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Abstract Objective To compare the artificial intelligence‐enabled electrocardiogram (AI‐ECG) atrial fibrillation (AF) prediction model output in patients with migraine with aura (MwA) and migraine without aura (MwoA). Background MwA is associated with an approximately twofold risk of ischemic stroke. Longitudinal cohort studies showed that patients with MwA have a higher incidence of developing AF compared to those with MwoA. The Mayo Clinic Cardiology team developed an AI‐ECG algorithm that calculates the probability of concurrent paroxysmal or impending AF in ECGs with normal sinus rhythm (NSR). Methods Adult patients with an MwA or MwoA diagnosis and at least one NSR ECG within the past 20 years at Mayo Clinic were identified. Patients with an ECG‐confirmed diagnosis of AF were excluded. For each patient, the ECG with the highest AF prediction model output was used as the index ECG. Comparisons between MwA and MwoA were conducted in the overall group (including men and women of all ages), women only, and men only in each age range (18 to <35, 35 to <55, 55 to <75, ≥75 years), and adjusted for age, sex, and six common vascular comorbidities that increase risk for AF. Results The final analysis of our cross‐sectional study included 40,002 patients (17,840 with MwA, 22,162 with MwoA). The mean (SD) age at the index ECG was 48.2 (16.0) years for MwA and 45.9 (15.0) years for MwoA ( p < 0.001). The AF prediction model output was significantly higher in the MwA group compared to MwoA (mean [SD] 7.3% [15.0%] vs. 5.6% [12.4%], mean difference [95% CI] 1.7% [1.5%, 2.0%], p < 0.001). After adjusting for vascular comorbidities, the difference between MwA and MwoA remained significant in the overall group (least square means of difference [95% CI] 0.7% [0.4%, 0.9%], p < 0.001), 18 to <35 (0.4% [0.1%, 0.7%], p = 0.022), and 35 to <55 (0.5% [0.2%, 0.8%], p < 0.001), women of all ages (0.6% [0.3%, 0.8%], p < 0.001), men of all ages (1.0% [0.4%, 1.6%], p = 0.002), women 35 to <55 (0.6% [0.3%, 0.9%], p < 0.001), and men 18 to <35 (1.2% [0.3%, 2.1%], p = 0.008). Conclusions Utilizing a novel AI‐ECG algorithm on a large group of patients, we demonstrated that patients with MwA have a significantly higher AF prediction model output, implying a higher probability of concurrent paroxysmal or impending AF, compared to MwoA in both women and men. Our results suggest that MwA is an independent risk factor for AF, especially in patients <55 years old, and that AF‐mediated cardioembolism may play a role in the migraine–stroke association for some patients.

9008 Background: Amivantamab, a fully human bispecific antibody targeting epidermal growth factor receptor (EGFR) and MET, is approved for the treatment of non-small cell lung cancer (NSCLC) with EGFR exon 20 insertion after prior platinum-based chemotherapy. Given its bispecific nature, amivantamab is being explored in patients (pts) with primary MET exon 14 skipping mutation (METex14) in the MET-2 cohort of the CHRYSALIS study. Methods: CHRYSALIS (NCT02609776) is an ongoing phase 1 dose escalation/dose expansion study of amivantamab in pts with advanced NSCLC. Pts with primary METex14 whose disease progressed on or who declined current standard of care therapy were treated with amivantamab 1050 mg (pts <80 kg) or 1400 mg (pts ≥80 kg) weekly in cycle 1 and biweekly thereafter. Response was assessed by investigators using RECIST v1.1. Results: As of 2 Dec 2021, 43 pts with METex14 had received amivantamab. Median age was 70 y (range, 43-88), 58% were women, median prior lines of therapy was 2 (range, 0-10) [eg, crizotinib (n=13), capmatinib (n=11), tepotinib (n=5), anti-MET antibody (n=1)], and 23% had history of brain metastases at baseline. In 36 pts with ≥1 postbaseline disease assessment, median duration of follow-up was 5.8 months (range, 0.3-15.8); 6 pts had no prior treatment, 11 had no prior MET inhibitor, and 19 had a prior MET inhibitor. Overall response rate was 33% (50% [3/6] in treatment-naïve pts, 46% [5/11] in pts with no prior MET inhibitor, and 21% [4/19] in pts with prior MET inhibitor therapy). Clinical benefit rate was >54% regardless of prior treatment (Table). Median duration of response (DOR) was not reached (range, 2.1-12.2 months); 67% (8/13) had DOR ≥6 months. Ten of the 12 responders remain on treatment (6.0-14.4 months) with ongoing responses; 2 discontinued after 2 and 12 months, respectively. Safety profile was consistent with previously reported experience of amivantamab (Sabari 2021 JTO 16(3):S108-109). Treatment-related adverse events leading to dose reduction or discontinuation occurred in 3 pts, each. Conclusions: Amivantamab demonstrates anti-tumor activity in primary METex14 NSCLC including after prior MET inhibitor treatment. Enrollment is ongoing and updated data will be shown. Clinical trial information: NCT02609776. [Table: see text]

9002 Background: KRAS is a key mediator of the RAS/MAPK signaling cascade that promotes cellular growth and proliferation. KRASG12C mutation occurs in ̃14% of NSCLC. Adagrasib, an investigational agent, is a KRASG12C inhibitor that irreversibly and selectively binds KRASG12C, locking it in its inactive state. Adagrasib is optimized for favorable pharmacokinetic (PK) properties, including long half-life (̃24 h), dose-dependent PK, and central nervous system penetration; it has demonstrated objective response and favorable tolerability in the Phase 1/1b setting. Methods: KRYSTAL-1 (NCT03785249) is a multicohort Phase 1/2 study evaluating adagrasib as monotherapy or in combination regimens in patients with advanced solid tumors harboring a KRASG12C mutation. Here we report the first disclosure from all patients enrolled in Cohort A, a Phase 2 cohort with registrational intent, evaluating adagrasib given 600 mg orally BID in patients with NSCLC previously treated with platinum-based chemotherapy and anti-PD-1/L1 therapy. Study objectives include evaluating efficacy (objective response rate [ORR], duration of response [DOR], progression-free survival [PFS], overall survival [OS]), safety, PK, and exploratory correlative analyses. Objective tumor response was assessed per RECIST v1.1 by blinded independent central review (BICR). Results: As of the 15 October 2021 data cutoff, 116 patients with NSCLC harboring a KRASG12C mutation were enrolled and treated, with a median follow-up of 12.5 months. Baseline characteristics include median age 64 years, 65% female, and 15.5%/83.6% with ECOG PS 0/1; 98.3% of patients received adagrasib following prior treatment with immunotherapy and chemotherapy, with a median of 2 prior systemic therapies. The ORR (by BICR) was 42.9% (48/112) and the disease control rate was 79.5% (89/112); 31 patients remain on treatment. Median DOR was 8.5 months (95% CI 6.2–13.8), median PFS was 6.5 months (95% CI 4.7–8.4), median OS was 12.6 months (95% CI 9.2–NE). Treatment-related AEs (TRAEs) of any grade occurred in 97.4% of patients, grade ≥3 TRAEs in 45.7%, 2 grade 5 TRAEs, and 8 (6.9%) TRAEs led to discontinuation. The most commonly reported (≥25%) TRAEs (any grade) were diarrhea (62.9%), nausea (62.1%), vomiting (47.4%), fatigue (40.5%), ALT/AST increased (27.6%/25%), blood creatinine increased (25.9%); the most commonly reported (≥5%) TRAEs (grade 3/4) were lipase increased (6%) and anemia (5.2%). Additional subgroup analyses will be presented, including selected demographics, molecular markers and sites of metastases. Conclusions: Adagrasib is well tolerated and demonstrates promising efficacy in pretreated patients with NSCLC harboring a KRASG12C mutation. A Phase 3 trial evaluating adagrasib monotherapy versus docetaxel in previously treated patients with KRASG12C-mutant NSCLC is ongoing (NCT04685135). Clinical trial information: NCT03785249.

3553 Background: Higher levels of plasma 25-hydroxyvitamin D [25(OH)D)] are associated with better outcomes in mCRC, but underlying biologic mechanisms are unknown. Key components of the VitD metabolic pathway include CYP27B1 (encodes 1-α-hydroxylase, converts 25(OH)D to active calcitriol), VitD receptor (VDR), and CYP24A1 (encodes 24-hydroxylase, degrades calcitriol and 25(OH)D into excreted metabolites). Since these factors may affect 25(OH)D levels and potentially mediate VitD activity in mCRC, we examined the relationship between tumoral gene expression (GEx) of CYP27B1, VDR, and CYP24A and pt outcome in a study nested in a randomized phase III trial of first-line chemotherapy plus biologics in mCRC pts, CALGB/SWOG 80405. Methods: We determined GEx of CYP27B1, VDR, and CYP24A1 by RNA sequencing (RNA-Seq) of archival tumor samples using the Illumina TruSeq platform. Primary endpoints were overall (OS) and progression-free survival (PFS). Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for prognostic and molecular characteristics. Results: 562 pts with RNA-Seq data were included. Pts with higher CYP27B1 expression (>median) were less likely to have BRAF wild type (WT) (79% vs 90%) compared to pts with lower expression (p=0.0007). Pts with higher VDR expression (>quartile 1 [Q1]) were younger (median age 59 vs 62 years; p=0.03), more likely to have left-sided (63% vs 46%; p=0.0005) and BRAF WT tumors (89% vs 70%; p<0.0001), and less likely to have RAS WT tumors (70% vs 80%; p=0.02) compared to pts with lower VDR. Pts with higher CYP24A1 expression (>median) were more likely to have left-sided tumors compared to pts with lower expression (63% vs 54%; p=0.03). On multivariable analysis, pts with higher CYP27B1 expression had significantly improved OS (HR 0.84; 95% CI, 0.75-0.93; p=0.002) and PFS (HR 0.89; 95% CI, 0.80-0.99; p=0.04). Higher VDR expression (up to Q1) was associated with significantly improved PFS (HR 0.69; 95% CI, 0.53-0.91; p=0.007) but not OS (HR 0.85; 95% CI, 0.66-1.09; p=0.20). Above Q1, this improvement attenuated. Higher CYP24A1 GEx was not associated with improved OS (HR 0.98; 95% CI, 0.88-1.08; p=0.66) or PFS (HR 0.98; 95% CI, 0.89-1.08; p=0.68). We found no significant interactions between GEx of CYP27B1, VDR, or CYP24A with baseline plasma 25(OH)D levels (p for interaction ≥0.10 for all). Conclusions: Our findings suggest an association between GEx of VitD pathway markers, particularly CYP27B1 and VDR, and survival in pts with mCRC, lending biologic plausibility to a role of VitD in CRC pathogenesis. Future studies are needed to confirm these findings and elucidate underlying mechanisms of action. Clinical trial information: NCT00265850 .

Background: Cellular redox control is maintained by generation of reactive oxygen/nitrogen species balanced by activation of antioxidative pathways. Disruption of redox balance leads to oxidative stress, a central causative event in numerous diseases including heart failure. Redox control in the heart exposed to hemodynamic stress, however, remains to be fully elucidated. Methods: Pressure overload was triggered by transverse aortic constriction in mice. Transcriptomic and metabolomic regulations were evaluated by RNA-sequencing and metabolomics, respectively. Stable isotope tracer labeling experiments were conducted to determine metabolic flux in vitro. Neonatal rat ventricular myocytes and H9c2 cells were used to examine molecular mechanisms. Results: We show that production of cardiomyocyte NADPH, a key factor in redox regulation, is decreased in pressure overload-induced heart failure. As a consequence, the level of reduced glutathione is downregulated, a change associated with fibrosis and cardiomyopathy. We report that the pentose phosphate pathway and mitochondrial serine/glycine/folate metabolic signaling, 2 NADPH-generating pathways in the cytosol and mitochondria, respectively, are induced by transverse aortic constriction. We identify ATF4 (activating transcription factor 4) as an upstream transcription factor controlling the expression of multiple enzymes in these 2 pathways. Consistently, joint pathway analysis of transcriptomic and metabolomic data reveal that ATF4 preferably controls oxidative stress and redox-related pathways. Overexpression of ATF4 in neonatal rat ventricular myocytes increases NADPH-producing enzymes‚ whereas silencing of ATF4 decreases their expression. Further, stable isotope tracer experiments reveal that ATF4 overexpression augments metabolic flux within these 2 pathways. In vivo, cardiomyocyte-specific deletion of ATF4 exacerbates cardiomyopathy in the setting of transverse aortic constriction and accelerates heart failure development, attributable, at least in part, to an inability to increase the expression of NADPH-generating enzymes. Conclusions: Our findings reveal that ATF4 plays a critical role in the heart under conditions of hemodynamic stress by governing both cytosolic and mitochondrial production of NADPH.

Abstract Internal validation is the most popular evaluation strategy used for drug–target predictive models. The simple random shuffling in the cross-validation, however, is not always ideal to handle large, diverse and copious datasets as it could potentially introduce bias. Hence, these predictive models cannot be comprehensively evaluated to provide insight into their general performance on a variety of use-cases (e.g. permutations of different levels of connectiveness and categories in drug and target space, as well as validations based on different data sources). In this work, we introduce a benchmark, BETA, that aims to address this gap by (i) providing an extensive multipartite network consisting of 0.97 million biomedical concepts and 8.5 million associations, in addition to 62 million drug–drug and protein–protein similarities and (ii) presenting evaluation strategies that reflect seven cases (i.e. general, screening with different connectivity, target and drug screening based on categories, searching for specific drugs and targets and drug repurposing for specific diseases), a total of seven Tests (consisting of 344 Tasks in total) across multiple sampling and validation strategies. Six state-of-the-art methods covering two broad input data types (chemical structure- and gene sequence-based and network-based) were tested across all the developed Tasks. The best-worst performing cases have been analyzed to demonstrate the ability of the proposed benchmark to identify limitations of the tested methods for running over the benchmark tasks. The results highlight BETA as a benchmark in the selection of computational strategies for drug repurposing and target discovery.

Introduction: Multiple supervised machine learning (ML) models have been used to assess the outcomes in patients who underwent transcatheter aortic valve replacement (TAVR) procedure, however, supervised ML requires significant expert time for annotation and labeling. Unsupervised ML can provide insight into the dataset without this process. Hypothesis: We hypothesized that unsupervised k-means ML can identify distinct phenogroups in TAVR patients that can predict prognosis without a priori knowledge. Methods: A retrospective study of patients who underwent TAVR (Jan 2012-Dec 2017) at Mayo Clinic sites was performed. Baseline demographics, EKG, cardiac computed tomography, and echocardiographic data were abstracted. Variables with ≥ 20% missing data were excluded. Prior to the k-means clustering algorithm, principal component analysis was used for dimensionality reduction. Input variables were analyzed according to k-means determined clusters. Kaplan-Meier survival analysis was used to assess the survival of each cluster. Results: A total of 1071 consecutive patients were included in the final analysis. A total of 141 unique variables were used. The mean age was 80.7±8.6 years, 58.2% were male. Patients were divided into 2 distinct phenogroups. In the two phenogroups, cluster 0 (n=639) has significantly better survival than cluster 1 (n= 432) (log-rank p=0.0002) (Figure 1). Cluster 1 has features of low flow-low gradient (LFLG) hemodynamic profile, including lower systolic blood pressure, mean aortic valve gradient, peak aortic valve velocity, and worse LV ejection fraction. Conclusions: Unsupervised ML can identify distinct phenotype features with prognostic significance in TAVR patients. Our results suggest that patients with LFLG hemodynamic features are intrinsically different from other TAVR patients and require more attention to avoid adverse outcomes.

AbstractOraxol consists of an oral dosage form of the chemotherapeutic agent paclitaxel administered with a novel P‐glycoprotein inhibitor encequidar methanesulfonate monohydrate (formerly named HM30181A), which allows oral treatment of cancers that would otherwise be treated with intravenous paclitaxel. Here we describe the population pharmacokinetics (popPK) analyses for oral paclitaxel in patients with advanced/metastatic solid tumors to characterize pharmacokinetic (PK) profiles and quantify sources of PK variability. The best fit popPK model for oral paclitaxel, based on data from seven clinical studies (197 patients with advanced/metastatic solid tumors), involves a linear two‐compartment structural model containing first‐order absorption with a short lag time and first‐order elimination as well as a log additive error. In this popPK model, lower population estimates of central volume for Asian patients versus Caucasian patients did not translate into clinical meaningful differences in oral paclitaxel exposure. Age, sex, body weight or surface area, mild hepatic impairment, and mild to moderate renal impairment had no clinically meaningful effects on the systemic exposure of oral paclitaxel. Simulations were performed on clinical therapeutic dose (oral paclitaxel 205 mg/m2 once daily ×3 days per week) to predict exposure of oral paclitaxel and to support treatment benefits observed in a pivotal phase III trial.