Citations

Abstract Aims SCN5A-E1784K (c.5350G>A) is the most common variant associated with the long QT (LQTS) and Brugada syndromes (BrS). It can manifest variably as LQTS, BrS, and/or conduction disorders. This presents a challenge for risk stratification. We aimed to describe clinical and ECG characteristics and identify risk markers that associate with arrhythmic events. Methods and results We undertook a retrospective observational multicentre study of a large cohort of 231 subjects with SCN5A-E1784K from Europe, USA, and Japan. Comprehensive demographic and clinical data, including initial presentation ECG and follow-up, were collected. ‘Lethal events’ were defined as sudden death, non-fatal cardiac arrest, and documented sustained VT or VF. ‘Cardiac events’ were defined as arrhythmic syncope plus any lethal events. Clinical characteristics and ECG parameters corrected for age were investigated for association with lethal and/or cardiac events. Fourteen (6%) subjects experienced a lethal event and 45 (19%) a cardiac event. PR interval and QRS duration were associated with lethal and cardiac events. In multivariable models, both PR interval and QRS duration were associated with lethal events, but only QRS duration was associated with cardiac events. Only age-corrected QRS (rQRS) was associated with lethal and cardiac event-free survival from birth after correction for multiple testing. Conclusion Ventricular myocardial conduction appears likely to play a role in the risk of arrhythmic events in patients with SCN5A-E1784K. This provides an important opportunity for the personalization of management and has the potential to guide preventative therapies.

BACKGROUND: Transthyretin amyloidosis with cardiomyopathy is a progressive, fatal disease characterized by deposition of extracellular misfolded transthyretin (TTR) in the myocardium. Eplontersen is an N-acetylgalactosamine ligand–conjugated antisense oligonucleotide targeting hepatocyte TTR messenger RNA to reduce the production of circulating TTR. METHODS: CARDIO-TTRansform is a Phase 3, randomized, double-blind, placebo-controlled trial to assess the efficacy and safety of eplontersen in transthyretin amyloidosis with cardiomyopathy. Key inclusion criteria include histological evidence of amyloid deposits or grade 2 to 3 cardiac uptake on cardiac scintigraphy in the absence of plasma cell dyscrasia, New York Heart Association class I–III, and end-diastolic interventricular septum thickness >12 millimeters. Participants were randomized 1:1 to receive eplontersen 45 mg or placebo, administered subcutaneously every 4 weeks for up to 140 weeks, followed by a 20-week post-treatment evaluation period or open-label extension. Participants received locally available standard of care, including unrestricted use of TTR stabilizers. The primary end point is a composite of cardiovascular mortality and recurrent clinical cardiovascular events through 140 weeks. Secondary end points, in order of testing hierarchy, include changes from baseline in 6-minute walk distance and Kansas City Cardiomyopathy Questionnaire overall summary score, recurrent cardiovascular events, all-cause mortality, the primary end point in the patient subgroup receiving stabilizers at baseline, and cardiovascular mortality. Echocardiography was performed in all participants, with cardiovascular magnetic resonance imaging and technetium scintigraphy in a subset. CONCLUSIONS: CARDIO-TTRansform is fully enrolled, with 1432 randomized participants who were dosed with study drug or placebo. As the largest transthyretin amyloidosis with cardiomyopathy study to date, it will evaluate whether eplontersen improves cardiovascular outcomes in patients receiving locally available standard of care, including TTR stabilizers. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04136171. URL: http://ClinicalTrialsRegister.eu ; Unique identifier: EudraCT number 2019-002835-27.

Background Coronary flow reserve reflects microvascular function, whereas filling pressure indicates myocardial hemodynamic burden. In angina with nonobstructive coronary arteries, abnormalities in either could contribute to a supply–demand mismatch; however, their combined prognostic significance remains unclear. Methods Patients with angina with nonobstructive coronary arteries who underwent invasive coronary reactivity tests were studied retrospectively. Coronary microvascular dysfunction (CMD) was coronary flow reserve <2.5. An artificial intelligence–enabled ECG marker of elevated filling pressure (AIEFP) was applied as a scalable prognostic marker of myocardial hemodynamic stress. Associations with major adverse cardiovascular events were evaluated using Cox regression and propensity score overlap weighting. Results Among 1957 patients with angina with nonobstructive coronary arteries (median age, 51.8 years; 67.2% women), CMD+ was identified in 26.4% and AIEFP+ in 6.6%. Over 8 years, 204 patients (10.4%) experienced major adverse cardiovascular events. In nested models, both CMD (hazard ratio [HR]=1.42 [95% CI=1.13–1.78]; P =0.002) and AIEFP (HR=2.28 [95% CI=1.67–3.11]; P <0.001) remained associated with major adverse cardiovascular events after adjustment. Adding AIEFP to the base model improved model fitness (Δχ 2 =23.65, P <0.001; ΔAkaike Information Criterion=−21.7) and modestly improved discrimination (ΔHarrell concordance index=0.02, P =0.02). In a 4‐group model, adjusted risks increased in a graded manner. Overlap‐weighted analysis after covariate balance demonstrated distinct temporal risk trajectories: CMD+/AIEFP+ had the highest 1‐year risk (12.7%), and AIEFP+ had the highest cumulative 8‐year risk (57% in CMD− and 51.8% in CMD+). Conclusions CMD and AIEFP provide complementary prognostic information, with AIEFP remaining significantly associated with outcomes after multivariable adjustment. A dual‐axis framework integrating myocardial hemodynamic stress (AIEFP) and microvascular function (coronary flow reserve) may enhance risk stratification and enable identification of clinically distinct angina with nonobstructive coronary arteries phenotypes with divergent trajectories.

Abstract Purpose: Circulating tumor fraction estimate (ctFE) is a machine learning–derived composite metric of circulating tumor DNA (ctDNA) burden. We hypothesized that pre-treatment and early on-treatment ctFE could robustly risk-stratify patients with locally advanced (LA) and oligometastatic non–small cell lung cancer (NSCLC) treated with radiotherapy (RT). Experimental Design: In a prospective phase II clinical trial (NCT03916419), 26 patients with unresectable stage IIB to IIIC NSCLC received magnetic resonance (MR)-guided hypofractionated chemoradiotherapy (chemoRT) followed by immunotherapy. Plasma ctDNA was profiled at baseline and mid-treatment (days 10–14) to derive ctFE and maximum variant allele frequency (Max VAF). A burden-based ctFE threshold derived from baseline samples was applied unchanged to mid-treatment samples and validated in two external cohorts: LA NSCLC treated with chemoRT (LA-RW; n = 94) and oligometastatic NSCLC treated with RT (OM-RW; n = 309). Results: Pre- and mid-treatment ctFE burden strongly stratified overall survival (OS) and progression-free survival (PFS), outperforming Max VAF and ctFE detectability. The baseline ctFE was prognostic for OS (HR 5.93, P = 0.005) and PFS (HR 11.08, P &lt; 0.001) and remained significant at mid-treatment (OS: HR 7.08; PFS: HR 12.06; both P &lt; 0.001). Early ctFE dynamics defined three molecular response groups with OS separation (median OS 60.8 vs. 13.0 vs. 2.9 months; P &lt; 0.001). ctFE remained associated with survival in both validation cohorts. Conclusions: Early ctFE derived from a clinically available, tumor-naïve ctDNA assay enables noninvasive risk stratification in LA and oligometastatic NSCLC treated with RT, supporting its use as a practical biomarker for precision treatment adaptation.

Abstract We present chromosome-level, phased diploid genome assemblies of two widely used human fibroblast cell lines: BJ (46,XY) and IMR-90 (46,XX). Using Oxford Nanopore, PacBio HiFi, and Hi-C sequencing data, we generated assemblies spanning 5.9 and 6.0 Gbp with diploid quality values exceeding QV 60. To validate structural integrity, we developed KaryoScope, an alignment-free tool for generating computational karyograms from k-mer feature databases. We identify &gt;50 000 structural variants relative to T2T-CHM13v2.0, the majority of which are heterozygous and cell-line-specific. Combining reference-based and de novo gene annotation, we uncover a previously unreported 1 Mbp homozygous duplication at the 16p11.2 locus in BJ, demonstrating that even karyotypically normal cell lines can harbor clinically relevant submicroscopic rearrangements. We show that mapping publicly available short-read, RNA-seq, and ChIP-seq data to sample-matched diploid assemblies substantially improves read alignment and enables haplotype phasing of 23%–28% of short reads. The BJ and IMR-90 assemblies and associated variant calls are publicly available as a resource for the research community.

The 6th edition of the WHO Classification of Breast Tumours introduces both major and minor changes based on recent advances in our understanding of breast biology, developments in diagnostic modalities, identification of specific molecular targets and new treatment regimens necessitating modifications to pathology reporting and tumour biomarker categorisation. This review summarises the main changes that strive towards a classification of global relevance. In invasive carcinoma, predictive factors increasingly inform modern breast cancer treatment. The 6th edition provides an update on HER2 reporting categories following the DESTINY‐Breast 04 and 06 trials. Terminologies used to classify invasive tumours are clarified, with the term ‘variant’ now reserved for molecular/genetic alterations. Invasive lobular carcinoma (ILC) with extracellular mucin is recognised as a new diagnostic entity with prognostic implications. The diagnosis of mucinous carcinoma (MC) is reserved for mucin secreting carcinomas with grade 1 or 2 morphology and a favourable biomarker profile. The diagnosis of malignant phyllodes tumours requires only four of the original five adverse histological criteria. Classification of neuroendocrine tumours (NETs) is revised, recognising that the unified model, promoted in the 5th edition, is difficult to apply to the breast. New approaches to the classification of adenomyoepithelioma are discussed but the 5th edition system is broadly retained. A new section on ‘Small Diagnostic Samples’ outlines the merits of non‐operative biopsy diagnosis, the B coding system and the importance of multidisciplinary review. Changes to diagnostic practice and the emerging role of artificial intelligence, with advantages and challenges, are discussed in a new section on ‘Digital Pathology’.

Abstract Purpose: In RET-rearranged non–small cell lung cancer (NSCLC), treatment options after first-generation selective RET inhibitors (SRI) are limited, and the value of SRI retreatment remains unclear. This study evaluates outcomes of SRI retreatment. Experimental Design: This multicenter retrospective study included patients with advanced RET-rearranged NSCLC who received ≥2 SRI-based therapy lines. Of 411 SRI-treated patients, 41 (10%) underwent SRI retreatment. Outcomes included objective response rate (ORR), progression-free survival (PFS), 6-month PFS, time to treatment failure, adverse events (AE). Results: Among 41 patients, 14 (34%) discontinued the initial SRI because of toxicity and 27 (66%) because of progression. After discontinuation for toxicity, all switched to an alternate SRI, achieving an ORR of 67%, median PFS of 9.9 months, and 6-month PFS of 80.3%. AEs reoccurred in nine patients (64%), with grade ≥3 AEs in 3 (21%) who switched at full dose. Among patients who discontinued because of progression, SRI monotherapy (n = 13) achieved an ORR of 23%, median PFS of 7 months, and 6-month PFS of 61.5%. Benefit was observed in patients with brain-only or oligoprogressive disease or dose reduction on first SRI. Combination therapy (n = 14; targeted agents, n = 11; chemotherapy, n = 3) achieved an ORR of 39%, median PFS of 4 months, and 6-month PFS of 27.3%. Conclusions: Same-class SRI switch after toxicity is feasible and clinically active but warrants cautious, dose-adjusted switching to mitigate toxicities. The efficacy of SRI rechallenge after progression seems limited overall. However, selected patients, such as those with brain-only or oligoprogressive disease, may derive benefit.

Abstract Background: Personalizing chemoradiotherapy (chemoRT) for locally advanced non-small cell lung cancer (LA-NSCLC) is limited by the lack of early biomarkers that inform response during treatment. Current circulating tumor DNA (ctDNA) molecular residual disease assays predict post-treatment outcomes but lack mid-treatment utility. ctDNA burden estimation has traditionally relied on variant-centric metrics such as maximum variant allele fraction (Max VAF), which rely on mutation-specific signals and may be confounded by histology-dependent shedding variability, allelic imbalance, and clonal hematopoiesis. Here we present circulating tumor fraction estimate (ctFE), a machine-learning composite score that integrates VAF distributions, copy-number alterations, and germline B-allele frequency deviations to approximate global tumor burden using a widely available, tumor-naïve clinical platform. Methods: A burden-based ctFE threshold was derived using pre-treatment plasma from a prospective phase II clinical trial of MR-guided hypofractionated chemoRT (LA-WU, n=26), locked, and applied unchanged to early mid-treatment samples (day 10-14). To test scalability and generalizability, its prognostic performance was validated in two real-world cohorts: 94 LA-NSCLC patients receiving definitive chemoRT (LA-RW) and 309 oligometastatic NSCLC patients receiving consolidative RT (OM-RW). ctFE and Max VAF were compared as continuous predictors across cohorts. Results: ctFE consistently outperformed Max VAF. In LA-WU, pre-treatment ctFE was associated with overall survival (OS HR=1.15, p=0.04) and progression-free survival (PFS HR=1.84, p=0.009), whereas Max VAF was not. Mid-treatment ctFE remained prognostic for PFS (HR=1.14, p=0.026). Early ctFE dynamics defined three molecular response groups with marked OS separation: consistently low, responder, and nonresponder groups (median OS 60.8 vs 13.0 vs 2.9 months, respectively; p&lt;0.001). In multivariable models including both biomarkers, higher ctFE remained independently associated with worse survival in LA-RW (OS HR=1.88, p=0.010) and OM-RW (OS HR=1.37, p=0.040; PFS HR=1.45, p=0.008), whereas Max VAF did not. The locked ctFE threshold stratified OS across all cohorts (LA-WU HR=5.93; LA-RW HR=9.08; OM-RW HR=2.26; all p&lt;0.001). Conclusion: ctFE provides clinically meaningful pre- and mid-treatment risk stratification and consistently outperforms Max VAF across locally advanced and oligometastatic NSCLC cohorts. We show that ctFE is a biologically informative, clinically generalizable and scalable ctDNA burden metric measurable using a tumor-naïve, off-the-shelf assay, supporting its practical utility in biomarker-adapted radiotherapy strategies. Citation Format: Ayesha Hashmi, Jessica Linford, Pradeep S. Chauhan, Kaushal Parikh, Rotem Ben-Shachar, John Guittar, Malvika Pillai, Jyoti Patel, Matteo Bergsagel, Nicholas P. Semenkovich, Kenneth R. Olivier, Sean S. Park, Dawn Owen, David M. Routman, Katie N. Lee, Alex D. Sherry, Aaron S. Mansfield, Daniel Morgensztern, Ramaswamy Govindan, Clifford G. Robinson, Carmen Bergom, Saiama N. Waqar, Bruna Pellini Ferreira, Gregory R. Vlacich, Aadel A. Chaudhuri. Early ctDNA quantification by ctFE outperforms Max VAF for survival stratification across locally advanced and oligometastatic NSCLC treated with radiotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1183.

Abstract Background: Spatial cellular ecosystems in the tumor microenvironment (TME) form dynamic signaling hubs that critically influence cancer disease progression and response to therapy, including response to immune checkpoint inhibitors (ICIs). However, tumor sampling bias and the impracticality of acquiring serial tumor biopsies have made it challenging to profile the TME clinically. To address this challenge, we developed Liquid EcoTyper, a multi-analyte AI framework to quantify TME spatial cellular ecosystems—termed spatial ecotypes (SEs)—noninvasively from cell-free DNA (cfDNA) methylation data. Methods: In previous work, we discovered nine spatial ecotypes, including SEs associated with ICI response (e.g., SE7 with benefit, SE4 with resistance), and quantified them from 1,249 bulk tumor RNA-seq profiles of melanoma, non-small cell lung cancer (NSCLC), and bladder cancer (BC) patients (Cancer Res (2025) 85 (8_Supplement_1): 153). Here we trained Liquid EcoTyper, an interpretable deep learning model, to transfer SE profiling to cell-free DNA using CpG methylation profiles. Performance was quantified using simulated and real data, including methylation profiles (EM-seq) of plasma cfDNA paired with tumor biopsy-derived SE levels determined by EM-seq (n=20 pairs) or 10x Visium (n=15 pairs). Clinical outcome prediction was evaluated using pretreatment plasma from patients treated with ICI alone (n=78 melanoma pts), chemotherapy and ICI (n=25 NSCLC pts), and enfortumab vedotin and ICI (n=10 localized muscle-invasive BC (MIBC) pts). Tumor mutational burden (TMB), tumor PD-L1, or circulating tumor DNA (ctDNA) were profiled as a comparator where possible. Results: We observed striking concordance between plasma-derived SE levels and tumor biopsy-confirmed SE levels from the same patients, demonstrating that liquid biopsy analysis of cfDNA methylomes can recapitulate TME spatial biology. Underscoring specificity, no reliable SE signal was detectable from peripheral blood mononuclear cells. In pre-ICI plasma, liquid SE levels were significantly associated with ICI-based response (SE7) versus resistance (SE4) in patients with melanoma, NSCLC, and MIBC, with a mean cross-cancer area under the curve (AUC) of 0.87 for SE7 (range 0.8-0.97) and 0.81 for SE4 (range 0.76-0.85)—far surpassing TMB, tumor PD-L1, and ctDNA in evaluable patients, both in binary analyses of response and multivariable models of survival. Our results also showed potential to predict pathologic complete response in the neoadjuvant setting. Conclusion: Liquid EcoTyper is a scalable noninvasive AI-based framework for spatiotemporal assessment of the TME. By enabling TME-informed risk stratification without surgical biopsies, Liquid EcoTyper has potential to enable more precise and actionable decision making in patients with solid tumors. Citation Format: Erin L. Brown, Wubing Zhang, Abul Usmani, Noah Earland, Ayesha Hashmi, Chibuzor Olelewe, Anushka Viswanathan, Pradeep S. Chauhan, Minji Kang, Chloé B. Steen, Hyun Soo Jeon, Susanna Avagyan, Irfan Alahi, Nicholas P. Semenkovich, Matteo Bergsagel, Janella C. Schwab, Chloe M. Sachs, Faridi Qaium, Peter K. Harris, Antonella Bacchiocchi, Qingyuan Cai, Andrew J. Gentles, Rondell P. Graham, Peter C. Lucas, Ryan C. Fields, Jacob J. Orme, Aaron S. Mansfield, Mario Sznol, Ruth Halaban, David Y. Chen, Aaron M. Newman, Aadel A. Chaudhuri. Liquid biopsy profiling of the tumor microenvironment to determine response to immunotherapy regimens across solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 94.