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Background: Multiple Myeloma (MM) is predominantly a disease of older adults. However, older patients vary widely in physiological status and treatment tolerance. The simplified frailty index (Facon 2020) incorporates age, ECOG performance status, and comorbidities (Charleston Comorbidity Index [CCI]) to classify patients as frail or non-frail. While frailty is associated with increased toxicity with conventional systemic therapies, its impact on outcomes of older patients treated with bispecific antibodies (BsAbs) has not been established. Thus, we conducted a retrospective study to evaluate the efficacy and toxicity of BsAbs in older patients based on frailty. Methods: This is a single institution study. We included patients with MM ≥65 years who initiated treatment with a BsAb at Mayo Clinic in Rochester, MN from August, 2018 to January, 2024. Patients who received a BsAb on trial or as standard of care were included. For patients who received 2 different BsAbs at different timepoints, we included the first treatment only. We grouped patients into frail and non-frail based on the simplified frailty index (score ≥2 = frail). We evaluated the overall response (ORR) and ≥very good partial response (VGPR) rates, progression-free (PFS) and overall (OS) survival, early mortality (within 90 days) including early non-relapse mortality (NRM), and toxicities including cytokine release syndrome (CRS), immune effector cell associated neurotoxicity syndrome (ICANS) and healthcare utilization. P values were insignificant (>0.05) unless otherwise stated. PFS and OS were calculated from the day of BsAb start. Results: A total of 99 patients age 65-89 years were included. The products used were teclistamab (N=43), talquetamab (N=2), and investigational agents (N=54); 67% were ≥70 and 29% were ≥75 years; 39% were female, 95% were non-Hispanic White and 4% were Black/African American. Seventy patients (71%) were considered frail and 29 (29%) were non-frail. At the time of BsAb start, a higher proportion of frail patients had platelets <75 x 10^9/L (30% vs 8%, P=0.04). Otherwise, there was no significant difference between frail and non-frail patients in age (median: 72 vs 70), hemoglobin <8 g/dL (19% vs 12%), absolute neutrophil count <1 x 10^9/L (6% vs 8%), presence of high-risk FISH (70% vs 60%), ISS stage 3 (32% vs 41%), high LDH (58% vs 61%), presence of extramedullary disease (39% vs 25%), serum creatinine ≥2 mg/dL (15% vs 8%), bone marrow plasma cell% (20% in both), triple- (83% vs 90%) and penta-class refractoriness (63% vs 48%), number of prior lines of therapy (median: 6 in both), prior exposure to BCMA-directed therapy (24% vs 21%, P=0.80) and prior autologous stem cell transplant (73% vs 86%). Step-up dosing was used in 81% vs 48% of patients (P=0.001), and treatment was initiated in the outpatient setting in 46% vs 28% (P=0.12) in frail and non-frail patients, respectively. The median follow-up was 1.9 (95%CI: 1.0-2.3) years. There was no significant difference between frail and non-frail patients in ORR (52% vs 62%), ≥VGPR (46% vs 48%), 1-year PFS (36% vs 48%, P=0.26), or 1-year OS (57% vs 61%, P=0.30), respectively. Age and CCI alone were not associated with PFS or OS, but ECOG >1 was associated with decreased PFS (hazard ratio: 3.1, P=0.001) and OS (hazard ratio: 3.1, P<0.001). There was no significant difference between frail vs non-frail patients in grade 3/4 thrombocytopenia (39% vs 17%, P=0.06), grade 3/4 neutropenia (27% vs 35%), total days of hospitalization (median: 8 vs 5, P=0.35), number of unplanned admissions in 6 months (median: 1 in both), or total hospital days for unplanned admissions (1 vs 2 days). There was no significant difference between frail and non-frail patients in early mortality (23% vs 10%, P=0.17), including early NRM (4% in both), CRS (59% vs 66%), grade 3-4 CRS (3% vs 7%), or CRS recurrence (21% vs 10%). ICANS occurred in 5 (9%) frail patients and 1 non-frail patient (grade 2); among frail patients, grades were: 1 in 3 patients, 3 in 1 patient, and 4 in 1 patient. Similarly, there was no significant difference in CRS/ICANS between the 2 groups when patients with and without step-up dosing were analyzed separately. Conclusion: Frailty, defined using the simplified frailty index, was not significantly associated with inferior efficacy or increased toxicity with BsAb therapy among older patients with MM. Poor performance status predicted inferior PFS and OS, while age and comorbidity scores did not.

Background: A deeper understanding of the cytogenetic features has enabled robust risk stratification for patients with newly diagnosed multiple myeloma (NDMM). However, heterogeneity persists in the currently available prognostic tools and there is further room for personalization. We assess the utility of PC-PRO, a test to measure the proportion of monotypic plasma cells in the synthetic phase (S-phase) of cell cycle, as a prognostic marker for NDMM. Methods: Patients with active MM diagnosed between January 2013 and January 2023 with a flow cytometry-based S-phase assessment at diagnosis were included. Flow cytometric immunophenotyping was performed using the following antibodies: CD19, CD38, CD45, CD138, cytoplasmic kappa and lambda immunoglobulin, and DAPI (4',6-diamidino-2-phenylindole). The percentage of plasma cells in S-phase was determined by measuring the proportion of cells with DNA content of the monotypic plasma cells between the G0/G1 and G2/M peaks. Plasma cell clonality was detected through demonstrating CD38 and CD138 positivity along with immunoglobulin light chain restriction, abnormality of CD19/ CD45 expression and/or ploidy difference by DAPI staining. High-risk cytogenetic abnormalities (HRCA) by FISH were defined as follows: presence of deletion 17p (del17p), t(4;14), t(14;16), t(14;20), 1q gain/amplification, 1p deletion (when available). Additionally, the second iteration of the revised ISS (R2-ISS), incorporating both laboratory and cytogenetic features as well an adaptation of the recently proposed International Myeloma Working Group (IMWG) Classification for high-risk disease, was utilized for risk stratification. All time-to-event analyses were performed using the Kaplan Meier method and compared using the log-rank test. Univariable and multivariable Cox proportional hazards analyses were performed to assess the independent prognostic impact of S-phase. Results: A total of 823 patients were included in the study. The median follow-up was 6 years [95% Confidence interval (CI): 5.5-6.3 years] and estimated median overall survival (OS) was 8.3 years. The median S-phase value for the cohort was 0.8 % (interquartile range: 0.5-1.4%), with 135 (16%) patients harboring an S-phase of ≥2% at diagnosis. Applying the R2-ISS prognostic model to our cohort, 11% (79/706) patients were stratified to the R2-ISS high-risk cohort; 93 patients (out of 788, 12%) had 2 or more HRCA at diagnosis. Patients with a S-phase ≥2% at diagnosis had a median OS of 3.9 years (95% CI: 2.9-5.7) vs. 9.2 years [95% CI: 7.9-not reached (NR)] for patients with a S-phase <2% [Hazard ratio (HR): 2.2 (95% CI: 1.7-2.8), p<0.0001]. The median OS was inferior for cohorts with an increasing S-phase value: S-phase of 0.1-1%: HR: 1 (standard), S-phase 1.1-3%: HR 1.7 (95% CI: 1.3-2.1), S-phase >3%: HR 3.0 (95% CI: 2.2-4.1)]. On a multivariable analysis including S-phase ≥2%, age at diagnosis of MM (>65 years) and R2-ISS high-risk status, S-phase ≥2% was an independent predictor of inferior OS [hazard ratio (HR) 1.9 (95% CI: 1.4-2.6), p<0.0001]. Age >65 years [HR 1.9 (95% CI: 1.5-2.5), p<0.0001] and R2-ISS high-risk status [HR 1.8 (1.3-2.6), p=0.001] were also independent predictors of OS. Within the sub cohort of patients with 2 or more of the listed high-risk cytogenetic features (n=93, 12%), a S-phase ≥2% (n=24) was associated with a worse median OS of 1.6 years (95% CI: 0.7-NR) vs. 6.2 years (95 % CI:3.3-NR) for S-phase <2% (p=0.002). Conclusion: Flow cytometry-based determination of the proportion of monotypic plasma cells in S-phase is an easy-to-study and powerful prognostic tool for NDMM. A S-phase of ≥2% at diagnosis is a predictor of OS independent of age and R2-ISS high-risk stage. An S-phase of ≥2% was able to identify a distinct group with markedly inferior outcomes even within the sub cohort of patients with 2 or more high-risk cytogenetic features.

Background and Methods: IEC-HS is a hyperinflammatory state with high morbidity and mortality. Effective interventions to reverse the process early in the clinical course may be critical to improve outcomes. We previously examined cytokine differences between IEC-HS and other secondary hemophagocytic lymphohistiocytosis, and found significant differences in the patterns and outcomes.(1) This study examines cytokine profiles (CP) of patients treated with CAR-T from 9/2019 to 3/2024 who developed CRS, MAS-L and IEC-HS. Demographics and lab results were compared among the three groups and correlated with outcomes. Results: CP was tested in 113 of 366 CAR-T patients: 74 with CRS, 19 with MAS-L, and 20 with IEC-HS. The racial distribution was 93% White/Caucasian, 2% Black or African American, 1% Asian, 1% Native American and 3% other or unavailable. No differences were seen in demographics between groups except a higher percentage of patients with ECOG performance status ≥2 in IEC-HS (p=0.037). Incidence of IEC-HS by disease: 3.6% (7/193) in lymphoma, 5% (8/159) myeloma and 28.5% (4/14) B-acute lymphoblastic leukemia (p=0.0002). Incidence of IEC-HS by CAR-T product: 3% (4/150) in Axi-cel, 23% (6/26) in Brexu-cel, 8% (1/13) in Tisa-cel, 5% each (3/60) in Cilta-cel and Ide-cel, and 0/17 in Liso-cel (p=0.001). Prior to lymphodepletion, labs were already different among the CRS, MAS-L, and IEC-HS groups: hemoglobin (g/dL: 11.1, 9.6, 8.45); platelets (x109/L: 168, 116, 52.5); ferritin (µg/L: 115, 946, 1944). CP was started when patients needed a second dose of tocilizumab or concern for developing MAS-L/IEC-HS, and continued daily until clinical improvement or resolution of inflammatory state. Tocilizumab and dexamethasone use were similar across groups. Other therapies used were vasopressors (3%, 10.5%, 45%; p<0.0001), Methylprednisolone (20%, 31.6%, 50%; p=0.027), Anakinra (12%, 63%, 85%; p<0.0001), Siltuximab (9.5%, 16%, 30%; p=0.06), Basiliximab (30% of IEC-HS), and continuous veno-venous hemofiltration (30% of IEC-HS). Among the first CP, the CRS group had lower levels of cytokines (in pg/mL) compared to MAS-L and IEC-HS groups: TNF (31, 62.9, 47.7), IL-10 (29.3, 97.7, 169), IL-18 (794, 1353, 2011), IFN-gamma (74, 281, 250), MCP-1 (689, 2722, 2485.5), MIP-1 alpha (220, 234, 247.5), IL-6 (>315: 45%, 79%, 70%), soluble IL-2R alpha (>4000: 45%, 84%, 70%). The percentage of patients who received anakinra before CP1 were 4% (CRS), 21% (MAS-L) and 25% (IEC-HS) (p=0.007). IL-1 beta was below threshold among all patients who received anakinra in CRS and MAS-L and 75% in IEC-HS, suggesting rapid and effective IL-1 suppression by anakinra except in IEC-HS. Cytokines trends 24 hours and 48 hours after the first CP differed between MAS-L and IEC-HS. MAS-L had decreased TNF (62.9, 40.4, 18.5) and MCP-1 (2722, 355, 104) while these cytokines remained elevated or increased in IEC-HS (TNF: 47.7, 105.5, 62.6; MCP-1: 2486, 2276, 1585). IL-18 was minimally elevated in MAS-L (1353, 1955, 3068) and significantly increased in IEC-HS (2011, 2420, 4048). Notably, CP2 and CP3 levels of these cytokines in IEC-HS were statistically significantly higher than corresponding CPs among CRS and MAS-L. In addition, patients who died with persistent E. faecium bacteremia had higher IL-18 on CP3. Infections occurred in 43%, 58%, and 85% respectively (p=0.002), including E. faecium bacteremia (3%, 5%, 35%; p=0.0004), CMV viremia (30% of IEC-HS patients vs. 11% of non-IEC-HS; p=0.025), and invasive fungal infections (15% of IEC-HS patients; p=0.0001). Between the IEC-HS and non-IEC-HS groups, day 100 non-relapse mortality was 35% vs. 0 (p<0.0001), day 100 all-cause mortality was 45% vs. 3% (p<0.0001), and E. faecium bacteremia-related deaths were 50% vs. 1% (p<0.0001). Conclusions: CRS, MAS-L andIEC-HS are known complications of CAR-T. Cytokine-directed therapy can modify the cytokine milieu and control the inflammatory process. However, excess immunosuppression may result in life-threatening infections. Further studies are needed to identify optimal biomarker-guided immunosuppressive strategies to control the inflammatory cascade, while avoiding excess immunosuppression. References: 1. Leung, Nelson, et al. “Outcomes of patients who received CAR T cell therapy and developed IEC-HS treated with cytokine directed therapy.” (2024): 7516-7516.

Introduction: Light chain multiple myeloma (LCMM) is a distinct subtype of multiple myeloma (MM) characterized by the exclusive production of immunoglobulin light chains, unlike the common form of MM that produces the complete immunoglobulin. There is a paucity of literature on the specific tumor cell alterations leading to light chain-only disease as opposed to the typical presentation in MM. Additionally, data on treatment response and outcomes in this subgroup of patients is sparse. This study explores the differences in baseline characteristics, including cytogenetic abnormalities and treatment response between LCMM and multiple myeloma with heavy chain involvement. Materials and Methods: We reviewed patient charts to obtain clinical and laboratory information for individuals diagnosed with LCMM and those with heavy chain MM (comparison cohort) from 2004 to 2022. Patients were matched for age, sex, and year of diagnosis. Data collected included treatment assessment, overall survival, and progression-free survival (PFS). Associations between outcomes and categorical variables were analyzed using the chi-square test, while the Mann-Whitney U test was employed to compare medians. Progression-free survival following initiation of initial therapy and overall survival were assessed using Kaplan-Meier analysis. The Mayo Clinic Institutional Review Board (IRB) approved the study. Results: We identified 848 patients, representing 17.1% of newly diagnosed MM cases. The median age of the LCMM cohort was 63 years (range 16-92), with a female-to-male ratio of 1:5. The LCMM cohort had higher levels of lactate dehydrogenase (LDH), beta-2 microglobulin (p<0.0001), higher baseline creatinine (p<0.0001) and calcium (p<0.0001). The two cohorts had no significant difference in the International Staging System (ISS) or revised ISS (R2-ISS). Additionally, hemoglobin (Hb) and white blood cell count at presentation were higher in the LCMM cohort. Chromosome 1 abnormalities were lower in the LCMM cohort: 1q gain (OR-0.7; 95% CI: 0.6-0.9) and 1p deletion (OR-0.7; 95% CI: 0.6-0.9, p=0.02). Likewise, the frequencies of trisomies and hyperdiploidy were lower in the LCMM cohort, with odds ratios of 0.32 (p=0.012) and 0.37 (p<0.001), respectively. The frequencies of translocations t(4;14) (OR-0.35, p<0.001) and t(14;16) (OR-0.6, p=0.03) were lower in LCMM compared to heavy chain MM. In contrast, the frequencies of t(11;14) (OR-3.4) and t(6;14) (OR-4.9) and deletion of 13q(OR-1.3) was higher in the LCMM cohort. There was no significant difference in the occurrence of del(17p)/TP53 abnormalities. The median PFS after the first regimen was shorter in the LCMM cohort (23 months vs. 27 months, p=0.03), and this difference remained significant after adjusting for baseline adverse prognostic indices and treatment regimen. Median PFS in LCMM patients with monoclonal antibody (Mab) as part of their treatment was 37 months vs. 23 months (Proteasome Inhibitor or immunomodulator-based regimen without Mab), though this difference is not statistically significant p=0.87. No significant difference was found in overall survival between the two groups. Conclusion: This study highlights unique features of light chain multiple myeloma, including increased frequencies of specific cytogenetic abnormalities. Further evaluation of observed differences in cytogenetic abnormalities may enhance our understanding of LCMM and potentially guide baseline treatment choices to improve outcome.

Background: Despite effective front-line therapies, DLBCL & MM have high relapse rates. Novel therapies like CAR-T & bispecific antibodies (BsAb) offer deep & durable remission compared to salvage therapies, but have a unique toxicity profile (TP) that requires monitoring. With no head-to-head trials, the rationale for therapy selection may vary. This study explores provider choices, sequencing preferences, & access barriers. Methods: Two anonymous surveys (MM and DLBCL) of US-based Hematologists were conducted from 2/2024 to 6/2024, on practice settings, CAR-T & BsAb availability, treatment preferences & barriers. Responses were analyzed to assess preferences across clinical scenarios. Results: Surveys were completed by 37 MM & 45 DLBCL providers. Most were at centers offering both CAR-T & BsAb. Most gave CAR-T inpatient, & BsAb outpatient. CAR-T was given by 73% MM providers & 66% DLBCL (92% used Cilta-cel, 96% used Ide-cel; 100% used Axi-cel, 90% used Liso-cel & 73% Tisa-cel). In MM, 78% used Teclistamab, 60% Talquetamab & 24% Elranatamab. In DLBCL, 62% used Epcoritamab & 40% Glofitamab. Providers preferred CAR-T over BsAb in MM after 4+ prior lines of therapy (LOT) (89%), & in DLBCL after 2+ prior LOT (93%). CAR-T was favored more among academic providers & those at CAR-T centers. Practice volume did not impact selection. Among providers at centers with BsAb-only, CAR-T was preferred by 60% (MM) and 50% (DLBCL). Providers at centers without both favored CAR-T (MM: 75%, DLBCL: 86%). CAR-T was chosen for better outcomes, short treatment, center choice, & prior experience. Other factors that influenced decisions were lower incidence of cytopenia/infection & “BsAb effective post-CAR-T, less so vice versa” (MM), & “curative potential of CAR-T” (DLBCL). Logistical barriers & institutional constraints influenced BsAb selection: CAR-T unavailability, access to specialized centers, referral complexity, insurance delay, manufacturing delay & hospitalization needs. In MM, 78% providers preferred Cilta-cel over Ide-cel, especially academic providers & those with CAR-T experience. CAR-T volume did not impact selection. Cilta-cel was preferred due to perceived better response rate (RR), more experience, “progression-free survival (PFS) benefit”, center choice, & logistical issues with Ide-cel. Ide-cel was selected due to center choice, favorable TP & insurance preference. Teclistamab was preferred by 78% due to more experience, better RR, TP & center choice, Elranatamab by 11% (better TP, RR, & “PFS”), & Talquetamab by 11% due to having a non-BCMA target. Academic providers preferred Teclistamab (89% vs 50%), & nonacademic providers preferred Talquetamab (38% vs 4%) and Elranatamab (13% vs 8%). In DLBCL after 2+ LOT, 69% favored Axi-cel due to prior experience, RR, center choice, & logistical issues with other products. Liso-cel & Tisa-cel were chosen by 27% & 2%, respectively, due to favorable TP. Axi-cel was also preferred 2nd line by 73% for similar reasons, while 24% favored Liso-cel for its favorable TP. Epcoritamab was preferred by 56% (subcutaneous injection, more experience & center choice) & Glofitamab by 42% (shorter treatment duration, easy administration, more experience, & center choice). Practice setting & volume did not impact selection between products in DLBCL. InBCMA-naïve MM pts, majority (97%) chose an anti-BCMA agent over GPRC5D due to better RR, TP, prior experience, & center choice. InBCMA-exposed pts, most (92%) favored an anti-GPRC5D agent. In contrast in DLBCL, 80% chose CD19 CAR-T after prior CD19-directed therapy, & 18% chose CD20 BsAb. Therefore, antigen escape was less of a concern in DLBCL vs MM. For relapse after 2nd line CAR-T in DLBCL, 78% preferred BsAb over other salvage options due to better RR, TP, & more experience. Providers prioritized RR, survival, & TP in decision making. Treatment logistics, duration, frequency, & cost were less crucial. MM providers also prioritized quality of life, which was less so in DLBCL. There were no differences in priority based on practice setting & experience with CAR-T. Conclusion: The study highlights factors influencing therapy choices in MM & DLBCL. Despite CAR-T's potential for better outcomes, significant access barriers exist. Efforts to streamline referral pathways, logistics, & expanding availability are crucial to improve outcomes. Understanding these preferences & barriers can guide future management strategies.

Abstract Patient-reported outcomes (PROs) are associated with treatment outcomes in multiple myeloma (MM) in the clinical trial setting. However, most PRO tools are time consuming, which hinders use in routine practice. Our institution incorporated a “Hematology Patient-Reported Symptom Screen” (HPRSS), a 3-item questionnaire for fatigue, pain, and quality of life (QOL). The main objective of this study was to evaluate the impact of these symptoms on progression-free survival (PFS) and overall survival (OS) in a real-world cohort of patients with newly diagnosed MM. This retrospective study included patients with MM diagnosed between April 2011 and December 2017, seen at Mayo Clinic (Rochester, MN), who completed the HPRSS. Patients rated their symptoms on a scale from 0 to 10. Clinically relevant symptoms were defined as scores ≥5 for pain and fatigue, and ≤5 for QOL. At diagnosis, 735 patients had scores for all domains. The median follow-up was 8.1 years. Age was associated with increased odds of fatigue and decreased QOL. Female sex and comorbidities were associated with fatigue and pain. Higher disease stage, anemia, lytic lesions, and increased plasma cell burden were associated with fatigue, pain, and decreased QOL. Clinically relevant fatigue, pain, and decreased QOL were associated with decreased PFS and OS. On multivariate analysis including age, International Staging System III, high-risk cytogenetics, and postinduction transplantation, fatigue and decreased QOL were independently associated with decreased OS. A composite HPRSS score stratified patients into 3 groups with distinct OS. Patient-reported symptoms are prognostic in patients with newly diagnosed MM. The prognostic values of fatigue and decreased QOL are independent of age, disease stage, and transplant status.

Patients with chronic liver disease commonly have abnormal lung function; however, the impact of smoking on outcomes in these patients is unknown. We hypothesized current or past smoking would be associated with worse survival in patients with advanced liver disease. The Pulmonary Vascular Complications in Liver Disease Study 2 (PVCLD2) was a prospective cohort of patients with advanced liver disease undergoing evaluation for liver transplantation (LT). Patients were classified by self-report as a “non-smoker,” “past smoker,” or “current smoker.” We used Cox proportional hazards models and Fine-Gray models with LT as a competing risk. Models were adjusted for age, sex, body mass index, race, family income, liver disease etiology, and Model for End-Stage Liver Disease-Sodium score. Of the 410 patients included, most (65%) were male and the mean age at enrollment was 56.5 years. One hundred sixty (39%) patients were nonsmokers, 183 (45%) were past smokers, and 67 (16%) were current smokers. In total, 151 (37%) patients received an LT, and 88 (20%) patients died. When compared to nonsmokers, current smokers had a 2.17-fold increase in risk of death overall (95% CI: 1.12–4.18, p = 0.02). There was a 7% increase in overall risk of death for every 5 pack-years increase (95% CI: 1.01–1.13, p = 0.02). With LT as a competing risk, the subdistributional HR of current smokers versus nonsmokers for death was 2.45 (95% CI: 1.31–4.60, p = 0.005). In this model, past smokers displayed a nonsignificant increase in the risk of death compared to nonsmokers (subdistributional HR: 1.58, 95% CI: 0.91–2.72, p = 0.10). Patients with advanced liver disease undergoing evaluation for LT who smoke have an increased risk of death. Smoking cessation could lead to improved overall survival with or without LT.

Older patients with multiple myeloma (MM) exhibit wide heterogeneity in their baseline physiologic and functional status, which demands an individualized treatment approach based on biological rather than chronological age. Various frailty scores have been developed for older patients with MM, but they are underutilized in clinical trials and in practice. Older patients with MM are underrepresented in therapeutic clinical trials, and treatment recommendations are currently derived from clinical trials of transplant-ineligible patients. This article provides a summary of phase II and III clinical trials in transplant-ineligible patients with newly diagnosed MM, highlighting outcomes in patients aged ≥75 years and frailty-based outcomes. The data available thus far show that triplet regimens are more efficacious than doublets in older patients but may be associated with higher toxicity. DRd (daratumumab/lenalidomide/dexamethasone) and VRd (bortezomib/lenalidomide/dexamethasone) are good options in patients who are nonfrail, whereas dose-adjusted DRd and VRd-lite should be offered to frail patients. Frailty should be assessed regularly to guide treatment intensification and/or deescalation. It is important that frailty measures are incorporated in clinical trials evaluating novel treatments to inform how older and frail patients will benefit from these treatments.

Background: Gain-of-function mutations in the canonical transient receptor potential 6 (TRPC6) channel contribute to heart failure (HF) and focal segmental glomerulosclerosis in humans. Our GWAS results indicated that the TRPC6 A404V variant, having a minor allele frequency of 12% in the population, is associated with doxorubicin-induced cardiotoxicity. However, the underlying ionic mechanisms of this variant have not been fully examined. Methods: Combining patch clamp recording, site-directed mutagenesis, and in-silico analysis, we evaluated the TRPC6 A404V variant function. Results: Whole-cell TRPC6 currents were elicited in HEK293 cells using a voltage ramp protocol from -100 mV to +100 mV with a holding potential of -60 mV, 48 hours after transfection with TRPC6 WT or A404V cDNAs. The inward-current densities at -100 mV and the outward-current densities at +100 mV for TRPC6 WT and A404V variant were similar at baseline. However, after exposure to 50 μM 1-oleoyl acetyl-sn-glycerol (OAG, a TRPC6 activator), these current densities were significantly increased by 2.6-fold and 4.5-fold respectively in the WT (n=20 cells), and by 8.4-fold and 8.9-fold respectively in the A404V variant (n=12 cells, p<0.05 vs. WT). The OAG effects were abolished by superfusion with 1 μM BI-749327 (a specific TRPC6 inhibitor). Moreover, a 24-hour treatment with 0.5 μM doxorubicin (DOX) further amplified the effects of OAG, increasing the total inward- and outward-current densities by 7.2-fold and 9.5-fold respectively in TRPC6 WT (n=11 cells), and by 13.9-fold and 14.7-fold respectively in the A404V variant (n=13 cells, p<0.05 vs. WT). In comparison, the OAG effects on TRPC6 WT and A404V channels were not potentiated by treatment with 0.5 μM doxorubicinol (DOXol, a metabolite of DOX) for 24 h (n=10-12 cells, p=N.S.). Molecular docking studies showed that OAG had a lower binding energy (-5.60 kcal/mol) and a smaller apparent equilibrium constant (Kd) of 0.079 mM with the A404V variant, compared to those of -4.49 kcal/mol and 0.511 mM respectively with TTRPC6 WT. Conclusion: TRPC6 A404V is a gain-of-function variant with a higher binding affinity to OAG. Treatment with DOX but not DOXol greatly enhances TRPC6 WT and A404V channel activation by OAG. Thus, cancer patients carrying the TRPC6 A404V variant may be more vulnerable to develop HF upon treatment with anthracycline.

AbstractObjectivesTo report lessons from integrating the methods and perspectives of clinical informatics (CI) and implementation science (IS) in the context of Improving the Management of symPtoms during and following Cancer Treatment (IMPACT) Consortium pragmatic trials.Materials and MethodsIMPACT informaticists, trialists, and implementation scientists met to identify challenges and solutions by examining robust case examples from 3 Research Centers that are deploying systematic symptom assessment and management interventions via electronic health records (EHRs). Investigators discussed data collection and CI challenges, implementation strategies, and lessons learned.ResultsCI implementation strategies and EHRs systems were utilized to collect and act upon symptoms and impairments in functioning via electronic patient-reported outcomes (ePRO) captured in ambulatory oncology settings. Limited EHR functionality and data collection capabilities constrained the ability to address IS questions. Collecting ePRO data required significant planning and organizational champions adept at navigating ambiguity.DiscussionBringing together CI and IS perspectives offers critical opportunities for monitoring and managing cancer symptoms via ePROs. Discussions between CI and IS researchers identified and addressed gaps between applied informatics implementation and theory-based IS trial and evaluation methods. The use of common terminology may foster shared mental models between CI and IS communities to enhance EHR design to more effectively facilitate ePRO implementation and clinical responses.ConclusionImplementation of ePROs in ambulatory oncology clinics benefits from common understanding of the concepts, lexicon, and incentives between CI implementers and IS researchers to facilitate and measure the results of implementation efforts.