Abstract
Background
Peripheral blasts (PB) ≥1% have long been considered an unfavorable feature for patients with primary myelofibrosis (PMF). Whether further quantification of PB blasts and their correlation with bone marrow (BM) blasts has incremental value with regards to patient prognostication is unclear. Similarly, the role of the JAK1/2 inhibitor ruxolitinib (RUX) in patients with increased blast is not well-defined.
Methods
Herein, we retrospectively studied 1316 patients with MF presented to our institution between 1984-2018 with available PB and BM blasts.
Results
Peripheral blast percentage influenced overall survival (OS) only among patients with BM blasts < 5% with median OS for patients with 0%, 1-3%, and 4% PB blasts being 64, 48, 22 months, respectively (p < 0.01). Patients with 4% PB blasts and 5-9% BM/PB blasts had similar clinical features as patients with 10-19% blasts. Although OS of the former patients was longer than in those with 10-19% blasts, it was not statistically different (medians of 22, 26, and 13 months OS, respectively, p > 0.05). Forty four percent of patients were treated with RUX throughout their disease course. All patients with <10% blasts (PB or BM) treated with RUX had superior OS compared to patients who did not receive RUX within the same group. Blasts ≥4% PB and ≥5% BM were significant for prediction of inferior survival by multivariate analysis.
Conclusions
This study provides comprehensive insight into the role of peripheral blasts in patients with MF and indicates that patients with ≥ 4% PB have unfavorable prognosis. RUX provides survival benefit to patients with < 10% PB blasts.
Keywords: myelofibrosis, outcome, blasts, ruxolitinib
Precis:
Myelofibrosis patients with ≥4% peripheral blasts and / or ≥5% bone marrow blasts have inferior outcome when compared to patients with lower blasts.
Ruxolitinib showed benefit in all patients with < 10% peripheral or bone marrow blasts.
Introduction:
Myelofibrosis (MF) is a Philadelphia chromosome (BCR-ABL1)-negative myeloproliferative neoplasm with variable overall survival (OS) ranging from decades to months 1. MF diagnostic criteria derive from atypical clonal myeloid proliferation and marrow fibrosis with ineffective hematopoiesis, e.g. proliferative phenotype with hyperleukocytosis, increased lactate dehydrogenase, splenomegaly and constitutional symptoms, anemia and leukoerythroblastosis.
Hyper-activated JAK-STAT pathway due to altered JAK2, MPN, or CALR signaling represents the major pathophysiologic hallmark of the disease. Prognostic value of molecular abnormalities is undeniable, albeit not exclusive, as many clinical factors play an equally important role. Several models have been developed to predict OS, as well as transformation to acute leukemia (≥20% blasts; AML) 2–5. The presence of circulating blasts (PB) remains relevant in the most commonly applied prognostic models in MF patients with cut-points of ≥1%, ≥2% or ≥3% at equal or lower hazard ratios for OS as other variables 6–10. Whilst the role of < 10% PB blasts is not well-delineated, 10-19% PB or bone marrow (BM) blasts defines an accelerated phase (AP) with clearly inferior outcome 11–13. BM blasts are not included in the diagnostic nor prognostic classifications of patients with MF, primarily due to the fibrotic marrow and their questionable accuracy. This is in contrast to patients with myelodysplastic syndromes, where both PB and BM blasts predict for different risk categories with distinct outcomes 14.
Patients with PB blasts ≥ 10% were excluded from the phase 3 COMFORT 1 and 2 studies 15,16 leading to regulatory approval of the JAK1/2 inhibitor ruxolitinib (RUX) which became the standard of care for patients with symptomatic MF, and so far the only medical therapy conferring an OS benefit 17,18. Similarly, patients with PB blasts ≥ 10% were excluded from the JAKARTA trials evaluating the second recently approved JAK inhibitor, fedratinib 19,20.
In this study, we sought to address whether further quantification of PB blasts impacts clinical outcome, and whether discordance with BM blasts matters. We also sought to evaluate the effect of RUX with regard to percentages of blasts in PB and BM.
Methods:
Medical charts of adult patients (≥18 years) presenting to our institution between July 1984 and December 2018 with a diagnosis of MF were retrospectively reviewed; 1316 patients with available PB and BM blasts remained in this analysis. Two consecutive PB blast % (max 2 months apart) were reviewed in all patients, and in case of discrepancy by ≥1%, a third, next closest PB blast % was added and an arithmetic median was calculated for the final PB blast assignment. All cases were assessed by immunohistochemistry, flow cytometry was used for blasts > 5%. Primary myelofibrosis (PMF) and post-polycythemia vera and post-essential thrombocytosis myelofibrosis (PPV/PET-MF) were diagnosed according to standard criteria 14,21. Cytogenetics were classified according to Caramazza et al 22. Molecular testing (28 or 81-gene panel) was performed by real time PCR-based sequencing, as previously described 23. Survival was calculated from the date of referral to the date of last follow-up or death, whichever came first, using the Kaplan–Meier method with log-rank test. Clinico-pathological parameters were analyzed using the Fisher’s exact, Kruskal–Wallis or Mann–Whitney U tests; and correlations were assessed by Pearson, Spearman or Cramer’s V tests, as appropriate. The predictive effects of patient and disease characteristics on OS were examined using univariate and multivariate Cox proportional hazard models. Analyses were performed using SPSS, version 23.0 (Chicago, IL).
Results:
The median age of the entire group was 66 years (range, 20-90 years), and the median follow-up was 27 months (range, 10-251). Fifty three percent of patients (n = 700) had 0% PB blasts and < 5% BM blasts. Among the remaining patients with ≥1% PB blasts, 88% (n = 465) had 1-4% PB blasts, 7% (n = 42) had 5-9% PB blasts and 5% (n = 32) had ≥ 10% PB blasts. Clinical and disease-specific characteristics are provided in Table 1.
Table 1.
Demographics and clinical characteristics of patients
| Pt. Characteristics | ALL N=1316 | PB 0% N=700 | PB 1-3% N=436 | PB 4% N=29 | BM / PB 5-19%, N=151 | P-value* |
|---|---|---|---|---|---|---|
| Median age, years (range) | 66 (20-90) | 65 (27-90) | 66 (20-85) | 70 (48-84) | 67 (28-86) | 0.02 |
| Age > 65 years, N (%) | 691 (53) | 350 (50) | 235 (54) | 20 (69) | 86 (57) | 0.09 |
| Males, N (%) | 809 (61) | 416 (59) | 270 (62) | 19 (68) | 104 (69) | 0.17 |
| PMF, N (%) | 828 (63) | 460 (66) | 263 (60) | 24 (83) | 81 (54) | 0.56 |
| Median WBC x109/L, (range) | 9.6 (1-361) | 8 (1-129) | 14 (1-228) | 12 (1-80) | 13 (1-361) | 0.00 |
| Median platelets x 109/L, (range) | 207 (1-2690) | 221 (1-2690) | 205 (4-1432) | 115 (14-423) | 155 (6-877) | 0.00 |
| Median hemoglobin g/dL, (range) | 10.4 (3.7-18.7) | 10.5 (3.7-19) | 10.3 (6-17) | 9.7 (6.7-17) | 9.7 (5-16) | 0.00 |
| Transfusion dependency, N (%) | 334 (25) | 161 (23) | 119 (27) | 8 (28) | 46 (30) | 0.16 |
| Splenomegaly, > 5 cm BCM, N (%) | 635 (48) | 274 (39) | 253 (58) | 20 (69) | 88 (59) | <0.00 |
| Symptoms, N (%) | 994 (76) | 505 (72) | 334 (77) | 25 (86) | 130 (86) | 0.01 |
| BM fibrosis, grade ≥2, N (%) | 1073 (82) | 538 (77) | 376 (86) | 26 (90) | 133 (88) | <0.00 |
| DIPSS, N (%) | ||||||
| Low | 103 (8) | 99 (14) | 0 | 0 | 4 (3) | NA |
| Int-1 | 588 (45) | 323 (46) | 199 (46) | 12 (41) | 54 (36) | 0.10 |
| Int-2 | 369 (28) | 210 (30) | 103 (24) | 10 (34) | 46 (30) | 0.08 |
| High | 256 (19) | 68 (10) | 134 (31) | 7 (24) | 47 (31) | <0.001 |
| Abnormal karyotype, N (%) | 480 /1236 (39) | 221 / 647 (34) | 160 / 417 (38) | 14 / 27 (52) | 85 / 145 (59) | 0.01 |
| Complex karyotype, N (%) | 72 (6) | 25 (4) | 26 (6) | 4 (14) | 17 (11) | 0.43 |
| JAK2 (+), N / N tested (%) | 765/1120 (68) | 424 / 613 (61) | 251 / 364 (69) | 16 / 24 (67) | 74 / 119 (62) | 0.49 |
| CALR (+), N (%) | 117 (12) | 57 (8) | 40 (9) | 4 (14) | 16 (11) | 0.23 |
| MPL (+), N (%) | 45 (5) | 26 (4) | 17 (4) | 1 (3) | 1 (1) | 0.17 |
| HMR, N, (%) | 164/582 (28) | 86/309 (28) | 53/187 (28) | 3/17 (18) | 22/69 (32) | 0.06 |
Abbr. and definitions: PRBC dependency: >4 UI PRBC / 2 months; WBC = white blood cells, BCM = below costal margin, BM fibrosis grading according to EUNMET, DIPSS = Dynamic International Prognostic Scoring System; complex karyotype = ≥3 unrelated abnormalities; HMR = high risk molecular mutations (ASXL1, EZH2, IDH1/2, SRSF2/U2AF1); AML, acute leukemia
Higher PB blasts showed negative associations with hemoglobin and platelets, and positive associations with white blood cells, age, presence of symptoms, grade ≥2 reticulin fibrosis, splenomegaly, unfavorable and complex karyotype (Supplemental Table 1).
Correlation between PB and BM blasts is depicted in Figure 1 and Supplemental Figure 1. All patients with ≥ 5% PB blasts had at least 5% BM blasts, whereas 14% (n = 77) of patients with 1-4% PB blasts had ≥ 5% BM blasts. On the other hand, 67% and 32% of patients with BM blasts 5-9% and 10-19% had PB blasts less than 5% and 10%, respectively.
Figure 1.
Correlation between peripheral and bone marrow blasts and overall survival.
Legend. Bars are showing % of patients with PB blasts % (Y axis) among different BM blast % groups. Survival was similar among different PB % in patients with BM 5-9% and those with BM 10-19% (median OS of 24 and 13 months, respectively, p, 0.19 [gray vertical boxes]). Dotted bars mean discordance in blast percentage between BM and PB, and only represent lower PB blasts in patients with BM blasts of 5-9% and 10 -19%, respectively. OS, overall; survival, m, month (range).
First, we calculated stepwise OS in patients by their BM and PB blasts (Supplemental Table 2). In patients with <5% BM blasts, PB blasts differentiated 3 groups with distinctive OS: PB 0%, 1-3%, and 4% with median OS of 64, 48, and 22 months, respectively (p < 0.001, Figure 2, Supplemental Table 3). HRs for inferior OS (95% CI) for PB 0% vs 1-3% and 4% were 0.69 (0.58-0.81), and 0.34 (0.27-0.43), all p < 0.01. On the contrary, PB blasts had no prognostic value for OS in patients with either 5-9% BM blasts or 10-19% BM blasts (Supplemental Table 3), and these patients were grouped into 5-9% or 10-19% blasts categories utilizing either PB or BM blasts. Finally, although patients with 5-9% PB/BM blasts had statistically indistinguishable OS from those with 10-19% PB/BM blasts (median OS of 24 and 13 months, respectively, p = 0.19), it was almost twice as long. Yet, for the purpose of further analysis, these 2 groups were combined into PB/BM ≥ 5% blasts group with a median OS of 19 months, HR 0.31 (95% CI 0.19-0.50) for PB 0% vs PB/BM ≥5% (p<0.001). Survival of patients with PB 4% was inferior to those with 0-3% PB blasts and was similar to those with PB/BM ≥ 5% blasts (Figure 2). Supplemental Figure 1 proposes a prognostic algorithm for using PB and BM blasts percentage in patients with MF as observed in our cohort.
Figure 2.
Overall survival of all patients stratified by PB and BM blasts into 4 groups
Statistically significant differences in clinical characteristics were identified mostly between patients with PB 0-3% and with PB 4% & PB/BM ≥ 5% (Table 1). Patients with PB 4%, PB/BM 5-9% and PB/BM 10-19% displayed similar clinical features (data not shown). Significant differences in cytogenetics and molecular characteristics were not noted between the groups (Supplemental Table 4).
The rate of progression to AML (n=146) was the highest in patients with ≥ 10% blasts. AML incidence was 3.4 cases per 100 person-years (2.2, 3.1, 6.0, and 13.5 cases per 100 person-years for PB 0%, 1-3%, and 4% and PB/BM ≥ 5% blasts; respectively, overall p<0.001; and p = 0.69 for PB 0% and 1-3%). Estimated leukemia free survival at 3 years (for PB 0%, 1-3%, 4% and PB/BM ≥ 5%) was 68%, 58%, 33% and 30%, respectively.
During course of the disease, 523 patients were treated with RUX (Table 2). OS of patients treated with RUX starting from presentation to our institution is summarized in Table 3, Figures 3A–C. Patients with < 10% PB/BM blasts who received RUX had superior OS compared to patients who did not receive RUX within the same PB blast category (Figures 3A–D, all p < 0.001, except for 3C with p = 0.32). HRs (95% CI) for death with RUX for PB 0%, PB 1-3%, PB 4% and PB/BM ≥ 5% blasts were 0.72 (0.56-0.91), 0.64 (0.59-0.93), 0.90 (0.96-0.99), and 0.57 (0.37-0.87). Sub-analysis of patients with PB/BM ≥ 5% blasts showed superior OS only in patients with 5-9% PB/BM blasts receiving RUX, but not in those with ≥ 10% PB/BM blasts (Figure 3E).
Table 2.
Treatment distribution
| Variables // N (%) | PB 0%, N=700 | PB 1-3%, N=436 | PB 4%, N=29 | PB 5-19%, N=151 |
|---|---|---|---|---|
| No therapy during follow-up | 96 (14) | 40 (9) | 2 (7) | 16 (11) |
| Therapy lines: 1 line | 232 (33) | 127 (29) | 9 (31) | 42 (28) |
| 2-3 lines | 280 (40) | 197 (45) | 15 (52) | 69 (46) |
| >3 lines | 92 (13) | 72 (17) | 3 (10) | 24 (16) |
| RUX therapy | 268 (38) | 190 (44) | 11 (38) | 54 (36) |
| Single RUX | 214 (31) | 150 (34) | 10 (34) | 38 (25) |
| RUX + azacitidine | 23 (3) | 19 (4) | 1 (3) | 9 (6) |
| RUX + others* | 31 (4) | 21 (5) | -- | 7 (5) |
RUX, ruxolitinib;
others: histone deacetylase inhibitors; immunomodulatory agents (thalidomide, lenalidomide, pomalidomide); bromodomain inhibitors; PRM-151; BCL-2 inhibitor
Table 3.
Overall survival in patients with and without RUX
| PB 0% blasts | PB 1-3% blasts | PB 4% blasts | PB 5-19% blasts | |||||
|---|---|---|---|---|---|---|---|---|
| ALL pts | N | OS (range) | N | OS (range) | N | OS (range) | N | OS (range) |
| Total | 700 | 64 (55-73) | 436 | 48 (43-53) | 29 | 22 (11-33) | 151 | 19 (11-27) |
| RUX | 268 | 81 (61-101) | 190 | 63 (51-75) | 11 | 27 (11-43) | 54 | 47 (23-71) |
| No RUX | 432 | 58 (50-66) | 246 | 40 (30-50) | 18 | 15 (6-24) | 97 | 15 (11-19) |
| HR (95% CI), p-value* | 0.72 (0.56-0.91), 0.01 | 0.64 (0.44-0.93), <0.001 | 0.91 (0.10-0.96), 0.03 | 0.57 (0.37-0.87), 0.007 | ||||
| PMF | N | OS (range) | N | OS (range) | N | OS (range) | N | OS (range) |
| Total | 499 | 59 (51-67) | 300 | 46 (39-53) | 26 | 27 (16-38) | 99 | 22 (14-30) |
| RUX | 183 | 66 (41-91) | 123 | 49 (44-54) | 9 | 27 (17-37) | 39 | 26 (9-43) |
| No RUX | 316 | 55 (46-64) | 177 | 34 (20-48) | 17 | 15 (6-24) | 60 | 14 (7-21) |
| HR (95% CI), p-value* | 1.29 (0.97-1.72), 0.08 | 1.41 (1.04-1.90), 0.02 | 3.2 (0.9-11.4), 0.05 | 1.55 (0.94-2.58), 0.08 | ||||
HR (95% CI) and p value between with and without RUX patients within blast groups, RUX-ruxolitinib
Figures 3.
A-D. Overall survival of groups stratified by blasts and the use of ruxolitinib: [A] patients with 0% PB blasts, [B] 1-3% PB blasts, [C] 4% PB blasts, [D] and 5-19% PB/BM blasts, [E] Fig D further stratified by 5-9% and 10-19% BP/BM blasts
Given the fact that most prognostic scores in MF were developed for PMF patients, we verified our results in PMF patients (n= 924, Table 3), where we also evaluated the impact of blast % on DIPSS scores. Respective OS of patients with PB 0%, 1-3%, 4% and PB/BM ≥5% blasts were 59, 46, 27, and 22 months (p<0.001 for all, p = 0.82 for PB 4% and ≥5%, Supplemental Figure 3A). Patients with < 10% blasts receiving RUX had superior OS than those not receiving RUX within the same group, but results were not statistically significant for patients with PB 0% and BM/PB 10-19% (Supplemental Figures 3B–E).
Blasts in PB ≥1% were noted in 45%, 42%, and 68% of intermediate 1, 2 and high risk DIPSS patients, respectively. About one third of patients within each DIPSS category had 4% PB & PB/BM ≥5% blasts (Supplemental Table 5). In all patients, DIPSS revealed 4 distinct OS groups (median OS of 134, 53, 42, and 28 months for low, intermediate-1, −2 and high risk, respectively, p < 0.001, Figure 4A). Patients with > 4% PB and ≥ 5% BM blasts within each DIPSS category had significantly inferior OS than patients with lower blast %; HRs (95% CI) for intermediate 1 DIPSS: 0% vs 4% vs ≥5% blasts, 0.31 (0.15-0.63) and 0.43 (0.27-0.67); for intermediate 2 DIPSS: 0% vs ≥5% blasts, 0.49 (0.31-0.81), for high DIPSS: 0% vs 4% vs ≥5% blasts, 0.25 (0.10-0.68) and 0.28 (0.15-0.54) (Figures 4 B–D, all p< 0.01).
Figures 4.
A-D. Overall survival according to DIPSS and blasts groups: [A] DIPSS groups, [B] DIPSS intermediate 1 and blasts %, [C] DIPSS intermediate 2 and blasts %, [D] high DIPSS and blasts %
Supplemental Table 6 summarizes clinical variables associated with inferior OS assessed by univariate and multivariate analyses (using variables from Table 1). In multivariate analyses, older age, higher WBC, lower hemoglobin and platelets, transfusion requirements, symptoms, any PB blasts and complex karyotype remained significantly associated with inferior OS. Notably, presence of any (≥1% PB/BM) blasts was significant, but the highest predictive value was observed with > 4% PB and ≥5% PB/BM blasts.
Discussion:
Several clinico-pathological factors are being used in prognostic models estimating outcome of patients with MF 2,4,5,24. Peripheral blasts ≥1% have been recognized as an adverse feature since establishment of the original IPSS model 24, and their negative impact on prognosis has been repeatedly confirmed using various cut-offs (mostly ≥ 1%, 2%, or 3%) 6,8,10,25.
At present, provisionally defined AP employs the existence of 10-19% PB / BM blasts and these patients are known to have inferior outcome 11,26. Yet, the 10% cut-off was set up arbitrarily based on a retrospective study with limited data and only defines patients with the worst outcome 11. The relevance of 5-9% PB blasts is not well-defined, as is the role of BM blasts, as regards to their correlation. This is not only in contrast with the excess marrow blast categories of the myelodysplastic syndromes, but even with the MPN data suggesting that 20% blasts in either the PB or the BM are equally useful for definition of AML arising from MPN 27. The significance of blast percentage is important since the approach to patients with AP should be more aggressive 26, and aimed to decrease the blast percentage, possibly delay time to AML transformation and implement curative therapies (e.g. stem cell transplantation, SCT) in fit patients. Still, general treatment algorithms are based on disease risk scores rather than blasts 26,28.
We therefore sought to analyze a large cohort of adult patients with MF to investigate whether further sub-classification of PB blasts in the context of BM blasts was more relevant for patient outcome, and whether RUX impacts OS in patients with higher blast percentage.
Several findings from this analysis are notable.
First, we demonstrated that PB blasts had impact on OS only in patients with < 5% BM blasts; whilst no effect of PB blasts was noted in those with ≥ 5% BM blasts. Actual compartmental discordance in blasts between PB and BM, especially in those with ≥5% BM blasts, mostly meant that these patients had lower PB blasts, and not the opposite. Reasons for this might include the use of the median of PB blast measurements as well as underestimation of BM blasts due to reticulin fibrosis, although patients with grade ≥2 fibrosis were distributed equally among groups. Nevertheless, patients with higher BM blasts are likely to have similar PB blasts, which should be easily accessible for prognostication.
Second, patients with 5-9% blasts had similar clinical characteristics as those with ≥ 10% blasts. Their OS was twice as high as that of those with ≥ 10% blasts, but it was not statistically significantly different. Patients with 4% PB blasts seemed to behave more like patients with ≥ 5% PB blasts than patients with lower blasts; but the small number of patients in this group precluded firm conclusions. A similar observation, where patients with 5-9% blasts (PB and BM) had actually the exact same OS as those with 10-19% blasts (median of 16 months for both) was reported by a recent study 27. Another group showed inferior OS of patients with 5-9% PB blasts to those with lower PB blasts; but did not directly compare OS between 5-9% and 10-19% blasts, but rather 2-9% and 10-19%, leaving the former comparison unspecified 29.
Third, the most important markers impacting patient OS were well-established clinical variables used in current models 2,4,5. Signs of advanced disease associated with inferior survival (e.g. anemia, thrombocytopenia) correlated with elevated blasts, and one might argue their confounding role. Yet, the highest predictive value and independent importance of ≥4% PB and ≥5% BM blasts from DIPSS classification, imply that increased blasts should be given the same attention as is presently used for unfavorable karyotype or multiple high molecular risk mutations 5.
Fourth, significantly better OS with the use of RUX during the disease course in patients with < 10% blasts suggests its very important role in clinical practice. However, shorter duration of RUX benefit in patients with 5-9% blasts, and their significantly high rate of progression to AML 30, calls for investigation of novel combinatorial approaches in these patients. Our inability to properly determine the true role of RUX in this setting is due to the retrospective nature of our study, various RUX regimens and different start times during the disease course. These represent limitations of our study, but do not undermine the importance of our findings. On the contrary, it should trigger closer follow-up of these patients and earlier initiation of therapy, including timely exploration of all life-saving measures, such as allogeneic SCT.
In summary, through a detailed evaluation of a large group of consecutive patients with MF, we conclude that PB blasts offer additional prognostic value in patients with < 5% BM blasts. Blasts ≥5%, both in the PB and BM, might define similarly unfavorable risk disease as the currently established AP (10-19% blasts), and should be given similar attention as unfavorable karyotype or adverse molecular features. Although RUX significantly improves survival of patients with < 10% blasts, combination approaches backed by strong preclinical evidence of synergism are desperately needed to improve outcomes of these patients.
Supplementary Material
Acknowledgments
Funding Source: This work was supported in part by a Cancer Center Support Grant to MD Anderson Cancer Center (P30 CA016672) from the National Cancer Institute.
Conflict of Interest Disclosures:
LM; ZE; LZ; SP: None. HK: Research Funding from Amgen, ARIAD, Bristol-Myers Squibb, Delta-Fly Pharma, Novartis, Pfizer. SV: Research Funding from Incyte. PB: Honoraria and Research Funding from Incyte, Celgene, CTI BioPharma, Blueprint and Kartos Therapeutics. Research Funding from Constellation Pharmaceuticals, Promedior, NS Pharma, Astellas and Pfizer. ND: Advisory role for Daiichi-Sankyo, BMS, Astellas, Abbvie, Genentech, Immunogen, Pfizer, Amgen, Forty-Seven, Novartis. Research funds: BMS, Pfizer, Forty-Seven, Genentech, Abbvie, Astellas, Daiichi-Sankyo, Incyte, Novimmune, Immunogen. NP: Consulting/honorarium: Pacylex, Celgene, Stemline, Incyte, Novartis, MustangBio, Roche Diagnostics, and LFB. Research funding from Stemline, Novartis, Abbvie, Samus, Cellectis, Plexxikon, Daiichi-Sankyo, Affymetrix, SagerStrong Foundation.
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