Schechter‐Finkelstein, Tal

Background: The majority of patients respond to steroid treatment for graft-vs-host disease (GVHD), but the typically high doses and prolonged courses can cause substantial morbidity. GVHD can be classified at onset into two groups with significant differences in treatment response and non-relapse mortality (NRM) by clinical criteria (Minnesota risk) but the more favorable standard risk group still experiences high rates of treatment failure and NRM [MacMillan, BBMT 2015]. We previously validated a serum biomarker-based (ST2+REG3α) risk stratification system, MAGIC algorithm probabilities (MAPs), that can stratify patients both at initiation and during treatment into risk groups for treatment response and NRM [Hartwell, JCI Insight 2017, Srinagesh, Blood Adv 2019]. GVHD that is Minnesota standard risk and has a low MAP (i.e., Ann Arbor 1) at start of treatment represents a low risk group with >80% response rate to steroids and ~10% NRM [Etra, Blood 2023]. We hypothesized that serial monitoring of GVHD symptom severity and MAPs twice (days (d) 7 and 14) in patients with clinical and biomarker defined low risk GVHD could further stratify patients into clinically meaningful groups. Methods: We retrospectively determined MAPs at d7 and 14 in 450 patients with low risk GVHD who participated in a prospective, multi-center, observational trial and were treated with systemic steroids between 2015-2023. MAPs <0.291 at days 7 and 14 were defined as low risk based on a previously validated threshold [Major-Monfried Blood 2018]. Clinical responses were scored as complete (CR), partial (PR), or non-response (NR) by standard criteria. Initiation of second line therapy was considered NR. Patients were categorized into three groups (A-C) based on clinical responses and MAPs at days d7 and 14. A: CR/PR by d14 and low MAP at both d7+14; B: stable or worse GVHD (NR) by d14 with low MAP at both d7 and 14; C: any response with a high MAP at d7 or 14. The endpoints were clinical response at day 28 (overall response rate, ORR=CR or PR), regardless of earlier response status, and 6-month NRM. Results: The median age of the study population was 54 years (range: 0-79); 19% of patients received PT-Cy for GVHD prophylaxis. Target organ involvement was skin ± upper GI (66%), lower GI (23%), isolated UGI (11%), and skin+liver (1%), and GVHD severity was grade I (35%), II (61%), and III (4%) at start of treatment. Patients in group A (n=310, 69%), clinical responders with low MAPs through day 14, had excellent d28 ORR (93%) and very low NRM (4%). GVHD in this group was considered ultra-low risk (ULR) and subset analyses revealed highly consistent d28 ORR and NRM, regardless of target organ severity, age (<18, 18-59, >60), HCT-CI score, conditioning intensity, and GVHD prophylaxis. Group B patients comprised clinical non-responders with low MAPs through day 14 (n=112, 25%); half of them responded by d28 and their NRM was low (8%), albeit double that of group A (p=0.079). Group C was small (n=28, 6%) and included both clinical responders (n=20, 4%) and clinical non-responders (n=8, 2%) who had at least one high MAP through day 14. Their d28 ORR was 54% but NRM increased four-fold (32%) and was significantly worse than patients who maintained low MAPs regardless of clinical response (p<0.001). Conclusion: Serial monitoring by clinical response and biomarkers during the first two weeks of treatment identifies a small number of high risk patients whose GVHD is initially low risk (group C). This group experiences high NRM regardless of clinical response to steroid treatment and may benefit from treatment escalation. Patients with low risk GVHD who do not have an early clinical response to steroids but maintain low MAPs, (group B) have reasonably good long-term outcomes with standard treatment. Finally, serial monitoring identifies a very large subset of patients with ULR GVHD (group A) who respond exceptionally well to standard treatment and experience very low rates of 6-month NRM regardless of pre-transplant characteristics and GVHD prophylaxis. Such patients may benefit from treatment de-escalation strategies such as shorter courses of lower dose steroids, a strategy we are currently testing in a clinical trial (NCT05090384).

Abstract The absence of a standardized definition for graft-versus-host disease (GVHD) flares and data on its clinical course are significant concerns. We retrospectively evaluated 968 patients across 23 Mount Sinai Acute GVHD International Consortium (MAGIC) transplant centers who achieved complete response (CR) or very good partial response (VGPR) within 4 weeks of treatment. The cumulative incidence of flares within 6 months was 22%, and flares were associated with a higher risk of nonrelapse mortality (NRM; adjusted hazard ratio [aHR], 4.84; 95% confidence interval [CI], 3.19-7.36; P < .001). Flares were more severe (grades 3/4, 41% vs 16%; P < .001) and had more frequent lower gastrointestinal (LGI) involvement (55% vs 32%; P < .001) than the initial GVHD. At CR/VGPR, elevated MAGIC biomarkers predicted the future occurrence of a flare, along with its severity and LGI involvement. In multivariate analyses, higher Ann Arbor (AA) biomarker scores at CR/VGPR were significant risk factors for flares (AA2 vs AA1: aHR, 1.81 [95% CI, 1.32-2.48; P = .001]; AA3 vs AA1: aHR, 3.14 [95% CI, 1.98-4.98; P < .001]), as were early response to initial treatment (aHR, 1.84; 95% CI, 1.21-2.80; P = .004) and HLA-mismatched unrelated donor (aHR, 1.74; 95% CI, 1.00-3.02; P = .049). MAGIC biomarkers also stratified the risk of NRM both at CR/VGPR and at the time of flare. We conclude that GVHD flares are common and carry a significant mortality risk. The occurrence of future flares can be predicted by serum biomarkers that may serve to guide adjustment and discontinuation of immunosuppression.

[Background] The current standard first-line treatment for acute graft-versus-host disease (GVHD), systemic high-dose steroids, induces clinical responses in a majority of patients. Flares of GVHD after initial improvement often occur during tapering or discontinuation of immunosuppression. There is no consensus regarding the definition of GVHD flare and little has been published regarding its natural history. [Methods] We retrospectively evaluated clinical data and blood samples from 968 allogeneic hematopoietic cell transplantation (HCT) recipients from 23 Mount Sinai Acute GVHD International Consortium (MAGIC) transplant centers who achieved complete response (CR) or very good partial response (VGPR) within 4 weeks of acute GVHD treatment between 2014 and 2021. VGPR was defined as the complete resolution of acute GVHD manifestations except residual stage 1 skin disease. Flares were defined as a recurrence of acute GVHD after achievement of CR/VGPR if (1) patients had an increased symptom severity of at least 1 organ stage; (2) received intensified treatment (increase in steroid dose ≥ 0.25 mg/kg or initiation of additional systemic immunosuppression); and (3) had no prior history of primary disease relapse or donor lymphocyte infusion preceding the flare. Serum samples obtained at the time of CR/VGPR and at the time of flares were analyzed for ST2 and REG3α concentrations that generated MAGIC algorithm probabilities (MAPs) resulting in previously validated Ann Arbor (AA) scores (1, 2, and 3). [Results] The median recipient age at HCT was 55 years (range: 0 to 79); 18.6% of patients had grades III-IV acute GVHD before CR/VGPR. The median maximum daily dose of corticosteroids before CR/VGPR was 1 mg/kg methylprednisolone equivalent (range, 0.1 to 3.2 mg/kg). Flares developed within 6 months following CR/VGPR in 210/968 (21.7%) patients with a median onset of 28 days (range: 2 to 448). Symptom severity at the onset of flare symptoms varied widely (grade I: 22%; grade II: 38%; grade III-IV: 41%) and the development of a flare was associated with a five-fold increase in NRM (hazard ratio [HR], 4.84 [95% CI, 3.19-7.36], P < 0.001) when considered as a time-dependent covariate in a multivariate regression model. The large majority of non-relapse deaths after flares (54/71, 76%) were due to acute GVHD or complications from its treatment. The AA scores at the time of first CR/VGPR successfully stratified patients for risk of six-month NRM (AA1: 5%, AA2: 11%, AA3: 34%, P < 0.001) (Figure A). Increasing AA score at CR/VGPR was also associated with significantly increased risk of GVHD flares (Figure B). Not only did the risk of flare increase with each rising AA score, but the number of patients with severe (grade III/IV) symptoms at flare onset also increased (AA1: 34%, AA2: 43%, AA3: 54%). We next generated a multivariate regression model of risk factors for the development of flares. High AA scores at the time of CR/VGPR (AA2: HR, 1.81 [95% CI, 1.32-2.48], P = 0.001; AA3: HR, 3.14 [95% CI, 1.98-4.98], P < 0.001), HCT from HLA mismatched unrelated donor (HR, 1.74 [95% CI, 1.00-3.02], P = 0.049), and interestingly, rapid achievement of CR/VGPR from the time of initial treatment (≤14 days) (HR, 1.84 [95% CI, 1.21-2.80], P = 0.004) were all identified as significant risk factors. Meanwhile, no other transplant, GVHD, or treatment characteristics associated with the development of flares including maximum GVHD severity, maximum steroid dose, and use of additional immunosuppressive agents other than steroids before CR/VGPR. AA scores measured at the onset of flare symptoms in 98 patients also predicted six-month NRM (AA1, 6%; AA2, 19%; AA3 42%, P = 0.01). [Conclusion] Despite advances in treatment, flares of GVHD symptoms following excellent (CR/VGPR) responses still occur in over one fifth of patients in current practice and are associated with a five-fold increase in six-month NRM. AA scores from serum biomarkers predict outcomes despite the absence of symptoms, suggesting that MAGIC biomarkers detect subclinical damage to GI crypts that can drive later recrudescence of clinical GVHD. Measurement of the MAP at the time of response to GVHD treatment may thus help to risk-stratify tapering strategies of immunosuppressive therapy.

The overall response rate (ORR) 28 days (D28) after treatment has been adopted as the primary endpoint for clinical trials of acute graft versus host disease (GVHD). ORR combines complete response (CR) and partial response (PR) because CR and PR have very similar non relapse mortality (NRM). D28 ORR has some disadvantages: first, physicians usually decide to modify immunosuppression much earlier than D28, and second, NRM does not always correlate well with ORR at D28, particularly for patients who present with intermediate risk or low risk disease. MAGIC serum biomarkers at day 14 (D14) of GVHD treatment have been shown to correlate better with NRM than clinical symptom response (Srinagesh et al, Blood Advances, 2019). We therefore hypothesized that a combination of clinical symptom severity and biomarkers at D14 of treatment would predict NRM at least as well and possibly better than clinical response at D28. We studied 1144 patients from 23 MAGIC sites who were systemically treated with at least 0.25 mg/kg/day of systemic steroids (prednisone equivalents) and had clinical data and serum samples available in the MAGIC database and biorepository. We divided the patients into a training set (n=764) and a validation set (n=380). We used 12-month NRM from the time of acute GVHD onset as the primary outcome of interest. We first trained a recursive partitioning algorithm in the training set to create a response model (MAGIC D14 clinical response) according to overall GVHD grade at both onset and D14 that predicted 12-month NRM and then applied it to the validation set. Patients that either progressed to grade III/IV GVHD, continued having grade III/IV GVHD, or only improved to grade II at D14 from grade III/IV at D0 had high NRM and were classified as non-responders. Patients with grade I/II GVHD at day 0 who had grade 0-II GVHD at day 14 and patients who improved to grade 0/I at day 14 from grade III/IV at day 0 had low NRM and were classified as responders. Although counterintuitive, responders included patients whose GVHD remained at grade II because the 12 month NRM of this group was only 20%. The new clinical model predicted NRM as well as the D28 standard response model in the validation set. When we integrated the D14 MAP biomarker score (low: ≤ 0.290 vs high: >0.290) with the new D14 clinical response (D14 MAGIC integrated response), we observed three response groups of integrated response with strikingly different 12 month NRM (8%, 35%, 76%, p<0.001), in contrast to the D28 standard response (Figure 1A, 1B). D14 complete response required MAGIC clinical response with low MAP; D14 partial response required either MAGIC clinical response with high MAP or MAGIC clinical non-response with low MAP; and D14 non-response required MAGIC clinical non-response with high MAP. The D14 response groups also displayed significant differences in 12 month OS (82%, 58%, 14% respectively, p<0.001) We then compared the D14 integrated response with the D28 standard response for 12 month NRM prediction. This D14 integrated response model was superior for time-dependent AUC (0.78 vs 0.71, P=0.03), sensitivity (0.71 vs 0.54), positive predictive value (0.52 vs 0.48) and negative predictive value (0.92 vs 0.89), with minimal loss in specificity (0.85 vs 0.87) in the prediction of 12-month NRM compared to the D28 standard response model. Using decision curve analysis, the D14 integrated response displayed higher net benefit (correct identification of patients that will experience NRM by 12 months) over the whole range of threshold probabilities/preferences for changing immunosuppression when 12-month NRM was used as the outcome. We conclude first, that the definition of response that uses onset and D14 grades is as accurate as D28 ORR model; and second, that a model using clinical grades and biomarkers on D14 more accurately predicts long term NRM than the standard D28 definition and may be useful as a clinical trial endpoint.

Abstract Background: A major cause of mortality in patients receiving hematopoietic stem cell transplantation (HCT) is acute graft-versus-host disease (GVHD), a multiorgan disorder that includes the skin, liver and gastrointestinal tract. We have previously identified elafin, a protease inhibitor overexpressed in inflamed epidermis, as a diagnostic biomarker of GVHD in the skin, the most commonly involved GVHD organ. However, our initial study was limited to a subset of patients with isolated skin GVHD. The main driver of nonrelapse mortality (NRM) in HCT patients is GI GVHD. Two biomarkers, Regenerating islet-derived 3a (REG3α) and Suppressor of tumorigenesis 2 (ST2), have since been validated as biomarkers of GI GVHD that predict long-term outcomes in patients treated for GVHD. We undertook this study to determine the utility of elafin as a prognostic biomarker of acute GVHD in the general population of previously unstudied acute GVHD patients, and to compare it to ST2 and REG3α. Study Design: 526 patients who received systemic corticosteroid treatment for skin GVHD were analyzed from the Mount Sinai Acute GVHD International Consortium (MAGIC), which includes patients from 25 HCT centers. We used ELISA to measure serum concentrations of elafin, ST2 and REG3α. Patients were divided randomly into equal training and validation sets; and we developed a competing risk regression model for 6-month NRM using elafin concentration in the training set. We developed additional models for 6-month NRM using concentrations of ST2 and REG3α, or the combination of all three biomarkers as predictors. We then constructed ROC curves to evaluate the predictive accuracy of each model and to analyze the ability of each model to stratify patients into high- and low-risk groups. We analyzed the cumulative incidence of 6-month NRM and overall survival in each model and compared the accuracy of each model in the validation set. Results: The area under the receiver operating curve (AUROC) for elafin alone was 0.55 whereas it was 0.75 and statistically superior (P = 0.02) for the combination of ST2 and REG3α. The combination of 3 biomarkers produced an AUROC of 0.76 that was not significantly better than the two biomarker model (P = 0.10). Elafin concentrations, either alone or in combination with ST2 and REG3α, did not produce higher hazard ratios of NRM (data not shown). Patients in the low-risk elafin group paradoxically demonstrated a higher incidence of 6-month NRM, although this difference was not statistically significant (17% vs. 11%, P=0.19), and both overall survival at 6 months (68% vs. 68%, P>0.99) and four-week response (78% vs. 78%, P=0.98) were similar in the low- and high-risk elafin groups (Figure 1). As demonstrated in previous data sets, the combination of ST2 and REG3α divided patients into two groups with a nearly five-fold difference in NRM (6.7% vs. 31%, P <0.001). Conclusion: We demonstrated that serum elafin concentrations measured at the initiation of systemic treatment for acute GVHD in a multicenter population of patients treated systemically for acute GVHD do not predict 6-month NRM, overall survival, or treatment response. As seen in previous studies, serum concentrations of the GI GVHD biomarkers ST2 and REG3α were significant predictors of NRM and the addition of elafin levels did not improve their accuracy. These results underscore the importance of GI disease in driving NRM in patients who develop acute GVHD. Figure 1. Cumulative incidence of nonrelapse mortality and overall survival in high and low risk groups Six-month cumulative incidences of nonrelapse mortality (NRM) in high (solid line) and low (dotted line) risk groups defined by optimized biomarker thresholds (upper panels) and six-month overall survival estimated using the Kaplan-Meier method (lower panels). (A) Cumulative incidence of NRM (14%) and overall survival (75%) in the total validation set (N=263). (B) Cumulative incidence of NRM in the low (N=150) and high (N=113) elafin group (17% vs. 11%, P=0.19). Overall survival in the low and high elafin group (68% vs. 68%, P > 0.99). (C) Cumulative incidence of NRM in the low (N=175) and high (N=88) ST2 + REG3a group (6.7 vs. 31%, P < 0.001). Overall survival in the low and high ST2 + REG3a group (77% vs. 51%, P < 0.001). (D) Cumulative incidence of NRM in the low (N=180) and high (N=83) elafin + ST2 + REG3a group (7.0 vs. 30%, P < 0.001). Overall survival in the low and high elafin + ST2 + REG3a group (79% vs. 64%, P < 0.001). Figure 1 Figure 1. Disclosures Ozbek: Viracor: Patents & Royalties: GVHD biomarker patent with royalties from Viracor. DeFilipp: Omeros, Corp.: Consultancy; Incyte Corp.: Research Funding; Regimmune Corp.: Research Funding; Syndax Pharmaceuticals, Inc: Consultancy. Grupp: Novartis, Kite, Vertex, and Servier: Research Funding; Jazz Pharmaceuticals: Consultancy, Other: Steering committee, Research Funding; Novartis, Roche, GSK, Humanigen, CBMG, Eureka, and Janssen/JnJ: Consultancy; Novartis, Adaptimmune, TCR2, Cellectis, Juno, Vertex, Allogene and Cabaletta: Other: Study steering committees or scientific advisory boards. Hexner: Blueprint medicines: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tmunity Therapeutics: Research Funding; PharmaEssentia: Membership on an entity's Board of Directors or advisory committees. Kitko: Co-investigator on two NIH grants as part of the cGVHD consortium: Research Funding; Vanderbilt University Medical Center: Current Employment; PER: Other: PER - CME educational talks about GVHD; Horizon: Membership on an entity's Board of Directors or advisory committees. Qayed: Novartis: Honoraria; Mesoblast: Honoraria; Medexus: Honoraria. Reshef: ilead, BMS, Precision, Immatics, Atara, Takeda, Shire, Pharmacyclics, Incyte: Research Funding; Bayer: Consultancy; Gilead and Novartis: Honoraria; BMS, Regeneron, TScan, Synthekine, Atara, Jasper, Bayer: Consultancy. Levine: Incyte: Consultancy, Research Funding; Viracor: Patents & Royalties: GVHD biomarker patent with royalties from Viracor; Mesoblast: Consultancy, Research Funding; Equillium Bio: Membership on an entity's Board of Directors or advisory committees; X4 Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Talaris Therapeutics: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Omeros: Membership on an entity's Board of Directors or advisory committees; Symbio: Membership on an entity's Board of Directors or advisory committees; Biogen: Research Funding; Kamada: Research Funding. Ferrara: Eurofins Viracor: Consultancy, Other: Royalties. Chen: Incyte: Consultancy; Gamida: Consultancy.

Background: The prognosis for patients (pts) with relapsed T-ALL and T-LL is dismal; the primary goal of T-ALL/T-LL treatment is to prevent relapse. AALL1231 was a COG phase 3 clinical trial that randomized children and young adults (age 1-30 years) to a modified augmented BFM (aBFM) backbone +/- the proteasome inhibitor bortezomib during induction and delayed intensification (DI) (1.3mg/m2 x 4 doses per block). Bortezomib was tested in frontline therapy based on strong preclinical data and data in relapse on COG AALL07P1. Pts were stratified as standard (SR), intermediate (IR), or very high risk (VHR), primarily based on disease response: morphologic and minimal residual disease (MRD) at end induction and end consolidation (T-ALL) and radiographic response (T-LL). To eliminate cranial radiation (CXRT) in all pts, (except VHR: Day 29 M3 marrow or EOC MRD >0.1% or pts with overt CNS leukemia at diagnosis, CNS3), the aBFM backbone was modified to use dexamethasone (dex) as the sole corticosteroid and an extra pegaspargase dose was added in both induction and DI, following the MRC strategy. IR pts received a second interim maintenance (IM) phase (one Capizzi MTX; one HD-MTX). Following consolidation, VHR pts received 3 BFM high-risk intensification blocks in lieu of IM. Results: AALL1231 accrued 847 patients (824 eligible and evaluable) of 1400 anticipated from 2014 until early closure in 2017 when COG AALL0434 established that nelarabine (NEL) improved DFS in T-ALL (AALL1231 did not include NEL). The 3-year EFS for Arm A (no bortezomib) vs Arm B (bortezomib) were 81.7±2.4% and 85.1±2.2 % (HR=0.782, p=0.074) (3/31/20 data cut-off; see Table 1 for additional outcomes). SR and IR pts, who account for 95% of pts, had significantly improved EFS on Arm B as compared with Arm A. Yet, VHR patients had improved EFS on Arm A. Patients with T-LL had improved EFS and OS with bortezomib: 3-year EFS (76.5±5.9% vs 88.3±4.5%; p = 0.01); 3-year OS (78.0±5.8% vs 89.5±4.2%, p = 0.007). A similar improvement in EFS and OS was not seen in T-ALL; however, with longer follow-up this may change. No excess toxicity was seen on Arm B. A dex-based Induction did result in lower MRD rates; more T-ALL pts on AALL1231 had Day 29 MRD <0.1% as compared with AALL0434 which used a prednisone-based Induction (AALL1231 Arm A: 69.6%; Arm B: 72.2%; AALL0434: 64.6%; p = 0.02). However, this did not translate into improved survival. Indeed OS, but not EFS was worse on AALL1231 than AALL0434. On-going analyses are investigating the increased mortality on AALL1231, but preliminary analyses suggest a combination of increased toxic deaths and overall poor outcome in the VHR group. On AALL0434, 90.8% of T-ALL pts received CXRT. On AALL1231, 9.5% of subjects were scheduled to receive CXRT (CNS3 T-ALL/T-LL: 5.7%; VHR T-ALL: 4.1%). A comparison of AALL0434 pts that received CXRT with similar AALL1231 pts not receiving CXRT on AALL1231 demonstrated similar EFS (p = 0.14) and OS (p = 0.42) (Table 2). CNS relapse rates were higher in these pts on AALL1231 (4.5%) as compared with AALL0434 (1.7%), but overall relapse rates were the same (6.5% vs 6.4%). Notably the benefit of NEL in AALL0434 was due to reduction of CNS relapses. 128 AALL1231 pts came off protocol therapy after the study was closed for physician or patient/parent choice. Data collection is underway to understand the reasons for removal, including if it was to receive NEL. Conclusions: Outcomes for SR and IR pts with T-ALL and T-LL treated with bortezomib were excellent despite the elimination of prophylactic CXRT. Bortezomib significantly improved 3-year EFS for these groups, comprising ~95% of pts. Outcomes for VHR pts were dismal and worse on the bortezomib arm. T-LL pts had significantly improved EFS and OS with bortezomib on the AALL1231 backbone. This is the first trial to demonstrate an OS benefit for de novo pediatric T-LL with a new agent; however, longer follow-up is needed. Therapy intensification allowed elimination of CXRT in the majority of pts without excessive relapse. These results should be interpreted cautiously as the 3-yr OS on AALL1231 was inferior to AALL0434. Nevertheless, incorporating bortezomib into standard therapy for de novo T-LL appears advantageous. Future COG T-ALL/T-LLy trials will build on the positive findings from AALL0434 and AALL1231, balancing intensity while mitigating toxicity to maintain high cure rates without routine cranial radiation. (MLL, SPH, EAR contributed equally) Disclosures Teachey: Amgen: Consultancy; Janssen: Consultancy; La Roche: Consultancy; Sobi: Consultancy. Dunsmore:Dexcom: Current equity holder in publicly-traded company. Galardy:Abbott: Current equity holder in publicly-traded company; Abbvie: Current equity holder in publicly-traded company. Harker-Murray:Regerenon Pharmaceuticals: Consultancy. Hermiston:Sobi: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Shimano:Novartis: Research Funding; Daiichi Sankyo: Research Funding; Pfizer: Research Funding; Dova Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. McKay:Immunogen: Current Employment. Bollard:Mana Therapeutics: Other: IP. Loh:Medisix Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pfizer: Other: Institutional Research Funding. Hunger:Novartis: Consultancy; Amgen Inc.: Current equity holder in publicly-traded company, Honoraria. Raetz:Celgene/BMS: Other; Pfizer: Research Funding. OffLabel Disclosure: Bortezomib for the treatment of acute lymphoblastic leukemia under an IND

Systemic glucocorticoids are the principal treatment for acute graft-versus-host disease (GVHD), which remains the major cause of non-relapse mortality (NRM) after allogeneic hematopoietic cell transplantation (HCT). However, there are no validated biomarkers that measure a patient's response to glucocorticoid therapy, and thus response is evaluated by the change in clinical symptom severity. A major weakness in the predictive power of clinical responses is that changes to all organs are weighted equally even though the major driver of NRM is irreversible damage to the crypts of the GI tract. Recent studies from the Mount Sinai Acute GVHD International Consortium (MAGIC) have validated an algorithm probability (MAP) that combines serum concentrations of two biomarkers of GVHD (REG3α and ST2) to generate an estimated probability of 6 month NRM for individual patients. The MAP has been considered a "liquid biopsy" that estimates the damage caused by GVHD to crypts throughout the lower GI tract (Hartwell et al., JCI Insight, 2017; Major-Monfried et al., Blood, 2018). We hypothesized that the change in MAP between start of treatment and 28 days later could serve as a response biomarker for GVHD and might compare favorably to the change in clinical symptoms that measures response to GVHD treatment, which is widely used as a surrogate for long term survival and is the primary endpoint in most GVHD treatment trials (Martin et al., BBMT, 2009; MacMillan et al., Blood, 2010). We prospectively collected serum samples and clinical staging from 368 sequential HCT patients who received systemic treatment for acute GVHD in one of 20 MAGIC centers between January 2016 and February 2018. We measured the serum concentrations of REG3α and ST2 before and after systemic therapy for acute GVHD and computed MAPs, the changes in MAPs, and clinical responses for each patient. MAPs of patients who experienced 6 month NRM showed significantly greater increases than MAPs of patients who survived (p=0.0004). In patients whose MAPs at the start of treatment were low (Ann Arbor 1, MAP < 0.141) or intermediate (Ann Arbor 2, 0.141 ≤ MAP ≤ 0.290), 6 month NRM clustered among those who had the greatest increases in MAP after 28 days (Fig 1A,B). In patients with high MAPs at the start of treatment (Ann Arbor 3, MAP > 0.290), those who survived tended to have the largest decreases in MAP (Fig 1C). These changes in MAP suggested crossing a single threshold could predict risk of mortality. We found that patients whose MAPs rose above a threshold MAP of 0.290 (5% of Ann Arbor 1, 27% of Ann Arbor 2) had significantly worse survival compared to those who remained below it, whereas the large number patients with initially high MAPs that remained above the threshold (66% of Ann Arbor 3) had a large increases in mortality (Fig 2). When measured at day 28, the MAP was significantly more accurate in predicting NRM than the gold standard of the clinical response, with areas under the receiver operating characteristic curve (AUC) of 0.86 and 0.70, respectively (p<0.0001). An algorithm that combined clinical response with biomarkers generated the same AUC as the MAP alone (0.83 v 0.86, p = NS). We next tested whether the same MAP threshold of 0.290 could predict risk within clinical response subsets. A significant minority (10%) of clinical responders had high MAPs and experienced three-fold greater NRM than those with low MAPs (40% v 12%, p<0.0001) whereas the majority (57%) of non-responders had low MAPs and experienced almost three-fold lower NRM than those with high MAPs (24% v 65%, p<0.0001) (Fig 3). Thus the MAP provides important prognostic information over and above the change in clinical symptoms, further stratifying both responders and non-responders at four weeks of treatment. The MAP threshold classified patients both with and without significant lower GI symptoms because the MAP is a more specific measure of irreversible cryptic damage in patients with copious diarrhea and more sensitive in patients with less than 0.5 liters of daily diarrhea (Fig 4). We conclude that the MAP is, to our knowledge, the first validated laboratory test to serve as response biomarker for the treatment for acute GVHD and a more accurate predictor of survival than clinical response after four weeks of treatment. The MAP may serve as a novel endpoint and an important complement to changes in clinical symptom severity in future trials of GVHD treatment. Disclosures Srinagesh: National Institutes of Health: Research Funding. Ozbek:Viracor: Patents & Royalties: Biomarker Patent. Ayuk:Novartis: Honoraria, Other: Advisory Board, Research Funding. Aziz:Doris Duke Charitable Foundation: Research Funding. Defilipp:Incyte: Research Funding. Grupp:Novartis: Consultancy, Research Funding; Roche: Consultancy; GSK: Consultancy; CBMG: Consultancy; Novartis: Research Funding; Kite: Research Funding; Servier: Research Funding; Jazz: Other: study steering committees or scientific advisory boards; Adaptimmune: Other: study steering committees or scientific advisory boards; Cure Genetics: Consultancy; Humanigen: Consultancy. Hexner:novartis: Research Funding. Kitko:Mallinckrodt: Honoraria; Novartis: Consultancy, Honoraria. Mielke:EBMT/EHA: Other: Travel support; ISCT: Other: Travel support; Miltenyi: Consultancy, Honoraria, Other: Travel and speakers fee (via institution), Speakers Bureau; Jazz Pharma: Honoraria, Other: Travel support, Speakers Bureau; IACH: Other: Travel support; Kiadis Pharma: Consultancy, Honoraria, Other: Travel support (via institution), Speakers Bureau; DGHO: Other: Travel support; Bellicum: Consultancy, Honoraria, Other: Travel (via institution); GILEAD: Consultancy, Honoraria, Other: travel (via institution), Speakers Bureau; Celgene: Honoraria, Other: Travel support (via institution), Speakers Bureau. Merli:Sobi: Consultancy; Amgen: Honoraria; Novartis: Honoraria; Bellicum: Consultancy. Pulsipher:Amgen: Other: Lecture; Miltenyi: Research Funding; Bellicum: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Other: Education for employees; CSL Behring: Membership on an entity's Board of Directors or advisory committees; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Medac: Honoraria. Qayed:Bristol-Myers Squibb: Honoraria. Reshef:Pfizer: Consultancy; Magenta: Consultancy; Kite: Consultancy, Research Funding; Atara: Consultancy, Research Funding; BMS: Consultancy; Pharmacyclics: Consultancy, Research Funding; Incyte: Consultancy, Research Funding; Celgene: Research Funding; Shire: Research Funding. Levine:Incyte: Consultancy, Research Funding; Biogen: Other: non-financial support; Viracor: Patents & Royalties: biomarker patent; Ironwood: Honoraria; bluebird bio: Consultancy; National Cancer Institute: Research Funding; Novartis: Honoraria; Kamada: Research Funding. Ferrara:National Institutes of Health: Research Funding; ViraCor: Consultancy; Incyte: Consultancy; Kamada: Consultancy; Mallinckrodt: Consultancy; Enlivex: Consultancy; Xenikos: Consultancy; CSL Behring: Consultancy.

Abstract Relapse of malignancy and lethal graft versus host disease (GVHD) are the principal causes of failure of allogeneic hematopoietic cell transplant (HCT). Recently we have shown that at seven days after HCT an algorithm using two serum biomarkers (ST2 and REG3α) can predict severe GVHD (Hartwell et al. JCI Insight 2017). We determined whether serial testing (in the first month following HCT) of patients with low probability biomarkers would improve the predictive accuracy of the algorithm and identify patients with different risks of relapse and lethal GVHD. Patients who received an HCT at 18 centers in the Mount Sinai Acute GVHD International Consortium (MAGIC) for hematologic malignancy and who supplied three blood samples were divided into a training set and validation set with equal numbers of lethal GVHD events, which was defined as death from GVHD or infection during treatment for GVHD. Patients in the training set (n=702) underwent HCT from January 1, 2006 until June 30, 2015, whereas patients in the validation set (n=906) underwent HCT from July 1, 2015 to May 1, 2017. Serum samples were analyzed using the previously published algorithm of two biomarkers up to three times (day 7, day 14, day 28 or GVHD onset, if onset occurred within the first 28 days). The algorithm generates a predicted probability of lethal GVHD between 0 and 1 for each patient. Patients were categorized as either low probability (LP) or high probability (HP) for lethal GVHD. HP thresholds of 0.20 and 0.16 were used to classify patients with and without GVHD symptoms, respectively (once categorized as HP, patients remained in that category and were not retested). All results were similar between training and validation sets, and we present here the validation set results. Serial testing identified 28% of patients as HP with a three-fold greater cumulative incidence of lethal GVHD at one year (13% vs 4%, p<0.001, Figure 1). Relapse rates were the same in both probability groups, and thus LP patients experienced significantly better relapse free survival (RFS) (69% vs 53%, p<0.001). As expected, significantly fewer LP patients experienced severe GVHD at onset (as measured by Minnesota risk), maximum grade III/IV GVHD, or steroid resistant GVHD by day 180 after HCT (Figure 2, p<0.001 for all three parameters). To measure the accuracy of prediction, at each timepoint we calculated the area under the curve (AUC) of receiver operating characteristic curves; the AUC increased significantly with each subsequent evaluation, from 0.59 at one timepoint (dotted line) to 0.74 at the third timepoint (solid line) (p<0.001), with a final sensitivity of 65% and specificity of 74% (Figure 3A). Early development of GVHD (by day 28) is a risk factor for lethal GVHD. Therefore, we next plotted RFS (dashed line), relapse (solid line), and lethal GVHD (dotted line) rates in patients who developed GVHD by day 28. 25% of patients with GVHD were categorized as HP and had a cumulative incidence of lethal GVHD more than four times higher (28%) than that of relapse (6%); however the risks were reversed for the 75% of patients who were LP, where relapse (15%) occurred twice as often as lethal GVHD (7%) (Figure 3B). In patients who did not develop GVHD in the first month, this reversal of risks was even more dramatic. Approximately half (53%) of the entire validation cohort did not develop GVHD by day 28 and was LP at all three evaluations. These patients had an exceptionally low risk of lethal GVHD and thus they relapsed (25%) much more often than they died from GVHD (3%). When malignancies were classified according to risk for relapse by the disease risk index (DRI) (Figure 3C), the probability of relapse was three fold higher than lethal GVHD in malignancies with a low DRI (12%), six fold higher for intermediate DRI (20%), and eleven fold higher for high/very high DRI (33%). We conclude that a serial monitoring strategy using GVHD biomarkers for one month after HCT is able to identify two groups of patients with very different risks of lethal GVHD and relapse. For these patients, the intensity of immunosuppression after day 28 could be tailored according to the probabilities of developing lethal GVHD and relapse in the context of clinical trials. Disclosures Aziz: Doris Duke Charitable Foundation: Research Funding. Ayuk:Therakos (Mallinckrodt): Honoraria; Novartis: Honoraria; Celgene: Consultancy; Gilead: Consultancy. Chen:REGiMMUNE: Consultancy; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; Magenta Therapeutics: Consultancy; Takeda Pharmaceuticals: Consultancy. Merli:Neovii Biotech: Honoraria; AMGEN: Honoraria. Roesler:Sanofi: Other: Travel, Accommodations, Expenses; Amgen: Equity Ownership; Jazz Pharmaceuticals: Other: Travel, Accommodations, Expenses; Immunomedics: Equity Ownership; Biogen: Equity Ownership; Merck: Consultancy; Pfizer: Consultancy. Kitko:Novartis: Consultancy, Honoraria; Mallinckrodt: Honoraria, Other: Travel, Accommodations, Expenses. Qayed:Novartis: Consultancy. Wölfl:Bristol-myers Squibb: Equity Ownership; Novartis: Equity Ownership; Taheda: Equity Ownership; Juno: Equity Ownership; Neovii: Other: Travel, Accommodations, Expenses. Mielke:Celgene: Speakers Bureau; DGHO: Speakers Bureau; EHA: Speakers Bureau; Kiadis Pharma: Speakers Bureau; Miltenyi: Speakers Bureau. Wudhikarn:Takeda Oncology: Other: Travel, Accommodations, Expenses. Nakamura:Celgene: Honoraria; Molmed: Honoraria; Merck: Consultancy; Pharmacyclics: Consultancy; Atara: Consultancy; Jazz Pharmaceuticals: Consultancy. Pulsipher:CSL Behring: Consultancy; Novartis: Consultancy, Honoraria, Speakers Bureau; Adaptive Biotech: Consultancy, Research Funding; Amgen: Honoraria. Reshef:Pfizer: Consultancy; Atara Biotherapeutics: Consultancy; Kite Pharma: Consultancy; Takeda Pharmaceuticals: Consultancy; Bristol-Myers Squibb: Consultancy; Incyte: Consultancy. Levine:Therakos: Consultancy; Novartis: Consultancy; Bluebird: Consultancy; Incyte: Consultancy; Kamada: Research Funding; Viracor: Patents & Royalties. Ferrara:Incyte: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses; Xenikos: Consultancy, Other: Travel, Accommodations, Expenses; Kamada: Consultancy, Research Funding; Viracor: Consultancy, Patents & Royalties.