Aneuploidy Is Associated with Inferior Survival in Relapsed Refractory Multiple Myeloma Patients

Objective To identify the association between aneuploidy and clinical outcome in patients with relapsed and/or refractory multiple myeloma (RRMM) who participated in MMRF (Multiple Myeloma Research Foundation) sequencing study at University of Michigan. Background: Aneuploidy, defined by abnormal copy number changes of chromosomes, is one of the hallmarks in cancer, reflecting and also contributing to genome instability (Ye, Regan et al. 2018). Approximately 90% of cancers have gained or lost one or both arms of at least one chromosome (Taylor, Shih et al. 2018). In recent years, large scale sequencing efforts have extended aneuploidy study, identifying DNA somatic copy number alterations (SCNAs). Published data suggest aneuploidy has a stronger impact on prognosis than gene mutations in multiple myeloma (Walker, Boyle et al. 2015; Bolli, Biancon et al. 2018; Jamal-Haniani, Wilson et al. 2017). Methods: Fifty one RRMM patients from our institute participated in Clinical-Grade Molecular Profiling of Patients with Multiple Myeloma and Related Plasma Cell Malignancies (MMRF-002) from Multiple Myeloma Research Foundation (MMRF) between March 2016 and November 2018. Genomic DNA was obtained from CD138+ sorted myeloma cells and a peripheral blood sample from each patient. Capture exome sequencing on a targeted panel of 1500 genes was performed by the Illumina HiSeq 2500 (2x115bp paired-end reads, average 520X coverage). Copy number changes, loss of heterozygosity (LOH) and tumor purity were jointly estimated using an in-house pipeline for matched tumor/normal libraries. We assessed aneuploidy using chromosomal and arm level SCNAs which are determined by the median of SCNAs and summation of gain and loss of SCNAs for a given chromosomal arm, which are then used for a time-to-event analysis of overall survival (OS) of the patients. The differences between Kaplan-Meier overall survival curves were tested using the log-rank test. Hazard ratios (HR) were estimated from Cox proportional hazard regression. A threshold of significance was taken as p<0.05. Results Patient demographic data is summarized in Table 1. All the patients in this study harbor DNA somatic copy-number abnormalities (SCNAs) on the arm level for at least one chromosome (Figure 1). Gain of a chromosome or a whole arm mostly occurs on 1q, 3, 5, 7, 9, 11, 15, 19, 21 while loss was noted in 1p, 8p, 13, 16q, and 17p. At a global-level, we find that whole genomic aneuploidies (genomic-level across all chromosomes) have a significant association with inferior OS. Specifically, patients with a high frequency of genomic aneuploidies (defined as number of SCNA >8, the first quartile) had a significantly worse prognosis than those with low number of SCNA events (<=8) (p=0.037, Figure 2). Arm-level aneuploidies with high incidences include 11q (54.9%), 13q (52.9%), 15q (51.0%), 1q (51.0%), 9q (51.0%), a finding consistent with previous studies (Walker, Leone et al. 2010). Aneuploidies in 10p (11.8%) and 10q (7.8%) are uncommon in agreement with previous studies (Tricot G, Sawyer et al. 2017) as myeloma structural or numerical abnormalities rarely occur on chromosome 10. Using univariate analysis, we identified five arm-level aneuploidies which are significantly associated with worse OS: 10p, 10q, 11p, 18q and 20q. It is noteworthy that aneuploidies in either arm of chromosome 10 (10p and 10q) had significant negative OS prognostic effect: 10p (median survival for diploid 28.9 vs. aneuploid 4.1 mo; p<0.001) and 10q (28.9 vs 3.8 mo; p=0.015). Similar results with a negative impact on OS were found from 11p (not reached vs 13.8 mo; p=0.036); 18q (28.9 vs 8.5 mo; p=0.025); and 20q (28.9 vs 3.1 mo; p=0.009). Given the small sample size we did not conduct a multivariable analyses and multiplicity adjustment in this preliminary analyses. Conclusion Aneuploidy measured by SCNAs is correlated with unfavorable survival in relapsed/refractory myeloma. The higher the occurrence of aneuploidies, the worse the overall survival, illustrating of the impact of cancer genome instability. Disclosures Ye: Janssen: Research Funding; Karyopharm: Research Funding; Portola: Research Funding; MingSight: Research Funding; Sanofi: Research Funding. Talpaz:Imago BioSciences: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; CTI BioPharma: Research Funding; Constellation: Research Funding; Incyte: Research Funding; Novartis: Research Funding; Samus Therapeutics: Research Funding. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy.

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FDA Analysis: Impact of Body Mass Index (BMI) on Outcomes in Relapsed-Refractory Multiple Myeloma

Blood ◽

10.1182/blood-2019-130551 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 5505-5505

Author(s):

Rachel Ershler ◽

Bindu Kanapuru ◽

Yutao Gong ◽

Urvi A Shah ◽

Sham Mailankody ◽

...

Keyword(s):

Multiple Myeloma ◽

Body Weight ◽

Board Of Directors ◽

Research Funding ◽

Small Sample Size ◽

Univariate Analysis ◽

Normal Weight ◽

Small Sample ◽

Advisory Committees ◽

Refractory Multiple Myeloma

Background: Obesity has been implicated as a risk factor for the development of certain types of cancers, including multiple myeloma (Wallin 2011). In a report published in NEJM in 2016, the relative risk of multiple myeloma for overweight to class 1 obese individuals was 1.2, versus a relative risk of 1.5 for class 2 to 3 obese individuals (Lauby-Secretan 2016). Recent reports indicate that BMI may impact prognosis in patients with newly diagnosed multiple myeloma (Beason 2013). Minimal information is available on impact of BMI and prognosis in patients with relapsed-refractory multiple myeloma. We analyzed the association between BMI and clinical outcomes in patients with relapsed/refractory multiple myeloma to determine if there is a difference in outcomes based on body weight. Methods: We conducted a retrospective analysis of four clinical trials evaluating novel therapeutics. These trials enrolled patients with relapsed/refractory multiple myeloma who had received one or more prior therapies. Patients were categorized into four groups, underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25.0-29.9 kg/m2) and obese (BMI >30.0 kg/m2). The Kaplan-Meier method was used to estimate progression free survival and overall survival. Results: A total of 2392 subjects were included in this analysis. The median age was 65 years (range 30-91 years). A total of 28 (1.2%) subjects were underweight, 733 (30.6%) were normal weight, 1032 (43.1%) were overweight, and 599 (25.0%) were obese. More of the underweight subjects were female (82.1%), whereas more of the overweight and obese subjects were male (62.9% and 56.6%, respectively). The median PFS and OS K-M curves are displayed below. In this univariate analysis, there were no differences in PFS (p=0.61) or OS (p=0.7) among the four groups. There were some differences in the underweight population; however, the small sample size of this group precludes any meaningful conclusions. Univariate analyses by gender did not reveal any differences in outcomes based on body weight. Conclusion: In patients with relapsed/refractory multiple myeloma, body weight had no impact on outcomes, as measured by PFS and OS. These results are consistent with previous findings on the effect of BMI on survival in subjects with multiple myeloma after autologous stem cell transplant (Kocoglu 2018). Limitations of this analysis include the use of a univariate analysis, the small sample size for patients who were underweight, heterogeneity in the treatment regimens, and immaturity of the OS data. Future studies are needed to evaluate other variables such as the relationship between cytogenetics and body weight, as well as analyses of safety based on body weight in this relapsed/refractory patient population. Figure Disclosures Shah: Physicians' Education Resource: Honoraria. Mailankody:Juno: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Takeda Oncology: Research Funding; CME activity by Physician Education Resource: Honoraria. Landgren:Sanofi: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees; Merck: Other: IDMC; Theradex: Other: IDMC; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: 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, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

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Indirect Comparison Using Individual Patient Level Data Comparing Efficacy and Safety of a Daratumumab Monotherapy Vs. EU Approved Comparator Therapies in Patients with Multiple Myeloma

Blood ◽

10.1182/blood-2018-99-116884 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 3541-3541 ◽

Cited By ~ 1

Author(s):

Irina Demmer ◽

Susanne Huschens ◽

Dietrich Potthoff ◽

Jörg Tomeczkowski ◽

Christian Englisch ◽

...

Keyword(s):

Multiple Myeloma ◽

Overall Survival ◽

Board Of Directors ◽

Real World ◽

Research Funding ◽

Sensitivity Analyses ◽

Control Group ◽

Efficacy And Safety ◽

Advisory Committees ◽

Refractory Multiple Myeloma

Abstract Introduction. Efficacy and safety of daratumumab monotherapy (DARA mono) in relapsed/refractory multiple myeloma (rrMM) has been shown in the single-arm phase I/II trial GEN501 and the single-arm phase II trial SIRIUS (1, 2). Since then, several indirect treatment comparisons of DARA mono versus comparator therapies have been published showing consistent results with an overall survival benefit for DARA mono (3, 4, 5, 6). This analysis compares efficacy and for the first time also safety of DARA mono data versus an international historic control group, adjusting for differences in patient populations based on individual patient level data (IPD). Methods. IPD from the SIRIUS trial and from the International Myeloma Foundation (IMF)-cohort (7), a retrospective, multicenter cohort, were compared using a multivariate Cox proportional hazards model, on the endpoints of efficacy (overall survival (OS)) and safety (discontinuation due to adverse events (DISCONAE)). The IMF-cohort included patients with rrMM who received at least three prior lines of therapy, were refractory to both an immunomodulator (IMiD) and a proteasome inhibitor (PI), and were exposed to an alkylating agent. An inclusion criterion for the historic control group in this analysis was treatment with EU approved regimens. Baseline covariates adjusted for in the regression model included age, gender, prior lines of therapy, albumin, beta-2 microglobulin, prior exposure to pomalidomide and carfilzomib, and PI/IMiD refractory status. Several sensitivity analyses were run, including multiple imputation of missing values. Results. Data from 106 patients treated with DARA mono (16 mg/kg) were available from SIRIUS; 258 patients from the IMF chart review fulfilled the inclusion criteria; most frequent treatment regimens contained pomalidomide plus dexamethasone (PomDex) (n=172), bortezomib (n=31), carfilzomib (n=21), cyclophosphamide (n=14) and lenalidomide (n=9). The adjusted HR for OS was 0.41 [0.25, 0.69], p<0.001, and 0.23 [0.05, 1.00], p=0.050 for DISCONAE, in favor of daratumumab. Results were consistent across a range of sensitivity analyses and were similar when restricting the comparison to DARA vs. PomDex, with HR=0.35 [0.19, 0.64], p<0.001 for OS and 0.20 [0.03, 1.54], p=0.123 for DISCONAE. Conclusions. This comparison using real-world data of rrMM patients suggests improved efficacy and safety for DARA mono compared to approved therapy regimens used in clinical practice, including PomDex. References. Lokhorst, H. M., Plesner, T., Laubach, J. P., Nahi, H., Gimsing, P., Hansson, M., et al. Targeting CD38 With Daratumumab Monotherapy in Multiple Myeloma. The New England Journal of Medicine. 2015. Lonial S, Weiss BM, Usmani SZ, Singhal S, Chari A, Bahlis NJ, et al. Daratumumab Monotherapy in Patients with Treatment-Refractory Multiple Myeloma (SIRIUS): An Open-Label, Randomised, Phase 2 Trial. The Lancet. 2016. Usmani S, Ahmadi T, Ng Y, Lam A, Desai A, Potluri R, Mehra M. Analysis of Real-World Data on Overall Survival in Multiple Myeloma Patients With ≥3 Prior Lines of Therapy Including a Proteasome Inhibitor (PI) and an Immunomodulatory Drug (IMiD), or Double Refractory to a PI and an IMiD. The Oncologist. 2016. Van Sanden S, Ito T, Diels J, Vogel M, Belch A, Oriol A. Comparative Efficacy of Daratumumab Monotherapy and Pomalidomide Plus Low-Dose Dexamethasone in the Treatment of Multiple Myeloma: A Matching Adjusted Indirect Comparison. The Oncologist. 2017. Usmani SZ, Diels J, Ito T, Mehra M, Khan I, Lam A. Daratumumab monotherapy compared with real-world historical control data in heavily pretreated patients with highly refractory multiple myeloma: An adjusted treatment comparison. American Journal of Heamtology. 2017. Jelínek T, Maisnar V, Pour L, Špička I, Minařík J, Gregora E, et al. Adjusted comparison of daratumumab monotherapy versus real-world historical control data from the Czech Republic in heavily pretreated and highly refractory multiple myeloma patients. Current Medical Research an Opinion. 2017. Kumar SK, Dimopoulos MA, Kastritis E, Terpos E, Nahi H, Goldschmidt H, et al. Natural history of relapsed myeloma, refractory to immunomodulatory drugs and proteasome inhibitors: a multicenter IMWG study. Leukemia. 2017. Disclosures Demmer: Janssen: Employment. Huschens:Janssen: Employment. Potthoff:Janssen: Employment. Tomeczkowski:Janssen: Employment. Englisch:Janssen: Employment. Thilakarathne:Janssen: Employment. Diels:Janssen: Employment. Kumar:AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: 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. Durie:Celgene: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Janssen: Consultancy. Eisele:Janssen: Employment.

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Presence of Extrachromosomal DNA (ecDNA) Impacts Both Progression Free and Overall Survival and Is an Independent Poor Prognostic Marker in Multiple Myeloma

Blood ◽

10.1182/blood-2021-151647 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 461-461

Author(s):

Parth Shah ◽

Anil Aktas-Samur ◽

Mariateresa Fulciniti ◽

Raphael Szalat ◽

Masood A. Shammas ◽

...

Keyword(s):

Multiple Myeloma ◽

Overall Survival ◽

Board Of Directors ◽

Copy Number ◽

Research Funding ◽

P Value ◽

Newly Diagnosed ◽

Extrachromosomal Dna ◽

Publicly Traded ◽

Advisory Committees

Abstract Background Focal amplifications and rearrangements drive tumor growth and evolution in cancer. Focally amplified regions often involve the juxtaposition of rearranged segments of DNA from distinct chromosomal loci into a single amplified region and nearly half of these regions can be explained by circular, extrachromosomal DNA (ecDNA) formation. Cancer-associated ecDNA shows a unique circular placing ecDNA at the interface of cancer genomics and epigenetics. As formation of ecDNA represents a manifestation of genomic instability, we have investigated presence and prognostic impact of ecDNA in multiple myeloma (MM). Methods Whole genome (WGS) and transcriptome (RNAseq) sequencing data from CD138 purified MM cells from 191 uniformly-treated newly diagnosed MM patients were used for this analysis. Copy number variants (CNV), single nucleotide variants (SNV) and structural variants (SV) were identified on all WGS samples using Facets, Mutect2 and Manta. Seed data from these CNV results was passed to the AmpliconArchitect tool to determine presence of focally amplified and rearranged segments of DNA. Seed CNV thresholds were set for a minimum CNV size of 100kb and a copy number of equal or greater to 5. Extrachromosomal calls were then annotated using the Amplicon Classifier to determine the presence of ecDNA. Multivariate survival analysis was performed after segregating samples into the conventional myeloma risk classifications including translocations, copy number alterations, ISS, age and mutations associated with risk. Differential expression analysis was performed on transcriptomic data using DEseq2. Results We identified 6.8% of the newly diagnosed patients with ecDNA, 12.5% with complex non-cyclic DNA amplifications and 10.1% with linear amplifications. ecDNA and complex events were targeting MM dependent genes, including MYC/PVT1, IRF4 as well as known driver genes such as CDYL and TRAF2. We further evaluated association between ecDNA, complex rearrangements, linear amplification and patients with none of these amplification types and found that patients with ecDNA had significantly poor PFS (median PFS 22 months vs. 41 months) and OS (median OS 41 months vs. 105 months). Patients having ecDNA in their MM cells did not show any significant enrichment for known translocations, double hit or TP53 mutations. In a multivariate model including ecDNA and all other known MM risk features, ecDNA was found to be an independent predictor of progression free survival.(HR 2.6, CI: 1.26 -5.6, p=0.0082) and overall survival (HR 7.94 CI:3.5-17.9 p < 0.0001). Patients with ecDNA have higher mutational load probability(8798 vs 6982, effect size = 0.64 , probability is 91.1). However, this was not reflected in heterogeneity by using MATH score. We found that patients with ecDNA are likely to have BRAF mutations (OR= 25.07 [2.57 - 330 95% CI], p value = 0.002), however overall RAS/RAF pathway mutations were similar to other patients. Patients with ecDNA showed fragile DNA with more breaks (median segments 197 vs. 125.5, p value = 0.001). Although ecDNA is defined as copy number gain with fragments having 5 or more copies, overall genomic gain between ecDNA and other patients were similar. However, overall genomic loss in patients with ecDNA were higher than others (7% vs. 4.2%, p = 0.06). By differential gene expression analysis we noted 98 differentially expressed genes in MM cells with ecDNA. The downregulated geneset involved pathways responsible for cell death as well as the RAS pathway. Interestingly, CD38 was upregulated in the ecDNA dataset suggesting greater potential for CD38 targeting therapies in these patients. Conclusions ecDNA, as an unique marker of perturbed genomic integrity, is observed in a subset of patients and is an independent prognostic marker in newly diagnosed MM patients. As patients with ecDNA are not fully captured by other risk features its incorporation in an expanded definition of a high risk group of multiple myeloma should be investigated. Future studies will endeavor to explore the biological mechanism through which ecDNA are formed and influences outcomes in myeloma. Figure 1 Figure 1. Disclosures Richardson: Sanofi: Consultancy; GlaxoSmithKline: Consultancy; Karyopharm: Consultancy, Research Funding; AstraZeneca: Consultancy; AbbVie: Consultancy; Oncopeptides: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy; Protocol Intelligence: Consultancy; Celgene/BMS: Consultancy, Research Funding; Secura Bio: Consultancy; Regeneron: Consultancy; Jazz Pharmaceuticals: Consultancy, Research Funding. Perrot: Abbvie: Honoraria; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: 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; Sanofi: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Moreau: Abbvie: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Sanofi: Honoraria; Celgene BMS: Honoraria; Oncopeptides: Honoraria. Thakurta: Oxford University: Other: Visiting Professor; BMS: Current Employment, Current equity holder in publicly-traded company. Anderson: Gilead: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Scientific Founder of Oncopep and C4 Therapeutics: Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company; Mana Therapeutics: Membership on an entity's Board of Directors or advisory committees. Munshi: Legend: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; Adaptive Biotechnology: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Celgene: Consultancy; Pfizer: Consultancy.

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Relative Clone Size By FISH of Both Del(13q) and Del(17p) Independently Impact Overall Survival

Blood ◽

10.1182/blood.v128.22.4444.4444 ◽

2016 ◽

Vol 128 (22) ◽

pp. 4444-4444

Author(s):

Soluman Culver ◽

Nita Williams ◽

Nidhi Sharma ◽

Yvonne A Efebera ◽

Ashley E Rosko ◽

...

Keyword(s):

Multiple Myeloma ◽

Overall Survival ◽

Board Of Directors ◽

Research Funding ◽

Staging System ◽

Maximal Effect ◽

Advisory Committees ◽

Clone Size ◽

Interphase Fish ◽

The Impact

Abstract Introduction: Interphase FISH is used in the risk stratification of newly diagnosed multiple myeloma. The presence of high-risk cytogenetics is a key component of the Revised International Staging System (R-ISS), despite the fact that precise cutoffs for positivity have yet to be standardized and usage differs between institutions and reference labs. For deletion 17p, Avet-Loiseau et al (2007) used a 60% cutoff and An et al (2015) used 50% as a positive cutoff. For del(13q), Avet-Loiseau used del(13q14) 74% and An et al used 10%. Methods: Since 2011, consecutive patients in Ohio State University's myeloma clinic were consented to participate in the Ohio Myeloma Initiative (NCT01408225), an observational registry. We identified patients with multiple myeloma who had a bone marrow biopsy performed within six months of diagnosis. All FISH was performed after CD138 magnetic separation. We assessed the impact of del17p (P53) and del13q (RB1) on overall survival (OS). Results: 1,029 myeloma patient were identified, 767 patients with a FISH study within 6 months of diagnosis with an age range of 26-91. 39% of patients had an ISS 1, 34% had ISS 2, and 27% had ISS 3 disease. The median duration of follow-up for these patients was 3.17 years. 82.7% of patients had data regarding del13q, 82.5% had data regarding del17p, and 78.4% had data regarding both del13q and 17p. Using iterative survival analysis we calculated a maximal effect of del17p on OS occurring at 50% positivity on interphase FISH. Additionally, our data suggests that positivity for del13q is maximal at 40% positivity and a predictor of moderately decreased overall survival independent of 17p status. Moreover, our data suggests that intermediate FISH positivity for 17p does have a dose-dependent effect on OS with the presence of even non-dominant del17p clones exerting a measurable influence similar in effect size to del13q. Analyzing those patients with del13q >40% that were negative for del(17p) and t(4;14) (n=27), these patients suffered an inferior overall survival when compared to patients that were negative for del13q, del17p, and t(4;14) (n=116), p=0.0042. Conclusions: These findings suggest that specific cutoffs for both the del(13q) and del(17p) clones at diagnosis independently have statistically significant effects on overall survival. At the meeting, additional analyses will demonstrate the percentages of del(13q) that impact similarly on overall survival to those patients with del(17p) alone. A scoring system will be created to estimate hazard ratios for relative clone size % of del(13q) and del(17p) separately and when combined. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures Hofmeister: Arno Therapeutics, Inc.: Research Funding; Signal Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Janssen: Pharmaceutical Companies of Johnson & Johnson: Research Funding; Karyopharm Therapeutics: Research Funding; Incyte, Corp: Membership on an entity's Board of Directors or advisory committees; Takeda Pharmaceutical Company: Research Funding; Teva: Membership on an entity's Board of Directors or advisory committees.

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Immunoglobulin Recovery after ASCT for Patients with Multiple Myeloma: Impact on Overall Survival and Progression-Free Survival

Blood ◽

10.1182/blood.v128.22.2263.2263 ◽

2016 ◽

Vol 128 (22) ◽

pp. 2263-2263

Author(s):

Victor Jimenez-Zepeda ◽

Peter Duggan ◽

Paola Neri ◽

Ahsan Chaudhry ◽

Jason Tay ◽

...

Keyword(s):

Multiple Myeloma ◽

Overall Survival ◽

Research Funding ◽

Progression Free Survival ◽

Partial Recovery ◽

Maintenance Strategy ◽

Free Survival ◽

Immune Enhancement ◽

The Impact

Abstract Introduction Immunoparesis, defined as suppression of uninvolved immunoglobulins (Igs), has been described as one of the most common indicators of immune dysfunction in patients with multiple myeloma (MM). The role of immunoglobulin recovery, however, has not been properly evaluated, in particular in the setting of immunomodulatory therapy. In the present study, we aimed to assess the impact of immunoparesis and Igs recovery after ASCT on Overall and Progression-Free survival (OS and PFS). Methods All consecutive patients undergoing ASCT at our center from 01/2004 to 03/2016 were evaluated. All patients received induction chemotherapy before undergoing auto-SCT. Patients received conditioning with either HDM at 200 mg/m2 (or adjusted as per renal failure) or HDM with Bortezomib (Bor-HDM). Definitions of response and progression were used according to the EBMT modified criteria. Immunoglobulin recovery was assessed at 12 months post-ASCT in those cases where immunoparesis was noted at diagnosis. Results Clinical characteristics are shown in Table 1. Decrease of uninvolved Ig's was noted in 94% of cases. At the time of analysis, 69.2% of patients are alive and 54.9% have already progressed, respectively. Median OS did not differ between patients with or without immunoparesis (p=0.851). With regards to Ig recovery at 12 months post-ASCT, median OS was longer for those patients with complete or partial normalization of Ig's compared to those with no recovery at all (Estimate median OS of 97, 77 and 69 months, respectively, p=0.008) (Fig1a). In addition, median PFS was longer for those patients with normalization or partial recovery of Ig's at 12 months post-ASCT (median of 40.3 and 38 months, compared to 24.6 months for those without Ig recovery, p=0.002) (Fig1b). Furthermore, 121 patients receiving lenalidomide maintenance were evaluated, 49% of cases exhibited complete or partial recovery of Ig's at 12 months post-ASCT, compared to 40% for those cases that were not treated with any maintenance strategy (p=0.6). In conclusion, Immunoglobulin recovery at 12 months post-ASCT is an important factor to predict for better progression-free and overall survival. The use of lenalidomide as a maintenance strategy did not seem to affect the process of Ig recovery. Based on our observations, the use of immune enhancement strategies in the post-transplant setting seem appealing and requires further investigation. Disclosures Jimenez-Zepeda: Janssen: Honoraria; Amgen: Honoraria; Takeda: Honoraria; Celgene, Janssen, Amgen, Onyx: Honoraria. Neri:Celgene and Jannsen: Consultancy, Honoraria. Bahlis:Celgene: Consultancy, Honoraria, Other: Travel Expenses, Research Funding, Speakers Bureau; BMS: Honoraria; Onyx: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Travel Expenses, Research Funding, Speakers Bureau.

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The Impact of Induction Regimen Choice on Transplant Outcome and Survival in Newly Diagnosed Multiple Myeloma in the Era of Novel Agents

Blood ◽

10.1182/blood.v126.23.3044.3044 ◽

2015 ◽

Vol 126 (23) ◽

pp. 3044-3044

Author(s):

Rajshekhar Chakraborty ◽

Shaji Kumar ◽

Francis Buadi ◽

David Dingli ◽

Angela Dispenzieri ◽

...

Keyword(s):

Multiple Myeloma ◽

Overall Survival ◽

Research Funding ◽

Novel Agents ◽

Agent Based ◽

Induction Regimen ◽

Baseline Characteristics ◽

The Impact ◽

Novel Agent

Abstract Background Induction with novel agents, including proteasome inhibitors and immunomodulators, prior to autologous stem cell transplantation (ASCT) is the standard of care frontline treatment of transplant-eligible patients with multiple myeloma (MM). Common novel agent-based induction regimens include three drug combinations with a backbone of bortezomib (V), thalidomide (T) and/or lenalidomide (R). There is limited information on the comparative efficacy of novel regimens used as part of initial therapy prior to an ASCT in terms of overall survival (OS). To address this question, we retrospectively analyzed 1096 consecutive patients undergoing ASCT for MM at Mayo Clinic. Methods Study patients included those who underwent first transplant within 12 months of diagnosis, did not receive more than one induction regimen, did not relapse prior to transplant and did not receive treatment for smoldering MM in the past. Baseline characteristics, response rates and survival data were extracted from an electronic medical record and statistical analysis was done using JMP 10.0.0 (SAS Institute Inc.). Choice of induction regimen was almost exclusively made by the referring physician. Results Median age at diagnosis was 60.3 years (Interquartile range 53.9-65.9). ISS staging at diagnosis was available for 49.7% of patients, of which, 34.2%, 39.3% and 26.5% of patients had ISS stage 1, 2 and 3 disease, respectively. Estimated median follow up was 65.6 months (95% CI 58.3-73.3). Baseline characteristics of patients by initial treatment have been summarized in table 1. Major subgroups by induction therapy included patients receiving Cy-Bor-d (n=193, 17.6%), Vd (n=64, 5.83%), Rd (n=253, 23.1%), VRd (n=126, 34.6%), Td (n=157, 14.3%) and VAD or dexamethasone alone as the non-novel agent comparator group (n=229, 20.9%). Median overall survival (OS) was significantly different between novel agent-based and conventional regimens (Log-rank test; p=0.0029), which were 102.7 months (95% CI, 95.2-112.2) and 78.8 months (95% CI, 67.8-92.6) respectively. Median OS with each regimen is shown in table 1. Among novel agent-based regimens, there was no significant difference in median OS, except Td, which was inferior to Rd (HR 1.62; 95% CI 1.17-2.24). Conclusion We cannot demonstrate with overall survival as an endpoint that the doublets of Vd and Rd are inferior to VRd or Cy-bor-d. There were insufficient patients treated with VTd to be included. Our study shows that the choice of novel induction regimen prior to ASCT does not affect survival (with the exception of Td being inferior to Rd), reflecting the wide array of effective salvage options. However, further prospective randomized clinical trials comparing these regimens are required to validate these findings. Table 1. Baseline characteristics and overall survival. Baseline characteristics and survival Cy-Bor-d (n=193) Vd (n=64) Rd (n=253) VRd (n=126) Td (n=157) VAD or Dex (n=229) p-value Median age 61.9 62.15 60.8 60.8 59.3 58.5 0.0041 Sex (percent males) 56.48 57.81 56.92 61.91 57.96 59.82 0.9271 ISS at diagnosis 1:24.82% 2:40.69% 3:34.48% 1:29.73% 2:24.32% 3:45.94% 1:40% 2:43.78% 3:16.22% 1:41.76% 2:34.06% 3:24.18% 1:28% 2:36% 3:36% 1:20% 2:60% 3:20% 0.0005 Median follow-up (95% CI) 20.3 (17.1-22.7) 49.5 (44.7-55.7) 59 (54.5-67) 26.9 (22.8-30.7) 126.7 (120.2-132.9) 143.4 (132.5-152.6) <0.0001 Median OS Not reached (Estimated 5 year OS rate 75%) 97.2 months (95% CI, 66.6-NR) 112 months (95% CI, 97.4-124.3) Not reached (Estimated 5-year OS rate 77%) 81.1 months (95% CI, 59.1-99.1) 78.8 months (95% CI, 67.8-92.6) 0.0019 Figure 1. Figure 1. Disclosures Kumar: Onyx: Consultancy, Research Funding; Novartis: Research Funding; Abbvie: Research Funding; Celgene: Consultancy, Research Funding; Millenium: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Gertz:Smith Kline: Honoraria; Novartis: Honoraria; Onyx: Honoraria; millenium: Consultancy, Honoraria; Celgene: Honoraria.

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Vorinostat, Bortezomib, Cyclophosphomide, Thalidomide, and Dexamethasone in Relapsed/Refractory Multiple Myeloma Patients

Blood ◽

10.1182/blood.v124.21.5773.5773 ◽

2014 ◽

Vol 124 (21) ◽

pp. 5773-5773 ◽

Cited By ~ 1

Author(s):

Charise Gleason ◽

Jonathan L. Kaufman ◽

Ajay K. Nooka ◽

Kelly Valla ◽

Leonard T Heffner ◽

...

Keyword(s):

Multiple Myeloma ◽

Overall Survival ◽

Combination Therapy ◽

Clinical Benefit ◽

Research Funding ◽

Response Rates ◽

Phase Iii ◽

Refractory Multiple Myeloma ◽

Heavily Pretreated ◽

Grade 3

Abstract The combination of vorinostat, a histone deacetylase (HDAC) inhibitor, is synergistic with proteasome inhibitors and IMIDs based upon preclinical and clinical data. Phase III trials with vorinostat in relapsed myeloma failed to demonstrate benefit due to excess toxicity that precluded chronic administration of the agent allowing patients to realize the clinical benefits. Herein we report on our experience combining vorinostat, or adding vorinostat to current treatments in the context of refractory myeloma. Methods: Forty RRMM pts that received vorinostat (V) (200mg orally daily on days 1-14) and bortezomib (B) (1.3 mg/m2 IV/SQ days 1,4,8, and 11) combinations, every 28 days from May 2008 until May 2014 at Emory University were reviewed. Cohort 1 consisted of 22 RRMM pts that received VBCyTD regimen (V,B, cyclophosphamide (Cy) (300 mg orally flat dose days 1, 8 and 15), thalidomide (T) (100 mg daily) and dexamethasone (D) 40 mg orally weekly), while cohort 2 consisted of 18 RRMM pts that received other combinations (VBCyD+lenalidomide (R): 4 pts; VBRD: 4 pts; VBCyD: 2 pts; VBD: 4 pts; VBTD: 4 pts and VCyTD+carfilzomib (Ca): 2 pts). The objectives are response assessment by IMWG criteria, progression-free survival (PFS) and overall survival (OS). Drug related adverse events (AEs) ≥grade 3 (CTCAE v3.0) were summarized. Results: Twenty-one males and nineteen females (median age at diagnosis: 56 years [range 28-89], median age at initiation of V treatment: 62 years [range 33-91]) that were heavily pretreated (median lines of therapy: 7 [range 3-14] were included in the analysis. Ninety-five percent of pts were B refractory and 85% pts were R refractory; 97.5% and 15% of pts underwent prior autologous and allogeneic SCT, respectively. High risk cytogenetic abnormalities were seen in 40% of pts. Time from diagnosis to initiation of V combination therapy is 58.5 months (range 18-138). The overall clinical benefit rate (≥SD) was 72.5%. Figure 1 illustrates response rates from both cohorts. Median PFS for cohort 1 is 3 months (95% CI 0.5-5.51) and for cohort 2 is 2 months (95% CI 0.8-3.2), respectively. At a median follow-up of 26 months from the time of V initiation, median OS for cohort 1 is 6 months (95% CI 0-13.6) and for cohort 2 is 3 months (95% CI 1.4-4.7). Median overall survival from diagnosis for these cohorts is 80 months (95% CI 70.2-89.8) and 70 (95% CI 55.6-84.4) months, respectively. ≥Grade 3 AEs include fatigue (15%); generalized weakness (12.5%); neutropenia (15%); and thrombocytopenia (35%). Conclusions: In heavily pretreated relapsed/refractory multiple myeloma patients with limited therapeutic options, vorinostat and bortezomib combination therapy offers clinical benefit with good response rates and acceptable tolerability, likely due to lower doses of vorinostat used. This data further supports the activity of HDAC inhibitors in the context of refractory myeloma. Figure 1 Figure 1. Disclosures Gleason: Celgene: Consultancy; Novartis: Consultancy. Heffner:Amgen: Honoraria, Research Funding; Biotest: Honoraria, Research Funding; Dana Farber CI: Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Idera: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; Onyx: Honoraria, Research Funding; Spectrum: Honoraria, Research Funding; Talon Therapeutics: Honoraria, Research Funding. Lonial:Millennium: The Takeda Oncology Company: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding.

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Development and Results of a Multiple Myeloma Specific Custom 77-Gene Mutation Panel for Clinical Targeted Sequencing

Blood ◽

10.1182/blood.v124.21.169.169 ◽

2014 ◽

Vol 124 (21) ◽

pp. 169-169 ◽

Cited By ~ 1

Author(s):

K. Martin Kortuem ◽

A. Keith Stewart ◽

Laura Ann Bruins ◽

Gregory Ahmann ◽

George Vasmatzis ◽

...

Keyword(s):

Multiple Myeloma ◽

Drug Resistance ◽

Copy Number ◽

Research Funding ◽

Pharmaceutical Research ◽

Advisory Committees ◽

Significant Information ◽

Precision Therapy ◽

Copy Number Changes ◽

Salary Support

Abstract Background:A goal of “post-genomic” cancer care is development of specific, affordable, reliable and rapid next-generation sequencing-based assays determining prognosis, therapeutic selection and minimal disease monitoring, replacing older technologies in the diagnostic and monitoring workup. In this regard, we designed and deployed a custom gene panel for identification of mutations, copy-number changes and clonal frequency in multiple myeloma (MM) samples. Methods: The MM Mutation Panel Version 2.0 (M3P 2.0)1 includes 1271 amplicons from 77 genes that are either mutated in MM (genes with a published mutation incidence ≥3%), represent critical pathophysiological pathways, are targetable with small molecule-based therapies and/or are associated with drug resistance (eg. XBP-1, CRBN, IZKF, IRF4). The amplicons are spread across 21 chromosomes, allowing the identification of copy-number changes in these regions. Results: We have sequenced 38 MM cases (150 will be presented) with paired tumor-germline DNA samples, using only 20ng of DNA for library preparation. Patients (Pts) included 29 untreated and 9 MM pts with multi drug refractory disease. Coverage depth averaged 964X. Hyperdiploid MM was successfully identified in 45% of cases, del(13q) in 34%, del(1p) in 18%, del(17p) in 8% and gain of 1q in 13%. Array CGH in representative cases confirmed concordance with semiconductor sequencing. Overall, 71 exonic missense and 3 nonsense mutations were detected, and 7 frameshift indels. In 89% of the pts a mutation in at least one M3P2.0 gene was identified (range 1-8). 92% of mutations were predicted damaging (Provean, Polyphene-2 or SIFT). Most commonly mutated were KRAS (37%), NRAS (21%), BRAF (13%), TP53, CDKN1B, DIS3 (each 11%), FAM46C, STAT3, and IRF4 (each 8%). The MEK-ERK pathway was mutated in 61% of cases and in 3 cases more than one gene in this pathway (NRAS, KRAS, BRAF) was simultaneously mutated. Six mutations in BRAF were identified in 5 untreated pts, 3 of them known to be activating and targetable (Val600E). Other commonly mutated pathways were the NFKB pathway in 24% of pts and the Cyclin D pathway, mutated in 16% of cases. Genes of the cereblon pathway (CRBN, IRF4, IKZF3), essential for the action of lenalidomide (len) were mutated in 5 Pts. One newly diagnosed and len refractory Pt harbored a subclonal CRBN mutation (Asn316Lys, allelic fraction [AF] 20%) as well as 4 clonal IRF4 mutations within the DNA binding domain of the gene (Lys89Asn (AF 78%), Lys77Glu, Ser48Arg and Cys49Ser (AF 80% each). Another IRF4 mutated (Lys123Arg, AF 90%) hemodialysis dependent Pt was responsive to dose adapted treatment of len and dexamethasone (dex). Mutations in the C2H2-type 3 region of IKZF3 in a len resistant (Gly191Arg, AF 48%) pt occured as well as in a len and dex responsive (Arg242Gly, AF 52%) Pt. Furthermore, we identified a truncating XBP1 mutation (p.Leu232*, 97% AF) in a Pt refractory to bortezomib. One patient harbored a mutation in the steroid receptor NR3C1 (Pro255Leu, 22% variant reads). Finally, integrated mutation and copy-number data identified biallelic deletions of CDKN2C and FAM46C in a multi drug refractory Pt. Mutation and/or copy-number losses in both alleles were found in DIS3 in 4 Pts, in CYLD, TP53 and TRAF3 in 2 Pts and in CARD11, CDKN2A, CDKN1B, RB1and STAT3 in one Pt each. Conclusion: In summary, we report the initial results from 38 MM Pts using a custom MM sequencing panel which employs small amounts of DNA requiring very few cells and providing deep coverage in clinically meaningful timeframes. Our findings frequently include prognostically significant information, actionable targets and mutations in genes related to drug resistance. Targeted mutation profiling will likely become part of the clinical workup in MM and our M3P2.0 mutation panel is a suitable tool to provide information needed to guide precision therapy and to set the basis for individually tailored treatment decisions. 1. Kortuem KM. et al. Development Of a 47 Gene Sequencing Panel For Common Mutations Present In Multiple Myeloma: Preliminary Results In 77 p53 Deleted Patients, ASH 2013. Disclosures Stewart: Celgene: Consultancy; Bristol Myers Squibb: Consultancy; Array BioPharma: Consultancy; Sanofi: Consultancy; Takeda Pharmaceuticals International Co.: Research Funding; Novartis: Consultancy. Bruins:OncoSpire: Salary support Other. Vasmatzis:OncoSpire: Salary Support Other. Kumar:Celgene: Consultancy, Research Funding; Millennium: The Takeda Oncology Co.: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding; Sanofi-Aventis: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Skyline Diagnostics: Membership on an entity's Board of Directors or advisory committees. Fonseca:Medtronic, Otsuka, Celgene, Genzyme, BMS, Lilly, Onyx, Binding Site, Millennium, AMGEN: Consultancy, patent for the prognostication of MM based on genetic categorization of the disease. He also has sponsored research from Cylene and Onyx Other, Research Funding. Bergsagel:MundiPharma: Research Funding; OncoEthix: Research Funding; Constellation Pharmaceutical: Research Funding; Novartis: Research Funding.

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Landscape of Driver Lesions in Multiple Myeloma and Consequences for Targeted Drug Response

Blood ◽

10.1182/blood.v124.21.3351.3351 ◽

2014 ◽

Vol 124 (21) ◽

pp. 3351-3351

Author(s):

David Tamborero ◽

Muntasir Mamun Majumder ◽

Raija Silvennoinen ◽

Samuli Eldfors ◽

Pekka Anttila ◽

...

Keyword(s):

Multiple Myeloma ◽

Positive Selection ◽

Copy Number ◽

Research Funding ◽

Drug Response ◽

Ex Vivo ◽

Genomic Data ◽

Genetic Alterations ◽

Gene Copy ◽

Copy Number Changes

Abstract Introduction Multiple myeloma (MM) is a heterogeneous disease that eventually becomes resistant to therapy. Determining the genomic lesions driving each stage of the tumor and identifying actionable items for novel targeted drugs will improve and increase therapeutic options for the malignancy. The aim of the present work is to obtain a comprehensive catalog of driver genomic lesions for both newly diagnosed (NDMM) and refractory/relapsed MM (RRMM) patients by integrating multiple genomic data and linking these to the action of targeted therapeutic approaches. Methods Molecular cytogenetics was assessed by fluorescence in situ hybridization and somatic mutations and copy number changes were identified by performing exome sequencing of DNA from CD138+ cell and skin paired samples collected from 30 MM patients (NDMM n=12; RRMM n=18). In addition, gene expression profiles were obtained by transcriptome sequencing. The proportion of tumor clones bearing a specific mutation was inferred from the variant allele frequency. Genetic alterations involved in the tumorigenesis of each patient (named drivers) were identified by combining an in silico method aimed to score their potential for being malignant with the a priori knowledge retrieved from the identification of complementary signals of positive selection in available tumor cohorts (Tamborero et al. Nat Sci Rep 2013). Selective drug response was assessed by testing the ex vivo sensitivity of patient derived CD138+ cells to 306 oncology drugs and comparing results with responses derived from healthy bone marrow control cells. Results Overall, 0.5 translocations, 3±2.8 mutations and 4.9±2.7 copy number changes per patient were identified as putative drivers. The total number of driver alterations did not differ between NDMM and RRMM samples, and no gene reached statistical significance for being more frequently altered in the latter group. However, the only mutations in RAS genes that appeared at sub-clonal proportions occurred in diagnosed samples, pointing out their positive selection among relapsed patients in which they were present in all clones. Translocations involving IGH@ were observed in 11 (37%) patients, and interestingly 3 other samples exhibited driver alterations in the oncogenes involved in these fusions (i.e. activating mutations in FGFR3 or gene amplification plus peaked overexpression of WHSC1 and CCND1). Recurrent alterations were observed among genes previously associated with MM, including DIS3 (n=15), KRAS (n=11), CYLD (n=8), TRAF3 (n=6) and FAM46C (n=5). Other genes not previously associated with or less-known to be involved in MM pathogenesis were also identified, including the histone methyltransferase MLL, the tumor necrosis factor associated genes FAF1 and TNFRSF13B, the p53-suppressing protein phosphatase PPM1D, and several genes related with blood cell differentiation and B-lymphocyte development (e.g. SOX7, BLK and PRDM1). Overall, the pathways most frequently targeted by driver alterations were MAPK (23 (77%) samples, mostly by mutations), NF-κB (17(57%) samples, mostly by gene copy loss), cell-cycle (18 (60%) samples), and RNA-processing (17 (57%) samples). Comparison of driver lesions to drug response using data derived from ex vivo testing of the same patient samples to different targeted small molecule inhibitors (e.g. PI3K/mTOR and MEK inhibitors) indicated that alterations affecting PI3K and p53 pathways were associated with increased drug sensitivity, while alterations involving activation of FGFR3 and copy loss of TRAF3 were associated with a more resistant phenotype. Conclusions The integration of multiple genomic data by combining different predictive computational tools can comprehensively identify cancer events in individual patients. Applying these tools to genomic data from MM patients identified both known and novel driver lesions, and some of these alterations were associated with the ex vivo response to selective drugs. However, further data is required to confirm biomarkers of response to those novel therapeutics and test potential benefits in MM patients. Disclosures Silvennoinen: Janssen, Sanofi, Celgene: Honoraria; Research Funding of Government Finland, Research Funding from Janssen and Celgene: Research Funding. Porkka:Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding. Heckman:Celgene: Research Funding.

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Whole-genome sequencing from the New Zealand Saccharomyces cerevisiae population reveals the genomic impacts of novel microbial range expansion

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkaa027 ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Peter Higgins ◽

Cooper A Grace ◽

Soon A Lee ◽

Matthew R Goddard

Keyword(s):

Saccharomyces Cerevisiae ◽

New Zealand ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Range Expansion ◽

Copy Number ◽

Small Scale ◽

Whole Genome ◽

Copy Number Changes ◽

The Impact

Abstract Saccharomyces cerevisiae is extensively utilized for commercial fermentation, and is also an important biological model; however, its ecology has only recently begun to be understood. Through the use of whole-genome sequencing, the species has been characterized into a number of distinct subpopulations, defined by geographical ranges and industrial uses. Here, the whole-genome sequences of 104 New Zealand (NZ) S. cerevisiae strains, including 52 novel genomes, are analyzed alongside 450 published sequences derived from various global locations. The impact of S. cerevisiae novel range expansion into NZ was investigated and these analyses reveal the positioning of NZ strains as a subgroup to the predominantly European/wine clade. A number of genomic differences with the European group correlate with range expansion into NZ, including 18 highly enriched single-nucleotide polymorphism (SNPs) and novel Ty1/2 insertions. While it is not possible to categorically determine if any genetic differences are due to stochastic process or the operations of natural selection, we suggest that the observation of NZ-specific copy number increases of four sugar transporter genes in the HXT family may reasonably represent an adaptation in the NZ S. cerevisiae subpopulation, and this correlates with the observations of copy number changes during adaptation in small-scale experimental evolution studies.

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