IgH Translocations Research Articles

639P Conditional survival in MM and impact of prognostic factors over time

Overall Survival (OS) estimates from diagnosis are important for predicting prognosis and guiding treatment selection in newly diagnosed patients, but do not consider the number of years already survived. Conditional survival (CS) estimates provide updated survival predictions over the disease course. Previous studies suggest that improvement in CS is less pronounced in multiple myeloma (MM) compared to other malignancies. It is unclear whether high-risk (HR) factors in MM retain their prognostic impact over time. This study was conducted to estimate CS at 1 to 5 years from diagnosis and evaluate the impact of baseline prognostic factors on CS over time in newly diagnosed MM patients. This is a retrospective study including 2556 MM patients diagnosed between 2004-2019. CS (t|s), defined as the probability of surviving additional t years given survival of s years, was estimated at 1 to 5 years from diagnosis using the conditional Kaplan-Meier method. The impact of baseline characteristics on CS was estimated using conditional Cox proportional hazards model. The median age was 64 years and 62% were male; >90% received novel-agent based induction; 46% had transplant within 1 year of diagnosis. The median follow-up was 6.2 years, and median OS was 7.5 years. The 5-year CS estimates at s=0, 1, 2, 3, and 5 years were 0.64, 0.61, 0.61, 0.61, and 0.58, respectively. On multivariate analysis, age ≥ 65 and proteasome inhibitor (PI)+Immunomodulatory (IMiD)-based induction retained prognostic significance at 5 years from diagnosis. The adverse impact of HR IgH translocations, 1q gain and ISS 3 was not significant at 5 years. Chromosome 17 abnormality predicted worse CS at 1 year, but not at 3 or 5 years from diagnosis (table).Table: 639PMultivariate CSVariableDiagnosisyear 1year 3year 5HRPHRPHRPHRPAge≥651.60<0.011.57<0.011.48<0.011.95<0.01Calcium ≥111.59<0.011.63<0.011.05NS1.05NSISS III1.74<0.011.75<0.011.80<0.011.52NSEarly transplant0.57<0.010.64<0.010.61<0.010.69NSPI+IMiD induction0.59<0.010.630.010.660.040.530.04LDH > 2221.29NS1.15NS1.13NS0.89NSCh17 abnormality1.53<0.011.430.021.32NS1.16NSHR IgH translocation1.90<0.011.97<0.011.550.041.51NSMonosomy 131.13NS1.09NS1.05NS0.86NS1q gain1.34<0.011.310.031.500.011.38NSSignificant P values are bolded. NS: not significant. Open table in a new tab Significant P values are bolded. NS: not significant. In a large cohort of MM patients treated with novel agents, CS was stable at 1 to 5 years from diagnosis. The adverse prognostic impact of HR cytogenetic factors and advanced ISS stage decreased over time.

IGH Translocations in Chinese Patients With Chronic Lymphocytic Leukemia: Clinicopathologic Characteristics and Genetic Profile.

Immunoglobulin heavy chain translocations (IGH-t) have occasionally been reported in Chinese patients with chronic lymphocytic leukemia (CLL). The objective of the present study was to identify the clinicopathologic features of patients with IGH-t CLL and compare them with those of patients with non-IGH-t CLL. We performed fluorescence in situ hybridization (FISH) based on a routine CLL prognostic FISH panel using IGH, IGH-BCL2, BCL3, IGH-CMYC, and BCL6 FISH probes. Furthermore, we retrospectively evaluated the clinical features of 138 newly diagnosed CLL patients via chromosome banding analysis (CBA), FISH, and targeted next-generation sequencing. IGH-t was identified in 25 patients (18.1%). Patients with IGH-t CLL had lower flow scores than those with non-IGH-t CLL. The most frequent translocation was t(14;18) (10 patients), followed by t(14;19) (3 patients), and t(2;14)(p13;q32), t(7;14)(q21.2;q12), t(9;14)(p13;q32) (3 patients). The remaining nine patients included three with abnormal karyotypes without translocation involving 14q32, four with a normal karyotype, and two who failed CBA. The most frequently concomitant FISH-detected aberrations were 13q deletion, followed by +12 and TP53 deletion, while one case involved ATM deletion. Complex karyotypes were detected in five patients with IGH-t CLL, in whom all partner genes were non-BCL2. Available mutational information indicated that KMT2D mutation was the most frequent mutation among tested 70 patients, while TP53 mutation was the most frequent mutation in the IGH-t group. Moreover, the IGH-t group had higher FBXW7 (P=0.014) and ATM (P=0.004) mutations than the non-IGH-t group, and this difference was statistically significant. Our study demonstrates that IGH-t is not uncommon among Chinese CLL patients, and that its partner genes are multiple. The gene mutational profile of the IGH-t group was distinct from that of the non-IGH-t group, and the concomitant chromosomal abnormalities within the IGH-t CLL group differed. Thus, identification of IGH-t and its partner genes in CLL patients may help further refine risk stratification and strengthen the accurate management in CLL patients.

What Is Genomic High-Risk Myeloma?

Although treatment of multiple myeloma has changed dramatically over time, there is still a subpopulation of patients who do not respond to treatments and are labeled as high risk. A combination of serum and genomic markers can be used to identify and stratify these patients according to associations with outcome. The most common method of identifying the genomic markers of high-risk multiple myeloma is using fluorescence in situ hybridization using probes to identify IgH translocations or copy number changes including the t(4;14), t(14;16), t(14;20), gain 1q, and del(17p). However, as research studies utilize newer technologies, such as whole genome sequencing, more high-risk factors are being identified including mutations of TP53, DIS3, BRAF, and complex structural events. Integration of comprehensive genomic studies into clinical trials will aid in defining the genomic high-risk landscape of multiple myeloma, which in turn can be transferred to individual patient diagnostics and treatment management.

Amp 1q21 is more predictable with dismal survival than gain 1q21 of newly diagnosed multiple myeloma in real-world analysis.

IntroductionThe gain/amplification (amp) of 1q21 is one of the most common high‐risk chromosome abnormality (HRCA) in multiple myeloma (MM). The prognostic value of 1q21+ remains to be controversial on the status of gain or amp and the combination of other HRCAs.MethodsIn this retrospective study, we included 318 newly diagnosed MM (NDMM) patients who had fluorescence in situ hybridization (FISH) data and treated with novel agents in our department.ResultsOur study noted MM patients with amp 1q21 were more likely accompanied with t(4;14), t(14;16), and t(14;20). Patients with amp 1q21 presented with elder age, advanced Revised International Staging System (R‐ISS) stages, anemia, and more plasma cells in bone marrow compared to patients with gain 1q21 alone and no 1q21+. Moreover, amp 1q21 alone correlated with shorter progression‐free survival (PFS) (22.8m vs. 40.5m vs. 39.6m) and overall survival (OS) (45.2m vs. NA vs. 83.5m) compared with gain 1q21 alone and no FISH abnormalities. Although the high ratio of proteasome inhibitor and immunomodulatory drugs used in patients with amp 1q21, the overall response (ORR) was the lowest compared with no 1q21+ and gain 1q21. Multivariate analysis defined amp 1q21 as an independent prognostic marker for NDMM patients, rather than gain 1q21.ConclusionThe amp 1q21 predict inferior treatment response and survival, especially coexisted with high‐risk IgH translocation.

Treatment strategies for multiple myeloma based on molecular pathogenesis

It is well documented that multiple myeloma (MM) originates in a single plasma cell transformed by chromosome 14q translocations or chromosomal hyperdiploidy and evolves with the accumulation of point mutations of driver genes and/or cytogenetic abnormalities. Furthermore, disease progression is accomplished by branching patterns of subclonal evolution from reservoir clones with a propagating potential and/or the emergence of minor clones, which already exist at premalignant stages and outcompete other clones through selective pressure mainly by therapeutic agents. Each subclone harbors novel mutations and distinct phenotypes, including drug sensitivities. Generally, mature clones are highly sensitive to proteasome inhibitors (PIs), whereas immature clones are resistant to PIs although could be eradicated by immunomodulatory drugs (IMiDs). The branching evolution is a result of the fitness of different clones to the microenvironment and their evasion of immune surveillance; therefore, IMiDs are effective for MM with this pattern of evolution. In contrast, ∼20% of MM evolve neutrally in the context of strong oncogenic drivers, including high-risk IgH translocations, and are relatively resistant to IMiDs. Treatment strategies considering the genomic landscape and the pattern of clonal evolution may further improve the treatment outcome of MM.

A simple additive staging system for newly diagnosed multiple myeloma

Risk stratification in multiple myeloma is important for prognostication, patient selection for clinical trials, and comparison of treatment approaches. We developed and validated a staging system that incorporates additional FISH abnormalities not included in the R-ISS and reflects the additive effects of co-occurring high-risk disease features. We first evaluated the prognostic value of predefined cytogenetic and laboratory abnormalities in 2556 Mayo Clinic patients diagnosed between February 2004 and June 2019. We then used data from 1327 patients to develop a risk stratification model and validated this in 502 patients enrolled in the MMRF CoMMpass study. On multivariate analysis, high-risk IgH translocations [risk ratio (RR): 1.7], 1q gain/amplification (RR: 1.4), chromosome17 abnormalities (RR: 1.6), ISS III (RR: 1.7), and elevated LDH (RR: 1.3) were independently associated with decreased overall survival (OS). Among 1327 evaluable patients, OS was 11.0 (95% CI: 9.2–12.6), 7.0 (95% CI: 6.3–9.2), and 4.5 (95% CI: 3.7–5.2) years in patients with 0 (stage I), 1 (stage II), and ≥2 (stage III) high-risk factors, respectively. In the MMRF cohort, median OS was 7.8 (95% CI: NR-NR), 6.0 (95% CI: 5.7-NR), and 4.3 (95% CI: 2.7-NR) years in the 3 groups, respectively (P < 0.001). This 5-factor, 3-tier system is easy to implement in practice and improves upon the current R-ISS.

The Alternative Splicing Landscape in Multiple Myeloma Is Determined By IGH Translocations and Mutations of RNA Processing Genes

Introduction: Alternative Splicing (AS) plays a key role in regulating numerous cellular processes in both normal and malignant cells. Previous studies have revealed mutations in the spliceosome complex, such as SF3B1, can cause increased AS frequencies in multiple myeloma (MM) patients, and patients with increased levels of AS are associated with a poor prognosis. Other frequently mutated genes involved in RNA processing include DIS3 and FAM46C, thus, systematically investigating other causes of AS abnormalities and pathologies in MM patients is highly necessary.Materials and Methods: RNA-seq data from 598 newly diagnosed MM patients from the MMRF CoMMpass study were utilized to generate AS comparisons. They were previously annotated for cytogenetic, copy number, and mutation data (version IA16). RNA-seq data were aligned to HG38 using STAR and Salmon. SUPPA2 was used for calling AS differences. For each identified AS event, the splicing level was defined by Percentage of Spliced-In (PSI) while the mean difference of splicing levels between two groups was measured by ΔPSI (dPSI) and by the P-value from independent T-tests against PSIs in the two groups. Filtering thresholds were determined to find high-quality differentially spliced events and were filtered for those also present in normal PCs (GSE110486). Geneset enrichment analysis was performed to identify dysregulated pathways caused by differential splicing and differential expression. Survival analysis was performed on clinical annotations of 598 NDMM patients while the Logrank test and Cox regression were used to evaluate the risk of AS and other genomic factors. Kaplan-Meier curves were plotted for various subgroups.Results: We compared 16 major cytogenetic subgroups, including Ig translocations (t(4;14), t(14;16), t(11;14)), hyperdiploidy, mutations in KRAS, NRAS, BRAF, FAM46C, SF3B1, DIS3 and TP53, combined events (t(4;14) plus DIS3 mutation), as well as those with biallelic abnormalities (DIS3, FAM46C, and TP53). Samples with SF3B1 hotspot mutations identified the greatest number of AS events (n=862), and samples with any SF3B1 mutation had approximately half as many. IGH translocations had an equivalent number of AS events to those with SF3B1 mutations, with t(14;16) having the most (n=587) followed by t(11;14) (n=366), and t(4;14) (n=256). We observed an increased number of significant AS events in bi-allelic DIS3 and FAM46C groups (n=404 and 171) compared to their mono-allelic abnormalities (n=114 and 35). As DIS3 mutations are enriched in the t(4;14) subgroup we also examined that interaction and found significantly more AS events (n=481; p<0.01) in the combination compared to either event alone. As expected, KRAS, NRAS and BRAF mutations did not have enrichment for AS events (n=2, 15, 23, respectively).The majority of AS events were unique to each subgroup, exemplifying the AS heterogeneity in these subgroups. Among overlapped events, an alternative first (AF) exon in ACACA was consistently more spliced in t(14;16), t(11;14) and t(4;14) groups (dPSI=0.18, 0.10, 0.12, P=2x10 -5, 2x10 -9, 5x10 -5). ACACA encodes an enzyme that significantly affects MM cell growth and viability, suggesting that similar regulations exist in the three translocation groups. Unique events were also detected including an AF event in MIB2 (E3 Ubiquitin Protein Ligase 2) in the t(11;14) group (dPSI=0.17, P=7x10 -14), and a skipped exon in UBXN4 (related to ER stress) in t(14;16) group (dPSI=0.1, P=3x10 -4). AS heterogeneity also leads to functional heterogeneity in the three groups. Besides commonly downregulated RNA catabolic processes, cell adhesion, migration and mobility related pathways are enriched pathways in t(14;16); cell growth related pathways in t(11;14); and ERK related pathways in t(4;14). High-risk events were identified through survival analysis and included a retained intron in RPS16 in the t(14;16) (Hazard Ratio (HR)=18.81, p=0.004). Similarly, high risk was associated with an AF event in DDX39B in t(11;14) (HR=2.62, p=0.001) and an AF event in COPA in t(4;14) (HR=6.29, p=0.001).Conclusion: AS is defined by multiple genomic events, including primary translocations and mutations in RNA processing genes, DIS3 and FAM46C, and interactions between genomic markers can increase AS. AS events contribute to outcome and some high risk AS events may serve as prognostic marker or potentially novel targets. DisclosuresWalker: Sanofi: Speakers Bureau; Bristol Myers Squibb: Research Funding.

Diagnostic Utility of Multimodal Genomic Profiling for Molecular Classification and MRD Assessment in Adult B-Cell Acute Lymphoblastic Leukemia

Genomic markers define molecular subtypes and measurable residual disease (MRD) targets in B-cell acute lymphoblastic leukemia/lymphoma (B-ALL) and are essential determinants of treatment. Current diagnostic approaches typically involve serial multi-step testing utilizing conventional cytogenetics (CC)/FISH and molecular genetic (RT-qPCR, MLPA, clonality PCR, NGS panel) techniques which are time and sample consuming and ultimately may not adequately identify genomically complex B-ALL subtypes. In contrast, single-step comprehensive genomic profiling by whole genome and whole transcriptome sequencing (WGS/WTS) may be more efficient for the molecular classification of established and newly described entities which are of increasing therapeutic relevance. We have instituted a multimodal platform for molecular testing in B-ALL performing WGS/WTS in parallel with deep NGS-based immunoglobulin (IG) rearrangement MRD and exploratory DNA-breakpoint based MRD assays. We aimed to determine the utility of this approach for subtype classification compared to a standard-of-care diagnostic approach of CC/FISH testing.Forty-two consecutive adult patients underwent both standard-of-care diagnostic testing and WGS/WTS. 20/42 (48%) patients had an abnormal CC/FISH result supporting classification into recognized molecular subgroups. WGS/WTS assessment incorporating somatic coding and non-coding mutations, structural variants, fusions, copy number abnormalities and gene expression subtype prediction (ALLSorts, https://github.com/Oshlack/ALLSorts) was performed with concordant results in all 20 patients. 16/22 patients that were unclassified by CC/FISH were successfully reclassified by WGS/WTS including subtypes enriched for cryptic rearrangements (Ph-like, DUX4, MEF2D) and groups characterized by heterogeneous genomic alterations or a distinctive gene expression signature (PAX5alt, ZEB2/CEBP). A low hypodiploid karyotype was observed in two cases with an apparently normal karyotype by CC. The six patients who remained without a subtype defining driver genetic alteration after comprehensive testing frequently harbored novel IGH translocations or a Ph-like expression signature but without a described fusion.In order to understand the relative contribution from WGS versus WTS, analysis of 36 patients was performed using a truth classification. WGS and WTS produced equivalent classifications for 22 cases. Two cases were based solely on WGS findings (iAMP21 and ZEB2/CEBP) and three cases were based solely on WTS findings (DUX4). Importantly the combination of both WGS and WTS was critical to correctly classify nine cases (Ph-like and PAX5alt).MRD was assessed by a sensitive NGS assay to IG rearrangements (Adaptive Biotechnologies) and by quantitative probe-based droplet digital PCR (ddPCR) assays designed to structural rearrangement DNA breakpoints from genome data (analytical sensitivity 10 -4). Patient-specific ddPCR assays were designed to eight structural variants (KMT2A and IGH translocations, and IKZF1 deletions) in seven patients and assessed in 36 remission samples with parallel testing by multiparametric flow cytometry (MFC). Concordant MFC and ddPCR was observed in 30/36 samples (19 MRD pos, 11 MRD neg). Discordances included two MRD pos by MFC-only and four MRD pos by ddPCR-only; the latter often occurring in the setting of antigen directed therapy or in ALL with a less informative immunophenotype, demonstrating the additional utility of non-MFC based MRD assessment in specific clinical settings. 27/42 patients in our cohort had ≥1 genomic structural rearrangement identified by WGS that could be used for patient-specific MRD monitoring to complement existing MRD assessment.In conclusion WGS/WTS provided a molecular subtype classification in 86% of our cohort compared to 48% by standard-of-care diagnostic testing highlighting that CC/FISH alone is inadequate for contemporary molecular classification of B-ALL, which may have implications for treatment decisions. Importantly, the combination of WGS and WTS was superior to WGS-only or WTS-only for correct molecular subtype assignment. This approach has the potential to improve risk assessment in adult B-ALL and the routine feasibility, improvement in clinical outcomes and health economic impact warrant further assessment. DisclosuresBajel: Abbvie, Amgen, Novartis, Pfizer: Honoraria; Amgen: Speakers Bureau. Dickinson: Janssen: Consultancy, Honoraria; Amgen: Honoraria; Celgene: Research Funding; Gilead Sciences: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Research Funding, Speakers Bureau; Takeda: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Other: travel, accommodation, expenses, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau. Tiong: Servier: Consultancy, Speakers Bureau; Amgen: Speakers Bureau; Pfizer: Consultancy.

Genomic Profiling of Smoldering Multiple Myeloma Classifies Molecular Groups with Distinct Pathogenic Phenotypes and Clinical Outcomes

Genomic Profiling of Smoldering Multiple Myeloma Classifies Molecular Groups with Distinct Pathogenic Phenotypes and Clinical Outcomes

Purine Nucleoside Analogs Plus Rituximab Is an Effective Treatment Choice for Hairy Cell Leukemia-Variant: Results from a Single Center in China

Background: Hairy cell leukemia-variant (HCL-v) is one type of chronic lymphocytic proliferative disorders which was classified into splenic B-cell lymphoma/leukemia, unclassifiable. Both clinical and laboratory characteristics and treatment strategy remain elusive due to the rarity of the disease. Here, we firstly presented the diseases features and efficacy of a variety of treatment options in a large cohort from China.Methods: Thirty-three patients were diagnosed with HCL-v in Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Science & Peking Union Medical College from June 1990 to February 2021. We analyzed the disease characteristics and treatment outcome, especially in terms of clinical manifestation, immunophenotypic and molecular evaluation and efficacy of multiple first-line treatment.Results: The median age of this cohort was 59 years (range, 34-79 years) at diagnosis, with 23 males and 10 females. Abdominal mass and relative signs (n=22) and abnormal complete blood count (n=9) were the most common chief complaints. Splenomegaly was present in 32 (97.0%) cases, among whom 26 (78.8%) cases were massive. Leukocytosis and leukopenia were presented in 23 (69.7%) patients and 5 (15.2%) patients, with a median white blood cell count of 21.58×10 9/L (range, 1.34-224.59×10 9/L). The median percentage of the leukemic cells in bone marrow tested by flow cytometry was 33% (range, 6.2%-96%), and immunophenotyping showed monoclonal B-cells positive for pan B-cell antigens (CD19, CD20, CD22, CD79b) in almost all patients (Table). CD11c was positive in all patients, and CD103 was positive in 20/26 (76.9%) patients. CD25 was negative in 30/33 (90.9%) patients, and CD23 was negative in 20/26 (76.9%) cases. CD200 was frequently expressed among patients (15/21, 71.4%). For the pathological pattern of bone marrow involvement, 20/27 (74.1%) patients showed a predominantly interstitial pattern. Moreover, Annexin A1 was negative in all (n=12) patients detected by immunohistochemistry. Conventional cytogenetic analysis showed abnormal karyotype in 10/24 (41.7%) patients, including 6 patients with complex karyotype. Fluorescence in situ hybridization analysis showed deletion of TP53 in 4/20 (20.0%) patients and IGH translocation in 5/16 (31.3%) patients. The BRAF V600E mutation was negative in all the patients (n=20). In 2 of 14 (16.7%) patients, TP53 mutation was detected by next-generation sequencing. Sixteen of nineteen (84.2%) patients showed monoclonal IGHV rearrangements, and the most common rearrangement fragment was VH4-34 (n=3, 18.8%). Six of seventeen (35.3%) patients presented with unmutated IGHV and patients with VH4-34 were all unmutated. 31 patients needed treatment finally. Treatment choices included interferon-α (IFN-α) in 11 patients, chlorambucil (CLB) in 5 patients, single purine nucleoside analogs (PNA) in 3 patients and PNA plus rituximab in 9 patients. Four patients who received IFN-α or CLB treatment also underwent splenectomy. The objective response rate was 100% for patients receiving PNA plus rituximab and 77% for cases receiving others. And people treated with PNA plus rituximab had a higher complete response rate compared to the other regimen (75% versus 12%, P = 0.004). During a median follow-up of 32 months (range, 3-207) for 29 patients, 14 (48.3%) patients experienced at least one relapse or progression, and 7 (24.1%) patients had 2 or more relapses. Of note, one case also underwent a diffuse large B-cell lymphoma transformation. The median PFS and OS were 31 months (95% CI 25.5-36.5) and 70 months (95% CI 50.5-89.5), respectively. PNA plus rituximab prolong PFS compared to the others (3-year PFS rate 80% [95%CI 20-97] versus 10% [95%CI 1-35], P = 0.012, Figure A). But no significant difference in 3-year OS rate was observed between two groups (100% [95%CI 100-100] versus 43% [95%CI 10-73], P = 0.128, Figure B).Conclusion: HCL-v is a rare disease with specific clinical and immunophenotypic features but may overlap with classic hairy cell leukemia or other splenic B-cell neoplasms. Overall, it is an indolent lymphoma with recurrent progression, and the use of PNA plus rituximab in first-line treatment can result in a deeper and longer remission. [Display omitted] DisclosuresWang: AbbVie: Consultancy; Astellas Pharma, Inc.: Research Funding.

B Cell Transcriptional Coactivator POU2AF1 (BOB-1) Is an Early Transcription Factor Modulating the Protein Synthesis and Ribosomal Biogenesis in Multiple Myeloma: With Therapeutic Implication

Multiple Myeloma (MM) is a malignancy driven by numerous genetic and epigenetic alterations. Recurrent IgH translocations, somatic mutations and copy number abnormalities all contribute to myelomagenesis, however true drivers of the disease have not been well defined.To identify new targetable dependencies in MM, we generated high-quality active enhancer landscape using large cohort of primary patient myeloma cells (n=70), MM cell lines, and normal plasma cells. We integrated this data with an in-house curated atlas of 600+ active enhancer profile across a wide range of tumor types and normal tissues. Combining these data with gene expression and genetic dependency (CRISPR KO) enabled a multidimensional integration of how transcriptional regulation intersects with tumor specific dependencies. We identified that many of the specific and potent dependencies in MM are transcription factors, especially those establishing plasma cell identity. Among these, the POU2AF1 gene, which encodes the OCA-B/BOB-1, a B cell transcriptional coactivator protein, represented the most striking dependency in MM. Although BOB-1 is expressed throughout B-cell development, we found it to be highly expressed in CD138+ plasma cells from patients with precursor conditions (MGUS and SMM) as well as symptomatic MM compared to normal plasma cells.To functionally validate the role of BOB-1 in MM, we performed loss-of-function studies using shRNA, siRNAs and antisense GapMers specific for BOB-1 and observed a significant impact on MM cell viability and cell cycle arrest. Transcriptomic analysis upon BOB-1 depletion by RNA-sequencing revealed a small set of genes commonly modulated in all 3 MM cell lines tested including the plasma cell differentiation related transcription factor XBP1 and heme oxygenase (HMOX1). Importantly, we observed ribosome biogenesis, RNA polymerase 1A transcription and mRNA translation and elongation processes to be significantly enriched among genes modulated by BOB-1 depletion in MM cells. Bob1 KD resulted in a rapid and robust decrease in the level of transcription of rDNA by RNA polymerase I as determined by qRT-PCR quantification of pre-rRNA (47S). In addition, ChiP assay revealed decreased binding of RNA polymerase 1A to the 18S ribosomal DNA promoter region in BOB-1 depleted cells compared to control. These data indicate that BOB1 downregulation results in the suppression of RNA-polymerase I activity in MM cells.RNA Pol I-dependent transcription governs abundance of rRNA and directly regulates cellular translational and proliferative capacity. Since high protein load is a feature of MM, we evaluated the role of BOB-1 in the translational efficiency of MM cells. We observed that in MM cells compared to control cells, BOB-1 KD decreased, while its overexpression significantly enhanced de novo protein synthesis. As MM is characterized by excess production of monoclonal immunoglobulins, we evaluated impact of BOB-1 perturbation on intracellular light chains (kappa or lambda) production. We observed changes in the intracellular abundance of the light chains with BOB-1 modulation in all MM cell lines tested. As a result of decreased protein production, BOB-1 depletion was associated with induction of resistance to proteasome inhibition suggesting that high expression of BOB-1 may be one the factors driving the exquisite sensitivity of MM cells to proteasome inhibitor. Interestingly, mass spectrometry analysis revealed BOB1 in a protein complex with mTOR, Raptor and mLST8 proteins which are members of mTORC1 complex which is also involved in ribosomal function and may suggest the mechanism of action of Bob-1 at molecular level.In conclusion, here we report BOB1 as a specific proximal dependency in MM cells with potential role in modulating the protein load/capacity balance and ribosomal biogenesis essential for MM cell protein production function and therefore their sensitivity to proteasome inhibition. DisclosuresShirasaki: FIMECS: Consultancy. Mitsiades: BMS: Research Funding; Nurix: Research Funding; H3 Biomedicine: Research Funding; Novartis: Research Funding; Abbvie: Research Funding; Arch Oncology: Research Funding; Janssen/Johnson & Johnson: Research Funding; Fate Therapeutics: Consultancy, Honoraria; Karyopharm: Research Funding; Sanofi: Research Funding; TEVA: Research Funding; EMD Serono: Research Funding; Adicet Bio: Membership on an entity's Board of Directors or advisory committees; FIMECS: Consultancy, Honoraria; Ionis Pharmaceuticals: Consultancy, Honoraria. Hajek: BMS: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharma MAR: Consultancy, Honoraria. Munshi: Abbvie: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Pfizer: Consultancy; Legend: Consultancy; Bristol-Myers Squibb: Consultancy; Janssen: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; Adaptive Biotechnology: Consultancy; Takeda: Consultancy; Amgen: Consultancy; Novartis: Consultancy.

A Clinically Validated Targeted Capture Panel to Identify Translocations, Copy Number Abnormalities, and Mutations in Multiple Myeloma

A Clinically Validated Targeted Capture Panel to Identify Translocations, Copy Number Abnormalities, and Mutations in Multiple Myeloma

Multiple myeloma from the pathologist's perspective

Multiple myeloma (MM) is one of the most common hematological neoplasms and accounts for approximately 1% of human cancers. Description of current diagnostics and classification of MM and related plasma cell neoplasms from the pathology viewpoint. Current knowledge regarding pathology and genetics of MM is summarized and tissue-based diagnostics following international consensus classifications and the current S3 guideline are described. MM and related neoplasms are composed of malignant plasma cells that secrete amonoclonal immunoglobulin, which is an important parameter of disease activity. MM shows amultistage development. Almost all cases are preceded by aclinically inapparent precursor lesion, monoclonal gammopathy of undetermined significance (MGUS), which can progress to smoldering myeloma with ahigher tumor burden, but absence of organ damage. Systemic MM needs to be discerned from the localized forms, solitary osseous and primary extramedullary plasmacytoma. MM is genetically very heterogeneous and can be broadly subdivided into two cytogenetic groups, cases with primary IGH translocations and cases with hyperdiploidy. Intratumoral genetic heterogeneity is frequently pronounced and correlates with the size of focal lesions in imaging. Diagnosis of plasma cell neoplasms is done according to the criteria of the International Myeloma Working Group (IWMG) and requires interdisciplinary evaluation of clinical, serological, pathological and radiological features. In addition to clinical parameters, molecular markers, especially cytogenetic aberrations, are of great prognostic relevance.

Abstract 2240: Genomic profiling of smoldering multiple myeloma classifies distinct molecular groups

Abstract Background: Multiple Myeloma (MM) is an incurable plasma cell malignancy with significant genomic heterogeneity. It is usually preceded by the asymptomatic stage known as smoldering multiple myeloma (SMM). SMM patients have a 10% annual risk of progression to MM. Genomic alterations that are observed in SMM patients include chromosomal gains and losses, translocations, and point mutations. However, current SMM risk models rely solely on clinical markers that do not accurately capture the progression risk. While incorporating some genomic biomarkers improves prediction, using all MM genomic features to comprehensively stratify patients may increase the precision of risk models. Methods: We obtained a total of 214 patients' samples at SMM diagnosis in the US and Europe. We performed whole exome sequencing on 166 tumors; of these, RNA sequencing was performed on 100. Targeted capture with a MM gene panel was done on an additional 48 tumors. We identified subgroups using binarized DNA features and performing consensus binary non-negative matrix factorization. Results: We identified six clusters (C1-C6) with the following features: four with a hyperdiploidy (HD) (&amp;gt;48 chromosomes) and two with IgH translocations. These subgroups have unique transcriptomic profiles overlapping with known MM signatures and biological pathways. One of the clusters harboring translocation (11;14), which we call C4-CCND1, was enriched with the previously defined CD-2 MM signature that uniquely expresses B cell markers CD20 and CD79A; shows upregulation of CCND1 and E2F7; and is enriched with pathways like DNA replication, heme metabolism, and NFkB signaling. The C3-MS_MF cluster with the IgH translocations (4;14) and (14;16) shows downregulation of ribosomal genes, TRAF2, and DUSP2. The MYC oncogene was highly expressed in the four HD clusters: C1-HD_NRAS, C2-HD_MAFB, C5-HD_KRAS, and C6-HD_1q (BH-P = 0.037). The clusters also showed different outcomes in terms of time to progression (TTP) to active MM (P = 0.005). Median TTP for patients in C2-HD_MAFB, C3-MS_MF, and C5-HD_KRAS was 3.7, 2.6, and 2.2 years, respectively; TTP for C1-HD_NRAS, C4-CCND1, and C6-HD_1q was 4.3, 11, and not reached, respectively. In multivariate analysis, C2-HD_MAFB, C3-MS_MF, and C5-HD_KRAS were independent predictors of progression after accounting for the clinical risk stage. Moreover, the odds of having evolving hemoglobin and monoclonal protein levels in these three clusters were 3.5 and 12.3 times higher than the other clusters, respectively (P = 0.01 and 0.002). Conclusion: We identified six distinct SMM molecular groups with corresponding transcription profiles and dysregulated pathways. These groups have different progression risks to active MM, with three groups being independent predictors of progression. Our results underscore the importance of molecular classification in MM to better understand and target various tumor vulnerabilities. Citation Format: Shankara Anand, Mark Bustoros, François Aguet, Romanos Sklavenitis-Pistofidis, Robert Redd, Benny Zhitomirsky, Andrew J. Dunford, Yu-Tzu Tai, Selina J. Chavda, Cody Boehner, Carl J. Neuse, Tineke Casneuf, Lorenzo Trippa, Chip Stewart, Kwee Yong, Irene Ghobrial, Gad Getz. Genomic profiling of smoldering multiple myeloma classifies distinct molecular groups [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2240.

Abstract 450: A targeted capture panel to identify translocations, copy number abnormalities, and mutations in multiple myeloma

Abstract Multiple myeloma (MM) is a genetically heterogeneous disease where risk stratification and outcomes are associated with translocations of the immunoglobulin (Ig) and MYC loci, copy number abnormalities and mutations. Therefore, we designed a comprehensive MM targeted sequencing panel (MM panel) to investigate the common genomic abnormalities and validated it against known standards. The MM panel includes targeted mutation and translocation panels encompassing ~ 990 kb and ~ 4.7 Mb respectively. The mutation panel includes exons of 228 genes and the translocation panel investigates the structural and copy number changes. The two panels are manufactured separately and combined in a 5:1 ratio to prevent over-sequencing of the larger translocation panel. To validate the MM panel, we performed targeted sequencing on 110 MM patient samples and compared the results to different orthogonal technologies. Libraries were prepared from the DNA extracted from CD138+ bone marrow cells and non-tumor tissue (peripheral blood or saliva) using the KAPA workflow. Following hybridization and amplification the libraries were sequenced using 75 bp paired end sequencing. Sequences were aligned to hg19 and mutations and translocations were identified using Strelka and Manta. Copy number was determined using the ratio of non-tumor to tumor reads in each targeted region. Data was further validated using clinical FISH (copy number and translocations), MLPA (copy number), known standards (mutations), or ddPCR (mutations). Canonical IgH translocations were detected in 33.6% of patients by sequencing which agreed with FISH except for one patient in which a t(11;14) was detected by FISH only. The overall sensitivity and specificity for translocation detection was 97.4% and 100%, respectively. Non-canonical translocations were detected in 14.5% of samples, 43% of which were to the MYC locus. MYC abnormalities were detected in 46.4% of samples. Copy number was determined by sequencing and MLPA for 22 regions that were directly comparable in 103 patient samples and the concordance between the technologies was R2=0.969. For the important prognostic regions, the concordance was R2=0.962 (CDKN2C), R2=0.986 (CKS1B), and R2=0.973 (TP53). Mutation detection validation was performed using samples with known variant allele frequencies (VAF) for common mutations. We were able to determine the sequencing VAF for 74 mutations across 5 samples with a concordance of R2=0.9849 between the expected and observed frequencies. The minimum detected VAF was 1.3% at an average depth of 891x. We also performed ddPCR on 6 patient samples with the common KRAS, NRAS and BRAF mutations with a VAF concordance of R2=0.9983. In summary, we have developed and validated a sequencing panel which is being deployed to clinical laboratories that is relevant to MM patient prognosis, risk stratification, and treatment. Citation Format: Brian Andrew Walker, Aarif Ahsan, Parvathi Sudha, Tasneem Kausar, Sushmita Rane, Erin Flynt, Anjan Thakurta. A targeted capture panel to identify translocations, copy number abnormalities, and mutations in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 450.

High-Resolution Architecture and Partner Genes of MYC Rearrangements in Lymphoma with DLBCL Morphology

High-Resolution Architecture and Partner Genes of MYC Rearrangements in Lymphoma with DLBCL Morphology

MYC Translocations Identified By Sequencing Panel in Smoldering Multiple Myeloma Strongly Predict for Rapid Progression to Multiple Myeloma

IntroductionSmoldering Myeloma (SMM) is a heterogeneous asymptomatic stage between Monoclonal Gammopathy of Unknown Significance (MGUS) and Multiple Myeloma (MM). Risk of progression to MM is 10% in the first 5 years following diagnosis and greatly diminishes thereafter (Kyle et al NEJM 2007). Early intervention in SMM patients at high risk of progression extends survival (Mateos et al NEJM 2013). The IMWG 2014 Updated Criteria establish a subset of SMM patients who are at ultra-high risk for progression to MM within 2 years, and therefore merit treatment (Rajkumar et al Lancet Oncol 2014). Analyses of the genetic and molecular landscape of SMM to date report a near identical picture to MM, however most patients in these studies progress rapidly and are therefore not representative of the entire group. We performed a comprehensive analysis of SMM and MGUS patients to determine markers of high risk of progression that could identify patients to benefit from early treatmentMethodsMGUS not progressing after at least 10 years of follow up and SMM in which follow up data were available were extracted from the Plasma Cell Dyscrasia Biobank. A clinically applicable Custom Capture MM-specific sequencing platform was developed for detection of the most frequently mutated pathways in MM based on analysis of CoMMpass dataset. Coding exons of actionable genes, clinically relevant copy number abnormalities, and regions surrounding IgH (0.5Mb), IgK (0.1Mb), IgL (0.1Mb) and MYC loci (1.6Mb) to identify relevant structural variants (SVs) were included, with combined design 2.2Mb. 12 samples were pre-pooled before capture, and 2 captures were sequenced per lane of Illumina HiSeq4000. Paired-end 150bp reads were mapped to hg19 using BWA-MEM. Single nucleotide variants (SNVs) and small INDELs in capture regions were identified using the GenomeGPS analytic pipeline following Broad GATK variant discovery practices. Copy number variants (CNVs) were identified by patternCNV. SVs of translocations, inversions, large INDELs, and segmental duplications were called by the SnowShoes-SV algorithm developed in-house. False positive SVs, polymorphic SVs, and other artefacts were filtered out using in-house normal SV database.ResultsWe identified and sequenced 128 patients including 32 MGUS patients not progressing after 10 years. Of 96 SMM patients included 36 had not progressed to SMM after minimum follow up of 5 years, while 37 and 23 progressed to MM in less than 2 years and between 2-5 years, respectively. The genetic subtype of each patient was determined and verified by clinical FISH. Proportions in each genetic subgroup in MM and SMM/MGUS were similar, indicating that these are primary genetic lesions occurring early in MM pathogenesis. Median SMM time to progression (TTP) was 46 months. As in other series, HRD with IGH translocation, and t(4;14) predicted shorter TTP.Analysis of CoMMpass dataset found frequent MYC SV (38%) in untreated MM with higher frequency in HRD versus NHRD MM: 53% versus 28% (Misund, ASH 2016). No MYC SV were detected in MGUS cohort, SMM non-progressors at >5 years or SMM progressing between 2-5 years. By contrast, MYC SV were detected in 49% SMM that progressed within 2 years, 55% in HRD and 41% NHRD. SMM with MYC SV had a significantly shorter median TTP compared to patients without MYC SV (11.5 months vs 61 month; p<0.0001). Multivariate analysis with high risk genetic groups and biomarkers for progression (BMPCs >/=60% and FLC ratio 100) confirm MYC SV as an independent variable for progression to MM (hazard ratio=7, 95% confidence interval 3.6-13.7, p=0.00001).RAS and NFKB pathway mutations were observed with similar frequencies in MM and SMM progressing within 5 years of diagnosis, but with lower frequency in those not progressing by 5 years follow up, and were not observed in the MGUS cohort. A trend toward shorter TTP was observed in patients with RAS pathway mutations but did not reach statistical significance.ConclusionIn conclusion, we describe MYC translocations as a genetic marker of and likely cause of progression to MM that are absent in MGUS and SMM with TTP >2 years. In contrast MM and SMM early progressors (TTP <2 years) share a similar genetic landscape. Identification of MYC translocations at diagnosis of SMM predicts short TTP to MM, defining a novel ultra-high risk category that merits validation in prospective clinical trials. [Display omitted] DisclosuresKumar:Skyline: Honoraria; Celgene, Millennium/Takeda, Onyx, AbbVie, Janssen, Sanofi, Novartis, Amgen, Genentech, Merck, Oncopeptides, Roche, Skyline Diagnostics: Research Funding; Celgene, Millennium, BMS, Onyx, Janssen, Noxxon, AbbVie, Amgen, Merck, Oncopeptides, Skyline Diagnostics, Takeda: Consultancy. Dispenzieri:Celgene, Millenium, Pfizer, Janssen: Research Funding. Fonseca:Novartis: Consultancy; Merck: Consultancy; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; AMGEN: Consultancy; Celgene Corporation: Consultancy, Research Funding; Sanofi: Consultancy; Mayo Clinic & Dr Fonseca: Patents & Royalties: Prognostication of myeloma via FISH, ~$2000/year; Jansen: Consultancy; Bristol-Myers Squibb: Consultancy; Bayer: Consultancy; Pharmacyclics: Consultancy; Takeda: Consultancy. Stewart:Bristol-Myers Squibb: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Roche: Consultancy; Amgen: Consultancy.

Definition of a Prognostic Risk-Classifier Based on SNPs Array Analysis of Copy Number Alterations in Newly Diagnosed Transplant-Eligible Multiple Myeloma Patients

BACKGROUND. The genomic heterogeneity that characterizes all Multiple Myeloma (MM) patients (pts) is the consequence of an evolutionary process operating during the pre-neoplastic phase of the disease. Whatever genomic event occurs, it accounts for the de-regulated expression of either one of the cyclin D or other key regulators of cell cycle progression. Therefore, a deficient regulation of cell cycle control is considered as a hallmark of MM. Moreover, among the MM genomic heterogeneity, several lesions are recurrent and their presence significantly impacts the prognosis.AIM. To deeply characterize the MM clone of newly diagnosed MM pts by means of a genomic approach, aimed to identify Copy Number Alterations (CNAs) affecting clinical outcomes.PATIENTS AND METHODS. We analyzed 247 pts who were enrolled in the EMN02/HO95 phase III study and were eligible for randomization to receive standard dose intensification therapy with bortezomib-melphalan-prednisone (VMP) (n=93) or high dose intensification therapy with autologous stem cell transplantation (ASCT) (n=154) after a V-based induction. Genomic data were obtained from all the pts, whose highly purified CD138+ BM plasma cells were profiled by SNPs array. Any CNA ≥50kb was evaluated. At a median follow-up of 34 months (m), the estimated progression-free (PFS) and overall survival (OS) was 63% and 85%, respectively.RESULTS. In order to identify genetically homogeneous subgroups of pts, we first dissected the genomic complexity observed in the overall population. As expected, most pts had a complex genomic background, while occasionally few of them (23/247, 9%) carried only one of the following alterations: CN losses (L) on chr. 13q, CN gains (G) on chr.1q, hyperdiploidy and any IgH translocations. Remarkably, these 4 alterations were also the most frequently observed across the overall pt population, and their combination identified 16 subgroups harbouring a progressively more complex genomic profile. This suggests that these 4 alterations - either combined or alone - are both necessary and sufficient to describe the genomic background of the whole population. Indeed, all the other observed CNAs have a lower frequency and were randomly scattered among the 16 subgroups.When the clinical outcomes of these subgroups were analyzed, it was found that those with inferior outcomes carried at the same time both CN-L on chr.13q and CN-G on chr.1q, regardless of others genomic lesions. Based on this, we re-stratified pts according to the absence or presence of 1 or both of these lesions, to define the following 3 groups: group 1 (64 pts), carrying both CN-L on chr.13q and CN-G on chr.1q; group 2 (94 pts), carrying either CN-L on chr.13q or CN-G on chr.1q; group 3 (89 pts), lacking both these lesions.Providing that pts included in these groups were correctly randomized in a 1:1 ratio to receive either VMP or ASCT, we observed that the 34-m estimates of PFS was significantly shorter in group 1 (48%, 61% and 72% respectively; p=0.0021). OS rates were 72% in group 1 vs 88% in group 2 and 91% in group 3 (p=0.0001).PFS hazard ratio (HR) of pts in group 1 (HR=2,51, 95%CI: 1.48-4.25, p=0.0006) was comparable to that of pts carrying either del(17p) (HR=2.09, 95%CI: 1.20-3.65) or t(4;14) (HR=1.84, 95%CI: 1.14-2.99), resulting as an independent factor in predicting PFS in a Cox multivariate analysis (both from del(17p) and t(4;14), p=0.01). PFS benefit correlated with ASCT in comparison with VMP was statistically significant in groups 2 and 3, while only a trend was observed in group 1 (table 1).The genomic background of pts belonging to group 1 was characterized by the presence of several genomic aberrations, which overall severely compromise genes involved in the control of cell cycle progression (Rb1, CKS1B, MDM4, MCL1, genes coding for the DREAM-complex components, YAP1, MYC, FANCA).CONCLUSIONS. Based on an evolutionary rationale, we proposed a simply, CNAs-based risk-classifier, which was able to segregate our cohort of pts with newly diagnosed MM into 3 well-populated groups, thus recapitulating most of the genomic aberrations commonly described in MM. The 3 groups have different clinical outcomes and PFS benefit imparted from ASCT as compared to VMP. According to the observed genomic background, a strong de-regulation of cell cycle control might be responsible of the dismal outcome of pts carrying both CN-L on chr.13 and CN-G on chr. 1q.Supported by AIRC, Fond. del Monte Bo e Ra [Display omitted] DisclosuresLarocca:Janssen: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; Amgen: Honoraria. Martinelli:Ariad/Incyte: Consultancy; Pfizer: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Johnson&Johnson: Consultancy; Roche: Consultancy. Sonneveld:Celgene, Amgen, Janssen, Karyopharm, Takeda: Consultancy, Honoraria, Research Funding; Celgene Corporation, Amgen, Janssen, Karyopharm, PharmaMar, SkylineDx: Honoraria; Celgene Corporation, Amgen, Janssen, Karyopharm, SkylineDx, PharmaMar: Consultancy.

Age Related Distribution of Cytogenetic Abnormalities in Multiple Myeloma

Introduction . Cytogenetic abnormalities (CA) detected by iFISH are among the most powerful prognostic factors in multiple myeloma (MM). With the advent of an unpreceded therapeutic armamentarium during the last years, a thoroughly assessment of individual patients characteristics is necessary in order to choose the best therapy. Among the former, age is an important biologic feature that stratifies patients with regard to treatment intensity.Aims . To study the distribution of individual CA by iFISH according to different age groups and to evaluate the relationship between age and different cytogenetic profiles.Materials and methods . We retrospectively evaluated 1116 patients (pts) analyzed in our laboratory between 01/2010 and 12/2016 for whom baseline cytogenetics by iFISH was available. iFISH was carried out on CD138 enriched plasma cells combined with immunofluorescent detection of light chain (LC) restricted plasma cells. The following CA were considered: gain(1q21), gain(9q34), del(13q14), del(17p13), t(4;14), t(11;14), t(14;16). Commercially available DNA probes were used according to manufacturer protocols (MetaSystems, Vysis). In house cutoff levels of 15% and 17% were set for chromosomal imbalances and IgH translocations respectively. Patients were stratified into 3 age groups: 1st group ≤ 45 years (y), 2nd group > 45y and ≤ 65y and 3th group > 65y. High risk cytogenetics (HRC) were defined according to IMWG criteria as at least one of the following by iFISH: del(17p), t(4;14) and t(14;16). Pairwise comparisons between subgroups were performed by the Mann-Whitney or Kruskal Wallis test for continuous variables and by Fisher's exact test for categorical variables. All statistical analyses were conducted in R, version 3.0.1.Results . The 1st group comprised 92 (8%) pts, the 2nd 581 (52%) pts and the 3rd 443 (40%) pts. The t(4;14) was detected in 109 (9.8%) pts with higher prevalence in the 2nd and 3rd groups (7.6% vs 10.3% vs 9.5%, p=0.67). The t(11;14) was detected in 198 (18%) pts with a higher prevalence in younger pts (26% vs 18 % vs 16%, p=0.15); age density plots showed two prevalence peaks at 45y and 65y respectively (Fig 1). The t(14;16) was identified in 26 pts (2.3%) and occurred more frequent under 65y (2.7% vs 4.2% vs 1.6%, p=0.11). Gain(9q) was identified in 365 (32%) of 781 evaluable patients occurring less frequently under the age of 45y (22% vs 35% vs 31%, p=0.4). Gain(1q) was detected in 249 (22%) pts with a trend towards higher prevalence in pts over 45y (14% vs 23% vs 23%, p=0.09). Del(17p) was detected in 153 pts (14%) slightly more frequent in the 2nd age group (13% vs 15% vs 12%, p=0.4). Del(13q) was more frequent in the 2nd group (32% vs 42% vs 37%, p=0.12).Next, we analyzed the distribution of HRC according to age category and identified 36 (21%) pts in the 1st group, 188 (26%) pts in the 2nd group and 119 (22%) pts in the 3rd group (p= 0.21). If gain(1q) was added to the HRC profile, the distribution of the HRC between groups differed significantly (27% vs 40% vs 34%, p=0.012).For the entire cohort, we further looked how t(4;14) and t(11;14) co-occur with gain(1q) and del(17p). Overall, 38% of the patients with t(4;14) had a gain(1q) (OR 2.8, p< 0.001). Conversely, no significant relation was detected for t(11;14) and for both translocations and del(17p). An inverse relation was found for del(17p) and gain(1q), with only 22% of pts with del(17p) harboring gain(1q) (OR 0.59, p=0.03). An interesting observation was the distribution of the k and λ LC across different CA. We found a significantly higher prevalence of k LC in MM with t(11;14) (60%, p=0.015), gain(1q) (54%, p=0.001) and HRC (67%, p<0.001). Regarding age, no significant difference was identified for the frequency of one type LC or another between age groups (p=0.978).Conclusion. In line with previous data,our study on a large unselected patient cohort suggests an age dependent distribution of CA. Though not reaching statistical significance, t(11;14) tends to occur more often in younger pts. The HRC profile is found more frequently in pts between 45y and 65y . Adding gain(1q) to the HRC panel delineates this group more clearly. Still, the prognostic value of 1q in the era of novel agents is controversial and might be related to the strong association with t(4;14). [Display omitted] DisclosuresKnop:Takeda: Consultancy.

The Cytogenetic Aberrations and Their Prognostic Value in 181 Untreated Patients with Lymphoplasmacytic Lymphoma/ Waldenström Macroglobulinemia in China

Background: lymphoplasmacytic lymphoma/ Waldenström macroglobulinemia (LPL/WM) is a rare B cell proliferative malignancy characterized by immunoglobulin M monoclonal gammopathy and /or bone marrow infiltration by lymphoplasmacytic cells. Cytogenetic aberrations are now the main prognostic predicators in some B-NHLs such as CLL. However, their prognostic valve in LPL/WM remains controversial and recurrently chromosomal abnormalities have rarely been reported. Furthermore, the genetic basis of LPL/WM in China is also unclear.Methods: A panel of DNA probes was used to detect cytogenetic aberrations by fluorescence in situ hybridization (FISH), including RB1/D13S25 at 13q14, ATM at 11q22, TP 53 at 17p13, CEP12 and IGH translocation at 14q32, MYB at 6q23. Chromosomes were identified by G-banding and karyotypes were described according to the International System for Human Cytogenetics Nomenclature (ISCN, 1995). Totally, 181 untreated LPL/WM patients were enrolled in this study.Results: The median age of 181 patients was 61 years (range 32-87). The male to female ratio was 2.75 (133/48). 90% and 15.7% patients showed an elevated serumβ2 microglobulin and LDH. The percentage of hepatomegaly, splenomegaly, lymphadenopathy and B symptom were 15.3%, 35.2%, 50% and 27.3%, respectively. Almost half patients were in the high risk ISSWM group. The chromosomal karyotypes were successful in 153/181 (84.5%) cases, of which 15 patients showed clonal abnormalities. 8 of the 15 patients with abnormal chromosome were complex. The main aberrations of chromosomal karyotypes were 6q deletion (3/15, 20%), and loss of sex chromosomes (3/15, 20%). The other abnormalities include trisomy 12, trisomy 4, trisomy 3, 20q deletion, 17p deletion and so on. All the 6q deletions patients were in the complex karyotype group. Moreover, the trisomy 12 detected by FISH were always accompanied with chromosomal karyotypes abnormalities. Of 181 patients, 139 patients had FISH detection, of which 25 patients (18%) had FISH abnormalities. The most common aberrations were 6q deletion (6/28, 21.4%), trisomy 12 (5/59, 8.5%), 17p deletion (8/131, 6.1%). 13q deletion, gain 1q21and 11qdeletion were 4.6% (6/130) and 2.8% (3/36) and 2% (2/99), respectively. About 5.4% (7/130) patients had IGH gene translocation. Although it was higher in our study, this aberration always accompanied with other clones. Besides, 17p deletion was also more frequent in complex clone group, while trisomy 12 was more common in the single clone group. In LPL/WM, the chromosomal abnormities was an adverse predictor for both progress-free survival (PFS) and overall survival (OS). The median PFS and OS for patients with this abnormity was 62 months (62m vs 69m, p=0.022) and 75 months (75m vs 109m, p=0.033), which was significantly higher than normal patients. In different FISH groups, only TP 53 deletion had a poor effect on both PFS and OS in LPL/WM patients. The median PFS and OS were significantly shorter than those without the abnormality (median PFS 34m vs 77m, p=0.008; median OS 34m vs 135m, p=0.006). However, the 6q deletion and trisomy 12 did not significantly influence both PFS and OS. In addition, we found that the number of different clones had an effect on the survival of patients. The complex clone group showed shorter PFS and OS than the single clone group (p<0.05).Conclusion: Although the detection of cytogenetic aberration is rare in Chinese patients, it plays an essential role in diagnosis and prognostication. DisclosuresNo relevant conflicts of interest to declare.