Abdallah, Nadine

Abstract Background: MASS-FIX is a novel method for detection, characterization and quantification of serum and urine monoclonal proteins in multiple myeloma (MM) which uses immunoglobulin enrichment coupled with matrix-assisted laser desorption ionization time-of-flight mass-spectrometry (MALDI-TOF). MASS-FIX has been endorsed by the International Myeloma Working Group (IMWG) as an alternative to immunofixation electrophoresis for diagnosis and disease monitoring in MM and has replaced immunofixation electrophoresis in our institution. This technique has demonstrated superior sensitivity and specificity compared to conventional gel-based methods, but its prognostic value is still unknown. We designed this study to evaluate whether serum M protein monitoring by MASS-FIX has prognostic significance in predicting disease progression in patients with MM. Methods: In the first part of the study, we included patients with MM who had a documented negative MASSFIX after first-line treatment and had serial MASS-FIX data available (n=187). We then compared the time to next treatment (TTNT) between patients who became positive by MASS-FIX and those who remained negative by last follow up. In the second part, we included patients who were positive by MASS-FIX within 90 days from diagnosis and had available serial MASS-FIX data (n=203). We compared TTNT between patients who became negative by MASS-FIX and those who remained positive by last follow up. TTNT was defined as the time of initiation of the first-line treatment to the time of initiation of second-line treatment or last follow up. Results: Part 1: We included 155 patients diagnosed with MM between January 2013 and December 2019 who had a documented negative MASSFIX with first-line treatment and had serial MASSFIX data available. After a median follow up of 3.1 (95%CI: 2.6-3.5) years, 44 (28%) patients became MASSFIX positive, while 111 (72%) still had negative MASS-FIX. The median time from treatment start to negative MASSFIX was 18.0 (IQR: 6.4-33.5) months. The median TTNT was 4.1 (95%CI: 3.2 - NR) years in patients who became MASSFIX positive and not reached (NR) (95%CI: NR-NR) in patients who were MASS-FIX negative by last follow up (P<0.001). The 2-year OS was 97% and 100% in the 2 groups, respectively (P=0.27). Part 2: We included 203 patients who had positive MASSFIX within 90 days from diagnosis and available serial MASSFIX data. The median follow-up was 1.5 (95%CI: 1.5-1.7) years. By last follow up, 39 (19%) patients became MASSFIX negative while 164 (81%) still had positive MASSFIX. The median TTNT was NR (95%CI: 2.0-NR) years in patients who developed negative MASSFIX and 2.3 (95%CI: 1.9 - NR) years in patients who were still MASS-FIX positive by last follow up (P=0.03). The 2-year OS was 97% and 94% in the 2 groups, respectively (P=0.84) Conclusion: The utilization of MASS-FIX in disease monitoring of MM patients provides prognostic information; among patients who become MASS-FIX negative after first line treatment, an earlier conversion to positive MASS-FIX predicts disease progression. Similarly, persistent MASS-FIX positivity after treatment initiation predicts earlier disease progression. Larger studies and longer follow up are needed to evaluate whether the MASS-FIX is associated with overall survival. Disclosures Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Dispenzieri: Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Gertz: Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Ionis Pharmaceuticals: Other: Advisory Board; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring. Dingli: Sanofi: Consultancy; GSK: Consultancy; Novartis: Research Funding; Apellis: Consultancy; Janssen: Consultancy; Alexion: Consultancy. Kumar: Amgen: Consultancy, Research Funding; Bluebird Bio: Consultancy; Antengene: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Merck: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Novartis: Research Funding; Tenebio: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Abstract Background: Systemic light chain (AL) amyloidosis is a plasma cell disorder characterized by multisystem deposition of misfolded immunoglobulin light chains produced by clonal plasma cells. Hematologic and organ responses with treatment have been shown to correlate with survival as early as 3 months from initiation of first-line treatment. Our group recently developed and validated a model integrating organ and hematologic responses for assessment of treatment outcomes at 6 months. Although current organ response criteria do not consider the depth of organ response, this has been shown to have prognostic utility in newly diagnosed patients. So, we designed this study to evaluate a composite hematologic and organ scoring system that also considers the depth of organ response at 1 to 6 months from initiation of first-line treatment. Methods: We included patients with AL amyloidosis who had at least one major organ involvement (cardiac, renal and/or liver involvement) and who had not started a second line treatment by 6 months from the time of initiating first-line treatment. For each patient, we calculated an organ response score and a hematologic response score at 1, 2, 3, 4, 5, and 6 months from initiation of first-line treatment. A score was assigned for each depth of hematologic response as follows: complete response=0, very good partial response=1, partial response=2, and no response/progressive disease=3). To calculate organ response, a score was assigned to each organ based on the depth of organ response (Muchtar et al. 2018): non-evaluable=0, complete response=1, very good partial response=2, partial response=3, and no response=4. The final organ response score was obtained by calculating the average of the individual involved organ scores. We then calculated the composite hematologic and organ response (HOR) score by adding the organ and hematologic responses at each interval and compared overall survival (OS) between patients with HOR score ≤ 5 (group 1) and those with score > 5 (group 2). Results: The cohort included 730 patients diagnosed with AL amyloidosis between February 10 th, 2006 and July 9 th, 2019. Median age was 63 (IQR: 56-69), and 65% were male. The involved light chain was Lambda in 75% of cases. Cardiac, renal, and liver involvement were found in 81%, 61%, and 17% of patients, respectively. Among all patients, 28% underwent autologous stem cell transplantation during their disease course. The median follow up in the entire cohort was 7.0 (95%CI: 6.4-8.0) years and OS was 3.6 (95%CI: 2.6-4.4) years. At 1 to 4 months, we observed a statistically significant difference in OS between patients with HOR score ≤5 vs. >5. However, there was no difference in OS between the 2 groups at 5 and 6 months. These results are presented in Table 1. Conclusion: A composite hematologic and organ response score that takes into consideration the depth of organ response can discriminate 2 groups of patients with distinct survival outcomes as early as 1 month from treatment initiation and maintains its predictive ability for up to 4 months. The lack of predictive ability beyond 4 months in this study may be due to limited sample size especially in group 2 as more patients achieve deeper responses with time. This approach can provide the basis for early changes in treatment but needs validation in future studies. Figure 1 Figure 1. Disclosures Dispenzieri: Janssen: Consultancy, Research Funding; Takeda: Research Funding; Sorrento Therapeutics: Consultancy; Oncopeptides: Consultancy; Pfizer: Research Funding; Alnylam: Research Funding. Gertz: Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Aurora Biopharma: Other: Stock option; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring. Kapoor: Ichnos Sciences: Research Funding; Karyopharm: Consultancy; Glaxo SmithKline: Research Funding; Pharmacyclics: Consultancy; Amgen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy; BeiGene: Consultancy; Regeneron Pharmaceuticals: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Dingli: GSK: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Novartis: Research Funding; Apellis: Consultancy; Alexion: Consultancy. Kumar: Oncopeptides: Consultancy; Merck: Research Funding; Antengene: Consultancy, Honoraria; Bluebird Bio: Consultancy; Roche-Genentech: Consultancy, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Carsgen: Research Funding; 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; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding; Takeda: 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.

Abstract Purpose: Structural variants (SV) of the MYC gene region are common in multiple myeloma and influence disease progression. However, the prognostic significance of different MYC SVs in multiple myeloma has not been clearly established. Experimental Design: We conducted a retrospective study of multiple myeloma comparing MYC SV subtypes identified by next-generation sequencing (NGS) and FISH to MYC expression and disease survival using 140 cases from Mayo Clinic and 658 cases from the MMRF CoMMpass study. Results: MYC SVs were found in 41% of cases and were classified into nine subtypes. A correlation between the presence of a MYC SV and increased MYC expression was identified. Among the nine MYC subtypes, the non-immunoglobulin (non-Ig) insertion subtype was independently associated with improved outcomes, while the Ig insertion subtype, specifically involving the IgL gene partner, was independently associated with poorer outcomes compared with other MYC SV subtypes. Although the FISH methodology failed to detect approximately 70% of all MYC SVs, those detected by FISH were associated with elevated MYC gene expression and poor outcomes suggesting a different pathogenic role for FISH-detected MYC subtypes compared with other MYC subtypes. Conclusions: Understanding the impact of different MYC SVs on disease outcome is necessary for the reliable interpretation of MYC SVs in multiple myeloma. NGS approaches should be considered as a replacement technique for a more comprehensive evaluation of the multiple myeloma clone.

PURPOSE: The benefit of routine pre-emptive screening for severe acute respiratory syndrome coronavirus 2 infections in patients with cancer before cancer-directed therapies is unclear. Herein, we characterize the outcomes of a cohort of patients with cancer who were diagnosed with COVID-19 by routine screening (RS) in comparison with those diagnosed on the basis of clinical suspicion or exposure history (nonroutine screening [NRS]). METHODS: A multisite prospective observational study was conducted at three major and five satellite campuses of the Mayo Clinic Cancer Center between March 18 and July 31, 2020. The primary outcome was COVID-19–related hospital admission. Secondary outcomes included intensive care unit admissions and all-cause mortality. RESULTS: Five thousand four hundred fifty-two patients underwent RS in the outpatient setting only, and 44 (0.81%) were diagnosed with COVID-19. RS detected 19 additional patients from the scheduled inpatient admissions for surgical or interventional procedures or inpatient chemotherapy. One hundred sixty-one patients were diagnosed with COVID-19 on the basis of NRS. COVID-19–related hospitalization rate (17.5% v 26.7%; P = .14), intensive care unit admission (1.6% v 5.6%; P = .19), and mortality (4.8% v 3.7%; P = .72) were not significantly different between the RS and NRS groups. In the multivariable analysis, age ≥ 60 years (odds ratio, 4.4; P = .023) and an absolute lymphocyte count ≤ 1.4 × 109/L (odds ratio, 9.2; P = .002) were independent predictors of COVID-19–related hospital admission. CONCLUSION: The COVID-19 positivity rate was low on the basis of RS. Comparing the hospital admission and mortality outcomes with the NRS cohort, there were no significant differences. The value of routine pre-emptive screening of asymptomatic patients with cancer for COVID-19 remains low.

Abstract Abstract Importance: The benefit of routine screening for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in patients with cancer before cancer-directed therapies is unclear. Herein, we characterize the outcomes of a cohort of cancer patients diagnosed with Coronavirus Disease 2019 (COVID-19) by routine screening in comparison with those diagnosed based on clinical suspicion or exposure history (non-routine screening). Objective: To describe and compare the outcomes of cancer patients diagnosed with COVID-19 on routine screening vs. non-routine screening at a multi-site tertiary cancer center. To identify risk factors for COVID-19-related hospital admission. Design: A multi-site prospective observational study was conducted between March 18 and July 31, 2020. Setting: Three major and 5 satellite campuses of the Mayo Clinic Cancer Center. Participants: Adult patients diagnosed with active cancer within the past five years and confirmed SARS-CoV-2 infection were included. Primary Outcomes and Measures: Clinical and laboratory data were assessed as independent variables. The primary outcome was COVID-19-related hospital admission. Secondary outcomes included intensive care unit (ICU) admissions and all-cause mortality. Results: Between March 18 and July 31, 2020, 5452 patients underwent routine screening in the outpatient setting, 44 (0.81%) were diagnosed with COVID-19. Routine screening detected additional 19 patients from inpatient and pre-procedural settings; 161 patients were diagnosed with COVID-19 based on non-routine screening. The median age of the entire cohort at diagnosis was 54 years, and 95 patients (42.2%) were female. COVID-19 related-hospitalization rate (17.5% vs. 26.7%, p=0.14), ICU admission (1.6% vs. 5.6%, p=0.19), and mortality (4.8% vs. 3.7%, p=0.72) were not significantly different between routine screening and non-routine screening groups. In the multivariable analysis, age ≥ 60 years (odds ratio: 4.4, p=0.023) and an absolute lymphocyte count ≤1.4 × 109/L (odds ratio: 9.2, p=0.002) were independent predictors of COVID-19-related hospital admission. Conclusions and Relevance: The COVID-19 positivity rate was low based on routine screening. Comparing the outcome with the non-routine screening cohort, there was no significant difference. These results led to an important practice change at our cancer center. We currently follow a testing strategy based on symptoms, exposure, risk factors, and clinical judgment. Citation Format: Zhuoer Xie, Antoine N. Saliba, Jithma Abeykoon, Umair Majeed, Daniel Almquist, Julia Wiedmeier-Nutor, Evandro Bezerra, Xavier Andrade-Gonzalez, Ashley Hickman, Karl Sorenson, Sagar Rakshit, Christopher Wee, Sri Tella, Anuhya Kommalapati, Nadine Abdallah, Joshua Pritchett, Mariza De Andrade, Dipesh Uprety, Andrew Badley, Joleen Hubbard, Naseema Gangat, Carrie A. Thompson, Thomas Witzig, Robert R. McWilliams, Konstantinos Leventakos, Thorvardur R. Halfdanarson. Outcomes of COVID-19 in patients with cancer: Results of a prospective observational comparison of routine screening strategy versus testing based on clinical suspicion [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2021 Feb 3-5. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(6_Suppl):Abstract nr S06-03.

Abstract The utility of systemic light chain (AL) amyloidosis staging systems has been validated for newly diagnosed patients, but their role in restaging after treatment has not been explored. We designed this study to evaluate whether the currently used systems are of prognostic value at 3 and 6 months of starting first-line treatment, and whether stage migration from diagnosis impacts survival. This is a retrospective study including Mayo Clinic patients with AL amyloidosis diagnosed between 1 January 2006 and 30 June 2019; 536 and 204 patients had restaging data for at least 1 system at 3 and 6 months, respectively. Using modified Mayo 2004 staging at 3 months, median overall survival (OSs) were 11.8, 10.8, 4.6, and 1.1 years for stage I, II, IIIa, and IIIb, respectively. Using Mayo 2012, median OSs were 11.8, 9.0, 5.2, and 0.8 years for stage I, II, III, and IV, respectively. Using modified Mayo 2004 staging at 6 months, median OSs were not reached (NR), NR, 5.4, and 0.9 years for stage I, II, IIIa, and IIIb, respectively. Using Mayo 2012, OSs were NR, NR, 4.6, and 0.9 years for stage I, II, III, and IV, respectively. Worsening stage at 3 or 6 months was associated with worse survival than retaining baseline stage. In conclusion, the current staging systems can be used for restaging at 3 and 6 months from treatment initiation. Migration to higher stage predicts poor prognosis.

Background: Multiple myeloma (MM) is an incurable plasma cell malignancy and genetic abnormalities contribute to disease heterogeneity and outcome. Primary abnormalities, namely recurrent immunoglobulin (Ig) heavy chain translocations and hyperdiploidy, occur early in disease course. Secondary events, such as MYC abnormalities occur upon progression. Earlier studies showed MYC abnormalities detected by FISH or by capture sequencing were independently associated with poor outcome (Walker, et al., BCJ, 2014), while recent studies using WGS did not support this finding (excluding MYC/IGL) (Mikulasova, et al. Haematologica, 2020; Misund, et al. Leukemia, 2020). We hypothesize these discrepancies are due to differences in methods and sensitivities of detection of MYC abnormalities by FISH vs. WGS. Given that MYC abnormalities often display remarkable genomic heterogeneity with numerous gene partners, reduced detection of MYC abnormalities by FISH is not unexpected. This hypothesis is supported by lower frequencies of MYC abnormalities found by FISH (15%) vs. NGS (30-35%) consistent with ~50% false-negative rate of the MYC FISH probe (Smadbeck, et al. BCJ, 2019). To better understand the role of MYC in myeloma disease outcome, we compared the MYC abnormality subtype identified by FISH or NGS vs. MYC gene expression levels and overall survival. Methods: We performed a retrospective study of newly diagnosed MM patients seen at Mayo Clinic or enrolled in the MMRF CoMMpass trial. For Mayo cases, MYC FISH results (breakapart probe, Abbott) were obtained from the Mayo Clinic Genomics database (N=1342) and mate pair sequencing (MPseq) was performed on 140 cases. For CoMMpass cases, we obtained tumor long-insert whole genome sequencing (WGS), RNA sequencing (RNAseq) for gene expression and clinical outcome data. Overall survival (OS) was defined as time from diagnosis to death from any cause or to last follow up. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical analyses performed using SPSS and JMP with significance determined when P <0.05. Results: We first evaluated the impact of MYC abnormalities on OS when detected by FISH or NGS. In Mayo cases, OS was significantly shorter in patients with MYC abnormalities compared to patients without MYC abnormalities using FISH (5.3 vs. 8.0 years, P<0.001, N=1342). In contrast, there was no significant difference in OS between patients with or without MYC or abnormalities using MPseq or WGS in both the Mayo and CoMMpass cohorts (Mayo: 6.4 vs. and 6.9 years P=0.78, N=140; CoMMpass: 4.9 vs. and 5.1 years P=0.74, N=546). Since FISH-detected MYC abnormalities were associated with poor outcome, we evaluated differences in the types of MYC abnormalities identified FISH and genome sequencing; 270 of 658 CoMMpass cases had a MYC abnormality and 12 abnormality subgroups were identified. In the Mayo cases, FISH preferentially detected translocations and complex abnormalities and missed insertions with flanking duplicating sequences or terminal tandem duplications (TTD) that occur telomeric to MYC. Since the level of MYC expression should be a consequence of the various genomic abnormalities altering the MYC gene region, we compared MYC expression levels in relation to MYC abnormality subgroups. Highest expression was seen with MYC amplification, followed by Ig abnormalities, non-Ig abnormalities, complex deletion/duplications, proximal deletions, non-Ig insertions, terminal deletions, TTD, trisomy 8, no MYC structural variation, monosomy 8 and cases with MAX mutations had the lowest expression. Abnormalities identified by FISH had higher MYC expression (83.5 TPM) compared to cases predicted to be missed by FISH (63.2 TPM). We tested if high MYC expression, irrespective of MYC structural abnormality, was associated with differences in OS. Boxplot analysis was used to categorize MYC expression in 631 CoMMpass patients as top quartile/high MYC expression (Q4≥ 75 TPM, n=159) and bottom quartile/low MYC expression (Q1≤ 16.5 TPM, n= 158) (see Figure). OS was significantly shorter in patients with high MYC expression compared to patients with low MYC expression (4.6 vs. 5.3 years, P <0.038). Conclusion: We show that FISH detects only a subset of the MYC abnormalities detected by genome sequencing, and that FISH-detected MYC abnormalities are associated with higher MYC gene expression and decreased survival. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Dr. Reddy's Laboratories: Honoraria; Cellectar: Other; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Tenebio: Other, Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Genecentrix: Consultancy; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Adaptive Biotechnologies: Consultancy.

Introduction: The utility of amyloidosis staging systems has been validated for newly diagnosed patients, but their role in restaging after starting treatment has not been explored. Given the high early mortality in this disease, restaging remote from the diagnosis may have clinical value. We designed this study to evaluate whether the currently used staging systems are prognostic when applied at 3 and 6 months from starting first-line treatment, and whether stage migration impacts survival. Methods: This is a retrospective study including patients with systemic light chain amyloidosis diagnosed between January, 1st 2006 and June, 30th 2019 and were seen in Mayo Clinic, Rochester, MN within 90 days of diagnosis; the analysis included 535 and 301 patients who had restaging data available for at least one of the staging systems at 3 and 6 months, respectively. Patients were grouped into 4 stages using the 2015 European modification of the Mayo 2004 staging system based on values of cardiac biomarkers (cardiac troponin T and NTproBNP), and using the Mayo 2012 staging system based on cardiac biomarkers and the difference in serum free light chain concentration (dFLC). Overall survival (OS) was calculated from the time of re-staging until death or last follow up. Results: Using the modified Mayo 2004 staging system at 3 months from starting first-line treatment, median OS was 11.8 [95%CI: 11.4-not reached (NR)], 10.8 (95%CI: 9.4-NR), 4.6 (95%CI: 2.8-6.7), and 1.1 (95%CI: 0.7-2.6) years in patients with stage I, II, IIIa, and IIIb, respectively. Using Mayo 2012 staging at 3 months, OS was 11.8 (95%CI: 10.9-NR), 9.0 (95%CI: 6.2-NR), 5.2 (95%CI: 3.3-6.1), and 0.8 (95%CI: 0.7-1.1) years in patients with stage I, II, III, and IV, respectively (Figure 1a &b). Using the modified Mayo 2004 staging system at 6 months from starting first-line treatment, median OS was NR (95%CI: NR-NR), 9.8 (95%CI: 6.2-NR), 5.4 (95%CI: 3.2-9.0) and 0.9 (95%CI: 0.6-3.7) years in patients with stage I, II, IIIa, and IIIb, respectively. Using Mayo 2012 staging at 6 months, OS was NR (95%CI: 8.4-NR), NR (95%CI: 7.9-NR), 4.6 (95%CI: 3.0-6.5), and 0.9 (95%CI: 0.2-1.8) years in patients with stage I, II, III, and IV, respectively (Figure 1c &d). On multivariate analysis, advanced (stage > 2) modified Mayo 2004 stage (HR: 1.6, P=0.004) and advanced (stage > 2) Mayo 2012 stage (HR: 2.4, P<0.001) at 3 months were associated with decreased survival independent of cardiac response, hematologic response, and transplantation status. Although advanced Mayo 2004 stage at 6 months was associated with decreased survival, it was not statistically significant (HR: 1.5, P=0.09). In contrast, advanced Mayo 2012 stage at 6 months was independently associated with decreased survival (HR: 2.1, P=0.02). For both systems, worsening stage at 3 months or at 6 months was associated with a worse survival than retaining the original stage. In contrast, improving stage as compared to remaining in same stage was not associated with better survival at 3 or 6 months (Table 1). When the analysis was restricted to patients who had an advanced stage at diagnosis, improving stage at 3 months was associated with longer survival compared to retaining the original stage, with both modified Mayo 2004 (10.8 vs. 3.3 years, P<0.001) and Mayo 2012 (8.1 vs. 2.6 years, P<0.001) staging systems. At 6 months, stage improvement was associated with longer survival than retaining the original stage when the modified Mayo 2004 staging system was used (NR vs. 5.0 years, P=0.02), but it was not statistically significant when the Mayo 2012 staging system was used (5.9 vs. 3.7 years, P=0.12). Conclusion: The modified Mayo 2004 and the Mayo 2012 staging systems have independent prognostic value when used for restaging after 3 and 6 months from initiation of first-line treatment. Migration to a higher stage from diagnosis predicts decreased survival, compared to retaining the same stage. Stage improvement is associated with a better OS in patients with advanced stage at diagnosis. Disclosures Dispenzieri: Alnylam, Intellia, Janssen, Takeda, Pfizer, Prothena, Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:GlaxoSmithKline: Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Celgene: Honoraria; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Cellectar: Consultancy. Dingli:Rigel: Consultancy; Millenium: Consultancy; Sanofi-Genzyme: Consultancy; Bristol Myers Squibb: Research Funding; Karyopharm Therapeutics: Research Funding; Janssen: Consultancy; Alexion: Consultancy; Apellis: Consultancy. Lin:Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gamida Cells: Consultancy; Takeda: Research Funding; Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Janssen: Consultancy, Research Funding; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding. Gertz:Alnylam: Consultancy; NCI SPORE MM: Research Funding; Ionis/Akcea: Consultancy; Amyloidosis Foundation: Research Funding; Celgene: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Advisory Board for Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Advisory Board for Proclara: Membership on an entity's Board of Directors or advisory committees; i3Health: Consultancy; Springer Publishing: Patents & Royalties; Prothena: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Data Safety Monitoring board from Abbvie: Membership on an entity's Board of Directors or advisory committees; International Waldenstrom Foundation: Research Funding. Kumar:Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Genecentrix: Consultancy; Cellectar: Other; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Kite Pharma: Consultancy, Research Funding; MedImmune: Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Karyopharm: Consultancy; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; BMS: Consultancy, Research Funding; Novartis: Research Funding; Adaptive Biotechnologies: Consultancy; Tenebio: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; Sanofi: Research Funding.

Abstract Purpose: Rearrangements involving the MYC protooncogene are common in newly diagnosed multiple myeloma, but their prognostic significance is still unclear. The purpose of this study was to assess the impact of MYC rearrangement on clinical characteristics, treatment response, and survival in patients with newly diagnosed multiple myeloma. Experimental Design: This is a retrospective study including 1,342 patients seen in Mayo Clinic in Rochester, MN, from January 2006 to January 2018, who had cytogenetic testing by FISH at diagnosis, including MYC testing using the break apart FISH probe (8q24.1). Results: A rearrangement involving MYC was found in 8% of patients and was associated with elevated β2-microglobulin, ≥50% bone marrow plasma cells, IgA multiple myeloma, and the cooccurrence of trisomies. There were no differences in overall response rates between patients with and without MYC rearrangement when induction chemotherapy was proteasome inhibitor (PI)-based, immunomodulatory drug (IMiD)-based or PI + IMiD-based. Overall survival was shorter in patients with MYC rearrangement compared with patients without MYC rearrangement (5.3 vs. 8.0 years, P < 0.001). MYC rearrangement was associated with increased risk of death on multivariate analysis when high-risk cytogenetic abnormalities, ISS stage III, and ≥70 years of age were included (risk ratio: 1.5; P = 0.007). Conclusions: MYC rearrangement is associated with high disease burden and is an independent adverse prognostic factor in patients with newly diagnosed multiple myeloma.

Abstract A gain in chromosome 1q (+1q) is among the most common cytogenetic abnormalities in multiple myeloma (MM). It is unclear whether +1q is independently associated with decreased overall survival (OS). The objective of this study was to evaluate the impact of +1q on clinical characteristics, treatment response, and survival outcomes. We included 1376 Mayo Clinic patients diagnosed with MM from 2005 to 2018 who underwent fluorescence in situ hybridization testing at diagnosis with a panel including the +1q probe. A gain in 1q was found in 391 patients (28%) and was associated with anemia, hypercalcemia, high tumor burden, International Staging System (ISS) stage 3, high-risk (HR) translocations, and chromosome 13 abnormalities. There was no difference in overall response or deeper responses to proteasome inhibitor (PI)–, immunomodulatory drug (iMiD)–, or PI plus IMiD–based induction. Time to next treatment was shorter in patients with +1q compared with those without +1q (19.9 vs 27.7 months; P < .001). On univariate analysis, +1q was associated with increased risk of death (risk ratio [RR], 1.9; P < .001), and decreased OS was seen in all treatment groups. +1q was independently associated with decreased OS on multivariate analysis when other HR cytogenetic abnormalities, ISS stage 3, and age ≥70 years were included (RR, 1.5; P < .001). Gain of >1 copy of 1q was not associated with worse OS compared with gain of 1 copy (4.9 vs 4.3 years; P = .21). +1q was associated with high tumor burden, advanced disease stage, and HR translocations. It is independently associated with decreased OS, even in the setting of novel therapy and transplant.