A novel podocyte protein, R3h domain containing-like, inhibits TGF-ß-induced p38 MAPK and regulates the structure of podocytes and glomerular basement membrane.

Not only in kidney glomerular physiological function but also glomerular pathology especially in diabetic condition, glomerular podocytes play pivotal roles. Therefore, it is important to increase our knowledge about the genes and proteins expressed in podocytes. Recently, we have identified a novel podocyte-expressed gene, R3h domain containing-like (R3hdml) and analyzed its function in vivo as well as in vitro. Transforming growth factor-ß (TGF-ß) signaling regulated the expression of R3hdml. And R3hdml inhibited p38 mitogen-activated protein kinase phosphorylation, which was induced by TGF-ß, leading to the amelioration of podocyte apoptosis. Furthermore, a lack of R3hdml in mice significantly worsened glomerular function in streptozotocin (STZ)-induced diabetes, while overexpression of R3hdml ameliorated albuminuria in STZ-induced diabetes. Our results surmise that the functional analyses of R3hdml may lead to the development of novel therapeutic strategies for diabetic nephropathy in the future. KEY MESSAGES: • A novel podocyte expressed protein R3h domain containing-like was identified. • R3HDML inhibits podocyte apoptosis by inhibiting TGF-ß-mediated p38 MAPK signaling. • Overexpression of R3HDML ameliorates albuminuria in STZ-induced diabetes mice. • R3HDML may prove to be a novel therapeutic strategy for diabetic nephropathy.

Transcriptomic and Proteomic Profiling Provides Insight into Mesangial Cell Function in IgA Nephropathy.

IgA nephropathy (IgAN), the most common GN worldwide, is characterized by circulating galactose-deficient IgA (gd-IgA) that forms immune complexes. The immune complexes are deposited in the glomerular mesangium, leading to inflammation and loss of renal function, but the complete pathophysiology of the disease is not understood. Using an integrated global transcriptomic and proteomic profiling approach, we investigated the role of the mesangium in the onset and progression of IgAN. Global gene expression was investigated by microarray analysis of the glomerular compartment of renal biopsy specimens from patients with IgAN (n=19) and controls (n=22). Using curated glomerular cell type-specific genes from the published literature, we found differential expression of a much higher percentage of mesangial cell-positive standard genes than podocyte-positive standard genes in IgAN. Principal coordinate analysis of expression data revealed clear separation of patient and control samples on the basis of mesangial but not podocyte cell-positive standard genes. Additionally, patient clinical parameters (serum creatinine values and eGFRs) significantly correlated with Z scores derived from the expression profile of mesangial cell-positive standard genes. Among patients grouped according to Oxford MEST score, patients with segmental glomerulosclerosis had a significantly higher mesangial cell-positive standard gene Z score than patients without segmental glomerulosclerosis. By investigating mesangial cell proteomics and glomerular transcriptomics, we identified 22 common pathways induced in mesangial cells by gd-IgA, most of which mediate inflammation. The genes, proteins, and corresponding pathways identified provide novel insights into the pathophysiologic mechanisms leading to IgAN.

Modeling mesothelioma utilizing human mesothelial cells reveals involvement of phospholipase-C beta 4 in YAP-active mesothelioma cell proliferation.

Mesotheliomas are frequently characterized by disruption of Hippo pathway due to deletion and/or mutation in genes, such as neurofibromin 2 ( NF2 ). Hippo disruption attenuates yes-associated protein (YAP) phosphorylation allowing YAP to translocate to the nucleus and regulate gene expression. The role of disrupted Hippo pathway in maintenance of established mesotheliomas has been extensively investigated using cell lines; however, its involvement in development of human mesothelioma has not been explored much. Here, we employed immortalized human mesothelial cells to disrupt Hippo pathway. YAP phosphorylation was reduced on NF2 knockdown and the cells exhibited altered growth in vitro , developing tumors when transplanted into nude mice. Similar results were obtained from enforced expression of wild-type or constitutively active (S127A) YAP, indicating the crucial role of activated YAP in the transformation of mesothelial cells. Gene expression analysis comparing control- and YAP-transduced immortalized human mesothelial cells revealed phospholipase-C beta 4 ( PLCB4 ) to be among the genes highly upregulated by YAP. PLCB4 was upregulated by YAP in immortalized human mesothelial cells and downregulated on YAP knockdown in Hippo-disrupted mesothelioma cell lines. PLCB4 knockdown attenuated the growth of YAP-transduced immortalized mesothelial cells and YAP-active, but not YAP-nonactive, mesothelioma cell lines. Our model system thus provides a versatile tool to investigate the mechanisms underlying mesothelioma development. We suggest that PLCB4 may be an attractive drug target for the treatment of mesothelioma.

STX11 functions as a novel tumor suppressor gene in peripheral T-cell lymphomas.

Peripheral T-cell lymphomas (PTCL) are a heterogeneous group of non-Hodgkin lymphomas with poor prognosis. Their molecular pathogenesis has not been entirely elucidated. We previously showed that 6q24 is one of the most frequently deleted regions in primary thyroid T-cell lymphoma. In this study, we extended the analysis to other subtypes of PTCL and performed functional assays to identify the causative genes of PTCL that are located on 6q24. Genomic loss of 6q24 was observed in 14 of 232 (6%) PTCL cases. The genomic loss regions identified at 6q24 always involved only two known genes, STX11 and UTRN. The expression of STX11, but not UTRN, was substantially lower in PTCL than in normal T-cells. STX11 sequence analysis revealed mutations in two cases (one clinical sample and one T-cell line). We further analyzed the function of STX11 in 14 cell lines belonging to different lineages. STX11 expression only suppressed the proliferation of T-cell lines bearing genomic alterations at the STX11 locus. Interestingly, expression of a novel STX11 mutant (p.Arg78Cys) did not exert suppressive effects on the induced cell lines, suggesting that this mutant is a loss-of-function mutation. In addition, STX11-altered PTCL not otherwise specified cases were characterized by the presence of hemophagocytic syndrome (67% vs 8%, P = 0.04). They also tended to have a poor prognosis compared with those without STX11 alteration. These results suggest that STX11 plays an important role in the pathogenesis of PTCL and they may contribute to the future development of new drugs for the treatment of PTCL.

Molecular characterization of chronic-type adult T-cell leukemia/lymphoma.

Adult T-cell leukemia/lymphoma (ATL) is a human T-cell leukemia virus type-1-induced neoplasm with four clinical subtypes: acute, lymphoma, chronic, and smoldering. Although the chronic type is regarded as indolent ATL, about half of the cases progress to acute-type ATL. The molecular pathogenesis of acute transformation in chronic-type ATL is only partially understood. In an effort to determine the molecular pathogeneses of ATL, and especially the molecular mechanism of acute transformation, oligo-array comparative genomic hybridization and comprehensive gene expression profiling were applied to 27 and 35 cases of chronic and acute type ATL, respectively. The genomic profile of the chronic type was nearly identical to that of acute-type ATL, although more genomic alterations characteristic of acute-type ATL were observed. Among the genomic alterations frequently observed in acute-type ATL, the loss of CDKN2A, which is involved in cell-cycle deregulation, was especially characteristic of acute-type ATL compared with chronic-type ATL. Furthermore, we found that genomic alteration of CD58, which is implicated in escape from the immunosurveillance mechanism, is more frequently observed in acute-type ATL than in the chronic-type. Interestingly, the chronic-type cases with cell-cycle deregulation and disruption of immunosurveillance mechanism were associated with earlier progression to acute-type ATL. These findings suggested that cell-cycle deregulation and the immune escape mechanism play important roles in acute transformation of the chronic type and indicated that these alterations are good predictive markers for chronic-type ATL.

Clonal heterogeneity of lymphoid malignancies correlates with poor prognosis.

Clonal heterogeneity in lymphoid malignancies has been recently reported in adult T-cell lymphoma/leukemia, peripheral T-cell lymphoma, not otherwise specified, and mantle cell lymphoma. Our analysis was extended to other types of lymphoma including marginal zone lymphoma, follicular lymphoma and diffuse large B-cell lymphoma. To determine the presence of clonal heterogeneity, 332 cases were examined using array comparative genomic hybridization analysis. Results showed that incidence of clonal heterogeneity varied from 25% to 69% among different types of lymphoma. Survival analysis revealed that mantle cell lymphoma and diffuse large B-cell lymphoma with clonal heterogeneity showed significantly poorer prognosis, and that clonal heterogeneity was confirmed as an independent predictor of poor prognosis for both types of lymphoma. Interestingly, 8q24.1 (MYC) gain, 9p21.3 (CDKN2A/2B) loss and 17p13 (TP53, ATP1B2, SAT2, SHBG) loss were recurrent genomic lesions among various types of lymphoma with clonal heterogeneity, suggesting at least in part that alterations of these genes may play a role in clonal heterogeneity.

SegAnnDB: interactive Web-based genomic segmentation.

MOTIVATION: DNA copy number profiles characterize regions of chromosome gains, losses and breakpoints in tumor genomes. Although many models have been proposed to detect these alterations, it is not clear which model is appropriate before visual inspection the signal, noise and models for a particular profile. RESULTS: We propose SegAnnDB, a Web-based computer vision system for genomic segmentation: first, visually inspect the profiles and manually annotate altered regions, then SegAnnDB determines the precise alteration locations using a mathematical model of the data and annotations. SegAnnDB facilitates collaboration between biologists and bioinformaticians, and uses the University of California, Santa Cruz genome browser to visualize copy number alterations alongside known genes. AVAILABILITY AND IMPLEMENTATION: The breakpoints project on INRIA GForge hosts the source code, an Amazon Machine Image can be launched and a demonstration Web site is http://bioviz.rocq.inria.fr.

Clonal heterogeneity of mantle cell lymphoma revealed by array comparative genomic hybridization.

Mantle cell lymphoma (MCL) is an aggressive B-cell non-Hodgkin lymphoma (NHL) characterized by the translocation t(11;14)(q13;q32). This lymphoma exhibits a poor prognosis and remains incurable with standard chemotherapy approaches. Recently, we have shown that a majority of patients with acute-type adult T-cell leukemia/lymphoma (ATLL) have multiple subclones that were likely produced in lymph nodes. We investigated whether MCL has multiple subclones as identified in ATLL by high-resolution oligo-array comparative genomic hybridization (CGH). Eleven of 20 (55%) evaluable MCL cases had a log2 ratio imbalance, suggesting the existence of multiple subclones in MCL. Based on the proportion of every subclone relative to the main clone, we were able to speculate clonal evolution in each MCL case with multiple subclones. Our analysis gave new insights into the clonal heterogeneity quantitatively and accurately. Furthermore, genomic copy number alterations are not hierarchical events and not necessarily the initial or later events for cells to become MCL.

The potential of copy number gains and losses, detected by array-based comparative genomic hybridization, for computational differential diagnosis of B-cell lymphomas and genetic regions involved in lymphomagenesis.

BACKGROUND: The differentiation of biologically and clinically different malignant lymphoma diseases or subtypes is crucial because it leads to better prognostication and therapeutic decision-making. Attempts have been made at subtype classification for diagnosing lymphomas on the basis of gene-expression profiling. Although array-based comparative genomic hybridization (array CGH) has identified a characteristic genomic alteration pattern for each disease entity, it has not been clear whether each patient with certain genomic alterations can be classified by array CGH data. DESIGN AND METHODS: Data on copy number gains and losses for 46 diffuse large B-cell lymphomas and 29 mantle cell lymphomas were used. The gene expressions of the diffuse large B-cell lymphomas cases were profiled and hierarchical clustering revealed that 28 of them were of the activated B-cell type and 18 were of the germinal center-B-cell type. Using these data, we developed a computer algorithm to classify lymphoma diseases or subtypes on the basis of copy number gains and losses. RESULTS: The method correctly classified 88% of the diffuse large B-cell lymphomas and mantle cell lymphomas, and 83% of the activated B-cell and germinal center-B-cell subtypes. These results demonstrate that copy number gains and losses detected by array CGH can be used for classifying lymphomas into biologically and clinically distinct diseases or subtypes. CONCLUSIONS: Our computer algorithm based on array CGH data successfully classified diffuse large B-cell lymphomas and mantle cell lymphomas and activated B-cell and germinal center-B-cell subtypes with high accuracy. An important finding is that the regions automatically identified by the computer algorithm were located in the critical regions that are likely to be involved in the development of lymphoma.

Gene expression profiling of diffuse large B-cell lymphoma supervised by CD21 expression.

This study investigated the gene expression profiles of 40 cases of diffuse large B-cell lymphoma (DLBCL) according to CD21 expression, a favourable prognostic factor in DLBCL. Signature genes were analysed by Gene Ontology Tree Machine, and genes concerned with the immune system and related categories were significantly upregulated in CD21- DLBCLs. Of 40 DLBCLs, four were germinal centre B cell-like (GCB) and 36 non-GCB. Of the 36 non-GCB DLBCLs, 14 CD21+ DLBCLs showed significantly better overall survival than the 22 CD21- DLBCLs (P = 0.036). Hierarchical cluster analysis of signature genes related to CD21 was applied to previously published data sets, resulting in two groups for each data set, CD21+ type DLBCLs and CD21- type DLBCLs. Survival of CD21+ type DLBCLs was significantly better than that of CD21- type (P = 0.006 and P = 0.004, respectively). In both data sets, CD21+ type DLBCLs predominantly included GCB DLBCLs compared with CD21- type. The top classifier gene of CD21 expression was IGHM, and the five of nine Gene Ontology categories significant in CD21- DLBCLs included IGHM. Immunohistochemical analysis of 216 DLBCLs confirmed that overall survival of surface (s) IgM+ DLBCLs was significantly poorer than that of sIgM- DLBCLs (P = 0.013).

Expression profiling analysis of the CD5+ diffuse large B-cell lymphoma subgroup: development of a CD5 signature.

Diffuse large B-cell lymphoma (DLBCL) accounts for 30% of non-Hodgkin's lymphomas and is known to comprise heterogeneous groups. We previously reported that CD5+ DLBCL is a clinically distinct subgroup of these tumors that is associated with poor prognosis. In our current study, we have used gene expression profiling technology in an attempt to identify new markers and to further characterize the biological features of CD5+ DLBCL. Candidate genes, which showed the greatest difference in expression between 22 CD5+ and 26 CD5- DLBCL cases, were selected from our screening and subjected to clustering analysis. This resulted in identification of a specific mRNA profile (a CD5 signature) for CD5+ DLBCL. The CD5 signature included downregulated extracellular matrix genes such as POSTN, SPARC, COL1A1, COL3A1, CTSK, MMP9 and LAMB3, and comprised upregulated genes including TRPM4. We tested this CD5 signature for its potential use as a relevant marker for CD5+ DLBCL and found that it did indeed recognize this subgroup. The tumors identified by the CD5 signature contained most of the CD5+ DLBCL cases and some CD5- DLBCL cases. Moreover, the subgroup of cases with this CD5 signature showed a poorer prognosis. The subsequent application of the CD5 signature to the analysis of an independent series of DLBCL microarray data resulted in identification of a subgroup of DLBCL cases with a similar clinical outcome, further suggesting that the CD5 signature can be used as a clinically relevant marker of this disease.

Comparison of genome profiles for identification of distinct subgroups of diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) comprises molecularly distinct subgroups such as activated B-cell-like (ABC) and germinal center B-cell-like (GCB) DLBCLs. We previously reported that CD5(+) and CD5(-)CD10(+) DLBCL constitute clinically relevant subgroups. To determine whether these 2 subgroups are related to ABC and GCB DLBCLs, we analyzed the genomic imbalance of 99 cases (36 CD5(+), 19 CD5(-)CD10(+), and 44 CD5(-)CD10(-)) using array-based comparative genomic hybridization (CGH). Forty-six of these cases (22 CD5(+), 7 CD5(-)CD10(+), and 17 CD5(-)CD10(-)) were subsequently subjected to gene-expression profiling, resulting in their division into 28 ABC (19 CD5(+) and 9 CD5(-)CD10(-)) and 18 GCB (3 CD5(+), 7 CD5(-)CD10(+), and 8 CD5(-)CD10(-)) types. A comparison of genome profiles of distinct subgroups of DLBCL demonstrated that (1) ABC DLBCL is characterized by gain of 3q, 18q, and 19q and loss of 6q and 9p21, and GCB DLBCL is characterized by gain of 1q, 2p, 7q, and 12q; (2) the genomic imbalances characteristic of the CD5(+) and CD5(-)CD10(+) groups were similar to those of the ABC and GCB types, respectively. These findings suggest that CD5(+) and CD5(-)CD10(+) subgroups are included, respectively, in the ABC and GCB types. Finally, when searching for genomic imbalances that affect patients' prognosis, we found that 9p21 loss (p16(INK4a) locus) marks the most aggressive type of DLBCL.

Contig array CGH at 3p14.2 points to the FRA3B/FHIT common fragile region as the target gene in diffuse large B-cell lymphoma.

Deletions of the 3p arm have been detected in various solid tumors, but no study to date has investigated this deletion in diffuse large B-cell lymphoma (DLBCL). Recently, we demonstrated that 3p14.2 was deleted in approximately 30% of DLBCL cases by use of a genome-wide array-comparative genomic hybridization (CGH). For a more detailed examination of the genomic losses at 3p14.2, here we made use of contig BAC array for 3p14.2, and found that 12 DLBCL samples displayed losses. All of the deleted regions were located within the fragile histidine triad (FHIT) gene, and the most frequent region of loss was mapped to 0.4 Mbp of the region encompassing the introns 4 and 5 and exon 5 of the FHIT gene. Concomitant analysis of transcripts showed that the FHIT gene was aberrantly transcribed in 31% of the DLBCL samples examined and that the lost exons of the aberrant transcripts were correlated with genomic deletions. These findings indicate that (1) loss of genomic material at 3q14.2 is responsible for exon losses of the FHIT gene, and (2) genomic loss of the FHIT gene is one of the causes of the generation of aberrant transcripts.

Genome-wide array-based comparative genomic hybridization of diffuse large B-cell lymphoma: comparison between CD5-positive and CD5-negative cases.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin's lymphoma and exhibits aggressive and heterogeneous clinical behavior. To genetically characterize DLBCL, we established our own array-based comparative genomic hybridization and analyzed a total of 70 cases [26 CD-positive (CD5+) DLBCL and 44 CD5-negative (CD5-) DLBCL cases]. Regions of genomic aberrations observed in >20% of cases of both the CD5+ and CD5- groups were gains of 1q21-q31, 1q32, 3p25-q29, 5p13, 6p21-p25, 7p22-q31, 8q24, 11q23-q24, 12q13-q21, 16p13, 18, and X and losses of 1p36, 3p14, 6q14-q25, 6q27, 9p21, and 17p11-p13. Because CD5 expression marks a subgroup with poor prognosis, we subsequently analyzed genomic gains and losses of CD5+ DLBCL compared with those of CD5-. Although both groups showed similar genomic patterns of gains and losses, gains of 10p14-p15 and 19q13 and losses of 1q43-q44 and 8p23 were found to be characteristic of CD5+ DLBCL. By focusing on the gain of 13q21-q34 and loss of 1p34-p36, we were also able to identify prognostically distinct subgroups among CD5+ DLBCL cases. These results suggest that array-based comparative genomic hybridization analysis provides a platform of genomic aberrations of DLBCL both common and specific to clinically distinct subgroups.

Analysis of chromosomal imbalances in de novo CD5-positive diffuse large-B-cell lymphoma detected by comparative genomic hybridization.

We recently demonstrated that the prognosis for de novo CD5-positive (CD5+) diffuse large-B-cell lymphoma (DLBCL) is markedly worse than that for CD5-negative (CD5-) DLBCL. Our findings also suggested that on the basis of its clinical features CD5+ DLBCL may constitute a unique disease category. However, the genetic basis for these two categories has not been established. Therefore, we performed comparative genomic hybridization analysis (CGH) of 26 cases of CD5+ DLBCL and 44 cases of CD5- DLBCL. Several identical changes in CD5+ and CD5- DLBCLs were found, such as gains of 3q, 9p, 12q, 13q, and 18q and losses of 1p, 6q, 17p, and 19p. However, distinct differences between the two categories were also detected. These included gains of 11q21-q24 (P=0.032) and 16p (P=0.005) in CD5+ DLBCL, and loss of 16p (P=0.028) in CD5- DLBCL. A comparison with results reported for mantle cell lymphoma, chronic lymphocytic leukemia, and Richter's syndrome demonstrated that the CGH pattern of CD5+ DLBCL was markedly different. This indicates that CD5+ DLBCL constitutes a disease category distinct from that of CD5- DLBCL and other CD5+ malignancies.

Multiple fuzzy neural network system for outcome prediction and classification of 220 lymphoma patients on the basis of molecular profiling.

A fuzzy neural network (FNN) using gene expression profile data can select combinations of genes from thousands of genes, and is applicable to predict outcome for cancer patients after chemotherapy. However, wide clinical heterogeneity reduces the accuracy of prediction. To overcome this problem, we have proposed an FNN system based on majoritarian decision using multiple noninferior models. We used transcriptional profiling data, which were obtained from "Lymphochip" DNA microarrays (http://llmpp.nih.gov/DLBCL), reported by Rosenwald (N Engl J Med 2002; 346: 1937-47). When the data were analyzed by our FNN system, accuracy (73.4%) of outcome prediction using only 1 FNN model with 4 genes was higher than that (68.5%) of the Cox model using 17 genes. Higher accuracy (91%) was obtained when an FNN system with 9 noninferior models, consisting of 35 independent genes, was used. The genes selected by the system included genes that are informative in the prognosis of Diffuse large B-cell lymphoma (DLBCL), such as genes showing an expression pattern similar to that of CD10 and BCL-6 or similar to that of IRF-4 and BCL-4. We classified 220 DLBCL patients into 5 groups using the prediction results of 9 FNN models. These groups may correspond to DLBCL subtypes. In group A containing half of the 220 patients, patients with poor outcome were found to satisfy 2 rules, i.e., high expression of MAX dimerization with high expression of unknown A (LC_26146), or high expression of MAX dimerization with low expression of unknown B (LC_33144). The present paper is the first to describe the multiple noninferior FNN modeling system. This system is a powerful tool for predicting outcome and classifying patients, and is applicable to other heterogeneous diseases.

Selection of causal gene sets for lymphoma prognostication from expression profiling and construction of prognostic fuzzy neural network models.

To assess the response of lymphomas to chemotherapy, gene expression profiling data from DNA microarrays were analyzed using the fuzzy neural network (FNN) modeling method. We used the FNN modeling method to produce 10 noninferior models. Using these models, we were able to predict diffuse large B-cell lymphoma (DLBCL) patient outcome with 93% accuracy. Of the 37 genes in the 10 models, 13 genes were repeatedly selected, indicating that these genes are important for prognostication. On Kaplan-Meier plots of overall survival, patients predicted by the FNN model to be cured survived significantly longer than those predicted to be refractory (P<0.0001), indicating that the FNN could successfully identify patients with a relatively poor prognosis among low-clinical-risk patients. The FNN modeling method presented here is able to precisely extract significant biological markers affecting prognosis.

Fuzzy neural network applied to gene expression profiling for predicting the prognosis of diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the largest category of aggressive lymphomas. Less than 50% of patients can be cured by combination chemotherapy. Microarray technologies have recently shown that the response to chemotherapy reflects the molecular heterogeneity in DLBCL. On the basis of published microarray data, we attempted to develop a long-overdue method for the precise and simple prediction of survival of DLBCL patients. We developed a fuzzy neural network (FNN) model to analyze gene expression profiling data for DLBCL. From data on 5857 genes, this model identified four genes (CD10, AA807551, AA805611 and IRF-4) that could be used to predict prognosis with 93% accuracy. FNNs are powerful tools for extracting significant biological markers affecting prognosis, and are applicable to various kinds of expression profiling data for any malignancy.

Prognostic factors in elderly patients with acute myelogenous leukemia: a single center study in Japan.

We retrospectively analyzed data of 47 patients aged 60 years or older, hospitalized in our institution with the diagnosis of acute myelogenous leukemia (AML), and searched for prognostic factors. Induction with anthracyclines significantly correlated with better complete remission (CR) rate (P = 0.0016) and overall survival (OS) (P < 0.001). Another factor significantly affecting CR rate was higher age (> 70 years) (P = 0.042). Therapy-non-related factors predictive for shorter OS in univariate analyses were age older than 70 years (P = 0.003), percentage of blasts in bone marrow more than 80% (P = 0.048), serum lactate dehydrogenase level higher than 250 U l(-1) (P = 0.032). In stepwise cox proportional hazard regression model, all the four factors predictive for poor OS remained to be independently and significantly prognostic for shorter OS. Only two patients receiving anthracyclines died within 30 days and the frequency was not different from that in patients not receiving anthracyclines. The use of anthracyclines as induction therapy is recommended even in the elderly patients.