Citations

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<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<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 Purpose Consensus recommendations and guidelines for reporting quantitative research in health professions education (HPE) research are lacking. This study synthesizes available quantitative reporting recommendations and guidelines to present a harmonized framework and derive quantitative standards for reporting HPE research. Method The authors identified existing standards, recommendations, and guidelines from peer-reviewed scientific journals in medicine, education, and social sciences by searching PubMed, Web of Science, and Google from August 2006 through April 2025. The authors also requested input from experts in HPE (scholars and journal editors) via electronic communication over 6 months (November 2024 to April 2025). The articles identified were then used to synthesize and generate an initial list of standards for reporting quantitative research in HPE. Two authors reviewed each article to rate its alignment with HPE research. All authors independently evaluated the full list of standards and discussed them as a group for their relevance and alignment for reporting in HPE; all authors also made recommendations for each standard (to report as is, report but modify, or drop). The group subsequently reviewed and collectively reached consensus on the final set of quantitative reporting standards. Results The authors reviewed a total of 34 articles, with 19 identified as having alignment with HPE quantitative research standards. Mean interrater agreement among author pairs was 98% (kappa = .96). Authors initially generated 40 reporting standards, of which 18 (45%) were modified and 1 (3%) was identified to be dropped. The final set of quantitative guidelines consisted of 39 standards, with each standard nested in one of 28 topic areas. Conclusions The quantitative reporting standards identified in this study provide guidance to ensure rigor in reporting expectations for HPE research. These standards may also facilitate critical appraisal of articles and enhance the quality and impact of quantitative HPE research.

Abstract Professional identity is defined as the attitudes, behaviors, values, and experiences by which individuals define themselves in a professional role and is influenced by socialization during training and in the workplace. As professional identity develops and is integrated with one's personal identities, it allows an individual to think, act, and feel like a member of their chosen profession and to develop a sense of meaning, confidence, and satisfaction in their work. Conflicts may arise due to perceived differences between one's professional identity and the collective identity of the profession, resulting in stress, burnout, and attrition, all of which can negatively impact patient care and the collective identity of the genetic counseling profession. Using Social Identity Theory (SIT) as a theoretical framework to develop the semi‐structured interview protocol, recorded interviews were conducted with 50 genetic counselors who were purposefully sampled to ensure diversity of personal demographics (gender, race/ethnicity, sexual orientation, disability, and caregiver status), as well as years, settings, and roles in genetic counseling practice. Transcripts were coded and subjected to codebook thematic analysis using NVivo. Genetic counselors described their professional identity in terms of who they are (characteristics and attributes), what they do (actions and skills), and what they have (training and knowledge). The majority of participants had a multidimensional perspective of what it means to be a genetic counselor, noting the transferability of their skills to a broad set of roles and settings, which supported their sense of professional identity, particularly for those who were no longer seeing patients. Yet many expressed tension with the collective identity of the profession. Expanded opportunities for genetic counselors to work in new settings and roles require review and revision of key professional documents to ensure they are reflective of the collective identity of the genetic counseling profession.

Background: Pancreatitis significantly alters the microbial composition of the oral and intestinal compartments, causing dysbiosis that may contribute to disease mechanisms and potentially serve as a basis for diagnosis or treatment. Objective: To determine whether the oral or gut microbial signature can classify chronic pancreatitis (CP). Methods: Stool samples (n=707) were collected from participants in the Prospective Evaluation of Chronic Pancreatitis for Epidemiologic and Translational Studies (PROCEED). Samples were distributed among 200 healthy (HC), 310 CP, 49 acute pancreatitis (AP), and 148 recurrent acute pancreatitis (RAP). In addition, saliva samples were collected for a subset of participants (n=156). Whole genome sequencing was performed to assess microbiome composition. Machine learning algorithms were utilized to identify a signature with microbial features predictive of CP. Results: Gut alpha diversity was significantly decreased in AP, RAP, and CP compared with HC, with CP exhibiting the lowest diversity. In contrast, oral microbial diversity showed no significant variation across groups. Beta diversity analysis revealed distinct gut microbiome compositions between HC and pancreatitis subtypes, with CP showing the most pronounced differences. Random forest models using gut microbial species demonstrated robust predictive performance for CP using a minimum of 10 species (Area under the curve—AUC: 0.834; accuracy: 0.774). Despite similarities in gut microbiome composition across pancreatitis subtypes, a unique gut microbial signature for CP was identified highlighting the microbiome’s potential in CP diagnosis. Conclusion: Our study reveals a gut microbial signature predictive of CP using machine learning models in a large US multi-institutional cohort.

Variants in TMEM106B and GRN , which encode lysosomal proteins, interact through unknown mechanisms to increase the risk of age-related cognitive decline and neurodegeneration. Here, we show that these variants converge on a single molecular intermediate: the cleaved intra-lysosomal fibril core of TMEM106B, a precursor to amyloid fibrils that accumulate in the aging brain. A protein-coding TMEM106B risk variant (p.T185) drives fibril core accumulation by impairing its degradation and GRN risk variants amplify this effect. Mice over-expressing the fibril core develop hallmarks of neurodegeneration, and cryo-electron tomography reveals intra-lysosomal fibrils in cultured neurons, mice, and diseased human brain. In GRN -mutation carriers, in whom fibril burden is greatest, fibrils extrude through ruptured lysosomal membranes. These findings identify intra-lysosomal TMEM106B fibrillization as a convergent neurodegeneration mechanism and potential therapeutic target.

PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes ( P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts ( P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS. Decision analysis demonstrated that iCPSS could refine the optimal timing of allogeneic transplantation at the individual level; compared with conventional prognostic tools, iCPSS-based decision modeling changed transplantation strategy in 31% of cases, resulting in a significant gain-in-life expectancy for eligible patient population ( P < .001). A federated learning platform was implemented to enable continuous, privacy-preserving model update across multiple centers. CONCLUSION Molecular information improves CMML classification and prognostication, supports more effective clinical decision making, and potentially refines the design of clinical trials.

Objective: The identification of reliable biomarkers in trauma patients (pts) remains a clinical challenge. Nucleosomes, which are DNA wrapped around histone protein cores, have been used as reliable markers for quantification in sepsis, acute respiratory distress syndrome, and lymphoma. We hypothesized that: 1) levels of circulating nucleosomes quantified after traumatic injury, specifically histone H3.1 and its citrullinated R8 posttranslation modification (H3R8 Cit), would be increased after trauma and 2) that levels of circulating nucleosomes would be further, increased in pts who went on to develop venous thromboembolism (VTE), as these nucleosomes may be clot-enhancing mediators. Methods: Trauma pts presenting to a Level I trauma center were evaluated for inclusion in a prospective case-cohort study, and citrated blood samples were collected within 12 hours of injury. Pts were followed for up to 90 days and VTE occurrence was confirmed via autopsy or imaging. Pts who developed incident, symptomatic VTE, and those who did not develop VTE were selected at a 1:3 ratio. The effect of trauma was assessed by comparison with healthy volunteer samples. Circulating nucleosomes were quantified using Nu.Q H3.1 and Nu.Q H3R8 Cit assays. Data are presented as median [interquartile range] or n (%), with Wilcoxon Rank-Sum or chi-squared test performed between trauma pts who developed symptomatic VTE versus those who did not, with a P value < 0.05 as statistically significant. Results: A total of 639 trauma pts were analyzed [51 years (33, 65), 71.0% male, 94.1% blunt, injury severity scores 17 (9, 27)]. Both H3.1 [359.7 (58.4, 1769.3) vs. 21.5 (15.3, 26.6) ng/mL, P < 0.001] and H3R8 Cit levels [209.4 (45.4, 665.5) vs. 22.3 (16.2, 28.9) ng/mL, P < 0.001] were greater in trauma pts than in 10 healthy volunteers. The 160 pts with VTE were then compared with 479 without VTE. VTE pts had a median time to VTE of 8.5 days, with 91 developing symptomatic deep venous thrombosis, 48 with pulmonary embolism, and 21 with both deep venous thrombosis and pulmonary embolism. No significant differences were found in age, sex, or mechanism between pts with or without VTE. However, VTE pts had higher injury severity scores [24 (14, 34), 14 (9, 24), P < 0.001] and body mass index [29.1 (24.3, 34.2), 27.6 (24.2, 32.0) kg/m 2 , P = 0.037]. A greater percentage of VTE pts underwent surgery requiring general anesthesia (53.1%, 34.0%, P < 0.001) and received blood transfusions within 24 hours of injury (51.9%, 24.0%, P < 0.001). H3.1 levels were significantly greater in trauma pts who developed VTE compared with those who did not [828.4 (112.0, 3186.5), vs. 276.7 (50.3, 1237.0) ng/mL, P < 0.001], as were H3R8 Cit levels [350.4 (77.4, 729.5), vs. 189.2 (40.8, 632.6) ng/mL, P = 0.005]. No differences in levels of H3.1 and H3R8 Cit were found between early (diagnosed day 0–7 after injury) and late (diagnosed > day 7) VTE. Conclusions: Levels of the H3.1 and H3R8 Cit nucleosomes are elevated early after traumatic injury, especially in those who developed VTE. These findings underscore the importance of understanding the pathophysiology of nucleosomes in inducing VTE and their role as biomarkers

Abstract Objectives Minimally invasive cardiac surgery (MICS) offers significant advantages over conventional sternotomy, including reduced trauma and faster recovery. Preoperative planning is crucial, with computed tomography (CT) emerging as an essential imaging tool. This systematic review aims to evaluate CT’s role in MICS planning, focusing on imaging protocols, surgical guidance, and patient outcomes. Methods This study included studies published between January 2003 and January 2025 that examined the role of CT imaging in planning minimally invasive valvular heart surgery. A comprehensive search was conducted in Medical Literature Analysis and Retrieval System Online (MEDLINE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Excerpta Medica Database (EMBASE) using predefined keywords and medical subject headings (MeSH) terms related to CT imaging, angiography, minimally invasive surgery, robotic surgery, aortic valve surgery, and mitral valve surgery. Results Initial search found 378 studies, and 17 studies were included in the review. The studies highlight CT’s value in assessing surgical feasibility, vascular access, and risk stratification. CT aids in selecting arterial cannulation sites, guiding aortic occlusion strategies, and optimizing port placement. It also identifies contraindications, such as extensive atherosclerosis and anatomical abnormalities, that may necessitate sternotomy. Conclusions Current evidence underscores CT’s critical role in optimizing MICS planning and enhancing patient safety.