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High Interleukin-15 Expression Characterizes Childhood Acute Lymphoblastic Leukemia With Involvement of the CNS

Gunnar Cario, Shai Izraeli, Anja Teichert, Peter Rhein, Julia Skokowa, Anja Möricke, Martin Zimmermann, Andre Schrauder, Leonid Karawajew, Wolf-Dieter Ludwig, Karl Welte, Holger J. Schünemann, Brigitte Schlegelberger, Martin Schrappe, Martin Stanulla

From the Department of Pediatrics, University Hospital Schleswig-Holstein, Kiel; Department of Pediatric Hematology/Oncology and Institute for Cell and Molecular Pathology, Hannover Medical School, Hannover; Department of Hematology, Oncology, and Tumor Immunology, Robert-Rössle-Clinic at the HELIOS Klinikum Berlin-Buch, Charité Medical School, Berlin, Germany; Department of Pediatric Hematology/Oncology, Sackler School of Medicine, Chaim Sheba Medical Center, Ramat Gan, Israel; and Clinical Research and Information Translation Unit, SC Epidemiology, Italian National Cancer Institute Regina Elena, Rome, Italy

Address reprint requests to Martin Stanulla, MD, MSc, Department of Pediatric Hematology and Oncology, Hannover Medical School, Carl-Neuberg-Str 1, 30625 Hannover, Germany; e-mail: stanulla.martin{at}mh-hannover.de

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
Purpose Applying current diagnostic methods, overt CNS involvement is a rare event in childhood acute lymphoblastic leukemia (ALL). In contrast, CNS-directed therapy is essential for all patients with ALL because without it, the majority of patients eventually will experience relapse. To approach this discrepancy and to explore potential distinct biologic properties of leukemic cells that migrate into the CNS, we compared gene expression profiles of childhood ALL patients with initial CNS involvement with the profiles of CNS-negative patients.

Patients and Methods We evaluated leukemic gene expression profiles from the bone marrow of 17 CNS-positive patients and 26 CNS-negative patients who were frequency matched for risk factors associated with CNS involvement. Results were confirmed by real-time quantitative polymerase chain reaction analysis and validated using independent patient samples.

Results Interleukin-15 (IL-15) expression was consistently upregulated in leukemic cells of CNS-positive patients compared with CNS-negative patients. In multivariate analysis, IL-15 expression levels greater than the median were associated with CNS involvement compared with expression equal to or less than the median (odds ratio [OR] = 10.70; 95% CI, 2.95 to 38.81). Diagnostic likelihood ratios for CNS positivity were 0.09 (95% CI, 0.01 to 0.65) for the first and 6.93 (95% CI, 2.55 to 18.83) for the fourth IL-15 expression quartiles. In patients who were CNS negative at diagnosis, IL-15 levels greater than the median were associated with subsequent CNS relapse compared with expression equal to or less than the median (OR = 13.80; 95% CI, 3.38 to 56.31).

Conclusion Quantification of leukemic IL-15 expression at diagnosis predicts CNS status and could be a new tool to further tailor CNS-directed therapy in childhood ALL.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
Modern treatment strategies for childhood acute lymphoblastic leukemia (ALL) are based on essential therapeutic phases that are consecutively applied over a time period of 2 to 3 years and lead to an overall long-term survival rate of approximately 80%.^1-4 CNS-directed therapy has become a prerequisite for successful treatment of childhood ALL. Before its introduction in the 1960s, more than 50% of children with ALL suffered from disease recurrence originating from the CNS.⁵ This high rate could be reduced to less than 5% through the introduction of cranial irradiation, intrathecal chemotherapy with methotrexate alone or in combination with other drugs (cytarabine and hydrocortisone), and systemic application of chemotherapeutics with adequate penetration into the CNS (high-dose methotrexate, dexamethasone, and high-dose cytarabine).^1-4,6

The intensity of CNS-targeted treatment is adjusted according to the risk of ALL relapse originating from the CNS, with the most important risk factor being overt CNS involvement at diagnosis (CNS3: puncture nontraumatic, > 5 WBC/µL CSF with identifiable blasts; see Patients and Methods).^6-8 Additional risk factors include a high initial WBC count, pro–B- or T-cell immunophenotype, and a traumatic lumbar puncture (TLP) with identifiable blast cells present at diagnosis.^1-4,9-11 The CNS risk profile determines the intensity of CNS-directed therapy, which may differ in the number of intrathecal injections and/or intrathecally applied drugs, as well as in the inclusion of cranial irradiation at different doses. Unfortunately, higher intensity of CNS-directed therapy, especially cranial irradiation, is associated with long-term sequelae (eg, leukoencephalopathy, impaired intellectual and psychomotor functioning, neuroendocrine system abnormalities, and secondary malignancies).^2,6 Thus, a more precise CNS risk assessment is not only important for the control of CNS leukemia but is also necessary to avoid overtreatment with potential deleterious long-term effects.

Despite extensive attempts to accurately assess CNS risk at diagnosis and to adjust routine CNS-directed therapy to avoid over- or undertreatment, the majority of relapses with CNS involvement occur in ALL patients who are CNS negative at diagnosis.¹¹ Therefore, current stratification strategies are insufficient for a comprehensive characterization of CNS status at diagnosis. We hypothesized that leukemic cells of patients with CNS involvement at diagnosis have distinct biologic properties reflected in a different pattern of transcribed genes and performed a translational study to further characterize this entity.

	PATIENTS AND METHODS

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Patients
Patient population. Between October 1999 and August 2004, 2,376 patients (aged 18 years) were enrolled onto Berlin-Frankfurt-Münster (BFM) multicenter trial ALL-BFM 2000 for the treatment of childhood ALL (for details, see Appendix, online only).^12-17 Informed consent was obtained from patients or legal guardians, and the protocol was approved by local and central ethical committees. All patients on ALL-BFM 2000 underwent diagnostic lumbar puncture and CSF examination at admission to the participating hospital. CNS status was defined as follows: CNS1: nontraumatic puncture without leukemic blasts after cytocentrifugation; CNS2: nontraumatic puncture, 5 WBC/µL CSF with identifiable blasts; CNS3: puncture nontraumatic, > 5 WBC/µL CSF with identifiable blasts; TLP positive: TLP with blasts; and TLP negative: TLP without blasts.^7,9-11

Patients included in gene expression analysis. We included CNS3 patients with diagnostic specimens available from the biologic specimen bank of trial ALL-BFM 2000 and frequency matched these patients at a ratio of at least 1:1 with CNS1 patients according to sex, age at diagnosis (between 1 and 10 years or 10 years), initial WBC count (< 10,000/µL; 10,000 to < 50,000/µL; 50,000 to < 100,000/µL; or 100,000/µL), and immunophenotype (precursor B-cell ALL: pro-B, common, pre-B; or precursor T-cell ALL). Bone marrow specimens were required to contain more than 70% blasts, as assessed morphologically before gradient centrifugation.

Patients included in validation analysis and patients who were CNS negative at diagnosis but experiencing relapse with CNS involvement. Validation analysis in independent patients with CNS3 status from the same population was performed with CNS1 control individuals of the same immunophenotype. Patients initially CNS1 with subsequent isolated or combined CNS relapse were compared with CNS1 patients with a minimum follow-up time of 3 years and no relapse (occurrence of CNS relapse after 3 years is a rare event).¹¹

Laboratory Analysis
Leukemic cell purification. Leukemic cells from cryopreserved diagnostic specimens were purified with a FACSVantage cell sorter (Becton Dickinson, Heidelberg, Germany) using anti-CD19 and anti-CD10 antibodies (Coulter-Immunotech Diagnostics, Miami, FL). For facilitation of leukemic cell isolation, normal T cells were labeled with anti-CD3 antibodies (Coulter-Immunotech Diagnostics).

RNA isolation, RNA amplification, and gene expression analysis. Total RNA of the primary set was isolated with Trizol reagent (Invitrogen, Paisley, United Kingdom) and subsequently passed over a Qiagen RNeasy column (Qiagen, Hilden, Germany) for the removal of small fragments. Each of the total RNA samples was linearly amplified using the MessageAmp aRNA Kit (Ambion, Austin, TX). Total and amplified RNA were quantified and validated for integrity using the Bioanalyzer 2100 (Agilent, Palo Alto, CA). The reference RNA used for all arrays was Universal Human Reference RNA (Stratagene Europe, Amsterdam, the Netherlands), which was linearly amplified using the same method. This reference RNA is isolated from 10 human cell lines derived from different human tissues to assure broad gene coverage.

For gene expression analysis, spotted cDNA microarrays that contained more than 43,000 features representing approximately 30,000 genes were used (Stanford Functional Genomics Facility, Stanford, CA). As previously described, sample RNA and the reference RNA were labeled with different fluorescent dyes (Cy5-deoxyuridine triphosphate and Cy3-deoxyuridine triphosphate; Amersham Pharmacia Biotech Europe, Freiburg, Germany) and comparatively hybridized to an array (protocols are posted at http://brownlab.stanford.edu/protocols.html).^18,19 The fluorescence intensities of Cy5 and Cy3 were measured using a GenePix 4000 scanner (Axon Instruments, Foster City, CA). Images were analyzed using GenePix Pro 4.1 software (Axon Instruments). Any areas of the microarrays that had obvious blemishes were manually omitted from subsequent analyses. Spots were considered well measured only if the reference RNA fluorescence intensity was greater than 2.5 times the local background and if the regression correlation was greater than 0.6. Any clone that was not well measured on at least 70% of the arrays was excluded from subsequent analyses. For each array, we used a scaling factor to set the mean sample-to-reference ratio for all well-measured spots to 1. For all subsequent analyses, we used log₂ of this normalized sample-to-reference ratio. We then mean centered the data for each clone across all arrays within each of two array print runs to minimize potential print run–specific bias (for details, see Appendix Table A1, online only). The primary data and the image files are stored in and are publicly available through the Stanford Microarray Database (http://smd.stanford.edu).

Real-time quantitative polymerase chain reaction analysis. Real-time quantitative polymerase chain reaction (RQ-PCR) analysis after reverse transcription was performed as described in the Appendix (online only). The expression level of the succinate dehydrogenase complex subunit A (SDHA) gene was used to normalize for differences in input cDNA. QuantiTect Primer Assays were used to measure mRNA abundances of the interleukin-15 (IL-15), 6-phosphofructo-2-kinase (PFKFB2), and SDHA genes (Qiagen). IL-15 mRNA primers detected both IL-15 isoforms.^20,21 Melting curve analyses were performed to verify the amplification specificity. Each sample was tested in duplicate. The expression ratio was calculated as 2ⁿ, where n was the threshold cycle (C_t) value difference normalized by the threshold cycle difference of a calibrator sample. All RQ-PCR analyses were performed blinded with regard to a patient's CNS status.

Statistical Analysis
To analyze the data derived in our gene expression experiments in an unsupervised manner, we used agglomerative hierarchical clustering. In the supervised analysis of the data, we used significance analysis of microarrays (SAM).²² SAM assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements. For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of genes identified by chance, the false discovery rate (FDR). The data file used for SAM analysis is available at http://www.uni-kiel.de/all-studie/All_lab_mRNA.htm (username: review; password: interleukin-15).

Proportional differences between patient groups were analyzed by the ² or Fisher's exact test. Comparison of IL-15 expression between groups was performed using the Mann-Whitney U test. Depending on the distribution of variables, correlation analyses were performed by computing Pearson's or Spearman's correlation coefficients. The association between IL-15 expression and CNS status was examined by use of unconditional logistic regression analysis to calculate odds ratios (ORs) and their 95% CIs. For measuring the power of IL-15 expression to change the pretest into the post-test probability of leukemic CNS involvement being present, likelihood ratios and their 95% CIs were calculated.²³ = .05 was used as criterion for statistical significance.

	RESULTS

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Gene Expression Analysis and Validation
We initially identified nine precursor B-cell ALL patients with CNS3 status who were frequency matched to 18 control patients with CNS1 status according to sex, age at diagnosis, initial WBC count, and immunophenotype (two control CNS1 patients per one CNS3 patient). In all but one sample (70% blasts), the specimens contained more than 90% blasts. Using the same criteria, eight additional patients with precursor T-cell ALL and CNS3 status were matched to eight controls because the T-cell ALL samples available to us allowed only frequency matching of one CNS1 patient per one CNS3 patient. All T-cell ALL samples contained at least 80% blasts. Characteristics of these patients are listed in Table 1. In the supervised analysis of the data, using SAM²² including 12,802 clones (1,000 permutations; fold-change: 2; FDR: 61%), we identified 18 differentially expressed genes (Fig 1). Because the FDR of 61% indicates that only approximately half of the genes discovered are truly described as significant, we next aimed to explore which genes these are. A high FDR might be a consequence of the broad biologic heterogeneity of samples included in our analysis (precursor T- and B-cell ALL with and without nonrandom recurrent chromosomal rearrangements) but could potentially also be a result of a contamination with nonmalignant cells. To assure that differential gene expression was not simply a reflection of different percentages of normal bone marrow cells in our analytic specimens, we purified leukemic cells from four precursor B-cell patients (two CNS1 and two CNS3 patients) with additional available cryopreserved diagnostic specimens and repeated the analysis. Purity of samples after sorting was 92.4%, 98.9%, 98.4%, and 99.6% in the four patients. Of the 18 genes, differential expression of IL-15 and PFKFB2 could be confirmed with an up to 10-fold higher expression in CNS3 patients (Fig 1). When the analysis of IL-15 expression was performed separately for precursor B- and T-cell ALL, IL-15 expression was found to be significantly different in both strata. IL-15 expression was validated by RQ-PCR in all patients included in the microarray analysis and showed a high correlation between the levels obtained by microarray and RQ-PCR analyses (correlation coefficient = 0.9). Most important, using this independent method, IL-15 was again found to be highly significantly different between CNS1 and CNS3 patients (P < .001; Fig 2A). PFKFB2 expression could be validated by RQ-PCR in patients included in microarray analyses but not in the independent patient sample (data not shown). Genes that could be confirmed in the sorted samples as being downregulated in CNS3 patients but that were not validated by RQ-PCR because of a higher variability after purification and/or low fold-changes included the Iroquois homeobox protein 2 (IRX2); protein tyrosine phosphatase, receptor type, S (PTPRS); sarcoglycan beta (SGCB); and regulating synaptic membrane exocytosis 3 (RIMS3; Fig 1).

View larger version (43K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 1. Left: Genes differentially expressed between CNS-negative and CNS-positive patients identified through significance analysis of microarrays (SAM; 1,000 permutations, fold-change 2, false discovery rate = 61%). Right: Gene expression of the differentially expressed genes identified by SAM analysis in four samples after leukemic cell purification using anti-CD19/anti-CD10 antibodies. Gray represents missing data.

View larger version (10K): [in this window] [in a new window] [PowerPoint Slide for Teaching]   Fig 2. Interleukin-15 expression in leukemic bone marrow cells at diagnosis as measured by real-time quantitative polymerase chain reaction after reverse transcription in patients without (nontraumatic puncture without leukemic blasts after cytocentrifugation [CNS1]) and with (puncture nontraumatic, > 5 WBC/µL CSF with identifiable blasts [CNS3]) leukemic CNS involvement. (A) Patients included in gene expression analyses using microarrays. (B) Patients from independent validation. (C) CNS1 patients in long-term remission or experiencing relapse with CNS involvement. AU, arbitrary units.

Table 2 shows the association of IL-15 expression quartiles with CNS status. Quartiles were calculated based on the IL-15 expression values of the 82 patients (52 CNS1 and 30 CNS3 patients) described in Table 1. A stepwise increase in risk of CNS3 status with increasing quartiles could be observed. In CNS3 patients, the highest quartile conferred a univariate 76-fold increase and multivariate 153-fold increase in risk of CNS3 status compared with CNS1 patients. The likelihood ratios for IL-15 expression to change the pretest into the post-test probability of CNS3 status were 0.09 (95% CI, 0.01 to 0.65) for the first and 6.93 (95% CI, 2.55 to 18.83) for the fourth IL-15 expression quartiles (Table 2). Thus, IL-15 expression levels are predictive of the CNS status at the time of diagnosis of ALL.

IL-15 Expression in Patients Who Were CNS Negative at Diagnosis but Who Experienced Relapse With CNS Involvement
Next, we studied whether the expression level of IL-15 at initial diagnosis of CNS-negative patients could predict CNS relapse. We analyzed IL-15 expression by RQ-PCR at initial ALL diagnosis in 22 CNS1 patients subsequently experiencing relapse with leukemic CNS involvement (nine isolated and 13 combined relapses, all occurring within 3 years of diagnosis) compared with 44 of 52 patients without CNS disease at diagnosis also included in the previous two analyses who remained in remission for more than 3 years (Table 3). The distribution of the two groups with regard to treatment allocation was significantly different (Table 3). A significantly higher IL-15 expression was detected in the diagnostic samples of patients with subsequent CNS relapse (P < .001; Fig 2C). We detected no difference in IL-15 expression levels between isolated and combined relapses (P = .764). In a logistic regression analysis controlling for the same variables mentioned earlier and treatment group, IL-15 expression levels greater than the median conferred a more than 13-fold increased risk of CNS relapse compared with expression equal to or less than the median (OR = 13.80; 95% CI, 3.38 to 56.31, P < .001). Thus, high expression levels of IL-15 in diagnostic leukemic bone marrow cells of patients with ALL and no overt CNS involvement are associated with subsequent CNS relapse.

	DISCUSSION

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The two major questions related to CNS leukemia are as follows: First, can we better identify those patients with occult CNS leukemia and thereby adjust the intensity of toxic CNS-directed antileukemic therapy more precisely to those patients who require it? Second, what are the biologic mechanisms of leukemic cell migration and growth in the CNS? Identification of such mechanisms could lead to a more specific and potentially less toxic therapy aimed at eliminating CNS leukemia.

To address these questions, we compared the gene expression profiles of ALL patients with CNS disease to the profiles of patients without overt CNS involvement. Although the initially observed FDR was high, we were able to confirm the higher mRNA expression of the cytokine IL-15 in leukemic bone marrow cells of CNS3 patients at diagnosis in an independent study set. Of note, altogether our analyses included 30 CNS3 patients; these patients represented the CNS-positive patients out of approximately 900 children with ALL. Furthermore and most significantly, IL-15 levels in the diagnostic bone marrow samples of patients without overt CNS involvement predicted eventual CNS relapse. These findings may not only have important clinical implications for refining CNS negativity (CNS1) and positivity (CNS3) in patients with childhood ALL, but they may also be helpful in guiding the intensively debated CNS-directed therapy in patients with low CNS positivity (CNS2) by distinguishing patients who may benefit from treatment intensification from patients not in need of it.^{8,10,11,26,27} Because, at present, the clinical relevance of CNS2 status for patients on different treatment protocols is not finally clarified, this group was not analyzed in our present study. In addition, IL-15 expression may also aid in characterizing a true CNS3 status in the group of patients with a TLP-positive status and in difficult morphologic interpretations (leukemic blasts v reactive mononuclear cells). Of particular importance, an improved assessment of CNS status could lead to a reduction of prophylactic CNS-directed therapy for a significant number of patients because low IL-15 expression has the true potential to rule out CNS involvement (Table 2). Next, undoubtedly, a careful prospective evaluation uniformly addressing all biologic subgroups that should also include IL-15 protein serum and CSF levels will be required before the information derived from our present study can lead to an improved assessment of CNS status at diagnosis in childhood ALL and the associated respective treatment adjustments. Finally, it also has to be acknowledged that other, currently unknown genes or genes identified by microarray analyses but not yet confirmed in independent samples may serve as biomarkers for CNS status in childhood ALL as well, but these could have been missed by our approach of selecting and pursuing the most promising candidates only.

IL-15 is a proinflammatory cytokine that promotes T-cell proliferation and induction of cytolytic effector cells.^28-30 Its main sites of synthesis are dendritic cells and monocytes, but it has also shown to be produced by other sources including macrophages, fibroblasts, and glial cells.³⁰ IL-15 acts through a heterotrimeric receptor composed of a specific high-affinity IL-15 receptor -chain, the interleukin-2 receptor β-chain, and the common cytokine receptor -chain.^28-30 Functions of IL-15 include the proliferation and differentiation of natural killer, T, and B cells, as well as the maintenance of memory T cells. In contrast to other interleukins, only small amounts of IL-15 are secreted to the extracellular space, and the majority acts as cell membrane-bound cytokine through direct cell-cell contact.^29-31 Of particular interest to our findings, membrane-bound IL-15 was described to upregulate cytokine secretion, cell adhesion, and migration of cells by phosphorylation of mitogen-activated protein kinase family members and focal adhesion kinase.³⁰ High levels of IL-15 mRNA in mononuclear cells and/or protein in the serum and CSF have been reported in patients with active multiple sclerosis, Alzheimer's disease, and vascular cerebral lesions in Behcet's disease.^32-35

CNS involvement in ALL is mainly a leptomeningeal disease, with leukemic cells first becoming apparent in superficial arachnoid veins and surrounding adventitia. With increasing cell number, arachnoid trabeculae are destroyed, and cells enter the CSF.²⁵ The mechanisms leading to leukemic cell migration into the CNS are not understood. Two studies provide indirect support for a role of IL-15 in that process. Mice that are triple mutant for RAG2, TP53, and PRKDC develop ALL with CNS involvement at a high incidence.³⁶ In this context, it is of interest that P53 was shown to suppress IL-15 production and that absence of wild-type P53 is associated with high expression of IL-15.³⁷ Finally, because monocytes are a major source of IL-15, the frequent involvement of the CNS in acute monoblastic leukemia may also be related to increased production of IL-15 by these cells.²⁴

In conclusion, our results suggest a potential diagnostic value of leukemic IL-15 expression for assessing CNS involvement in childhood ALL and for predicting CNS relapse. In addition, our results suggest a role for leukemic IL-15 in the pathogenesis of CNS involvement in ALL and provide a perspective for IL-15 as a novel therapeutic target in childhood ALL. The recent development of anti–IL-15 monoclonal antibodies provides a potential new tool for treatment and/or prevention of CNS leukemia.³⁸

	AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
The author(s) indicated no potential conflicts of interest.

	AUTHOR CONTRIBUTIONS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 
Conception and design: Gunnar Cario, Shai Izraeli, Martin Schrappe, Martin Stanulla

Financial support: Wolf-Dieter Ludwig, Brigitte Schlegelberger, Martin Schrappe, Martin Stanulla

Administrative support: Martin Schrappe, Martin Stanulla

Provision of study materials or patients: Gunnar Cario, Anja Möricke, Andre Schrauder, Wolf-Dieter Ludwig, Karl Welte, Martin Schrappe, Martin Stanulla

Collection and assembly of data: Gunnar Cario, Anja Teichert, Peter Rhein, Julia Skokowa, Martin Zimmermann, Leonid Karawajew, Wolf-Dieter Ludwig, Martin Schrappe, Martin Stanulla

Data analysis and interpretation: Gunnar Cario, Martin Zimmermann, Holger J. Schünemann, Martin Stanulla

Manuscript writing: Gunnar Cario, Shai Izraeli, Holger J. Schünemann, Martin Stanulla

Final approval of manuscript: Gunnar Cario, Shai Izraeli, Anja Teichert, Peter Rhein, Julia Skokowa, Anja Möricke, Martin Zimmermann, Andre Schrauder, Leonid Karawajew, Wolf-Dieter Ludwig, Karl Welte, Holger J. Schünemann, Brigitte Schlegelberger, Martin Schrappe, Martin Stanulla

	Appendix

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION AUTHORS' DISCLOSURES OF... AUTHOR CONTRIBUTIONS Appendix REFERENCES

 

CNS status was defined as follows: CNS1 (nontraumatic puncture without leukemic blasts after cytocentrifugation), CNS2 (nontraumatic puncture, 5 WBC/µL CSF with identifiable blasts), CNS3 (puncture nontraumatic, > 5 WBC/µL CSF with identifiable blasts), traumatic lumbar puncture (TLP)+ (TLP with blasts), and TLP- (TLP without blasts). In addition to the CNS3 group as defined above, patients with a cerebral mass or patients with cranial nerve palsy in combination with blasts after cytocentrifugation were regarded as having CNS3 disease (Bürger B, Zimmermann M, Mann G, et al: J Clin Oncol 21:184-188, 2003). In 65% of patients the CSF cytospin preparations were centrally reviewed.

Complete remission was defined as the absence of leukemic blasts in the peripheral blood and cerebrospinal fluid, less than 5% lymphoblasts in bone marrow aspiration smears, and no evidence of localized disease. Relapse was defined as recurrence of lymphoblasts or localized leukemic infiltrates at any site. Isolated CNS relapse was defined by more than 5 WBC/µL CSF and identifiable blasts on cytospin preparations with less than 5% of bone marrow blasts and no other localized leukemic infiltrates. Combined relapses included those with simultaneous recurrence in the bone marrow and in an extramedullary site.

Laboratory Analysis
Real-time quantitative polymerase chain reaction analysis. Real-time quantitative polymerase chain reaction analysis (RQ-PCR) was performed after random hexamer priming and MuLV reverse transcription (Fermentas, Hanover, MD) to generate cDNA. PCR was carried out on an Applied Biosystems Model 7300 Sequence Detector (Darmstadt, Germany) using the QuantiTect SYBR Green PCR kit (Qiagen, Hilden, Germany) as described in the manufacturer's instructions.

	ACKNOWLEDGMENTS

 
We thank all patients, nurses, and physicians for participation in ALL-BFM 2000.

	NOTES

 
Supported by the Madeleine-Schickedanz-Kinderkrebsstiftung, Verein zur Förderung der Behandlung krebskranker Kinder Hannover eV, Deutsche Krebshilfe, and the Bundesministerium für Bildung und Forschung.

Presented in part at the 48th Annual Meeting of the American Society of Hematology, December 9-12, 2006, Orlando, FL.

The Hannover Medical School, Germany, has filed a patent application associated with the findings reported in this article.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

	REFERENCES

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1. Pinkel D: Five year follow-up of "total therapy" of childhood lymphocytic leukemia. JAMA 216:648-652, 1971[Abstract/Free Full Text]

2. Pui CH, Evans WE: Treatment of childhood acute lymphoblastic leukemia. N Engl J Med 354:166-178, 2006[Free Full Text]

3. Schrappe M, Reiter A, Zimmermann M, et al: Long-term results of four consecutive trials in childhood ALL performed by the ALL-BFM study group from 1981 to 1995. Leukemia 14:2205-2222, 2000[CrossRef][Medline]

4. Silverman LB, Declerck L, Gelber RD, et al: Results of Dana-Farber Cancer Institute Consortium protocols for children with newly diagnosed acute lymphoblastic leukemia (1981-1995). Leukemia 14:2247-2256, 2000[CrossRef][Medline]

5. Evans AE, Gilbert ES, Zandstra R: The increasing incidence of central nervous system leukemia in children. Cancer 26:404-409, 1970[CrossRef][Medline]

6. Clarke M, Gaynon P, Hann I, et al: CNS-directed therapy for childhood acute lymphoblastic leukemia: Childhood ALL Collaborative Group overview of 43 randomized trials. J Clin Oncol 21:1798-1809, 2003[Abstract/Free Full Text]

7. Mastrangelo R, Poplack D, Bleyer A, et al: Report and recommendations of the Rome workshop concerning poor-prognosis acute lymphoblastic leukemia in children: Biologic bases for staging, stratification, and treatment. Med Pediatr Oncol 14:191-194, 1986[Medline]

8. Mahmoud HH, Rivera GK, Hancock ML, et al: Low leukocyte counts with blast cells in cerebrospinal fluid of children with newly diagnosed acute lymphoblastic leukemia. N Engl J Med 329:314-319, 1993[Abstract/Free Full Text]

9. Gajjar A, Harrison PL, Sandlund JT, et al: Traumatic lumbar puncture at diagnosis adversely affects outcome in childhood acute lymphoblastic leukemia. Blood 96:3381-3384, 2000[Abstract/Free Full Text]

10. Howard SC, Gajjar AJ, Cheng C, et al: Risk factors for traumatic and bloody lumbar puncture in children with acute lymphoblastic leukemia. JAMA 288:2001-2007, 2002[Abstract/Free Full Text]

11. Bürger B, Zimmermann M, Mann G, et al: Diagnostic cerebrospinal fluid (CSF) examination in children with acute lymphoblastic leukemia (ALL): Significance of low leukocyte counts with blasts or traumatic lumbar puncture. J Clin Oncol 21:184-188, 2003[Abstract/Free Full Text]

12. Stanulla M, Schaeffeler E, Flohr T, et al: Thiopurine methyltransferase (TPMT) genotype and early treatment response to mercaptopurine in childhood acute lymphoblastic leukemia. JAMA 293:1485-1489, 2005[Abstract/Free Full Text]

13. Breit S, Stanulla M, Flohr T, et al: Activating NOTCH1 mutations predict favorable early treatment response and long term outcome in childhood precursor T-cell lymphoblastic leukemia. Blood 108:1151-1157, 2006[Abstract/Free Full Text]

14. Bene MC, Castoldi G, Knapp W, et al: Proposals for the immunological classification of acute leukemias: European Group for the Immunological Characterization of Leukemias (EGIL). Leukemia 9:1783-1786, 1995[Medline]

15. Ludwig WD, Rieder H, Bartram CR, et al: Immunophenotypic and genotypic features, clinical characteristics, and treatment outcome of adult pro-B acute lymphoblastic leukemia: Results of the German multicenter trials GMALL 03/87 and 04/89. Blood 92:1898-1909, 1998[Abstract/Free Full Text]

16. Schrappe M, Reiter A, Ludwig WD, et al: Improved outcome in childhood acute lymphoblastic leukemia despite reduced use of anthracyclines and cranial radiotherapy: Results of trial ALL-BFM 90—German-Austrian-Swiss ALL-BFM Study Group. Blood 95:3310-3322, 2000[Abstract/Free Full Text]

17. Viehmann S, Borkhardt A, Lampert F, et al: Multiplex PCR: A rapid screening method for detection of gene rearrangements in childhood acute lymphoblastic leukemia. Ann Hematol 78:157-162, 1999[CrossRef][Medline]

18. Fine B, Stanulla M, Schrappe M, et al: Gene expression patterns associated with recurrent chromosomal translocations in acute lymphoblastic leukemia. Blood 103:1043-1049, 2004[Abstract/Free Full Text]

19. Cario G, Stanulla M, Fine BM, et al: Distinct gene expression profiles determine molecular treatment response in childhood acute lymphoblastic leukemia. Blood 105:821-826, 2005[Abstract/Free Full Text]

20. Onu A, Pohl T, Krause H, et al: Regulation of IL-15 secretion via the leader peptide of two IL-15 isoforms. J Immunol 158:255-262, 1997[Abstract]

21. Meazza R, Gaggero A, Neglia F, et al: Expression of two interleukin-15 mRNA isoforms in human tumors does not correlate with secretion: Role of different signal peptides. Eur J Immunol 27:1049-1054, 1997[Medline]

22. Tusher VG, Tibshirani R, Chu G: Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 98:5116-5121, 2001[Abstract/Free Full Text]

23. Guyatt G, Rennie D: Users' Guide to the Medical Literature: A Manual for Evidence-Based Clinical Practice. Chicago, IL, American Medical Association Press, 2002

24. Chamberlain MC, Nolan C, Abrey LE: Leukemic and lymphomatous meningitis: Incidence, prognosis and treatment. J Neurooncol 75:71-83, 2005[CrossRef][Medline]

25. Price RA, Johnson WW: The central nervous system in childhood leukemia: I. The arachnoid. Cancer 31:520-533, 1973[CrossRef][Medline]

26. Tubergen D, Cullen J, Boyett J, et al: Blasts in CSF with a normal cell count do not justify alteration of therapy for acute lymphoblastic leukemia in remission: A Children's Cancer Group report. J Clin Oncol 12:273-278, 1994[Abstract]

27. Gilchrist G, Tubergen D, Sather H, et al: Low number of CSF blasts at diagnosis do not predict for the development of CNS leukemia in children with intermediate-risk acute lymphoblastic leukemia: A Children's Cancer Group report. J Clin Oncol 12:2594-2600, 1994[Abstract/Free Full Text]

28. Fehniger TA, Caligiuri MA: Interleukin 15: Biology and relevance to human disease. Blood 97:14-32, 2001[Free Full Text]

29. Waldmann TA: The biology of interleukin-2 and interleukin-15: Implications for cancer therapy and vaccine design. Nat Rev Immunol 6:595-601, 2006[CrossRef][Medline]

30. Bulfone-Paus S, Bulanova E, Budagian V, et al: The interleukin-15/interleukin-15 receptor system as a model for juxtacrine and reverse signaling. Bioessays 28:362-377, 2006[CrossRef][Medline]

31. Dubois S, Mariner J, Waldmann TA, et al: IL-15R alpha recycles and presents IL-15 in trans to neighboring cells. Immunity 17:537-547, 2002[CrossRef][Medline]

32. Rentzos M, Cambouri C, Rombos A, et al: IL-15 is elevated in serum and cerebrospinal fluid of patients with multiple sclerosis. J Neurol Sci 241:25-29, 2006[CrossRef][Medline]

33. Kivisakk P, Matusevicius D, He B, et al: IL-15 mRNA expression is up-regulated in blood and cerebrospinal fluid mononuclear cells in multiple sclerosis (MS). Clin Exp Immunol 111:193-197, 1998[CrossRef][Medline]

34. Rentzos M, Zoga M, Parakevas GP, et al: IL-15 is elevated in cerebrospinal fluid of patients with Alzheimer's disease and frontotemporal dementia. J Geriatr Psychiatry Neurol 19:114-117, 2006[Abstract/Free Full Text]

35. Hamzaoui K, Hamzaoui A, Ghorbel I, et al: Levels of IL-15 in serum and cerebrospinal fluid of patients with Behcet's disease. Scand J Immunol 64:655-660, 2006[CrossRef][Medline]

36. Gladdy RA, Taylor MD, Williams CJ, et al: The RAG-1/2 endonuclease causes genomic instability and controls CNS complications of lymphoblastic leukemia in p53/Prkdc-deficient mice. Cancer Cell 3:37-50, 2003[CrossRef][Medline]

37. De Giovanni C, Nanni P, Sacchi A, et al: Wild-type p53-mediated down-modulation of interleukin 15 and interleukin 15 receptors in human rhabdomyosarcoma cells. Br J Cancer 78:1541-1546, 1998[Medline]

38. Morris JC, Janik JE, White JD, et al: Preclinical and phase I clinical trial of blockade of IL-15 using Mikbeta1 monoclonal antibody in T cell large granular lymphocyte leukemia. Proc Natl Acad Sci U S A 103:401-406, 2006[Abstract/Free Full Text]

Submitted March 22, 2007; accepted June 29, 2007.

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