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Background Hispanic patients continue to be underrepresented in clinical trials. To better understand the factors that impact clinical trial participation, we surveyed patients with NHL receiving care at an academic institution on their perspectives on clinical trials, barriers to care, and helpful aids to encourage clinical trial participation. Here we report the findings of the Hispanic patients and non-Hispanic white patients; accrual is ongoing for other cohorts of patients. Methods Consecutive patients ≥ 18 years old with histologically confirmed NHL who received care at MD Anderson Cancer Center in the Texas Medical Center in Houston, Texas were invited to participate regardless of treatment status. A self-administered questionnaire was used to assess patient sociodemographic factors, perceptions and willingness to participate in different clinical trial scenarios as well as participant perceived barriers to care and facilitators of trial participation. The questionnaire included a total of 53 items with an additional 13 demographic items. The questionnaire was available in English and Spanish. Results Of the 1204 patients invited, 316 consented to participate and 285 ultimately completed the survey (participation rate 23.7%). Among the total participants, this cohort included 100 self-identified Hispanic (H) participants and 103 non-Hispanic white (NHW) participants diagnosed with NHL who completed the survey and were included here. The histology of our cohort included Follicular Lymphoma (FL) [35.6%]; Diffuse Large B-cell lymphoma (DLBCL) [18.2%], Mantle cell lymphoma (MCL) [18.7%], T-cell Lymphoma (TCL) [9.4%] Marginal Zone Lymphoma [7.8%]. Compared with NHW participants, Hispanic patients were younger (Median age of 60 vs 66 years), less likely to be male (H 54% vs NHW 66%), less likely to commute more than an hour away from the doctor's office (54% vs 71.8%), had lower household income (income > $100,000 was 32% vs 41.7%) and less likely to have a bachelors' degree or higher (38% vs 50.5%). There were similar prevalence histologies such as DLBCL (H 20% vs NHW 16.5%) and FL (H 36% vs NHW 35%) compared to rarer histologies such as MCL (H 11.1% vs NHW 26.2%) and MZL (H 12% vs NHW 3.9% ) which had disproportional prevalences. Hispanic patients were less likely to have previously participated in a clinical trial (28% vs 51.5%) and less likely to have discussed clinical trials as an option (49% vs 70.9%). A majority of Hispanic (81.0%) and NHW (92.3%) respondents stated that they understood what was meant by a “clinical research study” or “clinical trial” somewhat well or very well. Less than half of Hispanic participants (38.0%) and NHW participants (48.5%) reported being very willing to participate in a cancer clinical trial as their initial course of treatment. The most prevalent concern of both Hispanic and NHW participants respectively was the cost of a clinical trial (34.0%, 22.3%). Other top concerns included distance to the treatment center (32.0%, 13.6%) and frequency of contact with the care team (26.0%, 14.6%). Participants identified access to written materials (69.0%, 60.2%), insurance aid (65.0%, 68.0%), and access to videos (64.0%, 51.5%) as extremely helpful resources that could reduce the burden of participating in a clinical trial. Participants identified that it was most important that a treatment may improve their quality of life by decreasing pain level, increasing activity level, or other symptoms (76.0%, 91.3%). Conclusions Although most Hispanic and NHW participants reported a very good understanding of clinical trials and similar facilitators/barriers for trial participation, Hispanic patients were less likely to have discussed trials as an option with their care teams and less likely to have previously participated in a trial. Evidence-based interventions to address various barriers to clinical trials exist but data on their effectiveness and application is limited. Implementing strategically designed evidence-based interventions to address identified barriers and facilitators will be necessary to improve participation in lymphoma clinical trials.

Introduction: Treatment for R/R MCL has evolved with the use of cBTKi monotherapy. Previously, we reported differences in RW time to next treatment (rwTTNT) and overall survival (rwOS) among patients (pts) treated with ibrutinib (ibr), acalabrutinib (acala), and zanubrutinib (zanu), but reasons for the differences were unknown (Phillips et al. EHA 2024). Our objectives were to re-evaluate trends in rwTTNT and rwOS; assess treatment patterns of cBTKis, including switching; describe reasons for cBTKi discontinuation; and compare RW effectiveness of ibr, acala, and zanu monotherapy. Methods: This retrospective cohort study included adult pts diagnosed with R/R MCL who initiated second-line (2L) or third-line (3L) first cBTKi treatment 01/2018-11/2023 and were followed until loss to follow-up or death using the US nationwide Flatiron Health EHR deidentified database. Patient characteristics and survival estimates based on Kaplan-Meier (KM) analyses were summarized. Adjusted analysis using a multivariate Cox model was applied to assess rwTTNT and rwOS. Key model variables were age, sex, POD24 (2L start ≤24 mo from first-line start), and number of prior lines of therapy. Reasons for discontinuation were abstracted from documentation in notes and included non-mutually exclusive categories. Results: This study included 698 pts who received cBTKi monotherapy in 2L or 3L for MCL. The median age at cBTKi start was 73 (range, 34-85 yrs); the majority of pts were male (74%) and White (White 78%, Black 3.2%, Asian 1.3%, Other Race 7.6%, Unknown 10%) and non-Hispanic/Latino (non-Hispanic/Latino 74%, Hispanic/Latino 6.0%, Unknown 20%). Patients varied by socioeconomic status (Yost index 1 [12%], 2 [16%], 3 [19%], 4 [24%], 5 [19%], Unknown [10%]). Patients also varied by baseline ECOG performance status, Ki67, comorbidities, and LDH. Most pts had stage III/IV at diagnosis (75%). Among pts who received a cBTKi at 2L or 3L index therapy, 135 received zanu (2L [79%], 3L [21%]), 342 received acala (2L [76%], 3L [24%]), and 221 received ibr (2L [75%], 3L [25%]). Follow-up time (median [IQR]) from start of 2L/3L for each cBTKi were zanu 15 mo (10, 25), acala 36 mo (20, 52), and ibr 57 mo (35, 67). Among the overall 2L/3L cBTKi monotherapy cohort, median rwTTNT was 11.5 mo (95% CI 10.0, 13.5) and median rwOS was 30.4 mo (24.7, 36.1). For each cBTKi therapy in unadjusted KM analyses, median rwTTNT for zanu was 16.8 mo (95% CI 11.1, 23.2), acala 11.9 mo (9.2, 14.6), and ibr 9.8 mo (7.6, 13.1); median rwOS was 28.8 for zanu (95% CI 23.7, not reached), acala 29.2 mo (22.9, 36.5), and ibr 29.3 mo (21.2, 39.1). Adjusted multivariate model showed a trend of longer rwTTNT with zanu compared to ibr (HR 0.76 [95% CI 0.57, 1.01]; P=.06) and acala (0.88 [0.67, 1.16]; P=.40), and significantly longer rwOS for zanu compared to ibr (0.67 [0.46, 0.98]; P=.04) but a nonsignificant trend in rwOS favoring zanu compared to acala (0.73 [0.51, 1.05]; P=.09). Forty-seven pts (6.7%) who received cBTKi monotherapy in 2L or 3L switched to another cBTKi; 31 (4.4%) switched from ibr to acala or zanu, 12 (1.7%) from acala to zanu, and <5 (0.1%) from zanu to acala. Reasons for discontinuation (~60% documented in cohort) varied by cBTKi monotherapy use. The most common documented reasons for discontinuation were disease progression (30% overall; zanu [24%], acala [35%], ibr [26%]) and toxicity (11% overall; zanu [7%], acala [10%], ibr [17%]). Among pts who switched from one cBTKi to another, the most documented reason for discontinuation was toxicity for ibr to acala or zanu (61%) and for acala to zanu (58%). Other reasons included financial (1%), non-cancer-related medical issue (4%), cancer-related symptoms not due to therapy (2%), and pt request (1%). Conclusions: Among RW pts with R/R MCL who received cBTKi monotherapy, zanu had a longer rwOS compared to ibr, and a trend of longer rwTTNT and rwOS compared to acala. Reasons for discontinuation were most commonly disease progression and toxicity. Among pts who switched cBTKis, the most common reason for switching was toxicity, which provides a broader scope of reasons for differences in rwTTNT that are not exclusive to disease progression.

Introduction: Given the major treatment advancements in relapsed/refractory multiple myeloma (RRMM) such as bispecific antibodies (BsAbs), understanding patient and healthcare provider (HCP) decision-making perspectives is crucial. This study investigated barriers to adopting resource-intensive novel therapies, unmet needs in access to care, and treatment decision priorities in one of the largest surveys of RRMM patients and HCPs. Methods: This prospective study was conducted from March to June 2024 using 30-minute web-based quantitative surveys fielded in 2269 participants (1301 RRMM patients and 968 HCPs) across 7 countries (US, UK, France, Germany, Italy, Spain, Japan). The survey collected data on pre-defined patient subgroups (line of treatment, ages <45, 46-65, 65+]) and in HCP subgroups (care settings: academic, community [non-Center of Excellence [COE]). Data were analyzed using descriptive statistics and chi-square tests. Results: Two themes that emerged from the findings were: 1) discrepancies in treatment considerations between patients and HCPs, and 2) Familiarity with and considerations around BsAbs among patients Discrepancies in HCP and Patient considerations HCPs and patients prioritized different considerations during treatment decision-making, particularly related to the importance of treatment related adverse events (TRAEs). 3L+ patients equally prioritized disease control and minimizing TRAEs (49% and 49%); HCPs prioritized disease control more often than minimizing TRAEs (59% and 40% for 3L+ patients). Patients considered many TRAEs extremely challenging to manage, whereas HCPs were less likely to do so (patients vs HCPs: bone-related AEs: 64% vs 39%, p<0.001; hypertension: 54% vs 28%, p<0.001; cholesterol: 53% vs 21%, p<0.001; skin-related AEs: 49% vs 30%, p<0.001). Limiting TRAEs was a concern particularly among patients over 65 (52%, p<0.001) and those with comorbidities (52%, p<0.001). Limiting costs and financial challenges (3L+ patients: 33% vs HCPs: 13%, p<0.001) and avoiding compromising the potential to receive treatment options in later lines (3L+ patients: 25% vs HCPs:14%, p<0.001) were other considerations patients prioritized more than HCPs. HCPs prioritized limiting side effects 9% more in 3L settings compared to 2L. Discrepancies in decision-making in 2L setting included a desire to limit treatment-related logistical burden (patients: 35% vs HCP: 17%, p<0.001), limit challenges for care partners (25% vs 13%, p<0.001), and ensure treatment without referral (24% vs 16%, p=0.001). Compared to their older counterparts, younger patients (<45 y v ≥45y) prioritized convenient treatment administration (39% vs 29%, p=0.024) and avoiding referrals to other institutions (32% vs 22%, p<0.001). Perspectives on treatment considerations specific to BsAbs Among 3L+ patients, most have not heard of BsAbs, or have heard but were unfamiliar with the option. A small proportion of 3L+ patients recalled their HCPs suggesting BsAbs as a treatment option (14%) although most patients decided to receive BsAbs treatment when it was offered (71%). Among patients on BsAb treatment, patients most often cited clinical reasons for going on BsAbs (i.e., remission, symptom relief, and likelihood of greater longevity). Among non-clinical reasons, lower time commitment and lower likelihood of negative financial impact compared with other treatments were also common. Notably, 36% of HCPs reported low confidence in identifying RRMM patients eligible for BsAbs. Compared with academic HCPs (32%), more community/non-COE HCPs (42% p=0.018) reported low confidence. Conclusions: HCPs and patients have different priorities during treatment decision-making, particularly regarding the importance of minimizing TRAE and in prioritizing efficacy and managing logistical burdens in later treatment lines. Among novel treatments, BsAbs are not frequently recalled by patients as a treatment option provided by HCPs. HCPs, especially in community settings, are often uncertain about identifying eligible patients for BsAbs, indicating a need for greater educational resources for HCPs. Increasing patient awareness of available treatments, HCP understanding of novel treatments, and fostering dialogue on patient priorities can increase the likelihood of informed, personalized shared decision-making, and optimize evidence-based patient outcomes.

Background: The FDA package inserts for all approved chimeric antigen receptor T-cell (CAR-T) therapies state that patients should universally refrain from driving for 8 weeks following infusion. However, there are no clear data to support this recommendation, particularly in multiple myeloma (MM) which all CAR-T therapies use 4-1BB as opposed to CD28 costimulatory domains. Specifically, no seizures were reported in the KarMMa, KarMMa-3, CARTITUDE-1, or CARTITUDE-4 trials. Because patients typically return to their referring oncologists after Day (D) +28 following CAR-T infusion, an additional month of driving restrictions can create confusion for referring oncologists, impose significant burdens for patients and caregivers, and potentially even affect the choice of MM therapy for patients living in remote areas. Methods: We conducted a two-part study within the US MM Immunotherapy Consortium. Firstly, we analyzed data from commercial idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel) recipients (leukapheresis cutoff December 31, 2023) to identify the prevalence of CRS, ICANS, or death between Weeks 5-8 (D+29 to D+56) following CAR-T (Day 0). Patients with index hospital stays lasting over 4 weeks and patients with <8 weeks of post-CAR-T follow-up were excluded. Secondly, we surveyed Consortium members about the prevalence of impaired driving risk (defined as “anything that could impair a patient's ability to drive safely, e.g. seizures, altered mental status, blindness, etc.”) and used 1-5 Likert scales to gauge the perceived importance of driving restrictions (assuming no FDA guidance existed) during Weeks 0-4 vs 5-8. This anonymous IRB-exempted survey was distributed via email to 63 CAR-T-prescribing physicians within the Consortium. Results: Of 553 analyzed patients, 41% (n=224) had received cilta-cel and 59% (n=329) ide-cel. The median age was 64 (IQR 58-70), 42% (n=231) were female, 78% White (n=434), 13% (n=72) Black, and 9% (n=51) Hispanic. ECOG PS at infusion was ≥2 in 11% (n=63) of patients, and 5% (n=28) had had previous CNS co-morbidities such as prior strokes. One patient (0.2%) developed Grade 2 CRS during Weeks 5-8 (onset D+47, resolution one day later); no patients had de novo ICANS after D+28. There were 16 cases of non-ICANS neurotoxicity (including 2 cases of Parkinsonism) diagnosed a median of 24 days after CAR-T (range: 17-147 days), of which 3 cases (all non-Parkinsonian) were first diagnosed during Weeks 5-8. There were 10 deaths (2%) during Weeks 5-8, one due to infection and the remainder from progressive MM. The survey was completed by 45 oncologists (71% response rate), 41 of whom had managed both >5 ide-cel and >5 cilta-cel recipients. Regarding impaired driving during Weeks 0-4, 20% of physicians felt this was never a risk, 36% a risk for 1-2% of patients, 29% a risk for 3-10% of patients, and 16% a risk for >10% of patients. The distribution was significantly different (p < 0.01) for Weeks 5-8: 49% never a risk, 36% a risk for 1-2% of patients, 16% a risk for 3-10% of patients, while no respondents felt this remained a risk for >10% of patients. For Weeks 0-4, 73% agreed that patients should be advised not to drive while 9% disagreed. In contrast, for Weeks 5-8, 14% of physicians agreed with driving restrictions while 78% disagreed (p < 0.01 compared to Weeks 0-4). Discussion: Our two-part study demonstrates that driving restrictions following Week 4 after CAR-T therapy in MM may not be required. The incidence of de novo CRS or any-type neurotoxicity being diagnosed during Weeks 5-8 was <1%, and - if such toxicities developed - patients and physicians could be expected to set appropriate restrictions at that juncture. While 73% of CAR-T-prescribing oncologists agreed that patients should refrain from driving during Weeks 0-4, 78% disagreed with this recommendation during Weeks 5-8. These findings complement other real-world studies (Wesson, Dima, et al, TCT 2024; Ahmed et al, Blood Advances 2024) reporting the rarity of CRS and ICANS after the first month in both MM and lymphoma. Our study is limited by a lack of patient-reported data, which was done intentionally to avoid asking patients about activities undertaken against medical advice. Nevertheless, we believe that narrowing universal driving restrictions to Weeks 0-4 following CAR-T therapy would constitute an evidence-based modification to the package inserts for ide-cel and cilta-cel.

BACKGROUND Several studies have highlighted the poor clinical outcomes observed among patients with relapsed/refractory multiple myeloma (MM), particularly those with triple-class refractory (TCR; refractory to at least one protease inhibitor [PI], one immunomodulatory drug [IMiD], and one anti-CD38 monoclonal antibody [mAb]) disease. The aim of this study was to describe the longitudinal changes in quality of life (QOL) and other patient-reported outcomes (PROs) among TCR MM patients who initiated a new line of therapy in real-world clinical practice. METHODS A prospective, multi-site observational study was conducted through the Mayo Clinic system. Patients with TCR MM initiating a new line of therapy (defined as the index date) were followed for a 12-month observation period. For patients initiating a CAR-T therapy, PRO survey assessments were conducted at apheresis, lymphodepletion chemotherapy, and every month after T-cell infusion until Month 6. All other patients received a survey assessment before index and every month thereafter until Month 6. PRO measures included the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ-C30; including the Global Health Score [GHS]), the EORTC Multiple Myeloma Questionnaire (QLQ-MY20; including the Disease Symptoms [DS] domain score), the EORTC QLQ for Chemotherapy-Induced Peripheral Neuropathy (CIPN20), the EuroQoL-5 Dimensions (EQ-5D), the Patient Global Impression of Severity (PGIS), and the Patient Global Impression of Change (PGIC). PRO surveys were supplemented with retrospective chart reviews conducted at 3 months and 12 months following the index date to obtain clinical information. Descriptive data were reported at each timepoint separately for patients who received CAR-T and non-CAR-T index therapies. The study is ongoing and this abstract reflects all patient data collected as of May 2024. RESULTS This interim analysis included 77 patients (58% male, 95% White, mean age 66 years). The median time interval between becoming TCR and the index date was 5.6 months (interquartile range [IQR]: 1.8, 18.2). Most patients had an Eastern Cooperative Oncology Group (ECOG) score of 0 or 1 (48% and 45%, respectively) and were Revised International Staging System (R-ISS) I or II (27% and 36%, respectively); 42% of patients had high-risk cytogenetics and 14% had extramedullary disease. The median (IQR) number of prior treatment lines was 4 (4, 5). Forty-two patients initiated a CAR-T therapy as their index therapy (12 and 30 treated with ide-cel and cilta-cel, respectively); the remaining 35 patients predominantly initiated a treatment regimen containing an IMiD (51%), a PI (54%), an anti-CD38 antibody (40%), or an alkylating agent (37%). Among these non-CAR-T patients, common regimens used were pomalidomide + elotuzumab + corticosteroids (26%), carfilzomib + cyclophosphamide + corticosteroids (20%), and pomalidomide + carfilzomib + corticosteroids (17%). Among CAR-T patients, QOL generally remained stable from apheresis (mean GHS and EQ-5D VAS were 62.3 and 66.4, respectively) to lymphodepletion (61.2 and 65.9) to Month 6 (64.2 and 68.9). Disease symptoms improved (mean DS domain scores at apheresis, lymphodepletion, and Month 6 were 25.7, 24.1, and 20.1, respectively) though pain, specifically, plateaued/worsened (mean pain domain scores were 24.5, 32.1, and 32.6). Based on the PGIC, 76% of patients reported being “a little better” or “much better” as early as Month 1, which stabilized over time (75% at Month 6). Among non-CAR-T patients, QOL largely remained stable (GHS and EQ-5D VAS was 62.9 and 68.4, respectively, at baseline and 64.9 and 67.7 at Month 6), though disease symptoms, including pain, improved over time (DS was 28.0 at baseline and 22.8 at Month 6; pain was 40.8 at baseline and 28.1 at Month 6). Based on the PGIC, 30.7% of patients reported being “a little better” or “much better” at Month 1, which improved to 52.7% by Month 6. CONCLUSIONS In this interim analysis of an ongoing prospective observational study, baseline values suggest a significant QOL burden among TCR patients. QOL generally remained stable for both CAR-T and non-CAR-T patients over the first several months post-therapy with some select improvements in disease symptoms. However, the patients (particularly CAR-T patients) directly reported some holistic improvement based on the PGIC as early as Month 1.

Introduction: Therapeutic advancements for MM have led to improved patient survival, but notable differences in management exist. Novel treatment options are resource-intensive and require adequate patient awareness as well as consideration of patient preferences such that informed decision making is practiced. Despite this, detailed understanding of factors that impact patient decisions regarding healthcare choices, and potentially contribute to variability in healthcare utilization, are under-studied. Additionally, with improved survivorship, the medical, psychosocial, and financial burden of MM management needs to be better understood. Methods: An anonymous, online, 45-question English survey exploring demographics, social determinants of health, selected clinical characteristics, treatment preferences, and survivorship burden was distributed to MM patients within Mayo Clinic and to all International Myeloma Foundation (IMF) support groups. Descriptive statistics were utilized to document participant socio-demographic characteristics, selected treatment history, factors affecting their preferences, and MM survivorship burden. Results: A total of 2239 participants responded to the survey with 54% males, median age 68 years (range 21-95) and median age at MM diagnosis of 67 years. Non-Hispanic Whites (NHW) were the largest (89%) racial-ethnic group. Most participants (71%) had a college degree and 67% had Medicare or Medicaid as primary insurance. MM was diagnosed within 5 years in 58% and 73% were currently on MM treatment at the time of responding to the survey. Majority (76%) had never been on a clinical trial, 59% had received stem cell transplant, 8% had undergone CAR-T therapy and 8% had received Bispecific antibodies as part of their MM management. Majority (64%) preferred oral drugs while 19% preferred injections and 14% infusion therapy.17% had ≥4 healthcare visits per month for MM treatment, 91% used their personal vehicle as the mode of transport for these appointments and the median time to travel to the treatment facility was 30-minutes.Survey participants reported that >10 days of work were missed per year due to MM management among 15% of the patients and 9% of the caregivers, while 15% reported suffering job loss related to MM management. Top factors for treatment decisions were physician recommendations (92%), effectiveness of treatment option (88%), understanding of the treatment(74%), side effects (57%), and family/caregiver input (38%). Psychological challenges and financial strain were reported by 38% and 18% of the respondents, respectively. Increase in healthcare needs since MM diagnosis were reported by 48% and majority reported ongoing symptom burden including fatigue (78%), pain (53%) and neuropathy (60%). Furthermore, of the participants with these symptoms, 67% reported that their fatigue was not relieved by rest, 73% reported their pain to be moderate to severe, and 29% reported their neuropathy to be moderate to severe. Only 42% reported being fully active with the rest reporting varying degrees of functional inabilities. Nearly half (47%) of the participants reported lack of interest or enjoyment in activities they used to like prior to MM diagnosis, however majority (74%) still reported “good” or “excellent” quality of life. A small number of participants reported lack of support from family and friends (4%), lack of support from their healthcare team (3%), difficulty accessing healthcare due to financial hardship (7%) or difficulty accessing healthcare due to job commitments (3%). Conclusions: Decision-making for MM treatment is complex and there are several factors that affect patients behavior. Improved survival in MM is associated with significant survivorship and caregiver burden which can also affect the patient's treatment choices for subsequent therapy. These factors must be addressed systematically to achieve equitable healthcare utilization, shared decision making, and optimal clinical, psychosocial and financial wellbeing of patients with MM.

Introduction: Brexucabtagene autoleucel (brexu cel) is a CD19-targeted chimeric antigen receptor (CAR) T cell therapy approved for the treatment of adults with relapsed/refractory (R/R) acute lymphoblastic leukemia (ALL). Some patients (pts) proceed with a consolidative allogeneic hematopoietic cell transplant (HCT) after breux cel. We do not know which pts can safely avoid a consolidative HCT and its associated morbidity. Methods: We conducted a retrospective cohort study utilizing the Real-World Outcomes Collaborative of CAR-T in Adult ALL (ROCCA) dataset. ROCCA is a registry of brexu cel pts in 32 centers in North America. We defined complete remission (CR) as < 5% blasts in the bone marrow and no central nervous system (CNS) or extramedullary (EM) disease on or around D28 after brexu cel. We defined measurable residual disease negative (MRD-) CR as CR and no abnormal blasts in the bone marrow by multiparameter flow cytometry, quantitative polymerase chain reaction, ClonoSeq next generation sequencing (NGS), or other sequencing modalities with lower sensitivity. ClonoSeq NGS has a sensitivity of 10-6, while the other modalities have a sensitivity of at least 10-4. We defined progression free survival (PFS) as the time from CAR-T infusion to relapse or death, censored at the date of last follow-up. Statistical analyses were performed in R. Univariable Cox proportional hazards regression analyses were performed to determine the association of pre-specified variables with PFS. Variables known to be associated with CAR T outcomes in ALL were entered into a multivariable model. HCT was incorporated as a time-varying covariate. Results: During the study period, 281 pts were infused with brexu cel. We focused our analysis on 172 (61%) pts with confirmed MRD- CR on D28, as that is the group with clinical equipoise regarding maintenance strategy. 38 (22%) of those pts received a consolidative HCT, 30 (17%) received another form of maintenance therapy (primarily tyrosine kinase inhibitors for Philadelphia (Ph)-chromosome positive ALL), and 104 (60%) pts received no maintenance therapy. Pts who underwent consolidative HCT were younger (median age 35 years) than those who received no maintenance (42y) (p = 0.023) and were less likely to have a history of prior HCT (13% vs. 47%, p < 0.001). No differences were observed with respect to sex, TP53 mutation status, prior inotuzumab (ino) or blinatumomab (blina) exposure, disease burden prior to CAR, or development of any cytokine release syndrome (CRS) or any neurotoxicity with brexu cel. We performed univariable Cox proportional hazard regression analyses among pts in MRD- CR on D28, excluding those who received other maintenance therapy besides HCT; the median follow up was 8.1 months. In univariable analyses, D28 MRD negativity by ClonoSeq NGS (versus MRD negativity by other, less sensitive methods), development of CRS, and pre-CAR BM blasts < 5% were associated with improved PFS; prior ino exposure was negatively associated with PFS (p < 0.05). Age, sex, Ph status, TP53 status, and neurotoxicity development were not associated with PFS. In a multivariable model incorporating ALL type, prior HCT, prior ino/blina, and pre-CAR blast burden, as well as consolidative HCT as a time-varying covariate, only MRD negativity by ClonoSeq NGS with at least 10-6 sensitivity retained statistical significance (PFS hazard ratio 0.34, 95% confidence interval (CI) 0.15-0.77, p = 0.005). Pts who were MRD- by ClonoSeq NGS on D28 and received no maintenance had favorable 6m PFS of 76% (95% CI: 59-98%) and OS of 100% with a median follow up of 6.3 months in this subgroup. Among those in MRD- CR by NGS, HCT as a time-varying covariate was not associated with improved PFS (HR 0.6, p = 0.6). Conclusions: In a large real-world cohort of adults with R/R B-ALL infused with brexu cel, we identified practice variation regarding the use of consolidative HCT. Among brexu cel recipients who entered an MRD- CR, we identified ClonoSeq NGS MRD negativity as a novel predictive factor of favorable oncologic outcomes, even without a consolidative HCT. Similar results have been obtained in pediatric ALL patietns ftreated with 41BB-based tisagenleucleucel (Pulsipher et al., Blood Cancer Discovery 2022). Longer follow-up is needed to validate the safety of omitting consolidative HCT in such pts, but these results encourage the potential for definitive therapy with brexu cel when D28 ClonoSeq NGS MRD is negative.

Introduction: WM is a rare subtype of lymphoma, identified by the presence of IgM paraprotein, infiltration of clonal, small lymphoplasmacytic B cells in the bone marrow, and the somatic mutation, MYD88 L265P, which is observed in over 90% of WM patients. We previously identified two rare variants at 6p25.3 (EXOC2) and 14q32.13 (TCL1) that were significantly associated with an increased risk of WM/LPL (PMID: 30305637). However, the genetic basis for WM/LPL predisposition remains largely unknown. We conducted the largest WM/LPL GWAS to discover further germline susceptibility loci for WM/LPL. Methods: Our meta-analysis discovery set included 1,707 cases and 58,328 controls of European ancestry from the InterLymph Consortium, genotyped on a high-density SNP array and imputed to TOPMed, providing over 10 million common variants for association testing. Germline genetic loci with suggestive significance (P<5x10-6) were selected for replication in four independent sets (570 cases and 771,770 controls; UK Biobank, Copenhagen Hospital Biobank, FinnGen, Mayo Clinic), giving us a total of 2,277 WM/LPL cases and 831,098 controls. Conditional and sensitivity analyses were performed considering family history and sex. A transcriptome-wide association study (TWAS) was performed using FUSION with expression quantitative trait loci (eQTL) data from GTEx and Young Finns Study in whole blood, lymphocytes, and other tissues. Functional annotations were done using FUMA, F-MAGMA, FORGE, and OpenTarget. Colocalization was measured using CoLoC with whole blood gene expression data. Results & Discussion: We identified 11 germline genetic loci associated with WM/LPL risk that replicated and reached genome-wide significance (P< 5x10-8), including the two known loci on 6p25.3 and 14q32.13 and nine novel loci in the following regions: 6p25.3 (n=2 independent loci), 2q37.1, 9p13.2, 6p21.32, 10q23.31, 16q21, 1p31.1, and 15q15.1. Four of the discovered variants showed strong associations with WM/LPL [odds ratios (ORs) >10]. Enrichment was observed for enhancer and promoter elements in B-cells (FDR q < 0.01), and gene-based and colocalization analyses identified several potential biological pathways. Colocalization analyses show the intronic PAX5 risk variant on 9p (OR=1.5, P= 2.3x10-25) associated with whole blood eQTL expression of PAX5, which plays an essential role in regulating lymphoid progenitors to the B-lymphocyte lineage, as well as RP11-297B17.3 (RNA gene, antisense to PAX5). In addition, GWAS have shown this variant is in linkage disequilibrium (LD) with GWAS loci for CD20 on IgD+ CD38- B cell that represents a specific immunophenotype that helps identify and characterize B cells involved with WM and other similar conditions. The 2q37.1 (SP140) locus (OR=1.6, P=1.2x10-33) contains variants linked to chronic lymphocytic leukemia (CLL) and autoimmune diseases, including multiple sclerosis and Crohn's disease. This locus is important in chromatin-mediated gene regulation, suggesting a significant role in the immune system. The specific variant influences exon-skipping and potentially protein expression, altering the gene's function. The variants on 10q23.31 in FAS (OR=1.3, P=4.4x10-13) and 15q15.1 (OR=1.2, P=8.5x10-11) in BCL2 modifying factor (BMF), are in strong LD with known CLL susceptibility variants. The 15q variant is also linked with multiple lymphoid leukemia GW significant SNPs. Sex-specific analyses identified one novel locus at 20q13.33 associated with the expression of ZGPAT and UCKL1 in males (OR=1.9, P=9.5x10-10). TWAS identified associations with CRHR1 and CDKN2A; overexpression of both are shown to be associated with an increased risk of WM/LPL. Expression of CDKN2A has been linked to childhood acute lymphoblastic leukemia, while CRHR1 has been associated with breast cancer risk. Conclusions: Our study, the largest GWAS of WM to date, has identified 11 susceptibility loci, including two previously known and nine novel regions. The findings underscore the genetic complexity of WM, with the PAX5 and SP140 loci implicated in both chromatin-mediated gene regulation and immune system functions. These insights not only enhance our understanding of WM predisposition but also pave the way for future research focused on functional understanding of these loci, potentially leading to new therapeutic strategies.

Despite the high initial responses to chimeric antigen receptor T (CART) cell therapy, most patients relapse within the first 1-2 years. T cell quality influences the success of CART cell therapies greatly, and T cells from cancer patients are prone to transition into dysfunctional states, such as exhaustion or senescence. The role of exhaustion in CART cell failures has been studied extensively; however, the role of T cell senescence has remained mostly unexplored. In this study, we aimed to determine the development of CART cell senescence and its impact on CART therapeutic efficacy. First, we studied the development of CART cell senescence using an in vitro model to induce CART cell dysfunction. Here, we cyclically activated CD19-directed chimeric antigen receptor T (CART19) cells (either costimulated via 4-1BB (BBζ) or CD28 (28ζ)). Activation cycles are designed to mimic recurrent activation of CART cells to study the impact of T cell activation on CART cell fates throughout treatment. We added a rest time in between activation cycles to focus on senesced CART cell populations since, unlike exhaustion, senescence is irreversible even after rest. We examined CART immunophenotype, cell cycle regulators, transcriptomic profile, senescence marker gene expressions and T cell effector functions on days 0 (D0-T cell), 8 (D8-baseline CART), and 15 (D15-CART cell after one activation/rest cycles). Following an activation/rest cycle, T cell exhaustion markers CTLA4, LAG3, and PD1 returned to basal levels after an initial increase due to activation, while only TIM-3 levels remained elevated (BBζ: p=0.0090, 28ζ: p=0.0394). Increased TIM-3 expression is associated with T cell senescence, which prompted us to further investigate the development of a senescence phenotype. We found a prominent T cell senescence phenotype in BBζ compared to 28ζ, as evident by increased expression of p53 (BBζ: p=0.0248), p21 (BBζ: p=0.0483), CD27 (BBζ: p=0.0080), CD28 (BBζ: p=0.0327), uPAR (BBζ vs. 28ζ: p<0.0001), and KLRG1 (BBζ vs. 28ζ: p=0.0029) in recurrently activated-rested CART cells. Next, we evaluated the transcriptomic signature of recurrently activated-rested CART cells. Gene set enrichment analysis (GSEA) indicated enrichment of gene sets related to senescent T cells as well as senMayo, a novel gene set which is reported to be selectively enriched in senescing cells or tissues, in BBζ, but not in 28ζ, compared to T cell D0 or in BBζ D15 compared to 28ζ D15 (p=0.00014 and p=0.089, respectively). MYC-related gene sets were found to be significantly enriched in recurrently activated/rested BBζ and depleted in 28ζ (p<0.1). MYC expression is increased in BBζ (p= 0.0010) while decreased in 28ζ (p=0.0036) upon recurrent activation and is higher in BBζ (D8: p=0.0018, D15: p= 0.0022) compared to 28ζ at indicated time points by qPCR. Given these results, we induced senescence in CART cells using two alternative strategies: MYC-T58A activation (oncogene-induced senescence) and irradiation. Senescence induced by MYC-T58A overexpression ameliorated only BBζ killing (p=0.0057), whereas senescence induced by irradiation improved 28ζ killing (p= 0.0086), indicating versatile impact of senescence on treatment outcome diverse CART cell therapies. Finally, analysis with two independent patient data sets correlated the emergence of senescence with contradicting clinical outcomes to BBζ and 28ζ treatments. The presence of senescent 28ζ cells in the peripheral blood of 28ζ-treated patients was reported to be associated with complete response in the clinic in an independent analysis. In another cohort, 28ζ-treated patients with higher senescence score were correlated with longer disease-free survival (p=0.0029), while senMayo gene set enrichment in BBζ-treated patients was associated with non-response in the clinic (p=0.014). In the same cohort, MYC-related gene sets-the same genes sets enriched in our recurrently activated/rested BBζ-are also enriched in nonresponsive BBζ-treated patients. In summary, our study indicates that (i) CART cells are susceptible to a state of senescence, as demonstrated using three independent approaches (repeated activation/rest, irradiation, and MYC modulation), (ii) CART senescence is more prominent in BBζ than 28ζ, and (iii) senescence is associated with worse outcomes following BBζ but not 28ζ treatment.

Introduction: In recent years, multiple myeloma (MM) research has increasingly focused on unraveling the complex interactions between malignant plasma cells and their surrounding bone marrow microenvironment (BMME). To further elucidate these interactions, we developed a comprehensive single-cell atlas of the MM BMME, integrating both coding and noncoding (ncRNA) transcriptional profiles. By correlating these profiles with specific cytogenetic abnormalities in myeloma cells, we aim to uncover how ncRNAs regulate the phenotypic and functional states of myeloma cells and, consequently, shape the cellular landscape of the BMME. A detailed understanding of how the noncoding transcriptome affects the cellular components and immune landscape of the BMME is essential for advancing our knowledge of MM pathogenesis and identifying novel biomarkers and therapeutic targets. Methods: Our atlas was constructed using single-cell RNA sequencing data from 481 samples of CD138neg cells sorted from bone marrow aspirates of MM patients enrolled in the MMRF CoMMpass study. This dataset includes accompanying whole-genome sequencing and survival data, enabling correlative analysis between transcriptional profiles, cytogenetic abnormalities, and patient outcomes. To generate a combined coding and non-coding transcriptome, we developed an expanded human reference genome by systematically merging mRNA and ncRNA transcripts from the LncBook2.0 and GENECODEv42 reference genomes. The sequencing data was aligned to this expanded genome, followed by quality control processing, batch correction, clustering, and supervised analysis. Results: The resulting coding and non-coding atlas comprises over 1.9 million cells, spanning immune, plasma, and stromal compartments. Remarkably, ncRNAs constituted 46% of the associated genes, including 22,102 long ncRNAs (lncRNAs) and 3,112 small ncRNAs. Subclustering analysis of the major immune compartments (B lymphoid, myeloid, and NK and T lymphoid) yielded 70 subclusters, with ncRNAs representing 24-38% of the top 100 differentially expressed genes within each compartment. This underscores the significant role of ncRNAs in distinguishing immune subpopulations. Moreover, examining the association between specific cytogenetic abnormalities and the immune composition of the BMME, 30 subclusters were found to be differentially abundant (P < 0.05) between cytogenetic abnormalities, supporting our hypothesis that myeloma cell genotypes significantly shape the immune microenvironment. For instance, patients with CCND1 amplification displayed an increase CD4+ central memory T cells with a decrease in CD8+ cytotoxic T cells. Similarly, patients with 1q21 gain exhibited an increase in TGFβ-stimulated monocytes, while a decrease in cytotoxic CD8+ T and CD56dim NK cells was observed in patients with 17p13 deletion. Next, examining which ncRNAs are associated with specific cytogenetic abnormalities, we identified 14 ncRNAs significantly differentially expressed across cytogenetic abnormalities. Increased expression of six of these ncRNAs were associated with poor overall survival both independently and in combination (P < 0.05, HR = 3.7). Notably, three of these ncRNAs have documented roles in cancer progression but have not been previously studied in the context of MM. Subsequently stratifying patients based on their enrichment of these outcome-associated ncRNAs revealed even stronger associations with immune composition, including an increase in CD4+ regulatory T cells (P < 0.05). This further supports our hypothesis that myeloma cell genotypes shape the BMME. Lastly, by constructing a gene regulatory network to predict the interactions between coding and noncoding RNAs, we illustrate the regulatory networks of ncRNAs modulating the phenotypes of myeloma and immune cell subpopulations. Conclusion: In summary, we present the first high-resolution transcriptomic atlas of the MM BMME, integrating both coding and noncoding RNAs. This study reveals distinct immune subpopulations associated with specific myeloma cell genotypes and highlights the central role of ncRNAs in modulating the phenotypic and functional states of both malignant and non-malignant cells in the MM BMME. Our findings emphasize the potential of ncRNAs as therapeutic targets and prognostic markers for MM, offering new avenues for research and clinical intervention.