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 Background: In metastatic cancer, Circulating Tumor cells (CTCs) are established prognostic indictors of patients (pts) less likely to respond to new lines of systemic therapy, with poor clinical outcomes, such as shorter progression free survival (PFS) and overall survival (OS). However, CTCs are typically found in specific malignancies (breast, prostate & colon), often in <20% of pts with metastatic disease, and pts without CTCs may also rapidly progress. Recently, an inflammatory pro-tumorigenic macrophage emanating from tumor stroma (i.e. Cancer associated macrophage-like cell [CAML]) was found in >90% of metastatic cancer pts, and whose phagocytic engorgement appears to correlate with poor outcomes, independent of CTCs. As CTCs and CAMLs are isolated in conjunction from a single blood sample, and both are prognostic for outcomes, we evaluated their utilization prior to induction of new systemic therapy in 6 types of metastatic cancer to model pt risk stratification based on 2 year outcomes. Methods: A prospective 2 year blind multi-institutional study was undertaken to model CTCs and CAMLs in prognosticating outcomes prior to induction of a new line of systemic therapy (n=233) in metastatic: Breast (n=60), Prostate (n=40), Pancreas (n=25), Colon (n=28), Renal Cell Carcinoma (RCC) (n=39), and Lung (n=40). Blood was filtered by CellSieveTM filters with subtypes of CTCs & hyper-enlarged CAMLs (≥100µm) enumerated. A machine learning algorithm was trained on this initial data set to develop predictive models which could stratify pt populations by risk for likelihood of PFS & OS over 2 years, including known clinical variables. Results: CTCs were absent in 80% (n=185/233) of pts, and their absence was prognostic for better PFS (HR=1.6, p=0.046), but not OS (HR=1.3, p=0.2045). In parallel, enlarged CAMLs (≥100µm) were found in 28% (n=51/185) of pts without CTCs, and were also prognostic for worse PFS (HR=2.0, p=0.0082) and OS (HR=1.9, p=0.0412). Specifically, CTCs were found in 55% (n=33) breast, 20% (n=8) prostate, 12% (n=3) pancreas, 11% (n=3) colon, 0% (n=0) RCC, and 0% (n=0) lung pts. Enlarged CAMLs were found in 45% (n=27) breast, 20% (n=8) prostate, 44% (n=11) pancreas, 44% (n=17) colon, 18% (n=7) RCC and 20% (n=8) lung pts. Overall, models indicated that ≥1 CTC (n=47) had mPFS=3.9 & mOS=14.9, while pts with 0 CTCs and ≥100µm CAMLs (n=51) had a mPFS=6.9 & mOS=13.8, and pts with 0 CTCs and <100µm CAMLs (n=134) had a mPFS=10.7 & mOS>24 months. Conclusions: These initial models confirm that both CTCs and enlarged CAMLs are prognostic indicators of worse PFS & OS. The simultaneous quantification both CTCs and CAMLs allows for more accurate pan-cancer risk stratification in an array of cancer pt populations. Additional clinical variables incorporated into the models may allow better risk subtyping and possibly forecast optimal treatment regimens. Citation Format: Daniel L. Adams, Steven H. Lin, Massimo Cristofanilli, Carolina Reduzzi, Saranya Chumsri, Martin J. Edelman, Susan Tsai, Raymond C. Bergan, Mohammed Aldakkak, Thai H. Ho, Cha-Mei Tang. Combining circulating tumor cells and cancer associated macrophage-like cells enhances risk stratification models in pan-cancer metastatic disease [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 1068.

Abstract The detection of genetic abnormalities is required during diagnostic workup and for potential individualization of therapy selection in multiple myeloma (MM) and its precursor conditions. At present, this relies on invasive bone marrow (BM) biopsies, severely limiting early detection, frequent longitudinal monitoring, and the precise selection of therapy. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect point mutations and other clinically relevant alterations. Consequently, the IMS-IMWG guidelines were recently updated to require next-generation sequencing for the classification of high-risk MM. To address these needs, we recently launched GenoPredicta, a CLIA-approved LDT that enables routine monitoring, informing diagnosis, and treatment selection by comprehensively characterizing MM genomes with whole genome sequencing (WGS) from as few as 50 circulating tumor cells (CTCs) isolated from peripheral blood (PB) or tumor cells from BM. Briefly, tumor cells are isolated from samples using fluorescence-activated cell sorting and subjected to WGS, from which copy number alterations, structural variants, and short variants (SNVs/indels) are identified using a fully automated pipeline generating physician-ready clinical reports from raw sequencing data in ∼6h. Analytical validation of GenoPredicta showed complete concordance with FISH results. Identifying alterations in therapeutic targets (e.g., BCMA, GPRC5D) for guiding MM immunotherapies is becoming increasingly important. Here, we describe GenoPredicta results from relapsed/refractory MM patients, highlighting resistance-conferring alterations that can only be detected by WGS, such as deletions in the kilo- to megabase scales that are observed in conjunction with SNVs and indels, leading to biallelic loss/inactivation of the gene, including at subclonal levels. In addition to biallelic loss of BCMA and GPRC5D in response to CAR T or T cell engager therapies, we observed similar resistance mechanisms for targets of immunomodulatory drugs, e.g., CRBN. The observation of these resistance mechanisms was consistent with patients’ clinical histories. In summary, we demonstrate that low input WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis and monitoring, with CTC-based measurements enabling comprehensive profiling of the MM genome. Crucially, this includes genetic alterations that confer resistance to therapy, allowing for both early detection of such alterations and more precise selection and guidance of therapy. The dramatically improved variant calling ability from WGS, especially in low-input CTC applications, extends to other malignancies and will gain wider adoption as sequencing costs continue to decrease. Citation Format: Bruno Paiva, Peter Voorhees, Patricia T. Greipp, Danielle Sookiasian, Julian Hess, Marisa DeMeo, Vicki Pounder, Sarah Calkins, Reid Meyer, Linda B. Baughn, Christine-Ivy Liacos, Meletios-Athanasios Dimopoulos, Alexandra Papadimou, Taouxi Konstantina, Efstathios Kastritis, Jesus Berdeja, Daniel Auclair, Valentina Nardi, Thomas Mullen, Francois Aguet, Shaji Kunnathu Kumar. Whole genome sequencing of multiple myeloma genomes with a novel clinical assay enables identification of genetic alterations underlying immunotherapy resistance [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 1067.

Introduction/Objectives: House call programs provide care for homebound patients. We conducted a case-control study to compare hospitalization and/or emergency department (ED) use by patients enrolled in a primary care house call program versus ambulatory (community-dwelling) patients. Methods: Program enrollees (cases) were matched by age and self-reported gender to community-dwelling patients (controls). The primary exposure was the combination of hospitalization and/or ED visits for 1 year before the index date (October 1, 2024). We used unadjusted and adjusted conditional logistic regression to determine differences in health care use. Results: We identified 26 cases (median [range] age, 84 [66-98] years; 16 [62%] female) and 130 controls. All cases had 4 or more chronic diseases, as compared with 87 (67%) of controls ( P = .003). A higher proportion of cases than controls had previous hospitalization and/or ED visits (84.6% vs 27.7%; P < .001). After adjusting for the number of chronic illnesses, no differences in previous hospitalization and/or ED use were identified between groups. Conclusions: Cases had more chronic illnesses and more hospitalizations and/or ED visits than community-dwelling controls. The comorbid health burden of participants in the house call program drove greater health care use and justifies a higher level of care for this medically complex patient population.

ABSTRACT Objectives To characterize the structure, resources, and educational practices of temporal bone laboratory training across ACGME‐accredited U.S. otolaryngology residency programs. Methods A national cross‐sectional survey was distributed to program directors and faculty responsible for temporal bone education. Survey domains included curriculum structure, training frequency, faculty involvement, assessment practices, and access to laboratory resources. Descriptive statistics and univariable regression analyses were performed to explore associations between program characteristics and neurotology fellowship pursuit. Results Thirty‐seven programs responded (28.2%). Laboratory structure varied widely, including longitudinal (monthly or weekly) and condensed (annual or 2–3 courses/year) formats. Programs with longitudinal sessions reported more annual lab hours than condensed formats (median 42 vs. 16 h/year, p = 0.003). All programs had access to cadaveric temporal bones (mean 2.25 ± 1.13 bones per resident/year), though five reported fewer bones than residents. The mean drill‐to‐resident ratio was 0.59, with 10.8% reporting a 1:1 ratio. Formal performance evaluation was used by 43.2% of programs. On exploratory univariable analysis, longer otology rotation duration was associated with having at least one neurotology fellow within five years ( p = 0.025). Larger resident cohort size ( p = 0.048) and older laboratory instruments ( p = 0.043) were associated with producing more than one fellow. Conclusion There is substantial variability in temporal bone education across U.S. otolaryngology training programs. Programs differ in curricula, resources, and access to cadaveric and simulation‐based training. Standardization of core components may improve educational equity and training consistency. Level of Evidence N/A.

Abstract Introduction Detecting and estimating blood volume loss are important for the diagnosis and management of life-threatening hemorrhage. There is a direct relationship between percent blood volume loss (BVL%) and falling in stroke volume (SV); furthermore, there is a direct relationship between diminishing SV and the corrected flow time of the carotid artery (ccFT). Therefore, we hypothesized that change in ccFT (ccFTΔ) would directly relate with BVL% in a phlebotomy paradigm. Materials and Methods A prospective, convenience sample of healthy volunteers was studied. Volunteers underwent blood donation protocol in a physiology lab. A wireless, wearable Doppler ultrasound system monitored ccFT during blood donation. Traditional vital signs were also measured throughout. The relationship between traditional vital signs as well as ccFTΔ were compared to BVL% using 2 mixed linear regression models. Results Data from 20 subjects and blood donations comprising 46,123 cardiac cycles are included. On average 413.5 ± 39 mL of blood were drawn representing 8.6 ± 1.6% BVL%. There was a significant and strong linear relationship between BVL% and ccFTΔ during blood draw with the regression slope demonstrating that for every 1 ms reduction in ccFT there was a 0.4% reduction in blood volume. Conclusions In healthy subjects and when blood loss is the sole mechanism for falling SV, we estimate that for every 1 ms reduction in ccFT, there is an approximate 0.4 BVL%. Validation of these results in patients with traumatic hemorrhage is underway.

PURPOSE Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The higher incidence and earlier onset of HCC in sub-Saharan Africa suggest a potential role for a genetic predisposition. This study evaluated the association of TERT -rs2242652-(A), a variant linked to lower HCC risk, with HCC in populations from Ghana, Nigeria, and Cameroon, compared with a population from the United States. METHODS The study included 537 patients with HCC: United States (n = 348), Ghana (n = 79), Nigeria (n = 43), and Cameroon (n = 67). The control group had 2,872 cancer-free individuals: United States (n = 2,399), Ghana (n = 323), Nigeria (n = 85), and Cameroon (n = 65). Whole-exome sequencing was conducted using germline DNA, and data for TERT -rs2242652 were analyzed. Odds ratios (ORs) and 95% CIs were calculated using unconditional logistic regression. Chi-square tests assessed protective allele frequencies. RESULTS In the US cohort, TERT -rs2242652 was significantly associated with lower HCC risk (OR, 0.75 [95% CI, 0.58 to 0.96]; P = .02), with an allele frequency of 18.8% (15.4% in HCC cases v 19.3% in controls). In the combined sub-Saharan African population, no significant association was observed, but there was a trend toward decreased HCC risk (OR, 0.80 [95% CI, 0.53 to 1.22]; P = .29), with an allele frequency of 12.2% (10.6% in HCC cases v 12.9% in controls). Separate analyses of Ghanaian, Nigerian, and Cameroonian populations showed similar nonsignificant trends. The protective allele frequency in the combined African populations was significantly lower than in the US cohort ( P < .0001). CONCLUSION In sub-Saharan African populations, there was a lower frequency of the HCC protective allele TERT -rs2242652 compared with European Americans. These findings underscore the importance of multiethnic genetic studies in understanding population differences in HCC risk and developing prevention strategies.

Human diseases are complex and arise from the coordinated action of multiple genes and their protein products. Genes’ behaviors extend beyond genetic variants, mutations, and differential expressions. Their coordinated activity across biological scales (molecules, cells, tissues, organs) produces emergent behaviors that shape health and disease. These emergent behaviors span time and space and are often hard to measure directly from observation when using standard experimental measurements. Yet these “hidden” or latent gene characteristics can be powerful drivers of disease. We propose a Mini-Galaxy Model (MGM), a systems-level AI-driven network framework that models cells as “mini-galaxies” composed of multilayered biological information, with each layer encoding a different dimension of genes’ behavior. Here, we delineate a strategy on how to construct and compare MGMs across health and disease and map their etiological relatedness. We also operationalize the MGM as a discovery platform for translational medicine, offering modules to allow target prioritization and editing. By reframing human diseases as the result of emergent behavior of multilayered multimode biological networks and their perturbations, the MGM yields actionable rules to streamline biomarker discovery, guide target selection and enable rational design of combinatorial interventions, and accelerate drug repurposing.

Abstract Background and Aims Stroke and systemic embolism are recognized but poorly characterized complications of atrial fibrillation (AF) and left atrial flutter (AFL) catheter ablation. Their incidence, outcomes, and procedural associations remain insufficiently defined. Methods Retrospective global registry was initiated by the European Heart Rhythm Association Scientific Committee. A secure database captured data from ablation centres worldwide on general AF and left AFL ablation activity, as well as detailed information on patients with symptomatic embolic events between 2017 and 2024. Results Overall, 204 centres reported 335 743 ablation procedures and 550 embolic events (incidence 0.16%). Centre-level rate ranged from 0% to 3.1%. Most events were cerebral (94%), followed by peripheral (5%), and combined (1%). Coronary air embolism accounted for 62% of all peripheral events. Intraprocedural events occurred in 93 patients (17%), within 72 h in 357 (78%) and beyond 72 h in 100 (22%); 128 cases (23%) were diagnosed after hospital discharge. Nonparoxysmal AF (0.23% vs 0.15%; P &lt; .001), centre experience, and ablation energy source (radiofrequency, 0.16%; cryoballoon, 0.16%; pulsed field ablation, 0.25%; laserballoon, 0.88%; P &lt; .001) were associated with embolic risk. Median NIHSS score after stroke was 4 (interquartile range, 2–9). Three-month follow-up was available for 518 patients with embolism (95%): 181 (35%) had sequelae and 16 (3%) died. Conclusions Symptomatic embolic events are infrequent but associated with significant morbidity and mortality. Most events occur early, though a substantial proportion arise later. Higher event rates were observed with laser and possibly with pulsed field ablation. A greater centre experience was associated with a lower embolism incidence.