scholarly journals Superior results of Total Therapy 3 (2003-33) in gene expression profiling–defined low-risk multiple myeloma confirmed in subsequent trial 2006-66 with VRD maintenance

Blood ◽  
2010 ◽  
Vol 115 (21) ◽  
pp. 4168-4173 ◽  
Author(s):  
Bijay Nair ◽  
Frits van Rhee ◽  
John D. Shaughnessy ◽  
Elias Anaissie ◽  
Jackie Szymonifka ◽  
...  

The Total Therapy 3 trial 2003-33 enrolled 303 newly diagnosed multiple myeloma patients and was noted to provide superior clinical outcomes compared with predecessor trial Total Therapy 2, especially in gene expression profiling (GEP)–defined low-risk disease. We report here on the results of successor trial 2006-66 with 177 patients, using bortezomib, lenalidomide, and dexamethasone maintenance for 3 years versus bortezomib, thalidomide, and dexamethasone in year 1 and thalidomide/dexamethasone in years 2 and 3 in the 2003-33 protocol. Overall survival (OS) and event-free survival (EFS) plots were super-imposable for the 2 trials, as were onset of complete response and complete response duration (CRD), regardless of GEP risk. GEP-defined high-risk designation, pertinent to 17% of patients, imparted inferior OS, EFS, and CRD in both protocols and, on multivariate analysis, was the sole adverse feature affecting OS, EFS, and CRD. Mathematical modeling of CRD in low-risk myeloma predicted a 55% cure fraction (P < .001). Despite more rapid onset and higher rate of CR than in other molecular subgroups, CRD was inferior in CCND1 without CD20 myeloma, resembling outcomes in MAF/MAFB and proliferation entities. The robustness of the GEP risk model should be exploited in clinical trials aimed at improving the notoriously poor outcome in high-risk disease.

2016 ◽  
Vol 6 (9) ◽  
pp. e471-e471 ◽  
Author(s):  
Y Jethava ◽  
A Mitchell ◽  
M Zangari ◽  
S Waheed ◽  
C Schinke ◽  
...  

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 162-162 ◽  
Author(s):  
Bart Barlogie ◽  
Elias J. Anaissie ◽  
John D. Shaughnessy ◽  
Frits van Rhee ◽  
Mauricio Pineda-Roman ◽  
...  

Abstract We have previously reported on the remarkable activity of the TT3 program that incorporated both bortezomib (V) and thalidomide (T) into the up-front management of 303 patients. TT3 consisted of 2 cycles each of induction prior to and of dose-reduced consolidation therapy with VTD-PACE (cisplatin, doxorubicin, cyclophosphamide, etoposide) after melphalan 200mg/m2 (M200)-based tandem transplants, followed by maintenance therapy for 3 years with VTD and, in later stages, VRD (substituting T for lenalidomide, R). Characteristics included a median age of 59yr (range, 33–75yr), B2M &gt;=4mg/L in 37%, albumin &lt;3.5g/dL in 26%, ISS stages II and III in 33% and 21%, cytogenetic abnormalities (CA) in 33% and gene expression profiling (GEP)-defined high-risk MM in 15% of the 275 patients with such data. With a median follow-up of 39 months, 4-yr overall survival (OS) and event-free survival (EFS) estimates were 78% and 71%, respectively, including 84% and 77% among the 85% with GEP-defined low-risk MM contrasting with 43% and 33% in the remainder with high-risk MM (both p&lt;0.0001). Near-CR and CR, attained in 86% and 63%, were sustained at 4 years from response onset in 78% and 87%, which pertained to 83% and 90% with low-risk MM but to only 44% and 57% with high-risk MM (all p &lt;0.0001). These results were corroborated in a TT3 extension trial (TT3E) that enrolled 175 additional patients, comprising higher proportions of CA (42%) and GEP-defined high-risk MM (21%). Two-year estimates of OS and EFS are 85% and 85%, with 94% and 92% in low-risk patients versus 61% and 62% in high-risk MM (p=0.0001, p=0.0003); the 2-yr estimate of remaining in CR is 93% including 100% in low-risk and 77% in high-risk MM (p=0.01). Multivariate analysis of features linked to OS in TT3 included GEP-defined high-risk, CA, B2M and LDH elevation, collectively accounting for 41% of outcome variability by R2 statistics; the corresponding R2 values for EFS and n-CR duration were 38% and 39%. Compared to the predecessor trial, TT2, that evaluated the role of T in a randomized trial design in 668 patients, TT3 data were superior for OS (p=0.08), EFS (&lt;0.0001), n-CR duration (p&lt;0.0001) and CR duration (p=0.0002). In the low-risk subgroup, EFS (p=0.0001), n-CR duration (p&lt;0.0001) and CR duration (Figure 1a; p=0.0002) all were superior in TT3 versus TT2; whereas, in the high-risk MM group, outcomes remained poor also with TT3 despite superior EFS (Figure 1b; p=0.03). Based on these data, we have now started a GEP-risk-based algorithm of assigning separate therapies to good-risk (TT4) and poor-risk MM (TT5). As the TT3 results for low-risk are difficult to improve upon, TT4 randomizes patients between standard TT3 and TT3-LITE that employs only 1 cycle each of induction and consolidation (with anticipated further improvement in compliance) and 4-day-fractionated M50×4 to enable the addition of VTD and thus exploit synergistic drug interactions to occur. In order to sustain tolerable effective therapies for at least 3 years and prevent recurrence from previous drug-free or insufficiently effective phases in TT3, TT5 for high-risk MM employs less dose-intense and more dose-dense highly synergistic combination therapy, utilizing M10-VTD-PACE for induction, M80 (in 4 daily fractions of M20) plus VRD-PACE tandem transplants, separated by 2 cycles of M20 (in 4 daily fractions of M5) plus VTD-PACE, and followed by 2 years of monthly alternating R-VD and M-VD. Figure 1a: Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1a:. Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1b: Superior event-free survival with TT3 v TT2 in GEP-high-risk MM: Figure 1b:. Superior event-free survival with TT3 v TT2 in GEP-high-risk MM:


2007 ◽  
Vol 13 (23) ◽  
pp. 7073-7079 ◽  
Author(s):  
Jeffrey Haessler ◽  
John D. Shaughnessy ◽  
Fenghuang Zhan ◽  
John Crowley ◽  
Joshua Epstein ◽  
...  

Blood ◽  
2009 ◽  
Vol 113 (26) ◽  
pp. 6572-6575 ◽  
Author(s):  
Bijay Nair ◽  
John D. Shaughnessy ◽  
Yiming Zhou ◽  
Marie Astrid-Cartron ◽  
Pingping Qu ◽  
...  

Abstract We report on prognostic implications for postrelapse survival (PRS) of a gene expression profiling (GEP)–defined risk score at relapse available in 120 myeloma patients previously enrolled in tandem transplantation trial Total Therapy 2. Among the 71 patients with additional GEP baseline information, 3-year PRS was 71% in 40 patients with low risk present both at baseline and relapse contrasting with only 17% in 28 patients with high risk at relapse, 12 of whom with baseline low-risk status fared better than the remainder (P = .08). On multivariate analysis of relapse parameters available in 104 patients, high risk conferred short PRS (hazard ratio = 4.00, P < .001, R2 = 33%), whereas relapse hyperdiploidy predicted long PRS (hazard ratio = 0.37, P = .022, cumulative R2 = 41%). In case the initial partial response lasted less than 2 years, relapse low-risk identified 26 patients with superior 3-year PRS of 61% versus 9% among 32 with relapse high-risk (P < .001). Based on its PRS predictive power, GEP analysis should be an integral part of new agent trials in search of better therapy for high-risk myeloma.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3264-3264 ◽  
Author(s):  
Ryan K Van Laar ◽  
Ivan Borrelo ◽  
David Jabalayan ◽  
Ruben Niesvizky ◽  
Aga Zielinski ◽  
...  

Abstract Background: There is a global consensus that multiple myeloma patients with high-risk disease require additional monitoring and therapy compared to low/standard risk patients in order to maximize their chances of survival. Current diagnostic guidelines recommend FISH-based assessment of chromosomal aberrations to determine risk status (i.e. t(14;20), t(14;16), t(4;14) and/or Del17p), however, studies show FISH for MM may have a 20-30% QNS rate and is up to 15% discordant between laboratories, even when starting from isolated plasma cells. In this study we demonstrate that MyPRS gene expression profiling reproduces the key high risk translocations for MM risk stratification, in addition to having other significant advantages. Methods: Reproducibility studies show that MyPRS results are less than 1% discordant starting from isolated plasma cells and return successful results in up to 95% of cases. 270 MM patients from Johns Hopkins University (MD) and Weill Cornell Medicine (NY) had both FISH and MyPRS gene expression profiling performed between 2012 and 2016 using standard and previously published methodology, respectively. Results: Retrospective review of the matched FISH and MyPRS results showed: 25/28 (89%) patients wish FISH-identified t(4;14) were classified as MMSET (MS) subtype. 10/10 (100%) patients with t(14;16) or t(14;20) were classified as MAF-like (MF) subtype 62/67 (93%) patients with t(11;14) were assigned to the Cyclin D (1 or 2) subtype. Patients with FISH hyperdiploidy status were classified as the Hyperdiploid (HY) subtype or had multiple gains detected by the separate MyPRS Virtual Karyotype (VK) algorithm, included in MyPRS. TP53del was seen in patients with multiple molecular subtypes, predominantly Proliferation (PR) and MMSET (MS). Assessment of TP53 function by gene expression is a more clinically relevant prognostic marker than TP53del, as dysregulation of the tumor suppressor is affected by mutations as well as deletions. Analysis of the TP53 expression in the 39 patients with delTP53 showed a statistically significant difference, compared to patients without this deletion (P<0.0001). Conclusion: Gene expression profiling is a superior and more reliable method for determining an individual patients' prognostic risk status. The molecular subtypes of MM, as reported by Signal Genetics MyPRS assay, are driven by large-scale changes in gene expression caused by or closely associated with chromosomal changes, including translocations. Physicians who are managing myeloma patients and wishing to base their assessment of risk on R-ISS or mSMART Guidelines may obtain the required data points from either FISH or MyPRS, with the latter offering lower QNS rates, higher reproducibility, assessment of a larger number of cells and a substantially lower price point ($5,480 vs. $1,912; 2016 CMS data). A larger cohort study is now underway to further validate these observations. Figure GEP-based TP53 expression in patients with and without Del17p. P<0.0001 Figure. GEP-based TP53 expression in patients with and without Del17p. P<0.0001 Disclosures Van Laar: Signal Genetics, Inc.: Employment. Borrelo:Sidney Kimmel Cancer Institute: Employment. Jabalayan:Weill Cornell Medical Center: Employment. Niesvizky:Celgene: Consultancy, Research Funding, Speakers Bureau; Takeda: Consultancy, Research Funding, Speakers Bureau; Onyx: Consultancy, Research Funding, Speakers Bureau. Zielinski:Signal Genetics, Inc.: Employment. Leigh:Signal Genetics, Inc.: Employment. Brown:Signal Genetics, Inc.: Employment. Bender:Signal Genetics, Inc.: Employment.


Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1705-1705
Author(s):  
Ricky D Edmondson ◽  
Sheeno P Thyparambil ◽  
Veronica MacLeod ◽  
Bart Barlogie ◽  
John D. Shaughnessy

Abstract Although melphalan-based autologous stem cell transplantation has improved prognosis for patients diagnosed with Multiple Myeloma, survival varies from a few months to more than 15 years with an individual’s risk not accurately predicted with standard prognostic variables. Correlating genome-wide mRNA expression profiles in purified myeloma cells with outcome, we recently showed that that the differential expression of 70 genes could identify patients at high risk for early disease related death [1]. The utility of a high throughput proteomics platform in the analysis of clinical samples has great potential but as of yet none have been firmly established. Herein, we describe the use of such a platform and its utility in stratifying patients with Multiple Myeloma in terms of high and low risk disease. Preliminary analysis indicates that the proteomics data can separate the patients into risk groups, although the proteins responsible for the assignment are not identical to the 70 genes identified in the gene expression profiling experiments. In addition to the proteomic analysis of plasma cells enriched using anti-CD138 immunomagnetic beads from mononuclear cell fractions of bone marrow aspirates from newly diagnosed myeloma patients; we have performed (in triplicate) LCMS profiling on plasma cells from 30 patients isolated prior to and 48 hours after a single test-dose application of bortezomib at 1.0mg/m2. An aliquot of 100,000 plasma cells was enzymatically digested with trypsin and a fraction (~5,000 cells) analyzed using our proteomics platform (an Eksigent nanoHPLC coupled to a ThermoElectron LTQ-Orbitrap with data analyzed using the Elucidator software package from Rosetta Biosoftware). The correlation of the proteomic profiles to gene expression profiles and clinical parameters will be presented. The analysis of proteins that were observed to change (p&lt;0.01) in abundance after the single agent dose of the proteasome inhibitor bortezomib yielded an unanticipated finding; the abundance of 30 proteins associated with the proteasome were observed to increase in a subset of patients. The majority of the patients with the increased levels of proteasome related proteins are predicted by GEP to have high risk disease. The proteomic data will be discussed in terms of its utility in the identification of activated pathways as well as in the development of a prognostic indicator as was achieved using gene expression profiling.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3123-3123
Author(s):  
Bart Barlogie ◽  
Emily Hansen ◽  
Sarah Waheed ◽  
Jameel Muzaffar ◽  
Monica Grazziutti ◽  
...  

Abstract Intra-tumoral heterogeneity (ITH) is increasingly viewed as the Achilles heel of treatment failure in malignant disease including multiple myeloma (MM). Most MM patients harbor focal lesions (FL) that are recognized on MRI long before bone destruction is detectable by conventional X-ray examination. Serial MRI examinations show that eventually 60% of patients will achieve resolution of FL (MRI-CR). However, this will lag behind the onset of a clinical CR by 18 to 24 months, thus attesting to the biological differences between FL and diffuse MM growth patterns. Consequently, we performed concurrent gene expression profiling (GEP) analyses of plasma cells (PC) from both random bone marrow (RBM) via iliac crest and FL. Our primary aims were to first compare the molecular profiles of FL vs. RBM, second to determine if ITH existed (as defined molecular subgroup and risk), and finally to investigate if the bone marrow micro-environment (ME) contained a biologically interesting signature. A total of 176 patients were available for this study with a breakdown of: TT3 (n=23), TT4 for low-risk (n=131) and TT5 for high-risk MM (n=22). Regarding the molecular analyses of PCs, GEP-based risk (GEP-70, GEP-5) and molecular subgroup correspondence were examined for commonalties and differences between RBM and FL. A “filtering” approach for ME genes was also developed and bone marrow biopsy (BMBx) GEP data derived from this method is under analysis. PC risk correspondence between FL and RBM was 86% for GEP70 and 88% for the GEP5 model. Additionally, 82% had a molecular subgroup concordance, however, they did differ among subgroups (p=0.020) by Fisher's Exact Test. A lower concordance was noted in the CD2, LB, and PR subgroups (67%, 69%, 73%, respectively). GEP70 and GEP5 risk concordance between RBM and FL samples by molecular subgroup was also examined. The overall correlation coefficients were 0.619 (GEP70) and 0.597 (GEP5). The best correspondence was noted for CD1, MF and PR subgroups especially for the GEP5 model. HY, LB and MS showed intermediate correlations, while CD2 fared worst with values of only 0.322 for GEP70 and 0.267 for GEP5 model. Figure 1 portrays these data in more detail for the GEP70 and GEP5 models. Good correlations were noted between RBM and FL based risk scores in case of molecular subgroup concordance (left panels) in both GEP5 and GEP70 risk models, whereas considerable scatter existed in case of subgroup discordance (right panels). The clinical implications in TT4 regarding RBM and FL derived risk and molecular subgroup information, viewed in the context of standard prognostic baseline variables are portrayed in Table 1. High B2M levels at both cut-points imparted inferior OS and PFS as did low hemoglobin. Although present in 42% of patients, cytogenetic abnormalities (CA) did not affect outcomes. FL-based GEP5-defined high-risk designation conferred poor OS and PFS. B2M>5.5mg/L and FL-derived GEP5 high-risk MM, pertaining to 29% and 11% of patients, survived the multivariate model for both OS and PFS. Next, in examining PC-GEP differences among RBM and FL sites, 199 gene probes were identified with a false discovery rate (FDR) of 1x10-6. Additionally, 55 of the 199 belong to four molecular networks of inter related genes associated with: lipid metabolism, cellular movement, growth and proliferation, and cell-to-cell interactions. Multivariate analysis identified the GEP5 high risk designation of focal lesion PCs to be significantly prognostic with a HR=3.73 (p=0.023).Table 1Cox regression analysis of variables linked to overall and progression-free survival in TT4.Overall SurvivalProgression-Free SurvivalVariablen/N (%)HR (95% CI)P-valueHR (95% CI)P-valueMultivariateB2M > 5.5 mg/L38/130 (29%)3.71 (1.49, 9.22)0.0053.84 (1.58, 9.31)0.003FL GEP5 High Risk14/130 (11%)3.68 (1.19, 11.41)0.0243.73 (1.20, 11.62)0.023HR- Hazard Ratio, 95% CI- 95% Confidence Interval, P-value from Wald Chi-Square Test in Cox RegressionNS2- Multivariate results not statistically significant at 0.05 level. All univariate p-values reported regardless of significance.Multivariate model uses stepwise selection with entry level 0.1 and variable remains if meets the 0.05 level.A multivariate p-value greater than 0.05 indicates variable forced into model with significant variables chosen using stepwise selection. Disclosures: No relevant conflicts of interest to declare.


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