 33 (3.3% of 1,000). PANTHER compares the number of observed Δ-genes with the number of expected Δ-genes of a biological process using statistical analysis. If the number of observed Δ-genes appears significantly reduced or elevated compared to the expected number of Δ-genes, the biological process the genes are involved is regarded as under- or overrepresented. The significance is shown as a p-value. Microarray assays and data analysis were done in collaboration with the Gene Expression Center MartinsriedTM (Munich, Germany).

RTQ-PCR (Micro Fluidic Card)

Equipment used for RTQ-PCR was obtained from Applied Biosystems (Weiterstadt, Germany). Aliquots of total RNA (10 µg) isolated from HSC45-M2 cells at 6, 24 and 48 h after 213Bi-d9MAb treatment were reversely transcribed over 2 h using a two-step PCR protocol (High Capacity Kit). A volume of 50 µl of the resulting cDNA typically contained 1 µg RNA equivalents. To this volume, a 50 µl aliquot of 2× RT-PCR master mix was added. Samples were mixed and pipetted into one fill port each of a micro fluidic card. Cards were centrifuged twice and sealed. After removal of the emptied fill ports, cards were transferred into the 7900 RTQ-PCR instrument equipped with a specially designed thermal cycler to run the RTQ-PCR with the 384 well micro fluidic card format for 2 h. Differential gene expression of 380 genes was calculated by the software using the ΔΔCT-quantitative approach. 18SrRNA, measured in the remaining 4 wells, was used for normalization of results. Genes were not selected in terms of the extent of differential gene expression but with regard to involvement in key biological processes like apoptosis, cell cycle control, signal transduction and DNA repair.

Statistics

Gene expression microarrays were performed once for screening purposes and validated in three independent experiments using RTQ-PCR (micro fluidic format). The geometric means were calculated with the aid of statistical software (Sigma Plot 2000, Jandel, Erkrath, Germany).

Results

213Bi-labelling of d9MAb, binding of 213Bi-d9MAb to HSC45-M2 cells and killing of cells following incubation with 213Bi-d9MAb

Labelling of d9MAb with 213Bi resulted in maximum specific activities of 1.5 GBq/mg. After removal of unbound 213Bi via size exclusion chromatography, the radiochemical purity of the labeled antibody fractions varied between 95% and 99%. 213Bi-d9MAb conjugates were stable at room temperature for at least four half-lives (3 h) of 213Bi. 213Bi-d9MAb showed highly specific binding to HSC45-M2 cells (25% binding) compared with unspecific 213Bi-d8MAb not targeting d9-E-cadherin (2% binding) (data not shown). Following incubation of HSC45-M2 cells with 213Bi-d9MAb (1.5 MBq/ml) almost 99% of cells were killed as demonstrated via clonogenic assays (data not shown). Monitoring of cellular morphology at different time points after incubation of HSC45-M2 cells with 213Bi-d9MAb, revealed deterioration of cellular morphology, indicative of cell death, at 72–96 h after irradiation of cells (data not shown).

Whole genome microarray analysis of 213Bi-induced differentially expressed genes in HSC45-M2 cells shows a high degree of correlation with corresponding RTQ-RCR analysis

Quantil normalized gene expression of nearly 33,000 probes (coding for 29,098 genes) of the microarray measured in both groups, i.e. in 213Bi treated cells and corresponding controls, was log2-transformed and plotted as a scatter plot after deletion of signals with a signal/noise ratio < 3 (fold change of the probe’s signal relative to the local background measured). A signal/noise ratio ≥ 3 guarantees a 99.9% probability that the measurements performed are correct. The Pearson coefficient (r2) expressing correlation of different templates varied between 0.983–0.988 in templates isolated at identical time points from 213Bi-treated HSC45-M2 cells and corresponding controls (Fig. 1). Compared to that, the diminished r2-values obtained from comparison of controls (0.977–0.979) and of 213Bi-treated cells (0.976–0.980) among each other at 6 h and 24 h, 6 h and 48 h, and at 24 h and 48 h, respectively, revealed less correlation in gene expression patterns (data not shown). Percentage of expressed probes showing a signal/noise ≥ 3 ratio ranged between 44.4% and 50.7% (data not shown). The number of differentially expressed probes (fold-change of normalized gene expression measured in 213Bi-treated cells versus control cells) with a fold-change > 2 (upregulated)/< 0.5 (downregulated) was 947/1005, 1125/666 and 682/1278 at 6 h, 24 h and 48 h after incubation with 213Bi-d9MAb, respectively.
https://static-content.springer.com/image/art%3A10.1007%2Fs10637-008-9214-4/MediaObjects/10637_2008_9214_Fig1_HTML.gif
Fig. 1

Quantil normalized gene expression (log2-transformed) of all gene probes measured with the microarray 6, 24 and 48 h after incubation of HSC45-M2 cells with 213Bi-d9MAb (1.5 MBq/ml) plotted against untreated cells (control). Blue dots show gene expression of genes representing control values in both groups with a differential gene expression between >0.5-fold and <2-fold. Green dots depict <0.5-fold downregulated genes while red dots reveal >2-fold upregulated genes. r2, Pearson coefficient expressing correlation between gene expression of control cells and 213Bi-treated cells at 6, 24 and 48 h after irradiation

From the 29,098 genes covered on the microarray, 380 were selected independently of the differential gene expression measured with the microarray, but in terms of relevance to radiation response and processed separately for each individual RNA sample utilizing an RTQ-PCR based Micro Fluidic Card (MFC) platform. Geometric means of differential gene expression measured with the microarray (semiquantitative method) were compared with the geometric means of the identical gene measured with the MFC (quantitative method). The MFC values served as a gold standard. The great majority of the genes (87.6%) showed identical differential expression, i.e. upregulation or downregulation, following analysis with both microarray and RTQ-PCR (MFC) (Fig. 2). The percentage of false positive genes, i.e. differentially expressed on the mircroarray while showing control values according to the MFC, was 6.1%. The percentage of false negative genes, showing control values on the mircroarray while being differentially expressed according to the MFC, was 5.4%. Inverse results, i.e. identical genes appear upregulated with one method and downregulated with the other method, were found in 0.9% of the genes examined (Fig. 2).
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Fig. 2

Differentially expressed genes of HSC45-M2 cells incubated with 213Bi-d9MAb relative to untreated controls: comparison of semiquantitative microarray results with quantitative RTQ-PCR-based MFC (Micro Fluidic Card) measurements of the same template RNA. Dots in light gray areas represent genes that show the same differential expression with both methods. Less than twofold differences in gene expression, i.e. >0.5-fold downregulation and <2-fold upregulation, are considered not to be statistically significant. Dots within dark grey areas reveal false positive and false negative measurements with regard to RTQ-PCR, representing the gold standard. Dots in the left or right white quadrants show inverse results representing genes appearing upregulated with one and downregulated with the other method. Results are summarized in the inserted table. Calculations in the table are based on 380 genes analyzed via RTQ-PCR (MFC) at three time points (6, 24 and 48 h) (3 × 380 = 1,140 genes). Total number of genes depicted in the inserted table is only 1,060 due to exclusion of genes that were outside the linear dynamic range in the RTQ-RCR analysis or showed a signal/noise ratio <3 in the microarray analysis

Overrepresentation of biological processes triggered by 213Bi-d9MAb in HSC45-M2 cells reveals a time-dependent shift

Upregulated genes with > 2-fold change in gene expression according to microarray analysis were categorized with regard to the biological processes they are involved and the molecular functions they code for using the PANTHER database. Among biological processes that showed a signifcant overrepresentation at at least two time points after incubation with 213Bi-d9MAb, were signal transduction at 6 h (p = 3 × 10−4), 24 h (p = 7 × 10−3) and 48 h (p = 8 × 10−6), cell surface receptor mediated signal transduction at 6 h (p = 5 × 10−5) and 24 h (p = 1 × 10−2) and processes related to development at 24 h (p = 3 × 10−3) and 48 h (p = 6 × 10−4) (Fig. 3). Cytokine and chemokine related cell signalling (p = 6 × 10−5 at 6 h), G-protein mediated signalling (p = 1 × 10−2 at 24 h), ligand signalling (p = 5 × 10−5 at 48 h) and processes related to immunity and defense (p = 1 × 10−8 at 48 h) revealed overrepresentation only at one time point (Fig. 3). Thus, 213Bi-d9MAb induced overrepresentation of biological processes based on upregulated genes varies with time after irradiation.
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Fig. 3

213Bi-d9MAb induced, time-dependent shift in overrepresentation of biological processes. Differentially expressed genes (top >2-fold upregulated, bottom < 0.5-fold downregulated) were categorized into biological processes and associated molecular functions according to PANTHER. Biological processes which appeared significantly overrepresented with regard to the number of observed relative to the number of expected differentially expressed genes are depicted versus time after 213Bi-irradiation. The p-values refer to the significance of overrepresented biological processes. The percentages at the biological processes reflect the proportion of differentially expressed genes involved in the respective biological process (e.g. signal transduction) relative to the total number of differentially expressed genes at that time. The percentages at the associated molecular functions reflect the proportion of the differentially expressed genes coding for the molecular function (e.g. cell adhesion) relative to the total number of differentially expressed genes of the corresponding biological process (e.g. signal transduction)

Genes revealing < 0.5-fold downregulation compared to untreated controls were categorized into 8 different biological processes showing overrepresentation according to PANTHER. Two of these biological processes, cell cycle control and mitosis control, were overrepresented at both 6 h (p = 6 × 10−4 and 2 × 10−3, respectively) and 24 h (p = 6 × 10−4 and 4 × 10−3, respectively) after incubation with 213Bi-d9MAb. Among biological processes that showed overrepresentation at only one time point after incubation with 213Bi-d9MAb were protein targeting and localization (at 6 h; p = 7 × 10−6), chromosome segregation (at 24 h; p = 5 × 10−3), cell structure and motility (at 24 h; p = 7 × 10−3), chromosome packaging and remodelling (at 48 h; p = 2 × 10−17), nucleic acid metabolism (at 48 h; p = 3 × 10−5), and B-cell/antibody mediated immunity (at 48 h; p = 3 × 10−4) (Fig. 3). Thus, at 6 h and 24 h after incubation with 213Bi-d9MAb, genes involved in regulation of cell cycle, mitosis and chromosome segregation appeared overrepresented, whereas at 48 h additional biological processes with regard to chromosome packaging and nucleic acid metabolism predominated, again indicating a time-dependent shift (Fig. 3).

213Bi-d9MAb treatment of HSC45-M2 cells triggers continuous downregulation of genes involved in chromosome segregation cell cycle regulation

In search of 213Bi-induced genes being differently expressed at all the three time points, i.e. at 6 h, 24 h and 48 h after incubation with 213Bi-d9MAb, 8 upregulated (Fig. 4A) and 12 downregulated genes (Fig. 4B) could be identified (Table 1). According to PANTHER 5 of these 20 genes were not associated with a biological process (ITM2C, FLJ11000, MSMB, HCG9, FLJ21439) and 4 genes could not be attributed to a molecular function (FLJ11000, HCG9, GAS2L3, FLJ21439) (Table 1). Among the genes being upregulated > 2-fold at 6 h, 24 h and 48 h that could be characterized via PANTHER were COL4A2, NEDD9, C3, NMES1 and RASA4 involved in cell adhesion, cell cycle control, complement-mediated immunity, carbon metabolism and signal transduction, respectively (Table 1). Biological processes of genes being downregulated throughout following incubation with 213Bi-d9MAb comprised cell cycle control/cytokinesis (CDC20, GAS2L3, ASPM) chromosome segregation (KIF20A, CENPE), chromatin packaging (HIST4H4), proteolysis (WWP2) and transcription regulation (RFX3, PHF17). This indicates that treatment of HSC45-M2 cells with the alpha-emitter 213Bi has severe effects on progression of the cell cycle.
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Fig. 4

Venn diagram illustrating the number of differentially expressed genes in HSC45-M2 cells after 213B-d9MAb treatment: Number of genes showing >2-fold upregulation (A) and < 0.5-fold downregulation (B) at 6, 24 and 48 h after start of incubation with 213Bi-d9MAb. Eight genes appeared upregulated and 12 genes downregulated at all time points analysed (see also Table 1)

Table 1

Molecular functions and biological processes of differentially expressed genes in HSC45-M2 cells at 6, 24 and 48 h after 213Bi-d9MAb incubation according to PANTHER

Gene symbol

Gene name

Fold-change

PANTHER family name

PANTHER function

PANTHER process

6 h

24 h

48 h

COL4A2

Collagen, type IV, alpha 2

2.2

2.4

3.7

COLLAGEN ALPHA RELATED

Extracellular matrix structural protein

Cell adhesion

Cell structure

ITM2C

Integral transmembrane protein 2C

2.3

2.3

3.2

INTEGRAL TRANSMEMBRANE PROTEIN 2 C

Miscellaneous function protein

(Biological process unclassified)

NEDD9

Neural precursor cell expressed, developmentally down-regulated 9

5.7

2.0

3.8

ENHANCER OF FILMENTATION 1

Cytoskeletal protein

Cell cycle control

Cell structure and motility

FLJ11000

Hypothetical protein FLJ11000, Transmembrane protein 140 (TMEM 140)

7.1

2.8

2.8

(Family not named)

(Molecular function unclassified)

(Biological process unclassified)

MSMB

Microseminoprotein, beta-

2.4

3.1

4.6

PROSTATE SECRETED SEMINAL PLASMA PROTEIN PRECURSOR

Peptide hormone

(Biological process unclassified)

C3

Complement component 3

4.0

6.5

7.1

COMPLEMENT C3

Complement component

Complement mediated immunity

NMES1

Normal mucosa of esophagus specific 1

4.9

3.3

2.4

NADH-UBIQUINONE OXIDOREDUCTASE MLRQ SUBUNIT

Oxidoreductase

Carbon metabolism

RASA4 (CAPRI)

RAS p21 protein activator 4

5.1

2.2

2.7

RAS GTPASE ACTIVATING PROTEIN 4

G-protein modulator

Signal transduction

CDC20

CDC20 cell division cycle 20 homolog (S. cerevisiae)

0.4

0.3

0.4

CELL DIVISION CYCLE 20 (CDC20) (FIZZY)-RELATED

Select regulatory molecule

Proteolysis, cell cycle control

KIF20A (RB6K) (RAB6KIFL)

Kinesin family member 20A

0.2

0.2

0.3

KINESIN FAMILY MEMBER 20 (RABKINESIN-6)

Microtubule binding motor protein

Protein trafficking, cytokinesis, chromosome segregation

HCG9

HLA complex group 9

0.3

0.4

0.5

(Family not named)

(Molecular function unclassified)

(Biological process unclassified)

GAS2L3

Growth arrest-specific 2 like 3

0.1

0.3

0.5

GROWTH ARRESTSPECIFIC 2-RELATED

(Molecular function unclassified)

Cell cycle control

HIST4H4

Histone cluster 4, H4

0.2

0.3

0.3

HISTONE

H4 Histone

Chromatin packaging and remodeling

UBR2

Ubiquitin protein ligase E3 component n-recognin 2

0.4

0.4

0.3

UBIQUITIN LIGASE E3 ALPHA-RELATED

Ubiquitin-protein ligase

Proteolysis

WWP2

WW domain containing E3 ubiquitin protein ligase 2

0.5

0.5

0.3

NEDD-4-LIKE E3 UBIQUITINPROTEIN LIGASE WWP1

Ubiquitin-protein ligase

Proteolysis

CENPE

Centromere protein E, 312 kDa

0.2

0.4

0.5

CENTROMERIC PROTEIN E (CENP-E PROTEIN)

Microtubule binding motor protein

Chromosome segregation

RFX3

Regulatory factor X, 3 (Influences HLA class II expression)

0.2

0.5

0.4

RFX TRANSCRIPTION FACTOR

Transcription factor

mRNA transcription regulation

ASPM

ASP (abnormal spindle)-like, microcephaly associated

0.2

0.4

0.5

ABNORMAL SPINDLE-LIKE MICROCEPHALY-ASSOCIATED PROTEIN

Actin binding motor protein

Muscle contraction, cytokinesis

PHF17 (JADE1)

PHD finger protein 17

0.3

0.3

0.3

JADE1L PROTEIN

Zinc finger transcription factor, nucleic acid binding

mRNA transcription initiation, oncogenesis

FLJ21439 (SPG11) (KIAA1840)

Hypothetical protein FLJ21439

0.1

0.2

0.3

(Uncharacterized)

(Molecular function unclassified)

(Biological process unclassified)

Whole genome gene expression was analysed via microarray compared to untreated controls. Semiquantitative fold-change results are shown for each time point examined

Discussion

Incubation of HSC45-M2 gastric cancer cells with 213Bi-d9MAb targeting d9-E-cadherin causes cell death within 72 to 96 h after application. Therefore, analysis of gene expression via microarray analysis covering 29,098 genes at 6, 24 and 48 h after incubation should reflect both early and late changes in the expression of genes that finally trigger cell death. In 213Bi-d9MAb treated cells we could show overrepresentation of processes involved in signal transduction, proliferation, chromosome segregation and chromatin structure (Fig. 3). Along with that, 8 genes appeared upregulated and 12 genes downregulated consistently, i.e. at all time points analysed. Validation of semiquantitative microarray data on differentially expressed genes was done via real-time quantitative (RTQ)-PCR. The great majority of genes (87.6%) showed identical up- or downregulation with both methods (Fig. 2). Almost identical differential gene expression as detected with microarray vs. RTQ-PCR is also in line with results obtained on a testis tumor (M. Abend, submitted) and thyroid cancer biopsies [23] showing 80% and 85% correspondence, respectively, even when using a macroarray platform (1,176 genes) and 32P-radiolabeled probes [24]. This demonstrates the accuracy of microarray data in terms of differential gene expression.

Differences in gene expression patterns between 213Bi-d9MAb treated cells and controls as expressed by the Pearson coefficient, never fell below 0.95 indicating only slight changes induced by the alpha-emitter 213Bi (Fig. 1). This is in line with the finding that the total number of 213Bi-induced, differentially expressed genes at each time point never exceeded 6% of the whole genome. Though triggering a drastic biological effect—cell death—213Bi-d9MAb conjugates only exert little influence on overall gene expression patterns.

The PANTHER tool allows analysis of significant alterations of biological processes versus time after 213Bi-d9MAb exposure. Throughout the whole time of examination the biological process of signal transduction showed overrepresentation, amongst others due to increased upregulation of genes coding for cytokines and chemokines (Fig. 3). Increased production of cytokines has also been observed following γ-irradiation in vitro in mononuclear blood cells and in vivo in mouse skin tissue, probably related with cellular damage repair [25, 26]. Overrepresentation of the biological processes of cell cycle and mitosis control was based on increased downregulation of genes coding for G2/M checkpoint regulating proteins and proteins involved in chromosome segregation (Fig. 3). Cell cycle arrest is a well described phenomenon following β- and γ-irradiaton of cells [27]. Our data on gene expression associated with death of HSC45-M2 cells following 213Bi-d9MAb treatment are in line with the results of RTQ-PCR analysis of selected genes and investigations of cell morphology [20]. 213Bi-d9MAb induced cell death showed unequivocal signs of necrosis and mitotic catastrophe, most likely as a consequence of altered chromosome segregation and the occurrence of multinucleated cells [15]. Signal transduction cascades involved in the control of chromosome segregation and cytokinesis have been elucidated recently [28, 29]. However, the effects of ionizing radiation on these processes are just beginning to be elucidated [30]. Besides the checkpoint dysfunction [31], other mechanisms such as the radiation-induced overduplication of centrosomes [32] and the polymerisation of α-, β- and γ-tubulin in response to ionising radiation are discussed [33]. This is in accordance with changes in the expression of genes coding for cytoskeletal and matrix proteins following γ-irradiation [34].

It is very well accepted for apoptosis and controversely discussed for necrosis, which are both induced by death domain receptors [35], that these biological phenomena both represent an active process of cell destruction that is controlled by the injured cell (so called apoptosis-necrosis continuum) [36]. We herein show that morphological changes caused by high LET α-particles in HSC45-M2 cells are associated with altered gene expression of key regulators coding for chromosome segregation, mitosis and cytokinesis. These findings together with the result that 94% of the genome of 213Bi-d9MAb treated HSC45-M2 cells remained silent up to 48 h after exposure, add to the view that α-particle radiation is a strong stressor leading to a very specific—active process—reaction of the injured cell. As a result, necrosis as well as mitotic catastrophe and multinucleated cells can occur [37].

Our experimental data further suggest that 213Bi-d9MAb triggers time-dependent shifts with regard to biological processes showing overrepresentation due to an increase in the number of upregulated and downregulated genes (Fig. 3). These shifts following 213Bi-d9MAb treatment of cells appear of particular interest in terms of biological dosimetry. It implies that a set of genes covering different biological processes might be needed for a biological dose estimate over a broader period of time.

A total of 20 genes were differentially expressed consistently, i.e. at 6 h, 24 h and 48 h after incubation of HSC45-M2 cells with the α-emitter conjugate 213Bi-d9MAb (Fig. 4, Table 1). Eight of them appeared upregulated and 12 downregulated throughout. According to PANTHER, for three of the upregulated genes (ITM2C, MSMB, FLJ11000) no biological processes, and for FLJ11000 not even a molecular function is classified. Our data strongly indicate that these genes are involved in processes regulating stress response induced by high LET ionizing radiation, e.g. cell cycle arrest, DNA repair and cell death. The same should hold true for the two consistently downregulated genes (HCG9, FLJ21439) that up to now are neither associated with a molecular function nor a biological process. Though the molecular function of GAS2L3 is unclassified so far, its continuous downregulation following 213Bi-d9MAb treatment impressively verifies its involvement in cell cycle control as outlined by PANTHER (Table 1). As we have shown recently, cell cycle is arrested upon 213Bi-d9MAb treatment of HSC45-M2 cells [20].

Among the 8 genes being consistently upregulated following 213Bi-d9MAb treatment, COL4A2, NEDD9, C3, NMES1 and RASA4 (CAPRI) have been associated with a biological process and a molecular function. Upregulation of COL4A2 triggered by TGF-β in kidney mesangial cells has been described to induce glomerulosclerosis [38]. NEDD9 overexpression has been suggested to govern metastatic potential in human melanoma [39]. So far, C3 is known as the pivotal protein in the complement pathway, which is activated by conversion to C3b [40]. The nuclear protein encoded by NMES1 is downregulated or completely suppressed in human esophageal squamous cell carcinoma, implicating a suppressive role of this protein in tumorigenesis of the esophagus [41]. RASA4 (CAPRI) is activated by elevated cellular Ca2+ and switches off the Ras-MAPK pathway regulating cell growth and proliferation [42]. So far, none of these genes has been associated with functions in response to high LET ionizing radiation. Because these genes revealed significant upregulation following 213Bi-treatment, additional, hitherto unknown functions in the defence of radiation damage are thus quite evident.

Following 213Bi-d9MAb treatment of HSC45-M2 cells 12 genes revealed continuous downregulation. Nine of these genes have been ascribed to a biological process and a molecular function according to PANTHER (Table 1). Among these genes CDC20, KIF20A, UBR2, CENPE and ASPM are involved in the control of cell proliferation, i.e. cell cycle control, mitosis and chromosome segregation. CDC20 is an essential regulator required for the completion of mitosis [43]. Knockdown of the motor protein KIF20A in adenocarcinoma cells drastically attenuated cell growth [44]. Loss of UBR2 resulted in a high incidence of chromosome breaks and a severe deficiency in homologous recombination repair [45]. Gene silencing of CENPE led to chromosome missegregation and mitotic delay [46]. SiRNA-mediated knockdown of ASPM encoding a mitotic spindle protein in glioblastoma cells inhibited tumor cell proliferation, probably due to disturbance of cleavage plane orientation [47]. Thus, downregulation of these genes following treatment with 213Bi-d9MAb impressively demonstrates the destructive potential of the α-emitter 213Bi toward tumor cells.

The observed, 213Bi-d9MAb-induced downregulation of HIST4H4, WWP2, RFX3 and PHF17 (JADE1) has not been described in direct connection with cell death so far. DNA double-strand breaks induced by etoposide in choriocarcinoma cells caused decreased biotinylation of histone H4 but not downregulation of the HIST4H4 gene product [48]. Downregulation of WWP2 encoding an ubiquitin E3 ligase of the large subunit of RNA polymerase II elevated its intracellular protein level due to attenuated ubiquitination [49]. As suggested by Weissman [50], the ubiquitin signal might not only be crucial in targeting for protein degradation but also function in DNA repair and stress response. However, following DNA damage ubiquitination and degradation of RNA polymerase II has been reported to increase in S. cerevisiae [51]. RFX3 plays a key role in controlling the expression of genes required for the formation of cilia, thus participating in mechanisms that govern pancreatic endocrine cell differentiation [52]. Another member of the RFX family of transcription factors, RFX1, has been described to be involved in DNA damage response. However, expression of RFX1 is upregulated in response to DNA damage due to a release of promoter autorepression [53]. Thus, downregulation of both WWP2 and RFX3 after 213Bi-d9MAb treatment of gastric cancer cells suggests additional, hitherto unknown functions of these genes in response to α-emitter induced DNA/cell damage.

PHF17 (JADE1), a putative renal tumor suppressor, has two zinc finger motifs that also function in chromatin remodelling. Upregulation of JADE1 has been described to increase apoptosis [54]. Thus downregulation of JADE1, as observed following 213Bi-d9MAb treatment finally causing cell death, should be due to a mode of cell death different from apoptosis. This is in accordance with previous results on 213Bi-induced changes in cell morphology and expression of genes involved in damage response [15, 20].

Taken together, these results of differential gene expression following incubation of gastric cancer cells with 213Bi-immunoconjugates present important new insights with respect to the response of tumor cells to high LET irradiation. To detect genes whose differential expression is exclusively due to irradiation with the high LET α-emitter 213Bi, whole genome gene expression patterns of gastric cancer cells following irradiation with low LET β- or γ-emitter immunoconjugates have to be determined. This will be the subject of a future study. The existence of such genes seems obvious because tumor cells that are resistant to β- and γ-irradiation can be eliminated following incubation with the α-emitter 213Bi.

Acknowledgements

We would like to thank R. Obermair and C. Baaske for their skilful and accurate technical assistance, K. Yanagihara at the National Cancer Center Research Institute (Tokyo, Japan) for providing the HSC45-M2 stomach cancer cell line, E. Kremmer at the Institute of Molecular Immunology, GSF (Munich, Germany) and K.-F. Becker from the Institute of Pathology, Technische Universität München (Munich, Germany) for providing the antibody d9MAb. This work was supported by the German Ministry of Defense (M. Abend) and Deutsche Forschungsgemeinschaft grants SE 962/2-4 (R. Senekowitsch-Schmidtke).

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© Springer Science+Business Media, LLC 2008