Chng, Wee Joo

Abstract Introduction: A number of cytogenetic abnormalities (CAs) are associated with poorer prognosis in MM, including del(17p), t(4;14), t(14;16), and amp1q21. There is a general consensus that treatment with proteasome inhibitors (PIs) benefits pts carrying these CAs (Sonneveld Blood 2016). This meta-analysis of four phase 3 studies assesses PFS benefit in pts receiving the oral PI ixa vs pbo regarding the specific adverse CAs. Methods: Pts in TOURMALINE-MM1 (N=722; relapsed/refractory MM; Moreau N Engl J Med 2016) and MM2 (N=705; newly diagnosed MM; Facon Blood 2021) received ixa plus lenalidomide-dexamethasone (Rd) vs pbo-Rd (1:1). Pts in TOURMALINE-MM3 (N=656; Dimopoulos Lancet 2019) and TOURMALINE-MM4 (N=706; Dimopoulos J Clin Oncol 2020) received ixa vs pbo (3:2) as maintenance following autologous stem cell transplant or as post-induction maintenance in transplant-ineligible pts, respectively. In TOURMALINE-MM1/MM2, CAs were centrally assessed on CD138 positive sorted cells from bone marrow samples collected at study entry using fluorescence in situ hybridization (FISH). Cutoff values for defining the presence of del(17p), t(4;14), and t(14;16) were 5%, 3%, and 3% positive cells, respectively, based on the false-positive rates (technical cutoffs) of the FISH probes used, and cutoff values of 3% (MM1) and 20% (MM2) were used for amp1q21. In TOURMALINE-MM3/MM4, cytogenetic assessment was performed locally using FISH or conventional karyotyping with locally defined thresholds for positivity. Results: 270/1227 (22%) vs 227/1019 (22%) evaluable pts receiving ixa-based vs pbo-based therapy had high-risk CAs [del(17p), t(4;14), t(14;16)]: 75 vs 62 in MM1, 60 vs 63 in MM2, 61 vs 54 in MM3, and 74 vs 48 in MM4. 957/1227 (78%) vs 792/1019 (78%) had complementary standard-risk CAs: 200 vs 216 in MM1, 231 vs 234 in MM2, 252 vs 152 in MM3, and 275 vs 190 in MM4. 555/1142 (49%) vs 479/955 (50%) evaluable pts receiving ixa-based vs pbo-based therapy had expanded high-risk CAs (high-risk CAs ± amp1q21): 155 vs 154 in MM1, 134 vs 146 in MM2, 116 vs 88 in MM3, and 150 vs 91 in MM4. 587/1142 (51%) vs 476/955 (50%) had complementary standard-risk CAs: 122 vs 126 in MM1, 164 vs 153 in MM2, 154 vs 89 in MM3, and 148 vs 108 in MM4. After a median follow-up in the pooled analysis of 25.6 months (mos; 12.7, 54.6, 29.7, and 21.3 mos in MM1, MM2, MM3, and MM4, respectively), the hazard ratio (HR) for PFS with ixa-based vs pbo-based therapy in pts with high-risk CAs was 0.74 (95% confidence interval [CI] 0.59-0.93; median 17.8 vs 13.2 mos) and 0.70, (95% CI 0.62-0.80; median 26.3 vs 17.6 mos) in pts with standard-risk CAs. In the subgroup analyses of expanded high-risk CAs, the HR for PFS with ixa-based vs pbo-based therapy in pts in the expanded high-risk group was 0.75 (95% CI 0.64-0.87; median 18.1 vs 14.1 mos; Figure 1) and 0.71 (95% CI 0.59-0.85; median 36.1 vs 21.4 mos) in the complementary standard-risk group. Analyses of PFS according to the presence of individual CAs (Figure 2) indicated differing magnitudes of PFS benefit. Notably, in pts with t(4;14) (n=124 vs n=102), the HR for PFS with ixa-based vs pbo-based therapy was 0.68 (95% CI 0.48-0.96; median 22.4 vs 13.2 mos), while for pts with amp1q21 (n=380 vs n=312), the HR was 0.77 (95% CI 0.63-0.93; median 18.8 vs 14.5 mos) and for pts with del(17p) (n=141 vs n=107) the HR was 0.80 (95% CI 0.59-1.09; median 15.7 vs 13.2 mos). Conclusions: This pooled analysis demonstrated a PFS benefit with ixa-based therapy vs pbo-based therapy regardless of the presence of specific adverse CAs, with a similar magnitude of benefit in pts with (expanded) high-risk CAs and the respective complementary standard-risk groups. However, due to the differences in study eligibility criteria and pt populations, ixa combined with Rd or as single-agent maintenance therapy may not abrogate the negative impact of high-risk CAs. Analyses of PFS in subgroups with specific CAs indicated that the greatest magnitudes of benefit (lowest HRs) with ixa-based vs pbo-based therapy were in pts with t(4;14) (HR 0.68) and pts with amp1q21 (HR 0.77), suggesting that the improved outcome with ixa-based vs pbo-based therapy in the expanded high-risk subgroup was primarily driven by PFS differences in pts with these more common CAs. Further study is needed, and additional sensitivity analyses will be presented in subsequent publications. Figure 1 Figure 1. Disclosures Chng: BMS/Celgene: Honoraria, Research Funding; Amgen: Honoraria; Takeda: Honoraria; Abbvie: Honoraria; Sanofi: Honoraria; Pfizer: Honoraria; Johnson and Johnson: Honoraria, Research Funding. Lonial: BMS/Celgene: Consultancy, Honoraria, Research Funding; AMGEN: Consultancy, Honoraria; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Merck: Honoraria. Morgan: Takeda: Honoraria. Iida: Amgen: Research Funding; Daiichi Sankyo: Research Funding; Glaxo SmithKlein: Research Funding; Ono: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Chugai: Research Funding; Abbvie: Research Funding; Janssen: Honoraria, Research Funding; Bristol-Myers Squibb: Research Funding. Moreau: Sanofi: Honoraria; Celgene BMS: Honoraria; Abbvie: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Oncopeptides: Honoraria. Kumar: Bluebird Bio: Consultancy; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Novartis: Research Funding; Oncopeptides: Consultancy; Tenebio: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Twumasi-Ankrah: Takeda: Current Employment. Kumar: Takeda: Current Employment, Current holder of stock options in a privately-held company. Dash: Takeda: Current Employment, Current equity holder in publicly-traded company. Vorog: Takeda: Current Employment. Zhang: Takeda: Current Employment. Suryanarayan: Takeda: Current Employment. Labotka: Takeda: Current Employment. Dimopoulos: Janssen: Honoraria; Takeda: Honoraria; Beigene: Honoraria; BMS: Honoraria; Amgen: Honoraria. OffLabel Disclosure: Use of the oral proteasome inhibitor ixazomib for the initial treatment of multiple myeloma and as maintenance treatment following stem cell transplantation or induction therapy in newly diagnosed patients

Abstract Background: Two global, randomized, placebo (pbo)-controlled phase 3 studies of single-agent ixazomib (ixa) maintenance therapy are currently ongoing for newly diagnosed MM patients following primary therapy that included autologous stem cell transplantation (ASCT) (MM3, NCT02181413) or excluded ASCT (MM4, NCT02312258). Both trials have demonstrated statistically significant and clinically meaningful improvement in their primary endpoint of progression-free survival (PFS): for MM3, median 26.5 months (mos) ixa vs 21.3 mos pbo (hazard ratio [HR] 0.720, 95% confidence interval [CI] 0.582-0.890, P=0.002); for MM4, median 17.4 mos for ixa vs 9.4 mos for pbo (HR 0.659, 95% CI 0.542-0.801, P<0.001). Data for the key secondary endpoint, OS, have not previously been published. Methods: Full methods have previously been reported (Dimopoulos, Lancet 2019; Dimopoulos, J Clin Oncol 2020). Eligible patients (MM3, N=656; MM4, N=706) were randomized 3:2 to receive maintenance therapy with single agent ixa or pbo for a maximum of approximately 24 mos (26 cycles, to the nearest complete cycle) or until progressive disease or unacceptable toxicity, whichever occurred first. Results: At the most recent data cut-off (MM3, 29 January 2021; MM4, 15 October 2020), with median follow up of 64 mos and 36 mos, respectively, 27% (MM3, 174/656) and 29% (MM4, 203/706) of the intention-to-treat (ITT) population had OS events. In MM3, the 5-year Kaplan-Meier estimate for OS was 74% for ixa and 73% for pbo, though the median OS had not yet been reached in either arm (HR 1.008, 95% CI 0.744-1.367, P=0.958; Figure). In MM4, the 5-year Kaplan-Meier OS estimate was 55% for ixa and 56% for pbo, though the median OS had also not yet been reached in either arm (HR 1.136, 95% CI 0.853-1.514, P=0.382; Figure). No new safety signals were identified, and the incidence of new primary malignancies in both studies was similar between ixa and pbo. Conclusions: These most current OS data for MM3 and MM4 have not demonstrated a statistically significant difference for the ixa or the pbo arm to date. After 64 mos of follow-up in MM3, the risk of OS does not differ between the study arms. After 36 mos of follow-up in MM4, the OS HR shows a trend that favors the pbo arm. Because interim analyses of OS may be overrepresented by deaths in patients who did not benefit from maintenance therapy, it is not known to what extent these results will be reflective of the ITT population at the time of the final analyses. As treatment options, including anti-CD38 mAb and other new mechanisms of action, for salvage therapies following progression continue to expand, OS is increasingly being confounded by subsequent therapies. Hence, demonstrating OS advantage for early line MM therapies is becoming increasingly challenging. OS data continue to be collected in these studies for later analyses. Figure 1 Figure 1. Disclosures Dimopoulos: Takeda: Honoraria; Amgen: Honoraria; Beigene: Honoraria; Janssen: Honoraria; BMS: Honoraria. Lonial: AMGEN: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding; Merck: Honoraria; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria. Chng: Johnson and Johnson: Honoraria, Research Funding; BMS/Celgene: Honoraria, Research Funding; Takeda: Honoraria; Abbvie: Honoraria; Sanofi: Honoraria; Pfizer: Honoraria. Iida: Takeda: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Ono: Honoraria, Research Funding; Chugai: Research Funding; Celgene: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; Daiichi Sankyo: Research Funding; Glaxo SmithKlein: Research Funding; Amgen: Research Funding; Abbvie: Research Funding; Bristol-Myers Squibb: Research Funding. Mateos: Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Kumar: Takeda: Current Employment, Current holder of stock options in a privately-held company. Suryanarayan: Takeda: Current Employment. Vorog: Takeda: Current Employment. Fergus: Takeda: Current Employment. Labotka: Takeda: Current Employment. OffLabel Disclosure: Use of the oral proteasome inhibitor ixazomib as maintenance treatment for multiple myeloma following stem cell transplantation or induction therapy in newly diagnosed patients.

Abstract Introduction: Belantamab mafodotin (belamaf) is a B-cell maturation antigen (BCMA)-targeting antibody-drug conjugate approved in the United States (US) and Europe as a monotherapy for triple-class refractory adult patients with relapsed or refractory multiple myeloma (RRMM). This hypothesis-generating post-hoc analysis of DREAMM-2 trial (NCT03525678) data examined relationships between corneal exam findings (superficial punctate keratopathy and/or microcyst like epithelial changes), best-corrected visual acuity (BCVA), and direct patient-reported ocular symptoms per the Ocular Surface Disease Index (OSDI) questionnaire. This approach could provide insight into the relationship between corneal exam findings, BCVA, and ocular symptoms and their impact on quality of life to help determine if BCVA decline and symptoms could guide dosing. Currently, in the US, eye exams with eye-care professionals (ECPs) are required for each belamaf treatment, which can add to patients' therapy-related burden. Identifying a surrogate marker for results from corneal exam findings would help providers determine if dosing adjustments are necessary. Methods: Eye exams (including a corneal exam and BCVA assessment using the Snellen chart) were performed on all patients receiving single-agent belamaf (2.5 mg/kg) by ECPs at baseline (BL) and before each dose, administered q3w. Corneal exam findings (keratopathy) and BCVA were assessed per protocol-defined criteria, and grade (GR) assessment was based on the worst finding in the worse eye. BCVA and keratopathy grading were relative to BL. Patient-reported ocular symptoms and vision-related functioning, as per the OSDI, were used to evaluate the impact of treatment-related ocular toxicity. The OSDI is a patient-reported outcome questionnaire that assesses eye symptoms and effects on vision-related function in the past week and was performed in all patients before each belamaf dose. Items 1-5 address the frequency of eye-related symptoms (eg, painful or sore eyes, blurred vision) while items 6-9 address the frequency of functional limitations (eg, driving at night or reading). OSDI was considered positive, clinically meaningful, and potentially associated with treatment when at least one question 1-5 (ie, sensitivity to light, gritty or painful eyes, blurred or poor vision) was reported as experienced "all of the time" and at least one question 6-9 (ie, driving at night, reading, working with PC, or watching TV) was reported as experienced "most of the time." Results: Overall, GR 3-4 (severe) keratopathy was observed only 5% of the time in patients who did not report frequent ocular symptoms as measured by the OSDI questionnaire (no items 1-9 ≥ "most of the time"). A further breakdown of the questions revealed that, in patients who reported no items 1-5 "all of the time" AND no items 6-9 ≥ "most of the time" (OSDI negative), GR 3-4 keratopathy was observed only 6% of the time (Table). When considering individual OSDI items, in patients who reported "no deterioration from BL" for any of the OSDI eye-related symptoms or functional limitations, GR 3-4 keratopathy was observed ~3%-7% of the time while GR 0-2 (mild) keratopathy was observed ~23%-34% of the time. Similar results were observed in patients with BCVA ≤20/30 at BL who reported "no deterioration from BL" for any eye-related adverse events (AEs) or functional limitations (GR 3-4 keratopathy: ~2%-6% of the time; GR 0-2 keratopathy: ~19%-28% of the time); patients with worse visual acuity at BL (BCVA >20/30) who reported "no deterioration" for items 1-9 had lower incidence of GR 3-4 and GR 0-2 keratopathy (~0%-1% and ~3%-8%, respectively). Conclusions: The results from this hypothesis-generating post-hoc analysis suggest that hematologists/oncologists may be able to use clinical indicators/tools (eg, ocular symptoms, the OSDI tool) as potential surrogate markers for eye exam results to help determine whether dosing changes are needed. This approach will be explored in trials with other belamaf dose regimens that are currently under evaluation. If the results are validated, it may be possible for hematologists/oncologists to manage belamaf dose modifications, due to ocular AEs, without a confirmatory eye exam by the ECP, reducing the patient burden. Funding Source: GSK (205678). Drug linker technology licensed from Seagen; monoclonal antibody produced using POTELLIGENT Technology licensed from BioWa. Figure 1 Figure 1. Disclosures Popat: Takeda: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; AbbVie, BMS, Janssen, Oncopeptides, and Amgen: Honoraria; Abbvie, Takeda, Janssen, and Celgene: Consultancy; Janssen and BMS: Other: travel expenses. Badros: GlaxoSmithKline: Research Funding; BMS: Research Funding; Janssen: Research Funding; J&J: Research Funding. Kumar: Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; BMS: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Oncopeptides: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Merck: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Rodríguez-Otero: Regeneron: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Kite: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel and other expenses. Cohen: BMS: Research Funding; GlaxoSmithKline: Other: Personal fees and other association with, Research Funding; Novartis: Research Funding; Celgene: Honoraria, Other: Personal fees and other association with; Janssen: Honoraria; Kite Pharma: Honoraria; Oncopeptides: Honoraria; Seattle Genetics: Honoraria; Takeda: Honoraria. Manier: Regeneron: Consultancy, Research Funding; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; Celgene - Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Voorhees: Secura Bio: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Gay: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Bluebird Bio: Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria. Rifkin: Takeda: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Fresenius-Kabi: Membership on an entity's Board of Directors or advisory committees; Coherus: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb (Celgene): Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; McKesson: Current Employment, Current equity holder in publicly-traded company; Karyopharm: Membership on an entity's Board of Directors or advisory committees. Martin: Janssen: Research Funding; Sanofi: Research Funding; Oncopeptides: Consultancy; Amgen: Research Funding; GlaxoSmithKline: Consultancy. Chari: Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Research Funding; GlaxoSmithKline: Consultancy, Membership on an entity's Board of Directors or advisory committees; Secura Bio: Consultancy, Membership on an entity's Board of Directors or advisory committees; Shattuck Labs: Consultancy, Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Research Funding; Pharmacyclics: Research Funding; Millenium/Takeda: Consultancy, Research Funding; Sanofi Genzyme: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS/Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Weisel: Bristol Myers Squibb: 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; Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy; Novartis: Honoraria; Pfizer: Honoraria. Farooq: Five Prime Therapeutics/Amgen: Consultancy; GlaxoSmithKline: Consultancy. Jeng: OysterPoint: Consultancy; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy; Eyegate: Current equity holder in publicly-traded company. Chng: Abbvie: Consultancy; GlaxoSmithKline: Consultancy; Takeda: Consultancy; BMS/Celgene: Consultancy, Research Funding; Sanofi: Consultancy; Novartis: Research Funding; Johnson & Johnson: Consultancy, Research Funding; Amgen: Consultancy; Antengene: Consultancy; Pfizer: Consultancy; Aslan: Research Funding. Lee: Takeda Pharmaceuticals: Consultancy, Research Funding; Oncopetides: Consultancy; Sanofi: Consultancy; GlaxoSmithKline: Consultancy, Research Funding; Legend Biotech: Consultancy; Karyopharm: Consultancy; Janssen: Consultancy, Research Funding; Genentech: Consultancy; Celgene: Consultancy; Bristol Myers Squibb: Consultancy; Amgen: Consultancy, Research Funding; Regeneron: Research Funding. Berdeja: BMS: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Celularity: Research Funding; CRISPR Therapeutics: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Kite Pharma: Consultancy; Legend Biotech: Consultancy; SecuraBio: Consultancy; EMD Serono: Research Funding; Genentech: Research Funding; GlaxoSmithKline: Research Funding; Ichnos Sciences: Research Funding; Incyte: Research Funding; Novartis: Research Funding; Poseida: Research Funding; Bluebird bio: Consultancy, Research Funding; Astex Pharmaceuticals: Research Funding; Amgen: Research Funding; Abbvie: Research Funding; Takeda: Consultancy; Sanofi: Research Funding; Acetylon: Research Funding; Teva: Research Funding; Lilly: Research Funding. Jadhav: GlaxoSmithKline: Current Employment, Current equity holder in publicly-traded company. Tosolini: GlaxoSmithKline: Current Employment, Current equity holder in publicly-traded company. Eliason: GlaxoSmithKline: Current Employment, Current equity holder in publicly-traded company. Palumbo: GlaxoSmithKline: Current Employment, Current equity holder in publicly-traded company. Dimopoulos: Beigene: Honoraria; BMS: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Takeda: Honoraria. Lonial: Merck: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; BMS/Celgene: Consultancy, Honoraria, Research Funding; AMGEN: Consultancy, Honoraria; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Trudel: Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Amgen Canada: Honoraria; Sanofi: Honoraria; Celgene: Consultancy, Honoraria, Research Funding; GlaxoSmithKline: Consultancy, Research Funding; Janssen: Honoraria, Research Funding; Genentech: Research Funding; Karyopharm: Honoraria. Richardson: Sanofi: Consultancy; Celgene/BMS: Consultancy, Research Funding; Protocol Intelligence: Consultancy; GlaxoSmithKline: Consultancy; Secura Bio: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy, Research Funding; Janssen: Consultancy; Oncopeptides: Consultancy, Research Funding; Regeneron: Consultancy; AstraZeneca: Consultancy; Takeda: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding. Terpos: Celgene: Consultancy, Honoraria, Research Funding; Genesis: Consultancy, Honoraria, Research Funding; GSK: Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; BMS: Honoraria; Janssen-Cilag: Consultancy, Honoraria, Research Funding; Novartis: Honoraria; Takeda: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding.

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 Background: Thalidomide is an active anti-myeloma agent with single agent activity in all stages of the disease. When combined with dexamethasone disease response is seen in nearly two-thirds of patients with newly diagnosed MM. Though initially evaluated for treatment because of its anti-angiogenic properties and the finding of increased bone marrow angiogenesis in MM, it has become clear that thalidomide exerts its anti-myeloma activity through several different mechanisms. While the mechanism of action of dexamethasone has been studied to a great extent in the setting of myeloma, the molecular basis for the activity of this combination is largely unknown. Methods: Myeloma cells from patients with newly diagnosed MM who were enrolled in a phase III trial (ECOG E1A00) comparing thalidomide and dexamethasone combination (T+D) with dexamethasone alone (D) were studied by gene expression profiling. Samples from diagnosis were compared to those at four months following therapy to study the effect of treatment. Four patients who achieved a partial response with T+D were studied and in addition compared to four patients achieving a partial response with D alone. Plasma cells from bone marrow aspirates were separated by magnetic bead selection of CD138 positive cells and studied using Affymetrix HG-U133A chips using standard methodology. The arrays were analyzed using Genespring 7.2 software following GCRMA normalization and genes with differential expression between the two datasets were examined. Differentially expressed genes were further analyzed using Ingenuity Pathways Analysis program Results: 549 genes were two fold or more differentially expressed between the pretreatment and post treatment samples in the T+D group, of which 275 genes were mapped to different networks using the Ingenuity program. Examination of the canonical pathways demonstrated several pathways that were altered as a result of the therapy. The most significant pathways included those related to immune function including antigen presentation (multiple HLA class II antigens), and PRG2 (NK cell activator). Several mediators of B cell signaling including CD45, PKC (α ,β), SHP2, and Erk1/2 were up regulated following treatment. Increase in the expression of several adhesion molecules including β integrins, fibronectin, VCAM1, L selectin, and LFA3 were noted. Up regulation of IL-6 signaling pathway including gp130, JAK2 and IL8 were noted following therapy. Striking increase in the gene expression for CXCR4 and its ligand SDF-1α was noted as well. 129 genes were differentially regulated by dexamethasone alone, of which 67 were mapped to different networks. The pathways influenced by the dexamethasone alone differed significantly from that of the combination. Conclusion: This exploratory analysis offers an interesting insight into the potential mechanisms of action of the T+D combination in MM. The up regulation of immune response related genes are in accordance with some of the mechanisms described for thalidomide. Also, the differences observed between the patients receiving T+D vs. D allows for assessment of the effects of thalidomide. These findings need confirmation in a larger study.

Abstract Background: The p53 tumor suppressor gene has a common sequence polymorphism that results in either proline or arginine at amino-acid position 72. The Pro72 and Arg72 variants have been reported to differ in its functional activity. The Arg72 variant induces apoptosis more efficiently than Pro72 variant by its greater ability to localize to the mitochondria and increase the release of cytochrome c into the cytoplasm. In addition, recent studies have demonstrated that Arg72 variant was a better suppressor of cellular transformation, an activity believed to rely on the pro-apoptotic function of p53. Moreover, the Pro72 variant has been associated with a higher incidence of tumors. Aim: To evaluate the effect of the polymorphic variants of codon 72 and clinical outcome in patients with plasma cell malignancies. Patients and Methods: We analyzed 79 patients with plasma cell malignancies seen at Mayo Clinic between 2000 and 2003. Genomic DNA was extracted from CD138+ sorted plasma cell from bone marrow aspirates. PCR amplification of codon 72 and posterior sequencing was used for the analysis. Results: A total of 79 patients were analyzed. Thirty-four patients (34%) were heterozygous for p53, 57 (59%) homozygous for Arginine and 6 (6%) homozygous for Proline. The distribution among disorders was as follow, 52 patients had MM, 14 patients with SMM and 13 with MGUS. Among patient with MM 25% were Pro/Arg heterozygous, 71 % were Arg/Arg homozygous and 3.8% Pro/Pro homozygous. Survival data among MM patients and genotype were analyzed to Kaplan- Meier method. No significant differences were found among patients who carried homozygous (72R) or heterozygous genotype and overall survival. We exclude the analysis in MGUS and SMM for a low number of patients available. Conclusions: These findings indicate that codon 72 arginine p53 may not be associated with a prolonged survival in patients with Multiple Myeloma, but further study is needed to assess whether this polymorphism is associated with progression of MGUS to MM, age of onset, clinical manifestations, response to treatment etc.

Abstract Cancer/testis antigens (CTAs), comprising the MAGE, CTAG, SSX and GAGE families, are expressed in different tumor types and restricted in normal tissues to germ cells of the testis. Many CTAs contain epitopes recognized by cytotoxic T cells and are potential targets for active immunotherapy. In MM, different CTAs have been shown to be expressed in cell lines and patient cells, and are associated with more proliferative and advance stage tumors. However, correlation with survival has never been reported. We undertook a global survey of CTA expression using gene expression profiling of CD138-enriched plasma-cell (PC) RNA in 15 normal, 101 MM, 22 MGUS and 24 SMM samples using the Affymetrix U133A chip (Affymetrix, Santa Clara, CA). 22 CTA genes were differentially expressed across the samples and unsupervised clustering using these genes clearly identifies a group of patients with high CTA expression. Most CTAs have significantly higher expression in MM as compared to SMM and especially MGUS, which has similar expression as normal PCs. As these antigens are not expressed in normal PCs, an upper limit of normal expression (ULN) was derived based on mean+3SD of expression in normal PCs for each CTA. A strict cut-off of normalized expression value greater than 2xULN was used to assign positive expression for each CTA genes. Using this method, the most commonly expressed CTAs are MAGE-A3 (73% of MM), MAGE-C1 (45%), MAGE-A6 (35%), SSX-1 (21%), GAGE-5 (18%) and NY-ESO-1 (14%). We then assigned patients with expression of more than 2 of these genes as having a CTA signature and correlated with clinical parameters. 45 patents (41 MM and 4 SMM) have the CTA signature. These patients have a significantly higher PCLI (median 0.2 v 0.7, p=0.0003). In fact, there is a significant correlation between the number of positive CTAs and PCLI (r=0.59, p&lt;0.0001). Interestingly, there is no association between patients with a CTA signature and any of the recurrent genetic abnormalities (IgH translocations, chromosome 13 deletion and TC classes), yet MM patients with this signature have a significantly shorter survival (median 459 days vs not reached, log-rank p=0.017). A prognostic hierarchy exists amongst these CTAs. Only MAGE-A6, MAGE-A12, SSX-1 and SSX-5 expression has significant prognostic implications with the SSX family conferring the worse prognosis. Using a restricted panel of 3 CTAs (SSX-1, -5 and MAGE-A12), about 28% of MM patients expressing one or more of these genes can be identified with poor survival (median less than 1 year) that is independent of genetic subtypes. The genes differentially expressed between patients with and without the CTA signature are mainly involved in cell cycle regulation. Since the expression of this large set of CTAs appears to be under epigenetic control, we speculate that the same epigenetic processes that lead to dysregulation of the cell cycle also cause ectopic expression of CTA genes. As CTA expression is rare in MGUS, epigenetic processes may therefore also mediate transformation from MGUS to MM. These poor prognosis patients represent good candidates for novel therapies targeting the epigenetic machinery.

Abstract Hyperdiploid myeloma (H-MM) affects about 50% of MM. These patients exhibit significant karyotypic and clinical heterogeneity. In this study, we addressed possible biological heterogeneity within H-MM by gene expression profiling of CD138-enriched plasma-cell RNA from 53 H-MM patients using the Affymetrix U133A chip (Affymetrix, Santa Clara, CA). Analysis was performed using GeneSpring 7 (Agilent Technologies, Palo Alto, CA). Unsupervised hierarchical clustering performed using the top 100 most variable genes (generated by ANOVA) identifies 4 putative patient clusters. These clusters were reproduced using principal component analysis. Cluster 1 was characterized by high expression of a large group of cancer testis antigens and mitosis/proliferation related genes (TOP2A, NEK, ASPM, CENPA). Cluster 2 was characterized by high expression of genes involved in IL-6 and HGF signaling (MET, IL6R, SOCS3, SPINT1). Cluster 3 was characterized by high expression of genes involved in TNF/NF-KB signaling and anti-apoptosis (NFKB2, CFLAR, BIRC3, TNFAIP3, RRAS2). Cluster 4 was characterized by high expression of genes involve in angiogenesis (protocadherin, EDNRB). Unsupervised hierarchical clustering using the same set of genes in an independent cohort of H-MM patients (n=60) yielded the same 4 patient clusters over-expressing similar genes. The gene expression profile of these clusters were not driven by differences in trisomies (only about 25% of genes that define the clusters were located on the commonly trisomic chromosomes). Association between the 4 clusters and clinical parameters such as survival, chromosome 13 deletion (Δ13), presence of IgH translocations, PCLI, RAS mutation and p16 methylation was analyzed. Cluster 1 tumors were more proliferative (median PCLI 3.8, p&lt;0.05). Cluster 2 was associated with presence of Δ13 (56%, p&lt;0.05) although none of the genes that defined this cluster falls on chromosome 13. p16 methylation was also less common in cluster 2 (13%, p=0.06). Cluster 3 was associated with low PCLI (median 0.2, P&lt;0.05). Most of the patients with p16 methylation also belonged to this cluster (67%, p=0.06). There was a complete absence of Δ13 in Cluster 4. Patients in the 4 clusters also had significantly different survival (log-rank p=0.002.). The difference in survival was independent of Δ13 since Δ13 has no impact on survival in this patient cohort. The molecular profiles of these subclasses may explain some of these associations. CTA expression is associated with proliferative tumors with poor prognosis. IL-6 is an important survival factor and HGF signaling has been associated with poor survival in MM which may explain the relative poor prognosis of this group. Cluster 3 may have better survival as it is associated with an anti-apoptotic signature rather than proliferative signature. In summary, gene expression profiling identified 4 sub-classes within H-MM (validated on an independent dataset and using different clustering techniques) with distinct clinical and biological associations. The gene signature associated with each sub-classes provide a molecular basis for the different clinical behaviour and further insights into deregulated pathways in H-MM.

Abstract Hyperdiploid (&gt;48 chromosomes) multiple myeloma (H-MM) and high hyperdiploid (&gt;50 chromosomes) acute lymphoblastic leukemia (H-ALL) are characterized by aneuploidy and multiple recurrent trisomies (chromosome 3,5,7,9,11,15,19 for H-MM and chromosomes X,4,6,10,14,17,18,21 for H-ALL). Little is known about the oncogenic events, consequences of the trisomies and reasons for the different recurrent trisomies. In an attempt to answer these questions, we undertook a combined gene expression and network/pathway analysis approach. Gene expression data was generated using the Affymetrix U133A chip (Affymetrix, Santa Clara, Ca) for 53 H-MM and 37 non-hyperdiploid MM (NH-MM) cases using CD138-enriched plasma-cell RNA. Gene expression data using the same chip for ALL was obtained from previous published data (Ross ME et al Blood2004; 104: 3679–3687). Analysis was performed using Genespring 7 (Agilent Technologies, Palo Alto, CA). By comparing the median expression of all genes on each chromosome between H-MM/H-ALL and their non-hyperdiploid counterparts (NH-MM and NH-ALL) for the 23 chromosomes (excluding Y), one can clearly identify the commonly trisomic chromosomes in H-ALL and H-MM. However, the relationship of gene expression was highly variable for H-MM and NH-MM as compared to H-ALL and NH-ALL which tended to have expression ratios close to 1 for the non-trisomic chromosomes. Sixty-nine percent of the differentially expressed genes generated by ANOVA analysis (p&lt;0.001) in H-ALL were on the commonly trisomic chromosomes and were upregulated whereas the corresponding figure in H-MM is 40%. These similarities and differences probably reflect both an overall gene dosage effect and the different complexities of the karyotypes of H-MM and H-ALL compared to NH-MM and NH-ALL respectively (MM karyotypes are more complex, hence difference between H and NH-MM is greater and less confined to the trisomic chromosomes). We next performed network analysis using a curated web-based software (MetaCore, GeneGo Inc, St Joseph, MI) using the 2 sets of differentially expressed genes. Majority of genes differentially expressed in H-MM are involved in mRNA translation/protein synthesis whereas the genes differentially expressed in H-ALL were mainly involved in signal transduction. Therefore the transcriptional program that characterize the difference between H and NH-MM/ALL seem to recapitulate normal cellular function: protein synthesis in the mature secretory plasma cells and signal transduction in response to cytokines in a differentiating early-B cell. However, due to the concurrent deregulation of many genes on these trisomic chromosomes, these and other cellular programs are deregulated resulting in malignant transformation. We also intersected the 2 lists of differentially expressed genes to find genes that are up- or downregulated in both H-MM and H-ALL relative to the NH tumors. Thirteen genes including interferon response genes (TNFSF10, MX1, ZNF185) and transcription factors like RUNX1 were upregulated, whereas 13 genes including a cancer testis antigen gene (MAGED4) were downregulated in both H-MM and H-ALL. These genes may point to common oncogenic mechanisms.

Abstract Background: Waldenström macroglobulinemia (WM) is a plasma cell dyscrasia characterized by a monoclonal IgM paraproteinemia. The most common genomic abnormality in the clonal cells of WM is loss of portions of the long arm of chromosome 6 (6q-), however a minimal area of deletion has yet to be identified. We decided to further clarify the area of deletion on the 6q-arm in WM along with its prevalence. Methods: Patients (n=41) were required to have a serum IgM paraproteinemia of 1.5 g/dl or greater and a monoclonal lymphoplasmacytic infiltrate. We used interphase fluorescence in situ hybridization (FISH) combined with cytoplasmic immunoglobulin (cIg) staining with an AMCA conjugated anti-IgM antibody along with cytomorphology for the detection of the clonal cells on cytospin slides. Ten probes were used including two commercial (CEP 6 and Telomere 6q) and eight Bacteria Artificial Chromosome (BAC). BAC clones were selected based on a specific gene encompassed in the insert and/or localization on the q arm. Genes of interest included BLIMP1, c-myb, BTF, SHPRH, LATS1 and FOP. BAC’s were grown in selective media; DNA was extracted and directly labeled with a SpectrumGreen or SpectrumOrange fluorophore by standard nick translation. Primers were designed to confirm the insert contained the gene of interest and probes were tested on normal metaphases to reaffirm localization to the correct area of the chromosome and rule out any cross hybridization. Results: Deletions of 6q were noted in 21 (51%) patients. Of the 19 abnormal patients with all probes tested 1 (5%) case had ten probes deleted, 7 (37%) cases had nine probes, 1 (5%) had eight, 4 (21%) had seven, 3 (16%) had six and 3 (16%) had four probes deleted. Only 3 cases retained the end of the q arm indicating an interstitial deletion while the remaining 16 cases indicate terminal deletions. Deletions of the BAC containing the gene SHPRH at 6q24 were seen in each of the 19 abnormal cases. The majority of patients exhibited little heterogeneity for any given deletion having greater than 80% involvement of the clone. Conclusion: This study demonstrates that large deletions of the long arm of chromosome 6 in WM are frequent and are usually terminal deletions rather than interstitial and have a common area of deletion of the q24 portion of the q arm. Using the given number of probes localizing along the q arm makes it highly unlikely of any areas of noncontiguous deletion. The presence of deletions in the majority of the clonal cells may suggest that clones with 6q- emerge early in the course of the disease and is selected because of growth advantage or apoptosis resistance. Whether 6q deletions are important for disease pathogenesis has yet to be determined. Clinical prognosis studies and microarray data analysis are pending.