Blood online
Home About Blood Authors Subscriptions Permission Advertising Public Access contact us
 

 
Advanced
Current Issue
First Edition
Future Articles
Archives
Submit to Blood
Search
American Society of Hematology
Meeting Abstracts
Email Alerts
Blood, 15 April 2007, Vol. 109, No. 8, pp. 3489-3495.
Prepublished online as a Blood First Edition Paper on January 5, 2007; DOI 10.1182/blood-2006-08-040410.


This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Supplemental Appendix
Right arrow All Versions of this Article:
blood-2006-08-040410v1
109/8/3489    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Right arrow Rights and Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via CrossRef
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Avet-Loiseau, H.
Right arrow Articles by Mathiot, C.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Avet-Loiseau, H.
Right arrow Articles by Mathiot, C.
Related Collections
Right arrow Oncogenes and Tumor Suppressors
Right arrow Clinical Trials and Observations
Right arrowRelated Article in Blood Online
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

arrow to previous article Previous Article  |  Table of Contents  |  Next Article next article arrow

NEOPLASIA

Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myélome

Hervé Avet-Loiseau1,2, Michel Attal3, Philippe Moreau1,4, Catherine Charbonnel1,2, Frédéric Garban5, Cyrille Hulin6, Serge Leyvraz7, Mauricette Michallet8, Ibrahim Yakoub-Agha9, Laurent Garderet10, Gérald Marit11, Lucienne Michaux12, Laurent Voillat13, Marc Renaud14, Bernard Grosbois15, Gaelle Guillerm16, Lotfi Benboubker17, Mathieu Monconduit18, Catherine Thieblemont19, Philippe Casassus20, Denis Caillot21, Anne-Marie Stoppa22, Jean-Jacques Sotto5, Marc Wetterwald23, Charles Dumontet8, Jean-Gabriel Fuzibet24, Isabelle Azais25, Véronique Dorvaux26, Marc Zandecki27, Régis Bataille1, Stéphane Minvielle1,2, Jean-Luc Harousseau4, Thierry Facon9, and Claire Mathiot28

1 Institut National de la Santé et de la Recherche Médicale (INSERM), Unité 601, Nantes, France; 2 Hematology Laboratory, University Hospital Hôtel-Dieu, Nantes, France; 3 Hematology Department, University Hospital Purpan, Toulouse, France; 4 Hematology Department, University Hospital Hôtel-Dieu, Nantes, France; 5 Hematology Department, University Hospital Michalon, Grenoble, France; 6 Hematology Department, University Hospital Brabois, Nancy, France; 7 Hematology Department, University Hospital, Lausanne, Switzerland, for the Swiss Group for Clinical Cancer Research (SAKK); 8 Hematology Department, University Hospital Edouard Herriot, Lyon, France; 9 Hematology Department, University Hospital Huriez, Lille, France; 10 Hematology Department, University Hospital Saint-Antoine, Paris, France; 11 Hematology Department, University Hospital Haut-Lévêque, Bordeaux, France; 12 Hematology Department, University Hospital, Haine, Belgium; 13 Hematology Department, University Hospital Minjoz, Besançon, France; 14 Hematology Department, University Hospital Jean Bernard, Poitiers, France; 15 Internal Medicine Department, University Hospital Sud, Rennes, France; 16 Hematology Department, University Hospital Morvan, Brest, France; 17 Hematology Department, University Hospital Bretonneau, Tours, France; 18 Hematology Department, Becquerel Cancer Center, Rouen, France; 19 Hematology Department, University Hospital, Pierre-Bénite, France; 20 Hematology Department, University Hospital Avicenne, Bobigny, France; 21 Hematology Department, University Hospital, Dijon, France; 22 Hematology Department, Paoli Calmette Cancer Center, Marseille, France; 23 Hematology Department, Hospital, Dunkerque, France; 24 Internal Medicine Department, University Hospital L'Archet 1, Nice, France; 25 Rheumatology Department, University Hospital Jean Bernard, Poitiers, France; 26 Hematology Department, Hospital Nôtre-Dame de Bon Secours, Metz, France; 27 Hematology Laboratory, University Hospital Larrey, Angers, France; 28 Hematology Department, Curie Cancer Center, Paris, France


    Abstract
 Top
 Abstract
 Introduction
 Patients, materials, and methods
 Results
 Discussion
 Authorship
 References
 
Acquired genomic aberrations have been shown to significantly impact survival in several hematologic malignancies. We analyzed the prognostic value of the most frequent chromosomal changes in a large series of patients with newly diagnosed symptomatic myeloma prospectively enrolled in homogeneous therapeutic trials. All the 1064 patients enrolled in the IFM99 trials conducted by the Intergroupe Francophone du Myélome benefited from an interphase fluorescence in situ hybridization analysis performed on purified bone marrow plasma cells. They were systematically screened for the following genomic aberrations: del(13), t(11;14), t(4;14), hyperdiploidy, MYC translocations, and del(17p). Chromosomal changes were observed in 90% of the patients. The del(13), t(11;14), t(4;14), hyperdiploidy, MYC translocations, and del(17p) were present in 48%, 21%, 14%, 39%, 13%, and 11% of the patients, respectively. After a median follow-up of 41 months, univariate statistical analyses revealed that del(13), t(4;14), nonhyperdiploidy, and del(17p) negatively impacted both the event-free survival and the overall survival, whereas t(11;14) and MYC translocations did not influence the prognosis. Multivariate analyses on 513 patients annotated for all the parameters showed that only t(4;14) and del(17p) retained prognostic value for both the event-free and overall survivals. When compared with the currently used International Staging System, this prognostic model compares favorably. In myeloma, the genomic aberrations t(4;14) and del(17p), together with ß2-microglobulin level, are important independent predictors of survival. These findings have implications for the design of risk-adapted treatment strategies.


    Introduction
 Top
 Abstract
 Introduction
 Patients, materials, and methods
 Results
 Discussion
 Authorship
 References
 
Multiple myeloma is the second most common hematologic cancer, representing 1% of all cancer diagnoses and 2% of all cancer deaths. Despite recent progress in the management of patients, myeloma remains an incurable disease, with a median survival not exceeding 4 years.1 However, this uniform evolution hides a wide heterogeneity in the clinical course; some patients die from disease evolution within a few weeks, whereas others live for more than 10 years. Several prognostic staging systems have been proposed, the most powerful being the recently reported International Staging System (ISS), based on the evaluation of 2 simple biological parameters (ie, the serum levels of ß2-microglobulin and albumin).2 Nevertheless, this staging system did not really include the role of (cyto) genetics since very few patients were analyzed for this parameter

Chromosomal abnormalities have been shown to display a major role in disease evolution in several hematologic malignancies. In myeloma, cytogenetics has been hampered by the low proliferative activity of the malignant plasma cells in vitro, and by the frequent low tumor cell infiltrate within the bone marrow specimens. Most large series reported about 30% abnormal karyotypes,35 although other techniques not dependent upon obtaining metaphases described genomic aberrations in almost 100% of the cases.6,7 Fluorescence in situ hybridization (FISH) is able to circumvent this pitfall, since it enables the detection of specific chromosomal changes even in noncycling interphase cells. Initial studies using this technique in myeloma demonstrated a high incidence of chromosomal changes,7,8 and suggested that FISH could be used for the assessment of single abnormalities useful for prognostic evaluation.913

We designed a study based on interphase FISH for the evaluation of a large series of homogeneously treated patients, using DNA probes specific for the most recurrent chromosomal aberrations observed in myeloma. Our objective was to assess the incidence and clinical relevance of genomic abnormalities in this group of patients treated with high-dose therapy.


    Patients, materials, and methods
 Top
 Abstract
 Introduction
 Patients, materials, and methods
 Results
 Discussion
 Authorship
 References
 
Approval for this study was obtained from the University Hospitals of Nantes, Toulouse, and Grenoble institutional review boards. Informed consent was provided in accordance with the Declaration of Helsinki.

Patients

Between April 2000 and December 2003, 1064 patients younger than 66 years of age with symptomatic newly diagnosed multiple myeloma were enrolled in the IFM99 therapeutic trials, run by the Intergroupe Francophone du Myélome (IFM; for 81 patients, bone marrow has been analyzed in other laboratories). Briefly, patients received an induction therapy with 4 courses of VAD (vincristine, adriamycin, and dexamethasone), followed by double intensive therapy. The IFM99-02 trial was dedicated for patients with fewer than 2 poor prognosis factors (ß2-microglobulin levels above 3 mg/L and del(13) by FISH). After induction, patients received 2 courses of high-dose melphalan (140 mg/m2 and 200 mg/m2), and were then randomized for maintenance therapy—none (arm A), pamidronate (arm B), or pamidronate plus thalidomide (arm C)—until relapse. This trial recruited 780 patients.14 The IFM99-03 trial enrolled 65 patients with 2 poor prognosis factors and with an HLA-identical familial donor.15 After induction, patients received 1 high-dose melphalan course (200 mg/m2), followed by a reduced intensity–conditioned allogeneic transplantation. Finally, the IFM99-04 trial enrolled 219 patients with 2 poor prognosis factors and no HLA-identical familial donor.16 After a similar induction and first high-dose melphalan course, patients received a second melphalan-based intensification (220 mg/m2), and were randomized to receive or not an anti–interleukin-6 (IL-6) antibody during the conditioning regimen. All the patients were analyzed for del(13) by FISH on bone marrow at diagnosis, and 983 of them were referred to the Hematology Laboratory of Nantes and are reported in this study.

Interphase cytogenetic analysis

After overnight shipment, mononuclear cells were separated by gradient-density centrifugation (Ficoll-Hypaque; Eurobio, Les Ulis, France). Plasma cells were then purified using CD138-coated magnetic beads according to the manufacturer's instructions (Miltenyi Biotec, Paris, France), enabling a plasma cell purity higher than 90% (controlled in each patient) as previously described.8 Plasma cells were then analyzed using DNA probes specific for the following chromosomal aberrations: del(13q14) t(11;14)(q13;q32), t(4;14)(p16;q32), MYC rearrangements, hyperdiploidy, and del(17p13). The del(13) was analyzed with a probe specific for the D13S319 locus (purchased from Abbott, Rungis, France). Probes specific for the t(4;14) and t(11;14) translocations were kindly provided by Abbott (Chicago, IL). Hyperdiploidy was assessed using a set of probes specific for chromosomes 5, 9, and 15 (kindly provided by Abbott, Chicago, IL), as previously described (hyperdiploidy if at least 2 probes show extracopies).17 Translocations involving the MYC locus were detected using yeast artificial chromosome (YAC) probes previously described,18 and a commercially available probe, kindly provided by Abbott (Chicago, IL). The del(17p) was assessed using a P53-specific bacterial artificial chromosome (BAC) probe at 17p13 (RPCI-613o12). Probe labeling and FISH procedures have been previously described.8

Statistical analyses

The primary endpoint was the correlation with survival from the time of diagnosis. Kaplan-Meier curves for event-free survival (EFS; defined by the time between diagnosis and the occurrence of progression, relapse, or death) and overall survival (OS) were plotted and compared by the use of the log-rank test. Comparison of frequencies between groups was performed using the chi-square test. Prognostic factors for EFS and OS were determined by means of the Cox proportional hazard model for covariate analysis. As possible prognostic factors, ß2-microglobulin levels, albumin levels, hemoglobin levels, platelet counts, isotype, and presence or absence of genomic aberrations (del(13) t(11;14), t(4;14), MYC translocations, hyperdiploidy, and del(17p)) were included in the regression model. For continuous variables, classical cutoffs were selected. To take into account the possible effects of treatment upon prognostic variables, treatment-adjusted statistical analyses were performed. The statistical analyses were performed with the SAS 9.1 software package (SAS Institute Inc, Cary, NC).


    Results
 Top
 Abstract
 Introduction
 Patients, materials, and methods
 Results
 Discussion
 Authorship
 References
 
Interphase cytogenetic analysis

Since del(13) assessment was required for enrolment in the different trials, patients were primarily analyzed for 13q deletions. Among the 983 bone marrow aspirates received in the lab, 936 were assessable for del(13) (lack of plasma cells or FISH failure in 47 samples). Other probes were analyzed in the following order: t(11;14), t(4;14), hyperdiploidy, MYC, and del(17p). Because of the small number of purified plasma cells in many specimens (median percentage of plasma cells was 6%), these probes have been tested in 746, 716, 657, 571, and 532 patients, respectively (Table 1). del(13) was observed in 449 (48%) patients. The median percentage of plasma cells exhibiting del(13) was 70% (range, 20%-100%). Translocation t(11;14) occurred in 154 (21%) patients, and was associated with del(13) in 60 patients (39% of the t(11;14)-positive patients). Translocation t(4;14) was observed in 100 (14%) patients, and was frequently associated with del(13) (85% of the t(4;14)-positive patients; P < .001). In contrast, t(4;14) and t(11;14) were never associated. Hyperdiploidy was assessed in 256 (39%) patients, and 36% of those presented del(13). A lower incidence of t(11;14) and t(4;14) was also observed in patients with hyperdiploidy (2% and 4.6%, respectively). MYC translocations were observed in 74 (13%) patients. No specific association was observed with other chromosomal abnormalities in these patients with rearranged MYC. Loss of 17p was present in 58 (11%) patients, in a median of 75% of the plasma cells (range, 32%-94%). del(13) was detected in 78% of these patients (P < .001). Translocations t(4;14) and t(11;14) were seen in 11 and 6 patients with del(17p), respectively. No correlation was found with MYC rearrangements or ploidy.


View this table:
[in this window]
[in a new window]

 
Table 1. Incidence of chromosomal abnormalities in multiple myeloma

 
Correlation with outcome

In a first step, we did analyze the prognostic impact of each individual chromosomal aberration on the EFS (Table 2; Figure 1) and OS (Figure 2). When attained, the median survival is given in months from diagnosis. Conversely, if the median survival was not attained, the percentage of patients alive at the median follow-up (ie, 41 months) is given. After a median follow-up of 41 months for surviving patients, 234 of the 936 patients analyzed for chromosomal abnormalities had died. The median EFS for patients with del(13) t(4;14), and del(17p) was 29 months (versus 41 months; P < .001), 20.6 months (versus 36.5 months; P < .001), and 15 months (versus 35 months; P < .001), respectively. Regarding OS, the median was attained for t(4;14) and del(17p) (ie, 41.3 months versus 79% alive at 41 months; P < .001), and 22 months (versus 75% alive at 41 months; P < .001), respectively. For del(13), evaluation at 41 months showed a percentage of surviving patients of 68% (versus 83%; P < .001). Regarding t(11;14), hyperdiploidy, and MYC translocations, no (or marginal) impact on both EFS and OS was observed. For del(13) and del(17p), the prognostic impact was even greater if we split the patients presenting the deletions according to a cutoff of plasma cells presenting the abnormality. Serial analyses showed that the most powerful cutoffs were 74% for del(13) and 60% for del(17p). The median EFSs were 27 months (versus 39 months; P < .001) and 14.6 months (versus 34.7 months; P < .001), respectively, for patients with del(13) of 74% and greater and del(17p) of 60% and greater. Using these cutoffs, 59% of patients with del(13) of 74% and greater were alive at 41 months (versus 80%; P < .001), whereas the median OS was 22.4 months for patients with del(17p) of 60% and greater (versus 75% of patients alive if del(17p) was less than 60%; P < .001).


View this table:
[in this window]
[in a new window]

 
Table 2. Prognostic value of chromosomal abnormalities (univariate analysis)

 


Figure 1
View larger version (10K):
[in this window]
[in a new window]

 
Figure 1. Impact of genomic aberrations on EFS. (A) Kaplan-Meier plot of the impact of del(13) on EFS for the 936 patients analyzed for this abnormality. (B) Impact of t(4;14), analyzed in 716 patients. (C) Value of del(17p) on EFS of 532 patients. The gray curve is for patients presenting the genomic abnormality, whereas the black curve represents the EFS of patients lacking the chromosomal aberration.

 


Figure 2
View larger version (10K):
[in this window]
[in a new window]

 
Figure 2. Impact of genomic aberrations on OS. (A) Kaplan-Meier plot of the impact of del(13) on OS for the 936 patients analyzed for this abnormality. (B) Impact of t(4;14), analyzed in 716 patients. (C) Value of del(17p) on OS of 532 patients. The gray curve is for patients presenting the genomic abnormality, whereas the black curve represents the OS of patients lacking the chromosomal aberration.

 
Multivariate analysis

We then performed a multivariate analysis including all the chromosomal aberrations significantly associated with EFS and OS in the univariate analysis (ie, del(13) t(4;14), del(17p), and ploidy) and other parameters shown to be associated with survival in this series: ß2-microglobulin level, albumin level, hemoglobin level, and platelet count (Table 3). The analysis was performed on the 513 patients for whom all the parameters were available. Of these, 4 parameters were statistically independent predictors of EFS: t(4;14), del(17p), ß2-microglobulin, and hemoglobin levels lower than 100 g/L. A similar analysis for prediction of OS identified 3 factors: t(4;14), del(17p), and ß2-microglobulin, with the delineation of 3 groups of patients with highly divergent outcomes (Figure 3). Of note, these analyses showed that the prognostic value of del(13) was almost entirely dependent on the frequent association with t(4;14) and del(17p). In patients lacking these 2 abnormalities, del(13) is not any more significant (Figure 4). Multivariate analyses clearly identified a group of patients with an excellent prognosis (36% of the series): those lacking t(4;14) and del(17p), with a low ß2-microglobulin level (expected survival at 4 years = 83%). Conversely, patients presenting either t(4;14) or del(17) and a high ß2-microglobulin level have a median OS of only 19 months. Analyses according to treatment randomizations did not modify the results; these 3 parameters retained their independent prognostic significance after treatment-adjusted analyses. We also analyzed the impact of these 2 chromosomal abnormalities in each ISS stage to evaluate the possibility of improving survival prediction. We showed that t(4;14) and/or del(17p) separated 2 groups of patients within each ISS stage (Figures 56).


View this table:
[in this window]
[in a new window]

 
Table 3. Results of Cox regression analysis of EFS and OS time from diagnosis

 


Figure 3
View larger version (17K):
[in this window]
[in a new window]

 
Figure 3. Influence of t(4;14), del(17p), and ß2-microglobulin level on overall survival. The black curve is for the 155 patients lacking del(13), t(4;14), and del(17p), and presenting a low ß2-microglobulin level (≤ 4 mg/L). The green curve represents the same patients, but with a high ß2-microglobulin level (> 4 mg/L; 74 patients). The blue curve depicts the 110 patients lacking t(4;14) and del(17p) with a low ß2-microglobulin level, but presenting a del(13). The red curve represents the 69 patients lacking both t(4;14) and del(17p) with a high ß2-microglobulin level and with a del(13). The gray curve shows the 63 patients with either a t(4;14) or a del(17p) in more than 60% of their plasma cells, and a low ß2-microglobulin level. Finally, the pink curve shows the overall survival of the 42 patients with either a t(4;14) or a del(17p) in more than 60% of their plasma cells, and a high ß2-microglobulin level.

 


Figure 4
View larger version (10K):
[in this window]
[in a new window]

 
Figure 4. Prognostic impact of del(13) in patients lacking t(4;14) and del(17p). (A) Prognostic influence of del(13) on EFS in patients presenting neither t(4;14), nor del(17p). (B) Impact of del(13) on OS. No statistically significant difference was observed for both EFS (P = .12) and OS (P = .41). The gray lines represent patients with del(13) but lacking t(4;14) and del(17p); the black lines represent patients lacking all 3 genomic aberrations.

 


Figure 5
View larger version (14K):
[in this window]
[in a new window]

 
Figure 5. Survival according the ISS stages. (A) EFS according to the ISS stages. (B) OS (in months).

 


Figure 6
View larger version (26K):
[in this window]
[in a new window]

 
Figure 6. Kaplan-Meier estimates of survival according to the ISS stages and t(4;14) and/or del(17p). (A) EFS among patients in the various ISS stages according to the presence or not of t(4;14) and/or del(17p). (B) OS (in months). Gray lines indicate patients presenting t(4;14) or del(17p); black lines, those lacking the aberrations.

 

    Discussion
 Top
 Abstract
 Introduction
 Patients, materials, and methods
 Results
 Discussion
 Authorship
 References
 
We found that even when focusing on a few number of recurrent chromosomal abnormalities, interphase FISH was able to detect genomic changes in almost 90% of the patients with myeloma at diagnosis, about 3 times more frequently than conventional chromosomal banding. This striking difference is most likely due to the low number of plasma cells within the bone marrow specimens sent for laboratory purposes. In this series, the median percentage of plasma cells after mononuclear cell separation was only 6%. In addition, the usually low proliferative activity of malignant plasma cells, and the fact that some of the chromosomal changes are cytogenetically silent at karyotype (like t(4;14)), explain the low informativity of cytogenetics in myeloma. However, the low plasma cell infiltrate present in the samples requires identification of the plasma cells beforehand to perform interphase FISH. Despite these pitfalls, this study showed that genomic information might be obtained in at least 95% of patients with myeloma, even in a multicenter setting.

This study is so far the largest series of patients with newly diagnosed myeloma, analyzed for genomic aberrations, enabling the description of definitive incidences of the most frequent chromosomal abnormalities. The del(13) is the most frequent abnormality (48%), followed by hyperdiploidy (39%), t(11;14) (21%), t(4;14) (14%), MYC translocations (13%), and del(17p) (11%). Moreover, all the patients have been treated with a homogeneous intensive strategy (double transplantation in all cases), which allows for highly valuable prognostic analyses. According to previously reported studies,911 del(13) was predictive for both EFS and OS with highly significant P values. However, del(13) was not found to be an independent prognostic factor in the multivariate analysis. Actually, most of the prognostic power of del(13) was related to t(4;14) and del(17p), which are frequently associated with del(13). In patients lacking t(4;14) and del(17p), del(13) was no longer prognostic, whatever the cutoff chosen for its definition (Figure 4).

The analysis of t(4;14) and del(17p) was much more powerful in the prediction of both EFS and OS. Translocation t(4;14) was associated with a median EFS of 20.6 months and a median OS of 41.3 months, which are both highly significantly shorter than those for patients lacking the translocation, in agreement with other smaller series.12,1924 However, despite its high impact on survival (shown by the multivariate analysis), t(4;14) has to be evaluated in the context of other parameters, and especially ß2-microglobulin level. As shown in Figure 3, patients with t(4;14) and a low ß2-microglobulin level displayed an outcome close to that of patients lacking the translocation but with a high ß2-microglobulin level. Similar conclusions can be drawn for del(17p).12,13,25 Patients presenting the deletion in more than 60% of their plasma cells had a short EFS (14.6 months) and OS (22.4 months), but patients with a low ß2-microglobulin level may expect a longer survival (Figure 3). The biological substratum of this major clinical impact is so far unknown for both abnormalities. Translocation t(4;14) is known to deregulate 2 genes, FGFR3 and MMSET.26,27 However, since FGFR3 is not expressed in about one-third of patients with t(4;14),20,21 the target gene is most likely MMSET, whose functions are currently not known. Similarly, the target gene(s) of del(17p) is (are) so far not identified. Even though several authors focused on the P53 gene, formal demonstrations of its deregulation are currently lacking.12,13,25

Other genomic changes have a lower impact on disease evolution. Translocation t(11;14) did not act upon survival, as suggested by some recent studies.28,29 The role of the consequently up-regulated CCND1 gene is not understood so far. Translocations involving MYC did not modify the course of the disease. However, as shown by gene profiling experiments,30 MYC is activated in a large number of patients with myeloma by mechanisms other than translocations, which may have hidden the prognostic impact of these rearrangements. Hyperdiploidy was marginally prognostic in this series. Previous series suggesting a favorable impact of hyperdiploidy on outcome were based on cytogenetics,5,31,32 and thus restricted to patients with an informative karyotype, and were mostly retrospective series including nonhomogeneously treated patients. Evaluation of ploidy by FISH was not dependent upon proliferation and may explore different groups of patients. Furthermore, the assessment of hyperdiploidy using FISH probably underestimates its frequency, and may slightly modify its specific prognostic impact. Nevertheless, because of the marginal impact of hyperdiploidy on survival, this pitfall probably did not introduce a major bias in the analysis. Regarding other potentially prognostic chromosomal aberrations not analyzed in this study, a specific comment is required for t(14;16)(q32;q23),33,34 which has been described as a poor prognosis factor. Because of the scarcity of available plasma cells, we chose to focus our analysis on the most frequent genomic changes, and did not analyze t(14;16), present in less than 5% of the patients.8 Because this translocation is associated with a poor prognosis,12 and is almost constantly associated with del(13), it is highly probable that it would have even "lightened" the prognostic impact of del(13). Finally, we showed that this prognostic model was independent of the treatment, at least in this series of young patients treated with tandem intensification. In particular, the poor prognosis associated with a high ß2-microglobulin level, t(4;14), and del(17p) seemed not to be modified by the administration of thalidomide as maintenance therapy. However, because the IFM99-02 trial was dedicated to patients with 0 or 1 poor prognosis factors, these abnormalities were underrepresented in this trial. The analysis could only be performed for del(13), showing that these patients did not benefit from thalidomide maintenance.14 We then analyzed the role of cytogenetic abnormalities according to the ISS. In this classification, only a few patients were analyzed for cytogenetics and/or FISH. We show here that the genetic parameters highly improved the survival prediction power in each ISS stage (Figure 6).

In conclusion, we show that genomic aberrations, evaluated by interphase FISH, play a major role in the evolution of patients with myeloma, extending previous conclusions focused on this topic.3537 Analysis at diagnosis enables the identification of 3 groups in this large series of patients homogeneously treated by double transplantations: patients who highly benefit from high-dose therapy (patients lacking t(4;14) and del(17p), and who have low ß2-microglobulin levels), patients who have a short survival with this type of treatment (patients with either t(4;14) or del(17p), and high ß2-microglobulin levels), and an intermediate group. These analyses may have implications for the risk-adapted management of patients with myeloma, at least for the youngest ones. Whether these prognostic parameters are still valid in older patients, or in patients treated with other therapeutic strategies, remain open questions currently under evaluation in other IFM trials.


    Authorship
 Top
 Abstract
 Introduction
 Patients, materials, and methods
 Results
 Discussion
 Authorship
 References
 
Contribution: H.A.-L. designed and performed the research and wrote the paper; M.A., P.M., and F.G. designed the research and coordinated one of the clinical trials; C.C. performed the statistical analysis; and all other coauthors are members of the IFM board, and participated in the design of the research and in the patients' management.

Conflict-of-interest disclosure: The authors declare no competing financial interests.

A complete list of the members of the IFM appears as Document S1 (available on the Blood website; see the Supplemental Materials link at the top of the online article).

Correspondence: Hervé Avet-Loiseau, Laboratoire d'Hématologie, Institut de Biologie, 9 quai Moncousu, 44093 Nantes, France; e-mail: herve.avetloiseau{at}chu-nantes.fr.


    Acknowledgments
 
We are indebted to Mrs Marine Aliaga, Nadège Gouy, Marie-Christine Boursier, and Karine Pennarun for excellent technical expertise.

This work was supported in part by grants from the Association pour la Recherche sur le Cancer, from the Ligue contre le Cancer (Equipe Labélisée), and from the French Ministry of Health (PHRC 2002).


    Footnotes
 
Submitted August 15, 2006; accepted September 21, 2006.

Prepublished online as Blood First Edition Paper, January 5, 2007 DOI: 10.1182/blood-2006-08-040410

The online version of this article contains a data supplement.

An Inside Blood analysis of this article appears at the front of this issue.

The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked "advertisement" in accordance with 18 USC section 1734.


    References
 Top
 Abstract
 Introduction
 Patients, materials, and methods
 Results
 Discussion
 Authorship
 References
 

  1. Kyle RA and Rajkumar SV. Plasma cell disorders. In Goldman L and Ausiello DA (Eds.). Cecil Textbook of Medicine2004; 22nd ed Philadelphia, PA W.B. Saunders pp. 1184–1195.

  2. Greipp PR, San Miguel J, Durie BG, et al. International staging system for multiple myeloma. J Clin Oncol 2005; 23:3412–3420.[Abstract/Free Full Text]

  3. Dewald GW, Kyle RA, Hicks GA, Greipp PR. The clinical significance of cytogenetic studies in 100 patients with multiple myeloma, plasma cell leukemia, or amyloidosis. Blood 1985; 66:380–390.[Abstract/Free Full Text]

  4. Sawyer JR, Waldron JA, Jagannath S, Barlogie B. Cytogenetic finding in 200 patients with multiple myeloma. Cancer Genet Cytogenet 1995; 82:41–49.[CrossRef][Medline] [Order article via Infotrieve]

  5. Smadja NV, Bastard C, Brigaudeau C, Leroux D, Fruchart C. Hypodiploidy is a major prognostic factor in multiple myeloma. Blood 2001; 98:2229–2238.[Abstract/Free Full Text]

  6. Barlogie B, Alexanian R, Dixon D, Smith L, Smallwood L, Delasalle K. Prognostic implications of tumor cell DNA and RNA content in multiple myeloma. Blood 1985; 66:338–341.[Abstract/Free Full Text]

  7. Drach J, Schuster J, Nowotny H, et al. Multiple myeloma: high incidence of chromosomal aneuploidy as detected by interphase fluorescence in situ hybridization. Cancer Res 1995; 55:3854–3859.[Abstract/Free Full Text]

  8. Avet-Loiseau H, Facon T, Grosbois B, et al. Oncogenesis of multiple myeloma: 14q32 and 13q chromosomal abnormalities are not randomly distributed, but correlate with natural history, immunological features and clinical presentation. Blood 2002; 99:2185–2191.[Abstract/Free Full Text]

  9. Zojer N, Königsberg R, Ackermann J, et al. Deletion of 13q14 remains an independent adverse prognostic variable in multiple myeloma despite its frequent detection by interphase fluorescence in situ hybridization. Blood 2000; 95:1925–1930.[Abstract/Free Full Text]

  10. Facon T, Avet-Loiseau H, Guillerm G, et al. Chromosome 13 abnormalities identified by FISH analysis and serum ß2-microglobulin produce a very powerful myeloma staging system for patients receiving high dose therapy. Blood 2001; 97:1566–1571.[Abstract/Free Full Text]

  11. Fonseca R, Harrington D, Oken MM, et al. Biological and prognostic significance of interphase fluorescence in situ hybridization detection of chromosome 13 abnormalities ({Delta}13) in multiple myeloma: an Eastern Cooperative Oncology Group study. Cancer Res 2002; 62:715–720.[Abstract/Free Full Text]

  12. Fonseca R, Blood E, Rue M, et al. Clinical and biologic implications of recurrent genomic aberrations in myeloma. Blood 2003; 101:4569–4575.[Abstract/Free Full Text]

  13. Chang H, Qi C, Yi QL, Reece D, Stewart AK. p53 gene deletion detected by fluorescence in situ hybridization is an adverse prognostic factor for patients with multiple myeloma following autologous stem cell transplantation. Blood 2005; 105:358–360.[Abstract/Free Full Text]

  14. Attal M, Harousseau JL, Leyvraz S, et al. Maintenance treatment with thalidomide after autologous transplantation for myeloma : final analysis of a prospective randomized study of the IFM. Blood 2006; Epub ahead of print.

  15. Garban F, Attal M, Michallet M, et al. Prospective comparison of autologous stem cell transplantation followed by a dose-reduced allograft (IFM99–03 trial) with tandem autologous stem cell transplantation (IFM99–04 trial) in high-risk de novo multiple myeloma. Blood 2006; 107:3474–3480.[Abstract/Free Full Text]

  16. Moreau P, Hulin C, Garban F, et al. Tandem autologous stem cell transplantation in high-risk de novo multiple myeloma: final results of the prospective and randomized IFM 99-04 protocol. Blood 2006; 107:397–403.[Abstract/Free Full Text]

  17. Wuilleme S, Robillard N, Lodé L, et al. Ploidy, as detected by fluorescence in situ hybridization, defines different subgroups in multiple myeloma. Leukemia 2005; 19:275–278.[CrossRef][Medline] [Order article via Infotrieve]

  18. Avet-Loiseau H, Gerson F, Magrangeas F, et al. Rearrangements of the c-myc oncogene are observed in 15% of primary human multiple myeloma tumors. Blood 2001; 98:3082–3086.[Abstract/Free Full Text]

  19. Moreau P, Facon T, Leleu X, et al. Recurrent 14q32 translocations determine the prognosis of multiple myeloma, especially in patients receiving intensive chemotherapy. Blood 2002; 100:1579–1583.[Abstract/Free Full Text]

  20. Keats JJ, Reiman T, Maxwell CA, et al. In multiple myeloma, t(4;14)(p16;q32) is an adverse prognostic factor irrespective of FGFR3 expression. Blood 2003; 101:1520–1529.[Abstract/Free Full Text]

  21. Santra M, Zhan F, Tian E, Barlogie B, Shaughnessy J. A subset of multiple myeloma harboring the t(4;14)(p16;q32) translocation lacks FGFR3 expression but maintains an IGH/MMSET fusion transcript. Blood 2003; 101:2374–2376.[Abstract/Free Full Text]

  22. Fonseca R, Debes-Marun CS, Picken EB, et al. The recurrent IgH translocations are highly associated with nonhyperdiploid variant multiple myeloma. Blood 2003; 102:2562–2567.[Abstract/Free Full Text]

  23. Chang H, Sloan S, Li D, et al. The t(4;14) is associated with poor prognosis in myeloma patients undergoing autologous stem cell transplant. Br J Haematol 2004; 125:64–68.[CrossRef][Medline] [Order article via Infotrieve]

  24. Jaksic W, Trudel S, Chang H, et al. Clinical outcomes in t(4;14) multiple myeloma: a chemotherapy-sensitive disease characterized by rapid relapse and alkylating agent resistance. J Clin Oncol 2005; 23:7069–7073.[Abstract/Free Full Text]

  25. Drach J, Ackermann J, Fritz E, et al. Presence of a p53 gene deletion in patients with multiple myeloma predicts for short survival after conventional-dose chemotherapy. Blood 1998; 92:802–809.[Abstract/Free Full Text]

  26. Chesi M, Nardini E, Brents LA, et al. Frequent translocation t(4;14)(p16.3; q32.3) in multiple myeloma is associated with increased expression and activating mutations of fibroblast growth factor receptor 3. Nat Genet 1997; 16:260–264.[CrossRef][Medline] [Order article via Infotrieve]

  27. Chesi M, Nardini E, Lim RS, et al. The t(4;14) translocation in myeloma dysregulates both FGFR3 and a novel gene, MMSET, resulting in IgH/MMSET hybrid transcripts. Blood 1998; 92:3025–3034.[Abstract/Free Full Text]

  28. Fonseca R, Blood EA, Oken MM, et al. Myeloma and the t(11;14)(q13;q32): evidence for a biologically defined unique subset of patients. Blood 2002; 99:3735–3741.[Abstract/Free Full Text]

  29. Stewart AK and Fonseca R. Prognostic and therapeutic significance of myeloma genetics and gene expression profiling. J Clin Oncol 2005; 23:6339–6344.[Abstract/Free Full Text]

  30. Zhan F, Hardin J, Kordsmeier B, et al. Global gene expression profiling of multiple myeloma, monoclonal gammopathy of undetermined significance, and normal bone marrow plasma cells. Blood 2002; 99:1745–1757.[Abstract/Free Full Text]

  31. Fassas ABT, Spencer T, Sawyer J, et al. Both hypodiploidy and deletion of chromosome 13 independently confer poor prognosis in multiple myeloma. Br J Haematol 2002; 118:1041–1047.[CrossRef][Medline] [Order article via Infotrieve]

  32. Debes-Marun CS, Dewald GW, Bryant S, et al. Chromosome abnormalities clustering and its implications for pathogenesis and prognosis in myeloma. Leukemia 2003; 17:427–436.[CrossRef][Medline] [Order article via Infotrieve]

  33. Chesi M, Bergsagel PL, Shonukan OO, et al. Frequent dysregulation of the c-maf proto-oncogene at 16q23 by translocation to an Ig locus in multiple myeloma. Blood 1998; 91:4457–4463.[Abstract/Free Full Text]

  34. Hurt EM, Wiestner A, Rosenwald A, et al. Overexpression of c-maf is a frequent oncogenic event in multiple myeloma that promotes proliferation and pathological interactions with bone marrow stroma. Cancer Cell 2004; 5:191–199.[CrossRef][Medline] [Order article via Infotrieve]

  35. Mitsiades CS, Mitsiades N, Munshi NC, Anderson KC. Focus on multiple myeloma. Cancer Cell 2004; 6:439–444.[CrossRef][Medline] [Order article via Infotrieve]

  36. Hideshima T, Bergsagel PL, Kuehl WM, Anderson K. Advances in biology of multiple myeloma: clinical applications. Blood 2004; 104:607–618.[Abstract/Free Full Text]

  37. Bergsagel PL and Kuehl WM. Molecular pathogenesis and a consequent classification of multiple myeloma. J Clin Oncol 2005; 23:6333–6338.[Abstract/Free Full Text]


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?

Related Article in Blood Online:

Multiple myeloma and FISH (but no CHIPS)
Rafael Fonseca
Blood 2007 109: 3132-3133. [Full Text] [PDF]



This article has been cited by other articles:


Home page
BloodHome page
J.-L. Harousseau, M. Attal, and H. Avet-Loiseau
The role of complete response in multiple myeloma
Blood, October 8, 2009; 114(15): 3139 - 3146.
[Abstract] [Full Text] [PDF]


Home page
JCOHome page
H. Avet-Loiseau, C. Li, F. Magrangeas, W. Gouraud, C. Charbonnel, J.-L. Harousseau, M. Attal, G. Marit, C. Mathiot, T. Facon, et al.
Prognostic Significance of Copy-Number Alterations in Multiple Myeloma
J. Clin. Oncol., September 20, 2009; 27(27): 4585 - 4590.
[Abstract] [Full Text] [PDF]


Home page
NEJMHome page
V. J. Louw, H. Louw, M. J. Webb, J.-L. Harousseau, and P. Moreau
Autologous Stem-Cell Transplantation for Multiple Myeloma
N. Engl. J. Med., September 10, 2009; 361(11): 1118 - 1119.
[Full Text] [PDF]


Home page
BloodHome page
D. Reece, K. W. Song, T. Fu, B. Roland, H. Chang, D. E. Horsman, A. Mansoor, C. Chen, E. Masih-Khan, Y. Trieu, et al.
Influence of cytogenetics in patients with relapsed or refractory multiple myeloma treated with lenalidomide plus dexamethasone: adverse effect of deletion 17p13
Blood, July 16, 2009; 114(3): 522 - 525.
[Abstract] [Full Text] [PDF]


Home page
BloodHome page
P. Kapoor, S. Kumar, R. Fonseca, M. Q. Lacy, T. E. Witzig, S. R. Hayman, A. Dispenzieri, F. Buadi, P. L. Bergsagel, M. A. Gertz, et al.
Impact of risk stratification on outcome among patients with multiple myeloma receiving initial therapy with lenalidomide and dexamethasone
Blood, July 16, 2009; 114(3): 518 - 521.
[Abstract] [Full Text] [PDF]


Home page
BloodHome page
D. Hose, J. Moreaux, T. Meissner, A. Seckinger, H. Goldschmidt, A. Benner, K. Mahtouk, J. Hillengass, T. Reme, J. De Vos, et al.
Induction of angiogenesis by normal and malignant plasma cells
Blood, July 2, 2009; 114(1): 128 - 143.
[Abstract] [Full Text] [PDF]


Home page
haematolHome page
L. Chiecchio, G. P. Dagrada, R. K.M. Protheroe, D. M. Stockley, A. G. Smith, K. H. Orchard, N. C.P. Cross, C. J. Harrison, F. M. Ross, and on behalf of the UK Myeloma Forum
Loss of 1p and rearrangement of MYC are associated with progression of smouldering myeloma to myeloma: sequential analysis of a single case
Haematologica, July 1, 2009; 94(7): 1024 - 1028.
[Abstract] [Full Text] [PDF]


Home page
NEJMHome page
J.-L. Harousseau and P. Moreau
Autologous Hematopoietic Stem-Cell Transplantation for Multiple Myeloma
N. Engl. J. Med., June 18, 2009; 360(25): 2645 - 2654.
[Full Text] [PDF]


Home page
BloodHome page
A. C. Sprynski, D. Hose, L. Caillot, T. Reme, J. D. Shaughnessy Jr, B. Barlogie, A. Seckinger, J. Moreaux, M. Hundemer, M. Jourdan, et al.
The role of IGF-1 as a major growth factor for myeloma cell lines and the prognostic relevance of the expression of its receptor
Blood, May 7, 2009; 113(19): 4614 - 4626.
[Abstract] [Full Text] [PDF]


Home page
BloodHome page
A. K. Stewart
Reduced-intensity allogeneic transplantation for myeloma: reality bites
Blood, April 2, 2009; 113(14): 3135 - 3136.
[Full Text] [PDF]


Home page
BloodHome page
B. Bruno, M. Rotta, F. Patriarca, D. Mattei, B. Allione, F. Carnevale-Schianca, R. Sorasio, A. Rambaldi, M. Casini, M. Parma, et al.
Nonmyeloablative allografting for newly diagnosed multiple myeloma: the experience of the Gruppo Italiano Trapianti di Midollo
Blood, April 2, 2009; 113(14): 3375 - 3382.
[Abstract] [Full Text] [PDF]


Home page
haematolHome page
A. H. Bryce, R. P. Ketterling, M. A. Gertz, M. Lacy, R. A. Knudson, S. Zeldenrust, S. Kumar, S. Hayman, F. Buadi, R. A. Kyle, et al.
Translocation t(11;14) and survival of patients with light chain (AL) amyloidosis
Haematologica, March 1, 2009; 94(3): 380 - 386.
[Abstract] [Full Text] [PDF]


Home page
The Annals of PharmacotherapyHome page
A. A Saad, M. Sharma, and G. M Higa
Treatment of Multiple Myeloma in the Targeted Therapy Era
Ann. Pharmacother., February 1, 2009; 43(2): 329 - 338.
[Abstract] [Full Text] [PDF]


Home page
haematolHome page
G. Desplanques, N. Giuliani, R. Delsignore, V. Rizzoli, R. Bataille, and S. Barille-Nion
Impact of XIAP protein levels on the survival of myeloma cells
Haematologica, January 1, 2009; 94(1): 87 - 93.
[Abstract] [Full Text] [PDF]


Home page
Am Soc Clin Oncol Ed BookHome page
D. Reece, J.-L. Harousseau, and M. A. Gertz
Nontransplant Therapy of Myeloma, High-dose Therapy for Myeloma, and a Personalized Care Plan for Treatment of Myeloma
ASCO Educational Book, January 1, 2009; 2009(1): 502 - 509.
[Abstract] [Full Text] [PDF]


Home page
BloodHome page
A. Dispenzieri
Biology, treatment, and time
Blood, October 15, 2008; 112(8): 2999 - 3000.
[Full Text] [PDF]


Home page
JCOHome page
O. Decaux, L. Lode, F. Magrangeas, C. Charbonnel, W. Gouraud, P. Jezequel, M. Attal, J.-L. Harousseau, P. Moreau, R. Bataille, et al.
Prediction of Survival in Multiple Myeloma Based on Gene Expression Profiles Reveals Cell Cycle and Chromosomal Instability Signatures in High-Risk Patients and Hyperdiploid Signatures in Low-Risk Patients: A Study of the Intergroupe Francophone du Myelome
J. Clin. Oncol., October 10, 2008; 26(29): 4798 - 4805.
[Abstract] [Full Text] [PDF]


Home page
J. Clin. Pathol.Home page
J Yeung and H Chang
Genomic aberrations and immunohistochemical markers as prognostic indicators in multiple myeloma
J. Clin. Pathol., July 1, 2008; 61(7): 832 - 836.
[Abstract] [Full Text] [PDF]


Home page
JCOHome page
J. San-Miguel, J.-L. Harousseau, D. Joshua, and K. C. Anderson
Individualizing Treatment of Patients With Myeloma in the Era of Novel Agents
J. Clin. Oncol., June 1, 2008; 26(16): 2761 - 2766.
[Abstract] [Full Text] [PDF]


Home page
BloodHome page
T. Bochtler, U. Hegenbart, F. W. Cremer, C. Heiss, A. Benner, D. Hose, M. Moos, J. Bila, C. R. Bartram, A. D. Ho, et al.
Evaluation of the cytogenetic aberration pattern in amyloid light chain amyloidosis as compared with monoclonal gammopathy of undetermined significance reveals common pathways of karyotypic instability
Blood, May 1, 2008; 111(9): 4700 - 4705.
[Abstract] [Full Text] [PDF]


Home page
ASH Education BookHome page
N. C. Munshi
Investigative Tools for Diagnosis and Management
Hematology, January 1, 2008; 2008(1): 298 - 305.
[Abstract] [Full Text] [PDF]


Home page
Am Soc Clin Oncol Ed BookHome page
J.-P. Fermand
Initial Therapy for Multiple Myeloma: Role of Stem Cell Transplantation
ASCO Educational Book, January 1, 2008; 2008(1): 375 - 379.
[Abstract] [Full Text] [PDF]


Home page
Am Soc Clin Oncol Ed BookHome page
A. K. Stewart
A Risk-adapted Approach to Myeloma Therapy
ASCO Educational Book, January 1, 2008; 2008(1): 380 - 384.
[Abstract] [Full Text] [PDF]


Home page
Clin. Cancer Res.Home page
K. Mahtouk, D. Hose, J. De Vos, J. Moreaux, M. Jourdan, J. F. Rossi, T. Reme, H. Goldschmidt, and B. Klein
Input of DNA Microarrays to Identify Novel Mechanisms in Multiple Myeloma Biology and Therapeutic Applications
Clin. Cancer Res., December 15, 2007; 13(24): 7289 - 7295.
[Abstract] [Full Text] [PDF]


Home page
BloodHome page
M. W. Jenner, P. E. Leone, B. A. Walker, F. M. Ross, D. C. Johnson, D. Gonzalez, L. Chiecchio, E. Dachs Cabanas, G. Paolo Dagrada, M. Nightingale, et al.
Gene mapping and expression analysis of 16q loss of heterozygosity identifies WWOX and CYLD as being important in determining clinical outcome in multiple myeloma
Blood, November 1, 2007; 110(9): 3291 - 3300.
[Abstract] [Full Text] [PDF]


Home page
BloodHome page
D. Gonzalez, M. van der Burg, R. Garcia-Sanz, J. A. Fenton, A. W. Langerak, M. Gonzalez, J. J. M. van Dongen, J. F. San Miguel, and G. J. Morgan
Immunoglobulin gene rearrangements and the pathogenesis of multiple myeloma
Blood, November 1, 2007; 110(9): 3112 - 3121.
[Abstract] [Full Text] [PDF]


Home page
JWatch Oncology and HematologyHome page
FISHing for Risk Profiles in Multiple Myeloma
Journal Watch Oncology and Hematology, May 7, 2007; 2007(507): 2 - 2.
[Full Text]


Home page
ASH Education BookHome page
R. Fonseca
Strategies for Risk-Adapted Therapy in Myeloma
Hematology, January 1, 2007; 2007(1): 304 - 310.
[Abstract] [Full Text] [PDF]


Home page
ASH Education BookHome page
M. Attal, P. Moreau, H. Avet-Loiseau, and J.-L. Harousseau
Stem Cell Transplantation in Multiple Myeloma
Hematology, January 1, 2007; 2007(1): 311 - 316.
[Abstract] [Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Supplemental Appendix
Right arrow All Versions of this Article:
blood-2006-08-040410v1
109/8/3489    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Right arrow Rights and Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via CrossRef
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Avet-Loiseau, H.
Right arrow Articles by Mathiot, C.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Avet-Loiseau, H.
Right arrow Articles by Mathiot, C.
Related Collections
Right arrow Oncogenes and Tumor Suppressors
Right arrow Clinical Trials and Observations
Right arrowRelated Article in Blood Online
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

 click for free articles
home about blood authors subscriptions permissions advertising public access contact us
  Copyright © 2007 by American Society of Hematology         Online ISSN: 1528-0020