Shaughnessy, John D.

Introduction Despite the remarkable success of combination treatments, multiple myeloma (MM) still poses significant challenges, with a high percentage of patients experiencing relapse over time. Additional metabolic alterations are found in relapsed and refractory MM; however, their impacts have not been fully elucidated. Expression of thyroid hormone receptor interactor 13 (TRIP13) has been identified by Gene Expression Profile (GEP)-70 to correlate with poor prognosis in MM. TRIP13 is an AAA ATPase that regulates the spindle assembly checkpoint in mitosis. Based on GEP data from 34 paired baseline and relapse samples, TRIP13 continuously increased from baseline to first and to second relapse. Overexpression of TRIP13 induces bortezomib resistance. In this study, we aimed to investigate how TRIP13 might regulate MM cell metabolism and to use this information to develop a novel combination strategy to overcome MM resistance. Methods Knockout (KO) of TRIP13 in OPM2 and MM1.S cells was generated by dual gRNAs CRISPR-Cas9 editing deleting a fragment between exon 4 and exon 5. Cell growth curves and response to bortezomib were recorded in the control and TRIP13-KO cells. Metabolomics was performed to reveal cellular metabolic alterations. Seahorse analysis was used to test the mitochondrial stress and glycolysis stress. To investigate whether TRIP13 KO promotes ferroptosis, an intracellular iron-dependent cell death characterized by the accumulation of lipid peroxides, we applied C11-BODIY staining after treatment with Erastin, a ferroptosis-inducer. Expression levels of cyclooxygenase 2 (encoded by PTGS2, a hallmark of ferroptosis), cystine transporter (xCT), and intracellular glutathione peroxidase 4 (GPX4) were analyzed. In addition, the protein levels of iron metabolic molecules, including iron importer transferrin receptor protein 1 (TFRC), iron exporter ferroportin 1 (FPN1), ferritin heavy chain 1 (FTH1), and nuclear receptor coactivator 4 (NCOA4) were assessed. To study whether TRIP13 KO delays MM progression in an immune-competent MM mouse model, Vκ12653 murine MM cells were genetically modified by CRISPR-mediated TRIP13-KO and then injected into C57BL/6 mice. Mouse survival was monitored. Results The cell-doubling rate of TRIP13-KO cells was decreased by 50% compared to control cells. After 24 hours of treatment with 5 nM bortezomib, cell viability of TRIP13-KO cells decreased by 31% compared with control cells. The metabolomic studies revealed that TRIP13-KO OPM2 and MM1.S cells both had significantly decreased intracellular L-serine (FC = 0.57) but increased pyruvate (FC = 1.79), citric acid (FC = 1.76), and isocitric acid (FC = 1.64), indicating TRIP13 may regulate serine metabolism, mitochondrial function, and cellular redox balance. Seahorse analysis indicated that TRIP13-KO MM cells showed decreased glycolysis (decreased by 30%, p < 0.001) and glycolytic capacity (decreased by 33%, p < 0.001) while oxidative phosphorylation showed little change. Moreover, lipid peroxidation and PTGS2 were increased in TRIP13-KO cells after Erastin treatment, indicating that these cells were more vulnerable to ferroptosis. Mechanistically, inhibition of TRIP13 decreased GPX4, FPN1, FTH1, and increased NCOA4, while overexpression of TRIP13 showed the opposite changes, suggesting that targeting TRIP13 sensitizes MM cells to ferroptosis by impairing cellular redox balance and increasing the labile-iron pool. Lastly, TRIP13-KO significantly prolonged mouse survival in the Vκ12653 mouse model (median survival: TRIP13-KO 93 days vs. Control 60.5 days, p < 0.001). Conclusion Our study revealed that TRIP13 plays a critical role in regulating MM cell metabolism. By suppressing TRIP13, we observed increased sensitivity of MM cells to bortezomib, leading to enhanced ferroptosis-mediated cell death and prolonged mouse survival. These findings strongly suggest that targeting TRIP13 could be a promising approach in MM therapy. Moving forward, our future investigations will concentrate on unraveling the precise molecular mechanisms underlying TRIP13-mediated alterations in cell metabolism. Additionally, we plan to explore the potential synergistic effects of TRIP13 inhibition in combination with metabolic targeted treatments, such as venetoclax, to further enhance therapeutic outcomes in MM.

Introduction: In recent years, increasing evidence suggests an important role of tumor-infiltrating B lymphocytes (TIL-Bs) in cancer immunity. In various types of solid tumors, high density of TIL-Bs and presence of mature tertiary lymphoid structures consistently correlate with better prognosis and response to immune checkpoint blockade therapies. Diffuse large B-cell lymphoma (DLBCL) is a type of aggressive lymphoma arising from mature B cells. TIL-Bs have been identified in DLBCL based on single-cell gene-expression data in several previous studies, but their prognostic significance in DLBCL is unknown. In this study, we determined the clinical significance of TIL-B abundance and investigated the potential underlying mechanisms. Patients and Methods: This abstract includes a discovery study in which we distinguished TIL-Bs from malignant B-cells by immunoglobulin gene (IG) clonotype analysis and a validation study using flow cytometry. In the discovery study, a molecularly well-characterized DLBCL cohort assembled by the International DLBCL R-CHOP Consortium Program was analyzed. DNA samples from DLBCL patients were sequenced by high-throughput ultra-deep sequencing assays using multiplexed forward and reverse primers. Based on the IG heavy chain (IGH) sequencing results, malignant B-cell and TIL-B VDJ clonotypes were identified for 138 patients, and the frequencies and numbers of TIL-B clonotypes in individual sequence repertoires were calculated. In 79 DLBCL cases, a DJ-only sequence was predominant and no productive VDJ sequences met the criteria for diagnostic sequences. Total frequencies of productive VDJ sequences in the sequence repertoires were then used to access high and low TIL-B frequencies. TIL-B frequencies were also evaluated by IG light chain clonotypes for these 217 patients and additional 52 patients. The TIL-B frequencies were correlated with patient survival, gene-expression profiling (GEP) data GSE31312, and frequencies of DLBCL-infiltrating immune cells quantified by fluorescent multiplex immunohistochemistry (mIHC). To validate the prognostic significance of TIL-B frequencies, we assembled a validation cohort of 94 DLBCL patients treated at Duke University Medical Center. TIL-Bs in tissues were quantified by flow cytometry immunophenotyping. Ratios of TIL-Bs to abnormal B cells were assessed for prognostic effects. Results: First, we found thathigh frequencies of TIL-Bs and clonotypic diversity were associated with significantly favorable prognostic effects in 138 DLBCL patients with their malignant B-cell IGH-VDJ clonotypes identified (Figure A). The prognostic effects of TIL-Bs outweighed those of the germinal center B-cell-like/activated B-cell-like classification (Figure B). Second, patients with high frequencies of TIL-Bs compared with those without had significant upregulation of immune response genes by GEP (Figure C), higher CD4 T cell infiltration quantified by fluorescent mIHC (Figure D), and enrichment of EcoTyper-defined specific cell states, including significantly increased frequencies of B cell state S2 (pre-memory), CD4 T cell state S3 (naïve), follicular helper T cell state S3, and endothelial cell state S3, whereas lower frequencies of B cell state S5 (plasmablast) and follicular helper T cell state S1. Third, high TIL-B abundance in 79 ‘DJ-only’ clonotype cases and additional 52 cases assessed by light chain clonotype analysis showed similar favorable prognostic effects and associations with upregulated immune gene expression and CD4 T cell infiltration. Fourth, the identified GEP signatures, prominent with genes involved in T-dependent B cell activation and T cell activation and differentiation, showed significant prognostic effects in two GEO datasets. Fifth, TIL-B abundance showed significant prognostic effects in DLBCL cases infiltrated with T-cells in both the discovery study (Figure E) and validation study (Figure F, flow cytometry cohort). Conclusions: TIL-B frequencies and clonotypic diversity have remarkable prognostic and biological effects in DLBCL, which has significant implications for developing novel therapeutic strategies. Our study identified a new prognostic biomarker in DLBCL and an important player in anti-lymphoma immune responses, providing a new point of view to analyze the tumor biology in aggressive B-cell lymphoma and precisely identify prognostic determinants.

Abstract Purpose: Tumor-infiltrating B lymphocytes (TIL-B) have demonstrated prognostic and predictive significance in solid cancers. In this study, we aimed to distinguish TIL-Bs from malignant B-cells in diffuse large B-cell lymphoma (DLBCL) and determine the clinical and biological significance. Experimental Design: A total of 269 patients with de novo DLBCL from the International DLBCL R-CHOP Consortium Program were studied. Ultra-deep sequencing of the immunoglobulin genes was performed to determine B-cell clonotypes. The frequencies and numbers of TIL-B clonotypes in individual repertoires were correlated with patient survival, gene expression profiling (GEP) data, and frequencies of DLBCL-infiltrating immune cells quantified by fluorescent multiplex IHC at single-cell resolution. Results: TIL-B abundance, evaluated by frequencies of normal B-cell clonotypes in the immunoglobulin repertoires, remarkably showed positive associations with significantly better survival of patients in our sequenced cohorts. DLBCLs with high versus low TIL-B abundance displayed distinct GEP signatures, increased pre-memory B-cell state and naïve CD4 T-cell state fractions, and higher CD4+ T-cell infiltration. TIL-B frequency, as a new biomarker in DLBCL, outperformed the germinal center (GC) B-cell–like/activated B-cell–like classification and TIL-T frequency. The identified TIL-B–high GEP signature, including genes upregulated during T-dependent B-cell activation and those highly expressed in normal GC B cells and T cells, showed significant favorable prognostic effects in several external validation cohorts. Conclusions: TIL-B frequency is a significant prognostic factor in DLBCL and plays a crucial role in antitumor immune responses. This study provides novel insights into the prognostic determinants in DLBCL and TIL-B functions with important therapeutic implications.

8521 Background: Several clinical and molecular prognostic factors (e.g, International Staging System [ISS] stage, plasma cell labeling index, genomic models) exist for multiple myeloma (MM). We hypothesized that exploiting gene signatures representative of oncogenic pathway deregulation (i.e., Ras, Myc, etc.), would improve MM prognostication and also aid with the identification of novel therapeutic targets. Methods: Using a discovery cohort (n=47) of patients with MM and corresponding gene expression data, we built upon current molecular risk-stratification and devised a Bayesian genomic (“metagene”) model for prognosis. We validated that model in an independent patient cohort (n=207). Finally, we incorporated ISS staging and clinical variables to construct a combined Clinico-Genomic Risk Stratification System. We further validated the combined model in a separate cohort (n=72), in a blinded manner. Results: Using gene signatures predictive of oncogenic pathway activation in the discovery cohort, we identified specific patterns (metagenes) of signaling pathway activation with prognostic relevance. In an independent validation cohort, this metagene-based model accurately predicted event free survival (EFS) independently of ISS (multivariate hazard ratio [HR] 3.4 for ISS stage, and 5.4 for the metagene model, p=0.002). Using multivariate risk modeling, we incorporated ISS staging and the metagene model into a Clinico-Genomic System and successfully stratified the validation cohort into three groups (low, intermediate, and high risk) with markedly different EFS (HR 4.2 for intermediate risk and 14.0 for high risk vs. the low risk cohort, p<0.0001). In an additional blinded validation, the Clinico-Genomic System again accurately predicted median overall survival (68.7 [low risk] vs 24.7 [intermediate risk] vs 18.7 months [high risk], p<0.0001); more accurately than either ISS or other reported genomic models. Conclusions: A combined Clinico-Genomic Risk Stratification System, building on patterns of oncogenic pathway activation and ISS staging system, improves upon current prognostic models in MM and identifies novel pathway targets for future therapeutic consideration. No significant financial relationships to disclose.

Abstract Glucocorticoid (GC) is an effective anti-myeloma agent by directly inducing apoptosis and growth inhibition in myeloma cells. The anti-myeloma action of GC is mediated by its intracellular receptor, the glucocorticoid receptor (GR). The response to GC is variable among myeloma patients and resistance to glucocorticoid treatment develops almost invariably. The mechanism regulating glucocorticoid-sensitivity in not well understood, although it has been hypothesized that the regulation might occur at both the receptor (GR) and post-receptor level. In MM.1 myeloma cell lines, we observed significant down-regulation of GR expression as the cells develop GC-resistance, suggesting that GR expression level is an important determinant of GC-response. Here we present evidence that GR expression level directly correlates with the clinical outcome in myeloma patients who were treated with GC-containing regimens. First, using a quantitative real-time PCR analysis, we performed a retrospective analysis of GR gene expression on bone marrow plasma cell samples from 35 patients with newly diagnosed myeloma who were then treated on the ECOG study E1A00. This is a phase 3 trial which randomized patients to dexamethasone (dex) alone vs. dex in combination with thalidomide. Pre-treatment expression levels of GR-alpha, GR-beta and GR-P splicing isoforms were measured for 35 patients, of whom, 10 had post-treatment samples available. Interestingly, a large variation of the GR expression levels was observed across the patient samples, with the GR-alpha being the predominant isoform. However, a clear correlation between GR expression and treatment response was not seen, likely due to the small sample size. To access a larger patient pool, we retrospectively analyzed the GR expression levels using the cDNA microarray data from the Arkansas group on 351 newly diagnosed myeloma patients treated with Total Therapy 2, of which dexamethasone was an essential component throughout the treatment course. Of the 351 patients, both event-free (EFS) and overall survivals (OS) were compared between 49 patients (14%) with low levels of GR expression and the rest (86%) with high levels of GR expression. Strikingly, the cases with low levels of GR expression were associated with statistically significantly worse EFS and OS compared to those with high levels of GR expression, with the 5-year EFS of 20% vs. 52% and OS of 34% vs. 68%, P &lt; 0.01. In summary, we have shown for the first time that the baseline level of glucocorticoid receptor expression in newly diagnosed myeloma patients predicts their clinical response to GC-containing regimen and the overall clinical outcome.

Abstract We have taken a genetic strategy to define the mechanisms underlying the increased risk of VTE in myeloma patient treated with thalidomide using clinical trial data derived from the MRC, ECOG, Little Rock and HOVON trial groups. Baseline VTE rates in the MRC IX study, (CTD vs CVAD; n=748 no prophylactic anticoagulation), were 14%. Rates in both arms were equal but in the thalidomide arm, thrombotic events were all DVT’s or PE’s, whereas in the CVAD arm they split equally between line related and VTE’s. In the other comparison (CTD vs MP; n=542), the VTE rate was 17%, all in the thalidomide arm. Rates were similar or higher (30%) in the other trials depending on the intensity of treatment used. We carried out a nested case control on DNA from MRC IX on 90 VTE (45 thalidomide, 45 non-thalidomide related), matched to 180 controls. SNPlex analysis for 60 SNPs in the coagulation cascade, DNA repair, thalidomide, metabolism and myeloma specific pathways, identified 7 genes which affected risk (NBS1, MTHFR, Ku80, Cyp3A5, LGAL52 and IL12B). This suggests three major pathways contribute to the risk of thalidomide related VTE, metabolism of thalidomide, tumour responsiveness and some pro-thrombotic factors. These factors differ from non-thalidomide related risk where a strong pro-inflammatory response is most relevant. We tested this hypothesis further using an expanded panel of 3,404 SNPs (BOAC panel), using the Megalle system. Statistical analysis of this data defined the top 20 thalidomide and non-thalidomide associated SNPs, which were consistent with the initial hypothesis, the results of which exclude variation in the coagulation cascade as being a significant risk factor. We explored this hypothesis further using pathway-based analysis focussing on the MTHFR, DNA repair and WNT pathways on data from the ECOG, HOVON and Little Rock data sets. The biological relevance of the SNPs and genes identified was validated by correlating the level of expression using the Affymetrix U133 CHIP with genetic variation at the DNA level. To verify the relevance of DNA repair variability to tumour response further, we correlated gene expression profiling with response and again Ku80 was identified as one of a cluster of genes defining increased risk. The data suggests that the risk of thalidomide related VTE relates to rapid tumour lysis combined with a prothrombotic tendency, whereas in line related thrombosis, risk is dependent upon a strong proinflammatory response. We are building this genetic data into a clinical risk model in order to allow us to develop a rationale for intervention strategies.

Abstract Background: Bone disease in myeloma occurs as a result of complex interactions between myeloma cells and the bone marrow microenvironment. To date, no studies have evaluated the potential impact of genetic polymorphisms upon and/or within this microenvironment. Patients and Methods: Peripheral blood DNA from 282 patients enrolled in the Total Therapy 2 (TT2) protocol was studied using the previously reported Affymetrix 3k BOAC custom chip to evaluate relevant genetic polymorphisms. DKK1 gene expression and high risk GEP gene signatures were assessed as previously reported (Blood109:4470–4477 and 109:2276–2284 2007). Patients were classified using both full skeletal x-rays and MRI findings. The lower cut-off used was absence of focal abnormalities on x-ray and/or <7 focal lesions on MRI (see JCO25:1121–1128 2007). Results: The top 200 SNPs were first evaluated based upon univariate P values linked to limited or extensive bone disease. The top 50 SNPs with the smallest P values were then selected (eliminating closely linked genes) for recursive partitioning analysis. The recursive partitioning was conducted both with and without the insertion of known biologically relevant SNPs. The pruned tree developed with recursive partitioning proved to be quite stable and incorporated 4 dominant SNPs: rs 3766934 Epoxide hydrolase (EPHX1); sr3783408 MAP kinase; sr 1062637 RNA helicase DDX18; and sr3181366 TNFSF8-TNF-α. No alternate SNP substituted for EPHX1 in the recursive model. The 4 SNP signature of EPHX1 GG, MAP4K5 AG/AA, DDX18 GG/CC plus TNFSF8 CT/TT was highly correlated with the number of MRI lesions: mean 8.66 lesions versus 3.33 for alternate SNPs (P<.001). In the univariate association of standard prognostic factors, 4 SNP signature and 70 and 17 gene models for high risk, the best correlation with bone disease was with the 4 SNPs (P<.0001) followed by the 17 gene GEP model (P=0.05). Using stepwise multivariate regression analysis the best correlation with bone disease was Log2DKK-1 expression (P=.0001) but closely followed by SNPs EPHX1 (P=.0009); MAP4K5 (P=.0071) plus TNFSF8 and serum LDH (P=.02). The various analyses training (2/3) and validation sets were used with assessment of sensitivity and specificity. The microenvironmental 4 SNP signature combined with GEP DKK1 provided the best prediction of myeloma bone disease and overall outcome. Conclusions: This first assessment of genetic polymorphisms linked to myeloma bone disease in myeloma has led to the identification of polymorphisms with both potential biologic relevance and utility in prognostic models of myeloma bone disease including risk stratification for bisphosphonate use. Validation of these findings may allow a search for potential therapeutic targets.

Abstract Abstract 743 Background There has been considerable recent focus upon the molecular classification of myeloma. However, the prognostic impact of molecular changes has mostly been assessed from small and/or incomplete studies from single institutions or groups. There has been no large scale analysis of molecular features linked to ISS stage. Methods In order to clarify the overall impact of molecular changes we undertook a collective analysis of 9,897 patients through the International Myeloma Working Group (IMWG). Within this population 2,295 patients had presence of cytogenetic abnormalities (Any CA); 1,713 hypodiploidy; 1,673 hyperdiploidy; 2,309 cytogenetic deletion 13; 3,226 deletion 13 by FISH; 1,573 FISH t(4;14); 1,486 FISH del p17; 1, 683 FISH t(11:14); and 366 FISH t(4;16). Enrolled patients had complete clinical and treatment details available including baseline standard prognostic factors, ISS stage, as well as both progression free survival (PFS) and overall survival (OS) information. Data came from 14 sites: 3 from the US and the remainder from Europe, Asia, and Latin America as for the ISS staging system analyses. Univariate and multivariate analyses were performed. Results Each of the known adverse molecular features had a negative impact upon both PFS and OS (p=002 - <0.0001). Among the deleterious FISH abnormalities the t(4;14) abnormality was the most highly correlated with poorer outcomes by PFS: 4 year estimate: 32% vs. 60% (p<0.0001). The t(4;14) abnormality combined with ISS Stage also significantly enhanced predictive capability: ISS Stage I without t(4;14) OS 81% @ 4 years; ISS Stage III with t(4;14) OS 22% @ 4 years (P<0.0001) [Figure 1]. The best outcomes were for ISS Stage I in the presence of t(11;14): OS 89% @ 4 years. Absence of any one adverse feature correlated with 80-81% OS @ 4 years for Stage I. Presence of any one adverse feature had a more variable impact and correlated with 22%-40% OS at 4 years for Stage III. In univariate correlations the most predictive correlations with OS were presence of Any CA, t(4;14), 17p-, hypodiploidy, cytogenetic 13q- with R2 values of 6.9%, 4.5%, 4.1% and 3.8% respectively. In multivariate analyses, ISS stage provided the best predictions: R2 values = 13.3%. The added contributions from molecular features were: t(4;14) 3.8%; cytogenetic 13q- 2.9%; Any CA 2.3%; and 17p- 1.0%. The maximum total R2 for OS was 22%. Conclusions This large multicenter analysis confirms the correlations between abnormal molecular findings and outcomes. Combinations with ISS Stage provide the best predictive capability. Presence of Any CA, t(4;14), 17p-, hypodiploidy and cytogenetic 13q- contribute to poorer outcomes by ISS stage. The presence of hyperdiploidy and/or t(11;14) contribute to better outcomes. There is thus validation of prior molecular studies related to prognosis utilizing this large IMWG database. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 194 Background: Immunomodulatory drugs (IMiDs) are key components of treatment for hematologic malignancies, especially multiple myeloma (MM). Recently, we demonstrated that CRBN expression is the major mediator of IMiD action operating at least in part via interferon regulatory factor 4 (IRF4), however the clinical significance of this finding remains unclear. Methods: To better understand clinical impact, we retrospectively reviewed 148 MM patients whose tumor cells were tested for CRBN expression by Gene Expression Profiling (GEP) prior to treatment with an IMiD containing therapy. Results: GEP studies show no significant differences in CRBN expression between MGUS, smoldering MM (SMM), untreated symptomatic MM and normal plasma cells. However, differences were observed between MM cell lines of varying drug sensitivity to IMiDs and between other B-cell Neoplasia (eg low grade lymphoma has higher levels). Within the genetic subtypes of MM, levels were significantly higher for hyperdiploid patients (median 1.26) as opposed to significantly lower levels for TC class D2 (median 0.76) and average for the 4p16 (median 0.97). We next screened the University of Arkansas Medical School (UAMS) GEP database of MM patients treated with combination therapies and did not find significant correlation between CRBN expression and survival in this multi-agent regimen. We then focused on patients that received only single agent IMiD therapy with low dose dexamethasone. Review of the twelve lowest expressing patients demonstrated a lack of response to IMiDs in any patient. Finally we analyzed 53 relapsed or relapsed/refractory patients treated homogeneously in a study with pomalidomide 2–4mg daily and weekly dexamethasone 40mg. CRBN levels were assessed prior to therapy initiation. Response rates varied significantly based on gene expression level. The percentage of patients that demonstrated at least a partial response was 0% for CRBN <0.81, 19% for CRBN expression of 0.81–0.90, and 33% for CBN expression >0.9. Significant differences in PFS (3.0 months vs. 8.9 months, p = 0.0006) and in OS (9.1 months vs. 27.2 months, p = 0.01) were observed when the lowest quartile of CRBN expression was compared to the top three quartiles. Values used for the cut offs are as follows: (25%: 0.889687; 50%: 1.026542, 75%: 1.211133). While this study demonstrates a positive correlation between CRBN expression and response to pomalidomide and dexamethasone, an important caveat with respect to PFS and OS is that CRBN mRNA level is primarily a reflection of the number of copies of CRBN. Since focal deletions are uncommon, this mostly reflects chromosome 3p copy number. Since trisomy 3 is common in hyperdiploid, good prognosis disease, CRBN not only is required for IMiD function but higher levels also serve as a surrogate for low risk disease. Optimal gene expression cut offs for survival were determined using the Contal and O'Quigley method. The optimal cut point for PFS was 1.18443 and for OS was 1.17816. Conclusion: In summary, this study demonstrates, for the first time, a clinical correlation between CRBN expression and response to IMiD and dexamethasone therapy. CRBN expression is also predictive of survival outcomes and when quantified prior to therapy could potentially be utilized as a predictive biomarker for response to an IMiD based treatment. Disclosures: Stewart: Celgene: Consultancy, Honoraria.

AbstractA panel of members of the 2009 International Myeloma Workshop developed guidelines for risk stratification in multiple myeloma. The purpose of risk stratification is not to decide time of therapy but to prognosticate. There is general consensus that risk stratification is applicable to newly diagnosed patients; however, some genetic abnormalities characteristic of poor outcome at diagnosis may suggest poor outcome if only detected at the time of relapse. Thus, in good-risk patients, it is necessary to evaluate for high-risk features at relapse. Although detection of any cytogenetic abnormality is considered to suggest higher-risk disease, the specific abnormalities considered as poor risk are cytogenetically detected chromosomal 13 or 13q deletion, t(4;14) and del17p, and detection by fluorescence in situ hybridization of t(4;14), t(14;16), and del17p. Detection of 13q deletion by fluorescence in situ hybridization only, in absence of other abnormalities, is not considered a high-risk feature. High serum β2-microglobulin level and International Staging System stages II and III, incorporating high β2-microglobulin and low albumin, are considered to predict higher risk disease. There was a consensus that the high-risk features will change in the future, with introduction of other new agents or possibly new combinations.