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8644 Background: RET fusions are targetable oncogenic drivers in 1-2% of non-small cell lung cancers (NSCLC). ARROW (NCT03037385) study results (final data lock May 20, 2024) supported the US FDA approval of pralsetinib, a highly potent, oral, selective RET inhibitor for metastatic RET -altered NSCLC. Here, we present final study results. Methods: ARROW was a phase 1/2 open-label study conducted at 84 sites in 13 countries. Phase 2 included patients with RET -fusion-positive NSCLC who received 400 mg pralsetinib once daily (QD). Initially, treatment-naïve patients were not candidates for platinum-based therapy and presented with several unfavorable prognostic factors; this requirement was removed by protocol amendment in July 2019. Primary objectives were overall response rate (ORR, per RECIST v1.1) and safety. Progression-free survival (PFS) and overall survival (OS) are reported in the full efficacy population; the measurable disease population (MDP) was the primary analysis population for ORR and duration of response (DOR). Results: 281 patients with RET -fusion-positive NSCLC received pralsetinib 400 mg QD, with a median duration of treatment of 14.95 months (mos). Median age was 60 years; 46% were male. In the MDP (n=259), ORR was 70.3% (95% confidence intervals [CI]: 64.3, 75.8) and median DOR was 19.1 mos (95% CI: 14.5, 27.9; Table). In the efficacy population (N=281), median OS was 44.3 mos (95% CI: 30.9, 53.1) with median follow up of 47.6 mos (95% CI: 44.8, 49.2), and median PFS was 13.1 mos (95% CI: 11.4, 16.8). ORR (Table) and median PFS were markedly higher in the US (25.9 mos, n=64) vs. Asia (12.6 mos, n=122) or Europe (12.9 mos, n=95). In the safety population, 95% of patients experienced treatment-related adverse events (TRAEs); 66% experienced ≥grade 3. Common TRAEs included increased AST (n=128 [46%]), anemia (n=121 [43%]), increased ALT (n=98 [35%]), and hypertension (n=77 [27%]). 3 patients died due to TRAEs (pneumonia, n=2; interstitial lung disease and rhabdomyolysis, n=1 each). No new safety signals were identified with this update. Conclusions: Pralsetinib produced clinically meaningful and durable responses in patients with RET -fusion-positive NSCLC (regardless of prior therapies) with a manageable safety profile, confirming with this longer follow up previously published results. Clinical trial information: NCT03037385 . All MDP(n=259) Prior Platinum (n=130) Treatment-naive(n=106) ORR, % (95% CI) Overall 70.3(64.3, 75.8) 63.1(54.2, 71.4) 78.3(69.2, 85.7) US (n=58)77.6(64.7, 87.5) (n=31)64.5(45.4, 80.8) (n=19)100(82.4, 100) Europe (n=89)65.2(54.3, 75) (n=36)63.9(46.2, 79.2) (n=43)65.1(49.1, 79) Asia (n=112)70.5(61.2, 78.8) (n=63)61.9(48.8, 73.9) (n=44)81.8(67.3, 91.8) Median DOR, mos (95% CI) a (n=182)19.1(14.5, 27.9) (n=82)31.8(15.1, 40.4) (n=83)13.4(9.4, 21.7) Median DOR follow up, mos (95% CI) 46.8(42.3, 50.2) 50.3(46.9, 56.8) 42.3(37.4, 44.2) a Per FDA censoring rule.

3116 Background: Pralsetinib is an oral tyrosine kinase inhibitor that selectively and potently targets oncogenic RET fusion and mutation proteins. RET fusions or mutations are present in various tumor types. We report the final results from the phase 2 portion of ARROW, a phase 1/2, open-label, multi-cohort, dose-expansion study evaluating the efficacy and safety of pralsetinib (NCT03037385) in patients with RET fusion-positive solid tumors other than non-small-cell lung cancer (NSCLC) and thyroid cancer. Methods: Eligible pts were ≥18 years of age with a pathologically documented, definitively diagnosed advanced solid tumor with an oncogenic RET fusion or mutation, had previously received standard of care appropriate for their tumor type, and were not eligible for any other study groups. Overall response rate (ORR) and safety were primary endpoints of the study. Key secondary endpoints included duration of response (DOR), progression-free survival (PFS), and overall survival (OS). The final database lock was May 20, 2024. Results: Twenty-nine patients were enrolled with 11 different solid tumor histologies. Twenty-six (90%) received prior systemic therapy. Median age was 58 years (range 25-75); 59% were female. Twenty-eight patients were included in the efficacy analysis. ORR (by RECIST) was 46.4% (13/28); 10.7% (3/28) achieved complete response (pancreatic cancer, n=2; cancer of unknown primary, n=1) and 35.7% (10/28) achieved partial response. Median PFS was 7 months (95% CI: 3.9, 12.8). Median DOR was 11.1 months (95% CI: 5.5, 25.1). Median OS was 10.3 months (95% CI: 6.8, 25.2). Twenty-five (86%) patients experienced treatment-related adverse events (TRAEs); 19/29 (66%) reported TRAEs ≥grade 3. The most common TRAEs included increased aspartate aminotransferase (11/29; 38%), increased alanine aminotransferase (10/29; 35%), and anemia (9/29; 31%). Four (13.8%) patients experienced hypertension, and 1 (3.4%) patient had ≥grade 3 hypertension. No new safety risks were identified; AEs remained manageable with supportive care and/or dose modifications. Conclusions: In the phase 2 portion of this trial, responses were observed in many tumor types (Table). Pralsetinib demonstrated robust and durable anti-tumor activity with an ORR of 46.4%. These data validate RET fusions as a tissue-agnostic target with sensitivity to RET inhibition and activity beyond NSCLC and thyroid cancer, further supporting the promising potential of pralsetinib to address the unmet medical need in these patients. Clinical trial information: NCT03037385 . Overall response rate by tumor type. Cancer Type (patient n) ORRn (%) Pancreatic (5) 5 (100) Cancer of unknown primary (1) 1 (100) Neuroendocrine (3) 2 (67) Sarcoma (3) 2 (67) Head and neck (2) 1 (50) Small cell lung (2) 1 (50) Hepatobiliary (4) 1 (25) Colorectal (5), gastric (1), ovarian (1), thymic (1) 0

Abstract Introduction: With over 80, 000 new cases of non-Hodgkin's lymphoma (NHL) diagnosed annually, modifiable risk factors remain unclear. Circadian disruption, linked to cancers like breast and prostate, affects immune cells (e.g., natural killer cells and T-helper cells) by altering their trafficking and proliferation. Some studies (PMID: 30566672, 27611440) suggest long sleep may increase overall NHL risk, including a Mendelian randomization (MR) study (PMID: 32895918). However, no research has examined the causal relationship between sleep traits, including long sleep, and NHL risk, by subtypes. We hypothesize that sleep traits are causally associated with NHL subtypes in European populations, testing this using MR with data from the International Lymphoma Epidemiology Consortium (InterLymph). Methods: We conducted two-sample MR using genome-wide association studies (GWAS) summary data for sleep traits and NHL subtypes. Only independent, genome-wide significant (p < 5×10-8) Single Nucleotide Polymorphisms (SNPs) were selected as valid instruments, sourced from the UK Biobank. Sleep traits included chronotype (153 SNPs), insomnia (48 SNPs), sleep duration (78 SNPs), excessive daytime sleepiness (37 SNPs), short sleep (27 SNPs), and long sleep (8 SNPs). NHL subtype data were from InterLymph: follicular lymphoma (6, 508 cases / 64, 183 controls), mantle cell lymphoma (1, 169 cases / 61, 603 controls), Waldenstrom macroglobulinemia/lymphoplasmacytic lymphoma (WM/LPL: 1, 697 cases / 59, 333 controls), and chronic lymphocytic leukemia (8, 522 cases / 67, 653 controls). The primary analysis used inverse-variance weighted (IVW) random-effects, with MR-Egger for pleiotropy adjustment. Results: Using the IVW method, we did not identify any statistically significant causal association between sleep traits and the risk of NHL subtypes, but did yield several intriguing trends. Long sleep (sleep duration >= 9 h per night) showed a marginally increased NHL risk [Odds ratio (OR) range: 1.51 - 247.9] across each subtype. Short sleep (sleep duration < 7 h per night) showed a similar trend [OR range: 1.25 - 1.81], except for WM/LPL, where we noticed a negative trend. The confidence limit for long sleep was imprecise due to the small number of variants. We did not notice any significant directional horizontal pleiotropy or weak instrument bias. Conclusions: We found no conclusive evidence of a relationship between sleep traits and four NHL subtypes. However, we see suggestive trends of long and short sleep associated with higher risk of some NHL subtypes. These findings align with the previous studies, which showed long sleep was associated with higher risk of NHL overall. Future directions include expanding our analysis to additional NHL subtypes, generating polygenic risk scores, and conducting stratified analyses. Citation Format: Pankhil Shah, Brittany Crawford, Anwar Merchant, Brenda Birmann, Angelica Macauda, Michelle A. Hildebrandt, Aaron Norman, Neil E. Caporaso, Meredith Yeager, Michael Dean, Immaculata De Vivo, Lynn Goldin, Nicola J. Camp, Rosalie Griffin, Delphine Casabonne, Federico Canzian, Pelin Unal, Elad Ziv, Catherine R. Marinac, Alexandra Nieters, Stephen J. Chanock, Mitchell J. Machiela, Michael Conry, Charlie Zhong, Hanla A. Park, Simon Cheah, Jonathan N. Hofmann, Elizabeth E. Brown, Celine Vachon, Susan Slager, Sonja Berndt, Sophia S. Wang, Vijai Joseph, James McKay, Henrik Hjalgrim, Lara Sucheston-Campbell, Karl Smith-Byrne, Alyssa Clay-Gilmour. Association between sleep traits and risk of non-Hodgkin's lymphoma subtypes: a mendelian randomization study in the International Lymphoma Epidemiology (InterLymph) Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7415.

Importance Semaglutide, a glucagonlike peptide-1 receptor agonist (GLP-1RA), has recently been implicated in cases of nonarteritic anterior ischemic optic neuropathy (NAION), raising safety concerns in the treatment of type 2 diabetes (T2D). Objective To investigate the potential association between semaglutide and NAION in the Observational Health Data Sciences and Informatics (OHDSI) network. Design, Setting, and Participants This was a retrospective study across 14 databases (6 administrative claims and 8 electronic health records). Included were adults with T2D taking semaglutide, other GLP-1RA (dulaglutide, exenatide), or non–GLP-1RA medications (empagliflozin, sitagliptin, glipizide) from December 1, 2017, to December 31, 2023. The incidence proportion and rate of NAION were calculated. Association between semaglutide and NAION was assessed using 2 approaches: an active-comparator cohort design comparing new users of semaglutide with those taking other GLP-1RAs and non–GLP-1RA drugs, and a self-controlled case-series (SCCS) analysis to compare individuals’ risks during exposure and nonexposure periods for each drug. The cohort design used propensity score–adjusted Cox proportional hazards models to estimate hazard ratios (HRs). The SCCS used conditional Poisson regression models to estimate incidence rate ratios (IRRs). Network-wide HR and IRR estimates were generated using a random-effects meta-analysis model. Exposures GLP-1RA and non–GLP-1RAs. Main Outcomes and Measures NAION under 2 alternative definitions based on diagnosis codes: one more inclusive and sensitive, the other more restrictive and specific. Results The study included 37.1 million individuals with T2D, including 810 390 new semaglutide users. Of the 43 620 new users of semaglutide in the Optum’s deidentified Clinformatics Data Mart Database, 24 473 (56%) were aged 50 to 69 years, and 26 699 (61%) were female. The incidence rate of NAION was 14.5 per 100 000 person-years among semaglutide users. The HR for NAION among new users of semaglutide was not different compared with that of the non–GLP-1RAs using the sensitive NAION definition—empagliflozin (HR, 1.44; 95% CI, 0.78-2.68; P = .12), sitagliptin (HR, 1.30; 95% CI, 0.56-3.01; P = .27), and glipizide (HR, 1.23; 95% CI, 0.66-2.28; P = .25). The risk was higher only compared with patients taking empagliflozin (HR, 2.27; 95% CI, 1.16-4.46; P = .02) using the specific definition. SCCS analysis of semaglutide exposure showed an increased risk of NAION (meta-analysis IRR, 1.32; 95% CI, 1.14-1.54; P < .001). Conclusions and Relevance Results of this study suggest a modest increase in the risk of NAION among individuals with T2D associated with semaglutide use, smaller than that previously reported, and warranting further investigation into the clinical implications of this association.

Introduction: Follicular lymphoma (FL) is the most common indolent subtype of non-Hodgkin lymphoma. Family history is a risk factor. Genome-wide association studies (GWAS) have identified several germline variants, especially within the HLA region, to be associated with an increased risk of FL, but these variants only explain a fraction (16%) of heritability. Here, we present novel findings from GWAS of FL uncovering multiple germline genetic variants contributing to disease susceptibility. Methods: A GWAS was performed comprised of a discovery analysis in 6,508 FL cases and 64,183 controls of European ancestry followed by a replication of the most significant variants (P<5x10-7) in 2,745 FL cases and 782,226 controls from the biobanks of UK, Copenhagen Hospital, FinnGen and Mayo Clinic . At 9,253 FL cases and 846,409 FL free controls imputed genome-wide, this is the largest FL GWAS of European genetic ancestry to date. HLA alleles were imputed, and Class I and Class II signals were analysed at the amino acid level. A transcriptome wide association study (TWAS) was performed using FUSION investigate relationship to expression in GTEx and Young Finns Study in whole blood and cross-tissue . Functional annotations were done using FUMA, F-MAGMA, Open Targets and FORGE. Colocalization was conducted using CoLoC with whole blood gene expression data to understand causal variants. Mendelian randomization (MR) was performed on blood cell traits and leukocyte telomere lengths (LTL) to infer their relationships with FL genetic risk. Results: We replicated the previously published susceptibility loci within and outside the HLA region, finding two additional independent SNPs at two known loci (P < 5 x10-8) and discovered thirteen novel, genome-wide significant loci located at chromosome 2q13, 3p13, 3p24.1,3q13, 3q24.1, 4q31.21, 6p21, 6p22, 7q31, 10p14, 10q22, 10q23, 17q12, 19p13 and 20p11 with P < 5 x10-8. These SNPs were located near genes that show relevance for B-cell biology, such as BCL2L11, FOXP1, CD86, EOMES, IZKF3, PRF1, KLF2 NKX2-2 and HLA Class I and Class II genes. TWAS uncovered a role for H2AX, IGKV2-29, IMP, UBE4A and IKZF3 and provided directionality of effect for associated transcripts. Colocalization analysis corroborated a positive association with IKZF3 expression showing a robust correlation with FL risk variants (posterior probability PP4>0.7). In addition, several genome-wide significant variants in IKZF3 colocalize with eQTLs across tissues. IKZF3 (Aiolos) is part of the Ikaros family of transcription factors, critically important to the regulation of B-cell development and function. Therapeutic strategies leveraging Immunomodulatory imide drugs (IMiDs) to degrade IKZF3 have shown efficacy in multiple myeloma, and we speculate may also have potential benefits in FL by enhancing anti-tumor immunity and disrupting malignant B-cell function. Gene-set analysis showed blood and spleen to be the most relevant tissues for FL risk variants with lymphocyte activation and immune cell type differentiation genes demonstrating enrichment based on gene-ontology terms. Associated traits included allergies, respiratory diseases (e.g., asthma phenotypes), inflammatory bowel diseases, type 1 diabetes (T1D), lipid levels and commonly measured blood cell traits, with some SNPs showing evidence of colocalization with select blood traits. Interestingly, no causal association to blood traits was observed using MR; however, MR analyses did reveal a strong association with LTL. For the HLA loci, FL shows a diverse set of amino acid associations in HLA Class I and Class II genes that extends beyond what is known from autoimmune disease associations, such as rheumatoid arthritis or T1D. Our study also reveals interesting biological insights about FL susceptibility, such as a novel locus intragenic to FOXP1, an activated oncogene preferentially expressed in FL and DLBCL tumors, but rarely observed in Hodgkin's lymphoma. High levels of FOXP1 are known to result in poor survival in FL. Conclusion: This large GWAS of FL has identified multiple susceptibility variants, uncovering interesting gene candidates for further pathophysiological characterization of FL risk and B-cell development. It suggests new biological pathways and genes that could be potential leads for drug development and targeting treatment, in addition to identifying genetically high-risk populations for FL susceptibility.

Introduction: Over 80,000 new cases of Non-Hodgkin's Lymphoma (NHL) are diagnosed annually, but modifiable risk factors are largely unknown. Circadian disruption has been identified as a risk factor for several cancers, including breast and prostate cancer, and affects immune cells such as Natural Killer (NK) cells and T-helper cells. Disruptions in circadian rhythms can lead to aberrant immune cell trafficking and proliferation. Despite this biological connection, evidence linking circadian disruptions to NHL remains inconclusive. Only single Mendelian Randomization (MR) study (PMID: 32895918) has explored the causal relationship between sleep traits and overall NHL risk, without examining NHL subtypes. Studies have shown distinct risk factor profiles among NHL subtypes. Therefore, this study aims to investigate the causal relationship between sleep traits and NHL subtypes in European populations using MR. Methods: We conducted a two-sample MR analyses using genome-wide association studies (GWAS) summary data on sleep traits and NHL subtypes. The GWAS summary statistics on sleep traits were obtained from publicly available UKBiobank datasets. The sleep traits analyzed included chronotype (N=449,734), insomnia (N=237,627), sleep duration (N=446,118), daytime sleepiness (N=452,071), short sleep (N=411,934), and long sleep (N=339,926). Only independent, genome-wide significant SNPs (p < 5×10-8) were considered as valid instruments. The NHL subtype-specific summary statistics came from the InterLymph including follicular lymphoma (FL: N=6,508 cases / 64,183 controls), mantle cell lymphoma (MCL: N=1,169 cases / 61,603 controls), and Waldenström macroglobulinemia/lymphoplasmacytic lymphoma (WM/LPL: N=1,697 cases / 59,333 controls). Our primary analysis used the random-effects inverse-variance weighted (IVW) method. In addition, we employed MR-Egger to adjust for directional pleiotropy. Heterogeneity in the MR results was evaluated with Cochran's Q statistic. Results: The IVW method did not identify any statistically significant causal association between sleep traits and the risk of NHL subtypes (FL,MCL,WM/LPL), but did yield several intriguing associations. Chronotype (early rising) showed a tendency towards a marginally an increased NHL risk across subtypes [Odds ratio (OR) range: 1.07 - 2.56]. Conversely, a decreased risk was noted for long sleep (≥ 9 hours vs. 7-8 hours) [OR range: 0.19 - 0.62], insomnia [OR range: 0.72 - 0.88], and short sleep (excludes MCL) [OR range: 0.12 - 0.72]. Confidence limit for long sleep was wide due to small number of variants (N=8). The MR-Egger regression analysis did not provide evidence of significant directional horizontal pleiotropy. The F-statistics for all sleep traits were greater than 10 indicating absences of weak instrument bias. Conclusions: Our study found no statistically significant associations between sleep traits and three NHL subtypes (FL, MCL, WM/LPL) in European populations. However, we observed potential influences of chronotype, long and short sleep, and insomnia on NHL risk. These findings align with and extend previous MR study by providing subtype-specific insights. Future directions include expanding our analysis to additional NHL subtypes, generating polygenic risk scores, and conducting stratified analyses using the InterLymph population. These efforts aim to further elucidate the complex relationship between sleep characteristics and NHL risk across diverse subtypes and populations.

AbstractBackgroundWe examined neuropsychiatric symptoms (NPS) and psychotropic medication use at the midway point of data collection of the Longitudinal Early‐onset Alzheimer’s Disease Study (LEADS). We compared amyloid‐positive early‐onset Alzheimer’s disease (EOAD) participants and amyloid‐negative early‐onset non‐Alzheimer’s disease [EOnonAD]) participants across NPS domains and psychotropic medication categories.Method282 participants enrolled in LEADS were compared across diagnostic groups – amyloid‐positive EOAD (n = 212) and amyloid‐negative EOnonAD (n = 70). All participants were between ages 40 and 64 at baseline. NPS were measured with the Neuropsychiatric Inventory – Questionnaire (NPI‐Q) and Geriatric Depression Scale – Short Form (GDS‐SF). Medications were categorized into psychotropic category (e.g., antidepressants, antipsychotics, benzodiazepines). Groups were compared on NPI‐Q using binary logistic regression adjusting for sex and disease severity, on GDS‐SF using linear regression adjusting for sex and disease severity, and on psychotropic medication use using Chi square or Fisher’s exact test.ResultDemographic data are presented in Table 1. Average total NPI‐Q score was higher in EOnonAD than EOAD (p = .002, ŋp 2 = .03). Regardless of diagnostic group, informants endorsed Affective behaviors most frequently (76.2%). EOAD informants endorsed fewer Distress‐Tension behaviors (p = .02, OR = .498) and Impulse Control behaviors (p = .01, OR = .438). EOAD informants also endorsed apathy (p < .001, OR = .316), irritability (p = .02, OR = .498), and disinhibition (p = .04, OR = .476) at lower frequency than EOnonAD. GDS‐SF showed that the EOnonAD participants self‐reported more symptoms of depression than the EOAD group (p = .002, ŋp 2 = .03). (Table 2A). A minority of participants, regardless of diagnostic group, reported psychotropic medication use (35%). There was higher use in EOnonAD (38%) than EOAD (24%) (p = .03, Cohen W = .14) (Table 2B).ConclusionNPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants, despite EOnonAD being less severely impaired. LEADS continues to collect data. Future studies will examine etiologies that may be larger drivers of NPS than AD neuropathology, mediators (e.g., race, ethnicity) in the association between NPS and diagnostic group classication, compare NPS in EOAD vs. LOAD, and examine longitudinal changes in neuropsychiatric profiles.

AbstractIntroductionWe examined neuropsychiatric symptoms (NPS) and psychotropic medication use in a large sample of individuals with early‐onset Alzheimer's disease (EOAD; onset 40‐64 years) at the midway point of data collection for the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS).MethodsBaseline NPS (Neuropsychiatric Inventory – Questionnaire; Geriatric Depression Scale) and psychotropic medication use from 282 participants enrolled in LEADS were compared across diagnostic groups – amyloid‐positive EOAD (n = 212) and amyloid negative early‐onset non‐Alzheimer's disease (EOnonAD; n = 70).ResultsAffective behaviors were the most common NPS in EOAD at similar frequencies to EOnonAD. Tension and impulse control behaviors were more common in EOnonAD. A minority of participants were using psychotropic medications, and use was higher in EOnonAD.DiscussionOverall NPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants. Future research will investigate moderators and etiological drivers of NPS, and NPS differences in EOAD versus late‐onset AD.

Despite many studies of potential delirium biomarkers, delirium pathophysiology remains unclear. Evidence shows that the quality of reporting delirium biomarker studies is sub-optimal. Better reporting of delirium biomarker studies is needed to understand delirium pathophysiology better. To improve robustness, transparency and uniformity of delirium biomarker study reports, the REDEEMS (Reporting Essentials for DElirium bioMarker Studies) guideline was developed by an international group of delirium researchers through a three-stage process, including a systematic review, a three-round Delphi study, and a follow-up consensus meeting. This process resulted in a 9-item guideline to inform delirium fluid biomarker studies. To enhance implementation of the REDEEMS guideline, this Explanation and Elaboration paper provides a detailed explanation of each item. We anticipate that the REDEEMS guideline will help to accelerate our understanding of delirium pathophysiology by improving the reporting of delirium biomarker research and, consequently the capacity to synthesise results across studies.