Superior Therapy Response Predictions for Patients with Myelodysplastic Syndrome (MDS) Using Cellworks Singula™: Mycare-020-02

Background: Therapy selection for MDS patients is often based on information considering only cytogenetics and single molecular aberrations and ignoring other patient-specific omics data that could potentially enable more effective treatments. In turn, despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of MDS patients remains relatively poor. The Cellworks Singula™ report predicts response for physician prescribed treatments using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. Methods: The performance of Singula™ was evaluated in an independent, randomly selected, retrospective cohort of 144 MDS patients aged 28 to 89 years (median 69). The pre-defined Singula™ Classifier utilizes an individual's genomics profile to provide a dichotomous prediction of response or non-responses to a given physician prescribed treatment (PPT). Outcome data for these subjects, including measurement of complete response (CR), were obtained from 42 PubMed publications, each including patient genomics data of either karyotyping, targeted gene panels, and/or whole exome sequencing. Blinded to clinical outcomes, Cellworks utilized these data to generate a Singula™ classifier of responder vs non-responder in this MDS cohort. Statistical analyses, including assessments of accuracy, sensitivity, specificity, negative (NPV) and positive predictive (PPV) values were performed on the merged data to compare the Singula™ predicted response with the actual observed CR. Multivariate logistic regression models of complete response were performed incorporating covariates for patient age, PPT, and the Singula™ Classifier. Results: Table 1 reveals that the pre-defined Singula™ classifier had 90.3% (Exact 95% CI: 84.2%, 94.6%) accuracy in predicting observed patient response from the physician prescribed treatment. In this study, Singula™ was able to accurately identify responders with 90.0% (81.2%, 95.6%) sensitivity. Importantly, Singula™ had 90.6% (80.7%, 96.5%) specificity for the subset of 64 patients (44.4%) that had a non-response. For 32% (17/54) of the non-responders patients, Singula™ provided an alternative Standard of Care treatment therapy, as shown in Table 2. The remaining 37 patients were predicted to be non-responders to all remaining Standard of Care options, so did not have alternate treatment predictions. Assuming at least 4% of these non-responding patients would have responded to the alternative Singula™ prescribed therapy, then these data support that Singula™ improves prediction of CR compared to the original PPT (McNemar's p-value < 0.05). In multivariate logistic regression models of CR that included patient age and prescribed drug therapy, the Singula™ Classifier remained an independent, significant predictor of CR (OR > 100, p-value < 0.0001), while both patient age (p = 0.372) and drug therapy (p = 0.720) fell off the model. Conclusions: Cellworks Singula™ has high accuracy and sensitivity in predicting CR for MDS patient response to physician prescribed therapies. Singula™ also has high specificity in identifying patients who are unlikely to respond to physician prescribed therapies and provides alternative treatment recommendations for these patients. The Singula™ Classifier is an independent and superior predictor of CR compared with other clinical (age) or therapeutic (PPT) factors. Figure Disclosures Stein: Amgen: Consultancy, Speakers Bureau; Stemline: Consultancy, Speakers Bureau. Watson:BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nair:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Ullal:Cellworks Research India Private Limited: Current Employment. Ghosh:Cellworks Research India Private Limited: Current Employment. Narvekar:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Prakash:Cellworks Research India Private Limited: Current Employment. Behura:Cellworks Research India Private Limited: Current Employment. Balakrishnan:Cellworks Research India Private Limited: Current Employment. Roy:Cellworks Research India Private Limited: Current Employment. Rajagopalan:Cellworks Research India Private Limited: Current Employment. Alam:Cellworks Research India Private Limited: Current Employment. Parashar:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Christie:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Marcucci:Abbvie: Speakers Bureau; Novartis: Speakers Bureau; Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Merck: Other: Research Support (Investigation Initiated Clinical Trial); Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Iaso Bio: Membership on an entity's Board of Directors or advisory committees.

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Assessment of Cellworks Omics Biosimulation Therapy Response Predictions for Patients with Acute Myeloid Leukemia (AML) Using Cellworks Singula™: Mycare-020-01

Blood ◽

10.1182/blood-2020-142184 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 35-35

Author(s):

Guido Marcucci ◽

Drew Watson ◽

Prashant Ramachandran Nair ◽

Kabya Basu ◽

Yashaswini S Ullal ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Response ◽

Board Of Directors ◽

Proportional Hazards ◽

Cox Proportional Hazards ◽

Patient Specific ◽

P Value ◽

Research Support ◽

Advisory Committees ◽

Limited Current

Background. In addition to clinical considerations (e.g., age, de novo vs secondary disease, comorbidities), therapy selection for AML patients is often based on information considering only cytogenetics and/or molecular aberrations and ignoring other patient-specific omics information that could potentially enable selection of more effective treatments. In turn, despite using cytogenetic and molecular-risk stratification, the current overall outcome of AML patients remains relatively poor. The Cellworks Singula™ report predicts clinical response to physician-prescribed treatments using the novel Cellworks Omics Biology Model (CBM) that simulate in silico downstream molecular effects on cell signaling and survival of drug treatments in patient-specific diseased cells. Methods. The performance of Singula™ was evaluated in a cohort of 474 AML patients aged 2 to 85. The pre-defined Singula™ Classifier utilizes individual patients' next-generation sequencing (NGS) profiles to provide a dichotomous prediction of response or non-response to the physician prescribed treatments. The clinical outcome data for these subjects, i.e., complete response (CR) and overall survival (OS), were obtained from the TCGA and other 144 PubMed publications, each including also information on patients' cytogenetics, targeted gene mutations, and/or whole exome sequencing. Blinded to clinical outcomes, Cellworks utilized the cytogenetic and molecular data to generate a Singula™ predicted response (i.e., CR vs non-response) classification for each patient. Statistical analyses, including assessments of accuracy, sensitivity, specificity, and negative (NPV) and positive predictive (PPV) values were performed to compare the Singula™ predicted clinical response to the actual observed clinical response. Kaplan-Meier curves, associated log rank tests and median OS are provided for patients stratified by Singula™ predicted response. Multivariate Cox proportional hazards regression was used to further test the hypothesis that Singula™ is an independent predictor for OS once adjusted for patient age and actual prescribed treatment. Results. Data are summarized in Table 1. The Singula™ classifier had 92.3% (90.6%, 95.3%) accuracy in predicting correctly observed patient complete response to the prescribed treatment. with 97.3% (95.0%, 98.8%) sensitivity. Singula™ had 83.3% (76.1%, 89.1%) specificity for the non-responder patients (n=138; 29.1%). For each of the non-responders, Singula™ provided an alternative treatment therapy predicted to produce clinical response. Assuming at least 2% of the non-responders would have responded to the alternative Singula™ prescribed treatment, Singula™ improves CR rates compared to the original physician prescribed treatment (McNemar's p-value < 0.05). Figure 1 provides the Kaplan-Meier curves of Singula-predicted responders vs non-responders for a subset of 292 subjects that had OS data available. In multivariate Cox proportional hazards models, the Singula Classifier remained a significant predictor of overall survival (HR = 2.171, p-value < 0.0001) once adjusted for patient age and physician prescribed treatment. Conclusions. Cellworks Singula™ has high accuracy and sensitivity in predicting CR for AML patient. Singula also has high specificity in identifying patients who are unlikely to respond physician and may prescribed potentially effective therapies. The Singula™ predicted responders have a significantly longer OS than the predicted non responders. Thus, Cellworks Singula™ can accurately predict AML response, be used to validate or reject a physician's therapy selection decision and, eventually, provide alternative treatment recommendations. Disclosures Marcucci: Novartis: Speakers Bureau; Abbvie: Speakers Bureau; Iaso Bio: Membership on an entity's Board of Directors or advisory committees; Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Merck: Other: Research Support (Investigation Initiated Clinical Trial). Watson:Mercy Bioanalytics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; SEER Biosciences, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioAI Health Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellmax Life Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nair:Cellworks Research India Private Limited: Current Employment. Basu:Cellworks Research India Private Limited: Current Employment. Ullal:Cellworks Research India Private Limited: Current Employment. Ghosh:Cellworks Research India Private Limited: Current Employment. Narvekar:Cellworks Research India Private Limited: Current Employment. Grover:Cellworks Research India Private Limited: Current Employment. Sahu:Cellworks Research India Private Limited: Current Employment. Amara:Cellworks Research India Private Limited: Current Employment. Pampana:Cellworks Research India Private Limited: Current Employment. Roy:Cellworks Research India Private Limited: Current Employment. Rajagopalan:Cellworks Research India Private Limited: Current Employment. Alam:Cellworks Research India Private Limited: Current Employment. Parashar:Cellworks Research India Private Limited: Current Employment. Mundkur:Cellworks Group Inc.: Current Employment. Christie:Cellworks Group Inc.: Current Employment. Macpherson:Cellworks Group Inc.: Current Employment. Kapoor:Cellworks Research India Private Limited: Current Employment. Stein:Stemline: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau.

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Superior therapy response predictions for patients with acute myeloid leukemia (AML) using Cellworks Singula: MyCare-009-01.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e19502 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e19502-e19502

Author(s):

Guido Marcucci ◽

Drew Watson ◽

Shweta Kapoor ◽

Swaminathan Rajagopalan ◽

Rajan Parashar ◽

...

Keyword(s):

Proportional Hazards ◽

Independent Predictor ◽

Alternative Therapy ◽

Therapy Response ◽

Complete Response ◽

Patient Specific ◽

P Value ◽

Omics Data ◽

Patient Age ◽

Patient Âgé

e19502 Background: Despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of AML patients remains relatively poor. Therapy selection is often based on information considering only cytogenetics and single molecular aberrations and ignoring other patient-specific omics data that could potentially enable more effective treatments. The Cellworks Singula™ report predicts response for physician prescribed therapies (PPT) using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. We test the hypothesis that Singula is a more accurate predictor of patient-specific therapy response than PPT. Methods: Singula’s ability to predict response was evaluated in an independent, randomly selected, retrospective cohort of 494 AML patients aged 2 to 85 years (median 54) treated with PPT. Patient omics data was available from PubMed. The accuracy of Singula was compared to that of PPT using McNemar’s test to account for the correlation between Singula and PPT. Multivariate logistic regression modeled complete response (CR) as a function of patient age, PPT, and Singula against any non-response (NR). Likelihood ratio tests were performed to further validate if Singula provides predictive information beyond PPT or patient age. Similar analyses were performed for overall survival (OS) using proportional hazards regression. Results: Singula was a better predictor for CR than PPT (McNemar’s χ2 = 72.0, p-value < 0.0001), with an overall accuracy of 88.5% (95% CI: 85.3%, 91.1%) compared to 70.2% (95% CI: 66.0%, 74.2%) for PPT. Singula exhibited a sensitivity and specificity of 97.1% and 68.0%, respectively. In multivariate regression analysis, Singula (p < 0.0001) remained an independent predictor for CR after adjusting for patient age (p = 0.0329) while PPT became not significant (p = 0.75). Singula was also an independent predictor for OS (p < 0.0001) after adjusting for patient age (p = 0.0018) and PPT (p = 0.0011). For all 100 true negatives, Singula generated alternative standard of care therapy selections with predicted clinical response. Conclusions: Singula is a superior independent predictor for CR and OS compared to PPT in AML patients. The Singula report can also validate therapy selection, correctly identify non-responders to PPT and further provide alternative therapy selections.

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Superior therapy response predictions for patients with myelodysplastic syndrome (MDS) using Cellworks Singula: MyCare-009-02.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e19528 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e19528-e19528

Author(s):

Anthony Selwyn Stein ◽

Drew Watson ◽

Shweta Kapoor ◽

Kunal Ghosh Ghosh Roy ◽

Aftab Alam ◽

...

Keyword(s):

Proportional Hazards ◽

Independent Predictor ◽

Alternative Therapy ◽

Therapy Response ◽

Patient Specific ◽

P Value ◽

Omics Data ◽

True Negative ◽

Patient Age ◽

Patient Âgé

e19528 Background: Despite using cytogenetic and molecular-risk stratification and precision medicine, the current overall outcome of MDS patients remains relatively poor. Therapy selection is often based on information considering only cytogenetics and single molecular aberrations and ignoring other patient-specific omics data that could potentially enable more effective treatments. The Cellworks Singula™ report predicts response for physician prescribed therapies (PPT) using the novel Cellworks Omics Biology Model (CBM) to simulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. We test the hypothesis that Singula is a more accurate predictor of patient-specific therapy response than PPT. Methods: Singula’s ability to predict response was evaluated in an independent, randomly selected, retrospective cohort of 146 MDS patients aged 28 to 89 years (median 69) treated with PPT. Patient omics data was available from PubMed and TCGA. The accuracy of Singula was compared to that of PPT using McNemar’s test to account for the correlation between Singula and PPT. Multivariate logistic regression modeled complete response (CR) as a function of patient age, PPT, and Singula against any non-response (NR). Likelihood ratio tests were performed to further validate if Singula provides predictive information beyond PPT or patient age. Similar analyses were performed for overall survival (OS) using proportional hazards regression. Results: Singula was a better predictor for CR than PPT (McNemar’s χ2 = 42.0, p-value < 0.0001), with an overall accuracy of 73.3% (Exact 95% CI: 65.3%, 80.2%) compared to 37.7% (95% CI: 30.0%, 46.1%) for PPT. Singula exhibited a sensitivity and specificity of 90.9% (95% CI: 80.0%, 97.0%) and 62.6% (95% CI: 51.8%, 72.6%), respectively. In multivariate regression analysis, Singula (p < 0.0001) remained an independent predictor for CR after adjusting for patient age (p = 0.0759) and PPT (p = 0.0496). Singula provided alternative therapy selections for 17 of 53 true negative detected by Cellworks. Conclusions: Singula is a superior independent predictor for CR compared to PPT in MDS patients. The Singula report can also validate therapy selection, correctly identify non-responders to PPT and further provide alternative therapy selections.

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Autologous Hematopoietic Cell Transplantation in Patients with High Risk Multiple Myeloma: Post- Transplant Responses Do Not Translate to Longer Survival

Blood ◽

10.1182/blood.v126.23.1979.1979 ◽

2015 ◽

Vol 126 (23) ◽

pp. 1979-1979

Author(s):

Manish Sharma ◽

Parmeswaran Hari ◽

Jennifer Le-Rademacher ◽

Amrita Krishnan ◽

Yago Nieto ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Complete Response ◽

Chromosome 1 ◽

P Value ◽

Stage At Diagnosis ◽

Risk Markers ◽

Advisory Committees ◽

Post Transplant ◽

African American Race

Abstract Background: Multiple myeloma remains an incurable disease with a heterogeneous clinical course, somewhat explained by the occurrence of high-risk prognostic markers. The International Myeloma Working Group defined high risk myeloma (HRM) as the presence of del17p13 or t(4;14) with ISS II/III. Conflicting data exist regarding t(14;16), hypodiploidy and chromosome 1 abnormalities (1q21 amplification, 1p deletion and others). Methods: We analyzed the outcomes of 142 HRM patients with high risk FISH or cytogenetic findings reported to the CIBMTR from 2008-2012 treated with an upfront (within 12 months of diagnosis), melphalan-conditioned autologous hematopoietic cell transplant and compared them to 573 patients with no high-risk markers (NHRM). Patients that received more than 2 induction regimens were excluded in this analysis. The HRM cohort comprised del17p13 (n=27), t(4;14) (n=27), t(14;16) (n=5), chromosome 1 abnormalities (n=42), hypodiploidy (n=13) and ≥2 high-risk markers (n=31). Planned post-transplant therapy was collected. Outcomes of interest included progression-free survival (PFS) and overall survival (OS). Results: The HRM and NHRM groups were similar to each other except for the following differences: HRM was associated with lower Karnofsky (KPS) (49% vs 36% with KPS<90, p 0.02) and higher stage at diagnosis (41% vs 28% with ISS/DSS III, p 0.008). More HRM patients received induction with bortezomib and immunomodulatory drug (imid) combinations (55% vs 43%, p <0.001) and had a lower complete response rate prior to transplant (12% vs 16%, p 0.04). More HRM patients had planned post-transplant combined bortezomib and imid therapy (27% vs 12%, p<0.0001). Median follow up in the 2 groups was 36 months for HRM and 44 months for NHRM. At 100 days post-transplant, similar numbers of patients had achieved complete and very good partial responses in the 2 groups (Table 1). At 3 years post-transplant, HRM patients had lower PFS (36% vs 50%, p <0.001) and OS (73% vs 85%, p <0.001) compared to NHRM. Univariate outcomes are shown in Table 2 divided by type of HRM. Table 3 shows the results of the multivariate analysis. The figure shows the Kaplan-Meier curves of probability of survival. Among the relapsed patients (HRM = 91, NHRM = 296), the 2 year survival was 48 (35-60)% for HRM and 70 (64-76)% for the NHRM groups, p-value 0.004. Conclusions: Patients with HRM achieved similar day 100 response compared to NHRM but were unable to maintain this response over time despite being more likely to receive post-transplant therapy. HRM was associated with shorter PFS and further shortened post-relapse survival. Patients with chromosome 1 abnormalities or del 17p alone appeared to have similar outcomes to those with NHRM while those with t(4;14) and those with more than 1 high-risk marker had the least favorable outcomes. In addition to HRM, obtaining less than complete response prior to transplant and the lack of post-transplant therapy were associated with worse PFS and OS. Finally, African-American race and higher stage at diagnosis were also associated with lower OS in our study. Table 1. Day 100 post-transplant response Variable HRM NHRM P-value Day 100 response 0.55 sCR/CR/nCR 40 (28) 176 (31) VGPR 43 (30) 174 (30) PR 39 (27) 129 (23) SD/NR 14 (10) 63 (11) Progression/relapse 5 (4) 13 (2) Missing 1 (<1) 18 (3) Table 2. Outcomes at 3 years post-transplant. Values are expressed as probabilities with 95% confidence intervals. NHRM t(4;14) del 17p Chr 1 ≥ 2 HR p-value PFS 50 (46-55)% 30 (12-51)% 44 (25-64)% 40 (24-56)% 23 (9-41)% <0.001 OS 85 (81-88)% 58 (36-78)% 81 (60-95)% 87 (74-96)% 65 (47-82)% <0.001 Table 3. Multivariate analysis Outcome Hazard ratio (95% CI) p-value PFS HRM vs NHRM 1.7 (1.3-2.3) <0.0001 Pre-transplant CR PR SD Progression 1 2.1 (1.2-3.7) 2.0 (0.8-5.0) 4.5 (1.9-10.3) 0.0245 0.008 0.14 0.0003 Planned post-transplant therapy vs no therapy 0.6 (0.4-0.8) <0.0001 OS HRM vs NHRM 2.0 (1.4-3.0) 0.0001 African-American race vs Caucasian 1.7 (1.1-2.5) 0.007 ISS/DSS III Yes vs No 1.8 (1.2-2.5) 0.0008 Pre-transplant CR PR SD Progression 1 1.4 (1.0-1.9) 1.8 (1.0-3.0) 2.7 (1.5-4.8) 0.008 0.03 0.02 0.0004 Planned post-transplant therapy vs no therapy 0.5 (0.3-0.8) 0.0001 Figure 1. Figure 1. Disclosures Krishnan: Onyx: Speakers Bureau; BMS: Consultancy; Janssen: Consultancy; Celgene: Consultancy, Speakers Bureau; Millenium: Speakers Bureau; Jazz: Consultancy. Gasparetto:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Onyx: Honoraria; Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

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Similar Efficacy and Safety of CT-P10 and Reference Rituximab in Patients with Advanced Stage Follicular Lymphoma: Updated Phase III Study Results

Blood ◽

10.1182/blood-2018-99-112716 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 1616-1616

Author(s):

Won-Seog Kim ◽

Christian Buske ◽

Larry W Kwak ◽

Michinori Ogura ◽

Bertrand Coiffier ◽

...

Keyword(s):

Board Of Directors ◽

Safety Profile ◽

Research Funding ◽

Complete Response ◽

P Value ◽

Maintenance Period ◽

Advisory Committees ◽

Significant Difference ◽

Duration Of Response

Abstract Background: CT-P10 is an approved biosimilar to the innovator rituximab (RTX) from many countries including European Union based in part on the pharmacokinetics (PK) equivalence and comparable efficacy in patients with previously untreated advanced follicular lymphoma (FL) when treated with rituximab plus cyclophosphamide, vincristine and prednisone (R-CVP) as an induction therapy (Coiffier B et al. ASH 2016; Kim WS et al. ASCO 2017). Objective: We report here the updated efficacy outcomes including progression free survival (PFS), duration of response, overall survival (OS), as well as updated safety profile of CT-P10 compared to RTX in advanced FL patients with median follow-up duration of 23 months including the Maintenance Period with rituximab monotherapy. Methods: These results were derived from an ongoing randomized and double-blind study in patients with previously untreated advanced FL (NCT02162771). A total of 140 patients were randomized in a 1:1 ratio and 124 patients completed 8 cycles of R-CVP induction therapy. One-hundred twenty two patients (62 patients in CT-P10 group and 60 patients in RTX group), who showed response during the Induction Period, entered the Maintenance Period where a total of 12 cycles of rituximab monotherapy was to be administered every 2 months. The study was planned to continue until death or up to 3 years from the randomized date of the last patient. Kaplan Meier (KM) method was used to estimate PFS, duration of response, and OS. Results: Both groups had similar baseline characteristics; overall median age of 58 years, 55% female, 57% with FLIPI score ≥3, 100% with Stage III/IV, 18% with bulky disease (≥7cm) and 26% with B-Symptom. As of the cut-off date for investigator-assessed PFS, duration of response and OS, median follow-up was 23 months (range, 0.5-34) in the CT-P10 group and 22 months (range, 0.2-33) in the RTX group. The proportion of patients who had experienced relapse, disease progression or death from any cause was 22.9% (16/70) and 24.3% (17/70) for the CT-P10 and RTX groups, respectively. There was no significant difference between CT-P10 and RTX groups in PFS (log rank, p-value: 0.806) with 2-year PFS of 75.2% and 73.5%, respectively (Figure 1). In terms of sustained response, the proportions of patient who showed relapse or disease progression after achieving overall response (Complete Response, unconfirmed Complete Response, or Partial Response) were 19.4% (13/67) in CT-P10 group and 21.3% (13/61) in RTX group, and the KM curves showed no statistically significant difference between CT-P10 and RTX (log rank, p-value: 0.997) (Figure 2). Death from any cause were 5.7% (4/70) and 2.9% (2/70) in the CT-P10 and RTX groups, respectively. There was no statistically significant difference in OS (log rank, p-value: 0.464) between the CT-P10 and RTX groups with 2-year OS of 93.2% and 95.3%, respectively. Overall safety profile of CT-P10 was consistent with that of RTX (Table 1). A similar number of patients in each treatment group experienced at least 1 Treatment Emergent Adverse Events (TEAE) considered to be related to the study drug, infusion-related reaction, and infection. The proportion of patients with positive anti-drug antibody was also similar in both groups (4.3% [3/70] vs 5.7% [4/70] in the CT-P10 and RTX groups). Neither progressive multifocal leukoencephalopathy nor Hepatitis B virus reactivation was reported in either group. Conclusion: At the median follow-up duration of 23 months, the updated efficacy data in advanced FL patients demonstrated comparable PFS, sustained response and OS between CT-P10 and RTX. CT-P10 was also well tolerated and its safety profile was similar to that of RTX. The updated safety results did not reveal any trends or new signals noted in the patients treated with CT-P10. Disclosures Kim: Mundipharma: Research Funding; Novartis: Research Funding; Kyowa-Kirin: Research Funding; Celltrion: Research Funding; Roche: Research Funding; J&J: Research Funding; Takeda: Research Funding. Buske:Roche: Honoraria, Research Funding; Bayer: Research Funding; Janssen: Honoraria, Research Funding. Ogura:MeijiSeika Pharma: Consultancy; Celltrion: Consultancy, Research Funding; Mundi Pharma: Consultancy; SymBio: Research Funding; Takeda: Honoraria; Cellgene: Honoraria. Coiffier:CELGENE: Consultancy, Membership on an entity's Board of Directors or advisory committees; MUNDIPHARMA: Membership on an entity's Board of Directors or advisory committees; CELLTRION: Membership on an entity's Board of Directors or advisory committees; MORPHOSYS: Membership on an entity's Board of Directors or advisory committees; NOVARTIS: Membership on an entity's Board of Directors or advisory committees. Lee:Celltrion, Inc: Employment. Kim:Celltrion, Inc: Employment.

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Hypomethylating Agent Therapy for Chronic Myelomonocytic Leukemia Does Not Impact Acute Myeloid Leukemia Transformation or Survival

Blood ◽

10.1182/blood-2020-142747 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 6-7

Author(s):

Sandrine Niyongere ◽

Yamini Kathari ◽

Zeba Singh ◽

Emily J. Vannorsdall ◽

Ashkan Emadi ◽

...

Keyword(s):

Clinical Trial ◽

Board Of Directors ◽

Myeloid Leukemia ◽

Research Funding ◽

Chronic Myelomonocytic Leukemia ◽

Institutional Research ◽

Research Support ◽

Advisory Committees ◽

Clinical Trial Research ◽

Myelomonocytic Leukemia

Background: Chronic myelomonocytic leukemia (CMML) is a clonal hematopoietic stem cell disorder with features of both myeloproliferative neoplasm and myelodysplastic syndrome (MDS). CMML is characterized by persistent blood monocytosis >1 x 109/L, bone marrow dysplasia in one or more hematopoietic cell lines, and increased risk of transformation to acute myeloid leukemia (AML). Our review of SEER Medicare data (Haematologica 2013;98:584) demonstrated that, compared to MDS, CMML has shorter overall survival (OS) and more frequent progression to AML. Hypomethylating agents (HMAs) have become standard therapy for CMML, with reported response rates of 37-69%, but their impact on AML transformation and OS is unclear. Methods: We retrospectively reviewed CMML patients treated at the University of Maryland Greenebaum Comprehensive Cancer Center between January 2000 and December 2019. Clinical characteristics, treatments, AML progression, time to AML progression (TTP), and OS were recorded and analyzed. Descriptive statistics were used for baseline characteristics and Kaplan-Meier analysis was performed for time-to-event data. Statistical analyses were performed using GraphPad Prism 8®. Results: We identified 71 patients with CMML, 82% male and 73% white, with a median age of 69 (range 25 - 96) years; 51% had <10% bone marrow (BM) blasts and 45% had low-risk cytogenetic findings (normal karyotype or -Y). Most patients treated prior to 2005 received hydroxyurea and/or erythropoiesis-stimulating agents or were enrolled on clinical trials, while patients treated since 2005 received HMAs as primary therapy. Median follow-up was 41.1 months. The median OS of the entire cohort was 20 months, with 46% of patients progressing to AML with a median TTP of 11.5 months. By the MD Anderson Prognostic Scoring System at time of diagnosis, CMML was low-risk in 24 patients, intermediate-1 in 16, intermediate-2 in 14, and high-risk in 17. Forty-six patients received HMAs, with an overall response rate (ORR) of 54% (complete response or partial response), while 25 patients did not receive HMAs. Patient and disease characteristics were similar in HMA- and non-HMA-treated patients (Table 1). The estimated OS of HMA-treated patients was 20 months, compared to 14 months for non-HMA-treated patients (p =0.43) (Figure 1). AML transformation occurred in 52% of patients treated with HMAs, with TTP ranging from 3 to 65 months, and in 33% patients not treated with HMAs, with TTP ranging from 5 to 47 months. Most patients receiving HMAs (63%) received ≥ 6 cycles; 46% transformed to AML despite initial response, often in a sudden and unpredictable manner. HMAs were azacitidine in 13 patients, decitabine in 24, azacitidine followed by decitabine in 4, and decitabine followed by azacitidine in 5. Five CMML patients in our cohort underwent allogenic stem cell transplantation. Four of the five relapsed with transformation to AML post transplant, and only one patient remains in remission, 9 months post transplant. Conclusions: Despite a 54% ORR, HMA treatment did not have a significant impact on frequency of AML transformation, or OS in our cohort. Based on our data, favorable response rates previously reported with HMAs and also seen in our patients do not appear to translate into decreased frequency of AML transformation or prolonged OS. Though our study is a retrospective study with inherent selection bias, our results underscore the ongoing need for novel therapies and for clinical trials for CMML patients. Disclosures Niyongere: Kartos Therapeutics: Other: Received clinical trial research support with Kartos Therapeutics ; Forty Seven: Other: Received clinical trial research support with Forty Seven. Emadi:Amgen: Membership on an entity's Board of Directors or advisory committees; KinaRx: Other: co-founder and scientific advisor; NewLink Genetics: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Research Funding. Doung:Pfizer: Membership on an entity's Board of Directors or advisory committees, Other: clinical trial research support; Incyte: Other: clinical trial research support; Astex: Other: clinical trial research support; MedPacto: Other: clinical trial research support. Baer:Takeda: Other: Institutional research funding; Oscotec: Other: Institutional research funding; Kite: Other: Institutional research funding; Incyte: Other: Institutional research funding; Forma: Other: Institutional research funding; Astellas: Other: Institutional research funding; AbbVie: Other: Institutional research funding.

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Hemorrhagic Cystitis in Patients Undergoing Allogeneic Hematopoietic Cell Transplant with Post Transplant Cyclophosphamide As GvHD Prophylaxis

Blood ◽

10.1182/blood-2020-139993 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 21-22

Author(s):

Dat Ngo ◽

Stephanie Mac ◽

Dongyun Yang ◽

Saloomeh Mokhtari ◽

Jason Chen ◽

...

Keyword(s):

Clinical Trial ◽

Board Of Directors ◽

Advisory Board ◽

Board Meeting ◽

Research Support ◽

Myeloablative Conditioning ◽

Advisory Committees ◽

Forced Diuresis ◽

Gvhd Prophylaxis ◽

Grade 3

The use of post-transplant cyclophosphamide (PTCy) as graft-versus-host-disease (GvHD) prophylaxis after hematopoietic cell transplantation (HCT) has increased significantly over the past decade due to expansion of donor pool with haploidentical and mismatched unrelated donors. A recently completed phase 2 study, PROGRESS-2 (NCT02345850), has highlighted the efficacy of PTCy in the matched donor setting. Hemorrhagic cystitis (HC) is the most notable toxicity associated with high dose Cy. However, data specific to the incidence and severity of HC in the post HCT setting is sparse, with no consensus on best practices to prevent HC in patients receiving PTCy. Current strategies to prevent HC in PTCy setting have been adapted from data in pre-HCT Cy (conditioning setting), such as hyperhydration with forced diuresis, continuous bladder irrigation, mesna as an intermittent and continuous infusion, or a combination of these methods. The aim of our study was to describe the incidence and severity of HC in patients undergoing HCT with PTCy as GvHD prophylaxis, identifying potential risk factors and impact of HC on HCT outcomes. We retrospectively reviewed 194 consecutive patients who underwent their first HCT with PTCy from 2014 to 2018 at our center. More than half of the patients (53%) received myeloablative conditioning regimen with majority receiving peripheral blood stem cells (81%) from haploidentical donors (96%). GvHD prophylaxis was unified with PTCy (50 mg/kg on Days +3 and +4), in addition to MMF (1 gm 3x daily starting on Day +5) and tacrolimus (1 mg as a continuous infusion daily starting on Day +5). Standard HC prophylaxis was hyperhydration with forced diuresis and mesna at 320% the daily dose of PTCy. Incidence of HC was based on physician documentation or presence of blood in urinalysis up to Day +100. To determine severity of HC, CTCAE 5.0 grading system was used. Median age of patients was 45 years (range: 2-73), with 60% of patients being male. KPS was ≥80% in 83% of patient and 40% had HCT-CI of ≥2. The most common diagnoses included: AML (41%), ALL (24%) and MDS/MPN (19%). There were 55 patients who received ≥3 lines of therapy, 116 patients received <3 lines of therapy pre-HCT, and 23 patients did not receive chemotherapy before HCT. DRI was high/very high in 38% of patients. Incidence, median onset, median days until resolution, severity, and the types of intervention for treatment of HC are displayed in Table 1. At a median onset of 12 days (range: 3-71) after HCT, a total of 61 patients (31.4%) developed Grade 1-2 (88.5%) and Grade 3 (11.5%); none of the patients developed Grade 4 HC. Viral HC (presence of either BK [n=26] or adenovirus [n=0] in urine) and non-viral HC were developed at a median of 34 (range: 6-71) and 7 days (range: 3-59, p<0.001), respectively. Most patients improved with supportive care over a median of 9 days (range: 1-69). Seven patients (11.5%) required continuous bladder irrigation, and six received anti-viral therapy. In multivariate analysis, age above 60 years (HR 4.16, 95% CI 1.52-11.42, p = 0.006) and myeloablative conditioning (HR 2.44, 95% CI 0.99-6.05, p = 0.054 [trend]) were associated with higher risk for HC. Disease type and risk, performance status and prior chemotherapy history were not associated with higher risk of HC in our cohort. By multivariate analysis, the incidence of HC or severe HC by Day +100 post-HCT was not associated with overall survival (OS), disease-free survival (DFS), non-relapse mortality (NRM), or grade 3-4 acute GvHD. In conclusion, hyperhydration with forced diuresis added to aggressive mesna dosing is an effective strategy in preventing severe HC in HCT patients receiving PTCy as GvHD prophylaxis. Incidence of Grade 3 or 4 HC was low and transient and did not impact HCT outcomes. Viral HC had a significantly later onset than non-viral HC, suggesting a different pathophysiology. Older age and myeloablative conditioning were independent factors for higher incidence of HC in our cohort. Disclosures Ali: Incyte Corporation: Consultancy. Salhotra:Celgene: Research Funding; Kadmon: Membership on an entity's Board of Directors or advisory committees. Aribi:Seattle Genetics: Consultancy. Pullarkat:Servier: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie, Inc.: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genetech: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Dova: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Stein:Amgen: Consultancy, Speakers Bureau; Stemline: Consultancy, Speakers Bureau. Marcucci:Merck: Other: Research Support (Investigation Initiated Clinical Trial); Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Abbvie: Speakers Bureau; Novartis: Speakers Bureau; Iaso Bio: Membership on an entity's Board of Directors or advisory committees; Takeda: Other: Research Support (Investigation Initiated Clinical Trial). Nakamura:NapaJen Pharma: Consultancy; Viracor: Consultancy; Kadmon Corporation: Other: Advisory board meeting; Magenta Therapeutics: Other: Advisory board meeting; Celgene: Other: Support on seminar; Kyowa-Kirin: Other: Support on a meeting presentation; Alexion: Other: Support on a meeting presentation; Merck: Other: advisory board meeting. Al Malki:Rigel Pharma: Consultancy; Jazz Pharmacuticals, Inc: Consultancy; Neximmune: Consultancy.

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High Expression Of Cereblon (CRBN) Is Associated With Achievement Of Complete Response To Thalidomide Plus Fludarabine Regimen In Chronic Lymphocytic Leukemia

Blood ◽

10.1182/blood.v122.21.4934.4934 ◽

2013 ◽

Vol 122 (21) ◽

pp. 4934-4934

Author(s):

Krzysztof Jamroziak ◽

Janusz Szemraj ◽

Tadeusz Robak ◽

Krzysztof Giannopoulos

Keyword(s):

Clinical Trial ◽

T Cell ◽

Chronic Lymphocytic Leukemia ◽

Board Of Directors ◽

Complete Response ◽

Lymphocytic Leukemia ◽

Receptor Expression ◽

Cell Populations ◽

Advisory Committees ◽

Pre Treatment

Abstract Cereblon (CRBN) has recently been identified as a target for immunomodulatory drugs (IMiDs), thalidomide, lenalidomide and pomalidomide, and its downregulation has been linked to resistance to IMiDs in multiple myeloma (MM). However, little is known on the role of CRBN as a resistance/response biomarker in other diseases in which treatment with IMiDs is investigated, such as chronic lymphocytic leukemia (CLL). Although lenalidomide has recently proven to be more promising drug in CLL, we had previously performed a clinical trial that assessed efficacy of thalidomide (100mg p.o on days 1-28) combined with fludarabine (25mg/m2 i.v. on days 7–11) given for six 4-week cycles in patients with CLL. The objective of the present study was to correlate retrospectively pre-treatment CRBN expression in CLL cells with response to thalidomide/fludarabine regimen as well as to cellular and molecular changes that were monitored in vivo after initial 7-day thalidomide monotherapy. CRBN and interferon regulatory factor 4 (IRF4) expressions were studied by quantitative RT-PCR using mRNA extracted from frozen pre-treatment CLL cells. Tumor necrosis factor (TNF) and TNF receptor expression were analyzed by ELISA. T-cell populations were estimated using flow cytometry during the clinical part of the study. Frozen biological pre-treatment samples were available for 27 out of 40 patients included to the thalidomide/fludarabine clinical trial. First, we verified that CRBN expression was independent from all established prognostic parameters in CLL including IGVH mutational status, high-risk FISH, ZAP-70 and CD38 expression and beta-2 microglobulin level (p>0.05 for all parameters). Subsequently, we analyzed the CRBN expression in regard to response and CLL prognosis. Interestingly, we found that patients with CRBN expression in the highest quartile tended to have significantly higher probability of complete response (CR) (50% vs. 10%, Fisher exact test p=0.56). However, although median CRBN expression was highest in patients with CR (median=0.80), it was lower in patients achieving partial remission (PR) (0.24) than in patients who did not responded (0.50), and the response categories did not correlate directly with CRBN expression in CLL cells, (r=0.07, p=0.71). Furthermore, no significant association was found between CRBN expression above and below median and duration of response after thalidomide/fludarabine treatment (28 vs. 29 month, p=0.88). Interestingly, in contrast to previous data in MM, we found that CRBN expression did not correlate with IRF4 expression (r=0.25, p=0.22). Furthermore, analysis of molecular and cellular parameters assessed after initial 7-day thalidomide monotherapy including the changes in TNF levels and regulatory T-cell populations did not reveal any significant relation to basal CRBN levels. In conclusion, we found that high pre-treatment CRBN expression in CLL cells is associated with CR achievement on thalidomide-containing chemotherapy. However, in contrast to published data on MM, CRBN expression in CLL cells does not correlate directly with CLL prognosis or molecular and cytological effects caused by thalidomide. Our results may indicate complex mechanisms of IMiDs activity in CLL and that basal CRBN levels in CLL microenvironment and immune effector T and NK cells may be more important for CLL outcome. Disclosures: Off Label Use: The presentation is a retrospective analysis of a clinical trial on thalidomide that is not approved in CLL. Currently, another IMiD, lenalidomid, is being investigated in CLL with promising activity,and the data from this retrospective study may add to understanding on its action. Robak:Novartis: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity’s Board of Directors or advisory committees.

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Next-Generation Sequencing-Based Assay Shows High Clonal Characterization Success Rate for Plasma Cell Neoplasms, and Concordance with Flow Cytometry in Minimal Residual Disease Detection

Blood ◽

10.1182/blood-2018-99-115690 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4475-4475

Author(s):

Caleb Ho ◽

Mustafa Syed ◽

Mikhail Roshal ◽

Kseniya Petrova-Drus ◽

Christine Moung ◽

...

Keyword(s):

Success Rate ◽

Board Of Directors ◽

Plasma Cell ◽

Research Funding ◽

Residual Disease ◽

Complete Response ◽

Patient Specific ◽

Advisory Committees ◽

Plasma Cell Neoplasms ◽

Generation Sequencing

Abstract Introduction After therapy or stem cell transplantation, multiple myeloma patients achieving complete response (CR) or stringent complete response (sCR) can still have a significant risk of disease relapse, illustrating the importance of using highly sensitive methods for minimal residual disease (MRD) detection and prognostication. Two techniques used clinically for MRD detection include multiparametric flow cytometry (FC), which has a sensitivity down to 2-6 X 10-6 of cells, and next-generation sequencing (NGS)-based assay for detection of patient-specific clonal IGH VDJ gene sequences associated with the neoplastic plasma cells (PC). We determined the clonal characterization success rate of plasma cell neoplasm samples from a single institution in a clinical lab, using a commercially available NGS-based assay, Lymphotrack® (Invivoscribe, San Diego, CA). The characterized clonal sequences were used for MRD detection in subsequent monitoring samples, and the results were compared to concurrent FC findings. Methods DNA was extracted from fresh marrow or formalin-fixed paraffin-embedded (FFPE) tissue, and amplified by PCR reactions using primers sets for IGH Leader, FR1, FR2, FR3 regions, and IGK. Sequencing was performed on the Illumina MiSeqTM Platform, and sequence analyses were performed using the Lymphotrack® software, and MSK-Lymphoclone, a software developed at our institution. Disease-associated clonal sequences were characterized based on predefined clonal calling criteria and stored. In subsequent samples sent for disease monitoring, a search for sequencing reads with high homology (>99%) to the patient-specific sequences was performed for MRD detection. 10-color FC for PC analyses were also performed on the same samples at our institution (Roshal M, et al. Blood Adv 2017;1(12):728-32), with a target minimum of 3 million cells for MRD analyses. Results Overall, clonal characterization was successful in 235/251 cases (93.6%), with no difference in number of sequencing reads between the successful and unsuccessful cases (p=0.24). Higher success rate was observed among cases with higher aspirate PC counts: ≥5% (95.6% success rate) and ≥10% (98.1% success rate). IGH FR1 and Leader primers together characterized 214/251 cases (85.3%), while the remaining cases required additional primers. The characterized clones showed high median somatic hypermutation (SHM) rate of 8.1% (range: 0.0-29.0%), as well as IGH V and J segment usage bias: V3 (50.2%), followed by V4 (20.3%); J4 (43.4%), followed by J6 (27.5%), concordant with prior literature. 187 samples from 124 unique patients were tested by the Lymphotrack® assay for monitoring purposes, of which the diagnostic clones were detected in 147/187 samples (78.6%), with no difference in number of sequencing reads between cases with and without detectable clone (p=0.35). Within the short median time interval of 9.5 months between the characterization and monitoring samples, most clonal sequences remained stable. In 2 cases, new clonal sequences emerged in subsequent samples. Overall, FC and Lymphotrack® showed high concordance rate for MRD detection (92.9%) (See figures). All discordant cases showed <5% PC by aspirate differential counts and CD138 immunostains. FC+/NGS- cases (9/184, 4.9%) showed abnormal PC comprising a median of 0.00095% of WBC by FC, while FC-/NGS+ cases (4/184, 2.2%) showed detectable clone at a median of 0.0405% of sequencing reads. Sampling differences might have contributed to the discrepancies. Additionally, in the FC+/NGS- cases, neoplastic subclones might be present at very low level in the characterization samples, below threshold for clonal calling, and therefore could not be specifically tracked in subsequent samples. Conclusions Our study demonstrated high clonal characterization success rate for plasma cell neoplasms using the Lymphotrack® assay when multiple primers sets were used, and the assay showed concordance with FC in MRD detection for the majority of cases. MRD detection sensitivity can be limited by low sample concentration/volume. Furthermore, the presence of very low level neoplastic subclones in the characterization samples might hamper clonal calling and detection in subsequent samples. Disclosures Ho: Invivoscribe, Inc.: Honoraria. Landgren:Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Takeda: Consultancy, 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; Pfizer: Consultancy; Karyopharm: Consultancy. Arcila:Invivoscribe, Inc.: Consultancy, Honoraria.

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Total Marrow and Lymphoid Irradiation (TMLI) at a Dose of 2000cGy in Combination with Post-Transplant Cyclophosphamide (PTCy)-Based Graft Versus Host Disease (GvHD) Prophylaxis Is Safe and Associated with Favorable GvHD-Free/Relapse-Free Survival at 1 Year in Patients with Acute Myeloid Leukemia (AML)

Blood ◽

10.1182/blood-2020-141469 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 41-42

Author(s):

Anthony S. Stein ◽

Monzr M. Al Malki ◽

Dongyun Yang ◽

Joycelynne Palmer ◽

Ni-Chun Tsai ◽

...

Keyword(s):

Clinical Trial ◽

Board Of Directors ◽

Chronic Gvhd ◽

Conditioning Regimen ◽

Advisory Board ◽

Board Meeting ◽

Relapse Free Survival ◽

Research Support ◽

Advisory Committees ◽

Free Survival

Background: Allogeneic hematopoietic cell transplantation (alloHCT) is the approach that offers the highest curative rate for acute myelogenous leukemia (AML) with intermediate or high-risk cytogenetics. Graft versus host disease (GvHD) has remained the main cause of post-transplantation mortality and morbidity, despite advances in prophylaxis and therapy, adding significant economic burden and affecting quality of life. It would be desirable to reduce the rate of GvHD among patients in complete remission (CR) without increasing the risk of relapse. In this study, we have developed a novel conditioning regimen of total marrow and lymphoid irradiation (TMLI) at 2000 cGy, together with post-transplant cyclophosphamide (PTCy), to 1) reduce the possibly increased risk of relapse from PTCy, by using escalated radiation doses of TMLI, as increasing radiation doses has the potential to decrease the post-transplantation relapse rate (Blood, vol 76, pp. 1867-1871, 1990); and 2) reduce the risk of chronic GvHD by using PTCy. The major goal of this pilot study of TMLI and PTCy (clinicaltrials.gov: NCT03467386), was to thus improve GvHD-free/relapse-free survival (GRFS), reported to be 45% from total body irradiation (TBI) and tacrolimus/sirolimus prophylaxis (BBMT, vol 26(2), pp. 292-299, 2020), in patients with AML in remission. Patients and Methods: A total of 18 patients were enrolled and treated (see Table) between March 2018 and December 2019. Key criteria were ages 18 to 60, first or second CR, minimal residual disease negative by multi-color flow cytometry, and normal organ function. TMLI was administered on days -4 to 0 without addition of chemotherapy. The radiation dose for all patients (n=18) was 2000 cGy, delivered in 200 cGy fractions twice daily. The radiation dose delivered to the liver and brain was kept at 1200 cGy. Remaining organs were considered non-targeted. All patients received peripheral blood stem cells on day 0. Cyclophosphamide was given on days +3 and +4, 50 mg/kg each day for GVHD prevention. Tacrolimus, 1 mg continuous infusion adjusted to maintain levels from 5 to 10 ng/mL was given from day +5 to day +90, and G-CSF 5 µg/kg daily was administered at day +5 until recovery of neutrophil counts. Endpoints included toxicity, GRFS at 1 year, engraftment, overall survival (OS), and non-relapse mortality (NRM). Toxicities were defined according to the Bearman and CTCAE 4.03 scales, the latter for hematologic toxicity. A patient safety lead-in segment (n=6) was conducted to ensure that there were no unexpected toxicities, allowing for a dose de-escalation to 1800 cGy. GRFS was defined as grade 3-4 acute GvHD, chronic GvHD requiring systemic treatment, relapse, or death (from any cause), whichever occurred first. Results: Bearman toxicity data are available for all patients. Among these patients, grade 2 toxicities were bladder toxicity and stomatitis. No grade 3-4 toxicities or toxicity-related deaths were observed. Acute GVHD (aGVHD) developed in 2 of patients (100-day Grade II-IV aGVHD: 11.1%, 95%CI: 1.7-30.4); of those, only 1 patient developed Grades III-IV (100-day Grade III-IV aGVHD: 5.6%, 95%CI: 0.3-23.1). Five patients developed mild chronic GVHD (1-year cGVHD rate: 28.6%, 95%CI: 7.5%-54.7%). The GRFS rate at 1 year was 59.3% (95% CI: 28.8-80.3) (Figure). The median follow up was 11.3 months (range 4.7 to 25.4) for surviving patients (n=17). All patients engrafted. Time to neutrophil and platelet recovery were 14 days (range 13-32 days) and 20 days (range 11-49 days), respectively. One-year estimates of OS and relapse-free survival were 100% and 80.8% (95% CI: 50.5-93.6), respectively (Figure). Disease relapse at 1 year was 19.2% (95% CI: 4.1-42.6). The estimates of NRM at 100 days and 1 year were both 0%. Relapsed disease after transplant occurred in 3 patients (16.7%). One patient died after relapse. Conclusions: 1) This chemotherapy-free conditioning regimen, together with PTCy and tacrolimus, is safe and feasible, with no NRM. 2) All patients achieved engraftment. 3) Participants with ≥1 year follow-up have discontinued immunosuppressive therapy, reducing financial burden and leading to improved quality of life. The preliminary results suggest an improved GRFS rate. A larger phase 2 trial is in preparation to corroborate these data. Disclosures Stein: Amgen: Consultancy, Speakers Bureau; Stemline: Consultancy, Speakers Bureau. Al Malki:Neximmune: Consultancy; Jazz Pharmacuticals, Inc: Consultancy; Rigel Pharma: Consultancy. Ali:Incyte Corporation: Consultancy. Aribi:Seattle Genetics: Consultancy. Marcucci:Novartis: Speakers Bureau; Takeda: Other: Research Support (Investigation Initiated Clinical Trial); Pfizer: Other: Research Support (Investigation Initiated Clinical Trial); Abbvie: Speakers Bureau; Merck: Other: Research Support (Investigation Initiated Clinical Trial); Iaso Bio: Membership on an entity's Board of Directors or advisory committees. Nakamura:Alexion: Other: Support on a meeting presentation; Kyowa-Kirin: Other: Support on a meeting presentation; Merck: Other: advisory board meeting; Celgene: Other: Support on seminar; Magenta Therapeutics: Other: Advisory board meeting; Viracor: Consultancy; Kadmon Corporation: Other: Advisory board meeting; NapaJen Pharma: Consultancy. Pullarkat:AbbVie, Inc.: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genetech: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Servier: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Dova: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Salhotra:Celgene: Research Funding; Kadmon: Membership on an entity's Board of Directors or advisory committees.

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