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ABSTRACT Biological aging greatly impacts the body’s ability to handle glucose, and represents a major risk factor the development and progression of type 2 diabetes (T2D). Nonetheless, despite advances in cellular senescence research and the development of new senolytic therapies, the heterogeneity of cellular senescence in the human endocrine pancreas, as well as its roles in normal aging, remains to be elucidated at the single-cell level. Here, we performed single-cell–resolved spatial proteomics and transcriptomics on intact pancreas from 26 donors (ages 20–80) and multiplexed single-cell RNA sequencing and functional assays on dispersed islets from 14 donors (ages 34–69). We identify two discrete SnC subpopulations distinguished by relative expression of CDKN1A and CDKN2A. CDKN1A ⁺ senescent cells (SnCs) exhibit loss of β-cell identity, impaired insulin secretion, and a proinflammatory SASP associated with increased islet immune infiltration. In contrast, CDKN2A ⁺ SnCs retain transcriptional identity and functional competence, with lower inflammatory signaling. Together, these findings identify heterogeneous and functionally divergent senotypes in the human pancreas, distinguishing an adaptive ( CDKN2A ⁺) from a maladaptive ( CDKN1A ⁺) senescence program, thus providing a mechanism-guided framework for senescence-targeted therapies in T2D.

TPS3686 Background: Currently, there are no biomarkers validated prospectively in randomized studies for resected colon cancer (CC) to determine need for adjuvant chemotherapy (AC). However, circulating tumor DNA (ctDNA) represents a highly specific and sensitive approach (especially with serial monitoring) for identifying minimal/molecular residual disease (MRD) post-surgery in CC patients (pts), and may outperform traditional clinical and pathological features in prognosticating risk for recurrence. CC pts who do not have detectable ctDNA (ctDNA–) are at a much lower risk of recurrence and may be spared the toxicities associated with AC. Furthermore, for CC pts with detectable ctDNA (ctDNA+) who are at a very high risk of recurrence, the optimal AC regimen has not been established. We hypothesize that for pts whose CC has been resected, ctDNA status may be used to risk-stratify for making decisions about AC. Methods: In this prospective phase II/III trial, up to 1,912 pts with resected stage IIB, IIC, and III CC will be enrolled. Based on the post-operative ctDNA status using personalized and tumor-informed assay (Signatera, bespoke assay), those who are ctDNA– (Cohort A) will be randomized to immediate AC with fluoropyrimidine (FP)+oxaliplatin (Ox) for 3-6 mos per established guidelines v serial ctDNA monitoring. Patients who are ctDNA+ post-operatively, or with serial monitoring (Cohort B), will be randomized to FP+Ox v more intensive AC with addition of irinotecan (I) for 6 mos. One cycle of chemotherapy is allowed while awaiting ctDNA testing results for cohort assignment. The primary endpoints for Cohort A are time to ctDNA+ status (phase II) and disease-free survival (DFS) (phase III) in the immediate v delayed AC arms. The primary endpoint for Cohort B is DFS in the FP+Ox v FP+Ox+I arms for both phase II and phase III portions of the trial. Secondary endpoints include prevalence of detectable ctDNA post-operatively, time-to-event outcomes (overall survival and time to recurrence) by ctDNA status, and the assessment of compliance to adjuvant therapy. Biospecimens including archival tumor tissue, as well as post-operative plus serial matched/normal blood samples, will be collected for exploratory correlative research. Active enrollment across the NCTN started in June 2022 with CCTG sites joining in August 2023. Accrual is 1,123/1,912 (as of 1/20/2026). *Drs. Dasari and Lieu contributed equally to the development of this trial. Clinical trial information: NCT05174169 .

TPS10628 Background: Despite advances in cancer treatment, a lack of established population-level cancer screening strategies for early detection across cancer types contributes to cancer-related mortality. Emerging MCED liquid biopsy tests represent a screening approach with potential to enable detection of multiple malignancies at earlier stages in the disease process. We previously showed that an initial classifier based on a genome-wide methylome enrichment platform detected 12 cancer types, including early-stage, low-shedding tumors (Park et al. AACR 2023. Abs 1030). However, clinical performance of the platform has not been evaluated prospectively. Thus, the CAMPERR study (NCT05366881) was designed to train and validate a cell-free methylated DNA immunoprecipitation and high throughput sequencing (cfMeDIP-seq)-based test for detection and differentiation of 20 pre-selected cancer types, representing 93% of annual cancer incidence and 88% of annual cancer deaths. Longitudinal follow-up for a subset of participants with lung cancer will enable training and validation for MRD-based recurrence prognostication. Methods: This case-control study is enrolling participants with 20 different pre-specified cancer types (n=2400) and those without known cancer (n=3900). Eligible participants are ≥40 years of age and not receiving treatment for cancer at the time of enrollment or taking any demethylating/hypomethylating agents. Cases include individuals with newly diagnosed (≤120 days), untreated cancer or recurrence of a cancer originally diagnosed >5 years ago. Cancers of interest are stage I-IV bladder, brain, breast, cervical, colorectal, endometrial, esophageal, gastric, head and neck, hepatobiliary, leukemia, lung, lymphoma, multiple myeloma, ovarian, pancreatic, prostate, renal, sarcoma, and thyroid. Participants with stage I-III lung cancer will have clinical follow-up and blood draws after completion of first-line treatment, every 3 mo for the first year thereafter, and every 6 mo for an additional 2 years. Eligible control participants have not been diagnosed with invasive cancer in the last 5 years and will have clinical follow-up ≥12 mo from enrollment to evaluate cancer status. Liquid biopsy results will not be returned to clinicians or participants. The primary objective is cancer detection. Secondary objectives include detection of specific cancer types, identification of the tissue of origin, and prognostication of clinical outcomes (eg, recurrence-free survival, overall survival). CAMPERR is currently enrolling at 15 sites. As of December 3, 2025, 2108 of 2400 cancer cases have been enrolled, including prostate (n=225), lung (n=216), colorectal (n=211), breast (n=193), and pancreatic (n=192); controls are fully enrolled. Clinical trial information: NCT05366881 .

e13661 Background: The process of data abstraction and curation represents a significant proportion of clinical trial costs, requiring up to $30,000 per patient depending on the data complexity. Research variables such as stage, performance status (PS), and cancer disease status are typically present in the electronic health record (EHR) in free text but require abstraction for research use. Structuring these real-world data (RWD) in an exportable format utilizing minimum common oncology data elements (mCODE) could reduce the need for abstraction and the potential for erroneous transcription that has been shown to be 5.51-7.72% in a meta-analysis. We assessed the feasibility, availability, and accuracy of RWD for use across Alliance for Clinical Trials in Oncology sites by comparing RWD to matched electronic case report form data (CRF data) at 2 sites where EHR-integrated tools collect structured RWD for all solid tumor patients. Methods: Stage, PS, and cancer disease status (CDS) were extracted from the EHR as RWD and from eCRFs for 100 patients enrolled in National Clinical Trials Network trials across multiple disease sites from 2022 through 2025. Data from baseline and day 1 of cycles 1-4 were compared (500 encounter timepoints). Results: Stage, PS, and CDS were available from RWD more often than CRFs (85 vs 70 / 100 patients, 436 vs 416 / 500 encounters, and 345 vs 83 / 500 encounters respectively). When stage was present in both (n = 58), there were 5 mismatches (8.6%). PS had 22 mismatches (4%) and CDS had 45 mismatches (11.4%). After correcting for differences in CRF vs RWD definitions, CDS mismatches dropped to 1.2% (n = 4). Discordance between RWD and CRF data was related to differences in the timepoint of data collection (e.g., systemic staging scans completed after the initial consult), CRF data obtained from other EHR notes (e.g., oncology research nurse notes containing PS), inherent discordance between RWD and CRF data choices (e.g., responding vs complete or partial response), and failure to update EHR data capture tool fields. RWD were available 21 days (median) before CRF data. Conclusions: Our results suggest that RWD captured directly within clinical notes match CRF data, are more often present, and are available sooner. RWD could serve as a data source for trials, decreasing the need for manual curation and cost. Although some discordance exists, overall rates are low and close to the published error rate for abstraction.

e13660 Background: We previously showed success with collection of structured data elements within the electronic health record using the minimum common oncology data elements (henceforth, mCODE tool) supported by soft-stop close visit validation (CVV) and staff support interventions in a limited cohort. Since the additional interventions are resource-intensive and difficult to apply across an entire department, we therefore implemented a department-wide roll-out supported by the least resource-intensive interventions while monitoring uptake. Methods: The mCODE tool collects five data elements: stage, disease status, performance status, intent of treatment, and intent to change therapy. The Department of Oncology providers received education on the mCODE tool and were asked to implement use at a faculty meeting; soft-stop CVV was enabled at that time. The percentage of data captured for each data element was collected from the notes of providers who did not participate in prior pilots for the 4 months post-implementation. mCODE tool usage was defined as entry of at least one data element except stage (as stage has long been a structured data element in Epic, can be entered independently of the mCODE tool, and many providers were entering stage prior to mCODE tool introduction). Results: 86 MDs and 20 APPs for a total of 106 providers were included, resulting in 14,973 visits and 8,745 unique patients. 73.6% of providers (n =78) utilized the mCODE tool. Of those who utilized the tool, median overall data capture across the four data elements was 24.0%. 22.6% of providers (n =24) achieved > 80% overall data capture and 32.1% (n =34) had over 50% overall data capture despite minimal intervention. 75.6% of MDs (n = 65) utilized the tool with a median data capture of 16.3% compared to 65% of APPs (n = 13) with a median data capture of 90.3%. Rates of data capture for individual data elements were similar. Conclusions: Use of soft-stop CVV appears to drive utilization of the mCODE tool but is insufficient to promote > 80% data capture for most providers without more intervention. Supportive interventions such as individualized assistance with incorporation into existing templates and directed communication from leadership remain necessary to promote use of structured data elements and will be implemented in sequence to understand how we achieve the target data capture ( > 80%) at scale.

Context.— In 2016, the College of American Pathologists published an evidence-based guideline to develop recommendations for interpretive diagnostic error reduction in anatomic pathology. New evidence, together with evolving practice environments and the continued adoption of digital technologies, including artificial intelligence, has prompted a review of the guideline. Objective.— To assess evidence published since the release of the original guideline and update evidence-based recommendations for the reduction of diagnostic errors. Design.— The College of American Pathologists, in collaboration with the Association of Directors of Anatomic and Subspecialty Pathology, convened a panel of experts to update the 2016 evidence-based guideline. A systematic literature review was conducted to address 4 key questions. Using the Grading of Recommendations Assessment, Development and Evaluation approach, recommendations were created based on the available evidence, certainty of that evidence, and key judgments as defined in the Grading of Recommendations Assessment, Development and Evaluation framework. Results.— Two strong recommendations and 4 good practice statements were established for the reduction of diagnostic error. Conclusions.— The expert panel recommends that anatomic pathologists implement procedures for the review of pathology cases to detect and correct potential interpretive errors to improve patient outcomes.

9524 Background: Unresectable melanoma in-transit metastases (ITM) can pose a significant clinical challenge. Our recently published data comparing first-line treatments for ITM, isolated limb infusion or perfusion (ILI/ILP), immune checkpoint inhibitors (ICI) and intralesional talimogene laherparepvec (TVEC), found superior outcomes with TVEC. However, TVEC was used more often in patients with lower disease burden and earlier stage (IIIB vs. IIIC/D). Therefore, we sought to better investigate these differences with a propensity score-matched (PSM) analysis. Methods: A multi-institutional, international IRB- approved retrospective analysis was conducted for unresectable melanoma ITM from 2016-2022. PSM analysis comparing first-line ILI/ILP, ICI, and TVEC for was performed. Patients were matched for stage, number of ITM, anatomical site, CLND status, gender and age. Kaplan-Meier curves (OS, PFS, DMFS) and Cumulative incidence function (MSS) were used to visualize time-to-event outcomes in the PSM cohort, though both methods do not account for the matched structure. Results: 274 patients were identified, 120 female/154 male; 96 treated with ILI/ILP, 111 with ICI, and 67 with TVEC. Median follow-up was 40 months (range, 1-80). PSM was performed and identified 36 TVEC–ICI pairs and 27 TVEC–ILI pairs. These were combined resulting in a final cohort of 108 observations (45 TVEC, 36 ICI and 27 ILI). The groups were well balanced. No statistical difference was found for metastasis-free survival (DMFS), progression-free survival (PFS), melanoma-specific survival (MSS), and overall survival (OS) between treatment modalities. TVEC was associated with significant improvement in local PFS (median was 2.2 years (y) for ILI/ILP, 1.5y for ICI and not reached for TVEC, p=0.048). While not statistically significant, a clinical benefit was seen in PFS being longer for TVEC (2.1y for TVEC vs. 1.2y for ILI/ILP and 1.1y for ICI; p=0.2) and OS (not reached vs 2.9y for ILI/ILP and 5.2y for ICI; p=0.2). On mixed effect Cox regression proportional hazard model using the matched data set, there were no significant differences in any of the survival and recurrence outcomes. Conclusions: When patients are propensity-matched, there were no significant differences in first-line treatment modalities for unresectable melanoma ITM. Treatment with TVEC did result in clinically meaningful improved overall and local PFS and OS. This supports that selection of ITM therapy should incorporate an individualized approach, incorporating disease distribution, stage, burden, treatment side effects and patient priorities.

9030 Background: AI use is ubiquitous among HOT and healthcare workers, but with variable base knowledge and comfort level. Its indiscriminate use may be problematic. To address this educational gap, we developed a WS for HOT to assess their use of AI and educate them on how to employ it in MedEd and patient-centered CP based on LSP. Methods: A faculty member developed a WS on how to use AI in MedEd and CP based on LSP of analogy, contrasting cases, elaboration, generation, and question driven learning. The WS was for HOT, but faculty could join. It had 3 sections: introduction to basic concepts of AI; principles of the Health Insurance Portability and Accountability Act and protected health information; AI in MedEd; and AI in CP. Sections had real use case examples of AI, for participants to interact, ask questions, and share their personal use cases. HOT were invited to compare and generate examples during the WS, based on their educational and clinical experience and needs. Participants’ AI use and self-perceived and objective knowledge about it were assessed in a pre activity survey, a post WS survey, and a post 8 week survey to evaluate long term learning. Results: A 2 hour WS with 9 HOT and 2 faculty was completed successfully. 10 participants completed the pre WS survey, and 11 completed the post WS and the post 8 week surveys. 100% of them used generative AI tools before the WS, while 10% had prior training in AI. 90% used AI in personal life and MedEd, 70% used it in CP, and 30% in academic research. Table 1 shows participants’ self-assessed knowledge of AI, comfort level in using AI for MedEd and CP, self-assessed preparedness to implement AI in MedEd and CP, and objective knowledge. 8 weeks post WS, 91% of participants reported increased AI use in CP, leading anywhere from slight to significant decreases in time spent on documentation tasks for 91% of them. In MedEd, 73% reported increased AI use, and 82% described slight to significant improvement in the quality of time dedicated to it. 82% described the WS as extremely relevant to their daily responsibilities, and 91% reported confidence navigating ethical and privacy risks of AI in HemOnc. All participants were interested in having a similar WS in the future. Conclusions: An LSP based WS about AI increased the self-perceived and objective knowledge of HOT about using this tool in MedEd and CP. It also increased HOT comfort level, preparedness, and efficiency using AI. With the ubiquitous use of AI by HOT, ongoing education about it focused on supporting high-quality patient care should be a part of fellowship curriculum. Pre WS % Post WS % Post 8 week % Moderately/Very knowledgeable about AI 50 91 100 Comfortable using AI in MedEd 60 82 82 Prepared to implement AI in MedEd 30 91 73 Comfortable using AI in CP 40 73 82 Prepared to implement AI in CP 0 91 73 Correct answers on objective assessment 53 68 71

8049 Background: Multiple pulmonary nodules (MPN) pose significant challenges for accurate staging of non-small cell lung cancer (NSCLC). As next generation sequencing (NGS) technologies have become more widely available on smaller amounts of tissue, the prevalence and clinical implications of heterogeneity between MPNs are poorly understood. This study retrospectively evaluates the histopathological and NGS findings after MPN biopsy in a single robotic-assisted bronchoscopy (RaB) procedure. Methods: 191 patients were retrospectively enrolled at 6 geographically diverse centers in the US. All patients had 2+ pulmonary nodules biopsied and staging EBUS in the same procedure. An expert molecular pathologist reviewed NGS data between nodule pairs to determine if they were discordant, concordant, or indeterminate. Results: Of 191 patients, 85 patients had 2 malignant nodules with 15 of those demonstrating histopathologic heterogeneity (e.g., one adenocarcinoma, one squamous cell carcinoma). 26 patients with 2 malignant nodules of similar histopathology demonstrated molecular heterogeneity between nodules. These cases were reviewed by an expert molecular pathologist who determined the following breakdown: -15 discordant pairs (57.7%) -3 concordant pairs (11.5) -8 indeterminate pairs (30.8%) Breakdown by nodule density: -Discordant: 7 same density, 8 different density -Concordant: 3 same density -Indeterminate: 5 same density, 3 different density Breakdown by nodule laterality: -Discordant: 7 ipsilateral, 8 contralateral -Concordant: 2 ipsilateral, 1 contralateral -Indeterminate: 4 ipsilateral, 4 contralateral Staging EBUS was performed in all 26 cases with malignancy identified in 2 cases. NGS sufficiency for NSCLC from three sites with standardized NGS reporting was as follows: 1 st nodule biopsied: 42/54 (77.8%), 2 nd nodule biopsied: 37/51 (72.5%), 3 rd nodule biopsied: 2/4 (50%). In total, 90/109 (82.6%) NSCLC samples had adequate tissue for NGS. In 85 cases with 2 malignant nodules, 35 (41.2%) had all nodules Stage IIB or lower. Notably, 25 (29.4%) of the cases did not have NGS available on one or more of the nodules, thus precluding staging. Conclusions: This study highlights the frequency and clinical relevance of histopathologic and molecular heterogeneity among synchronous MPNs. Importantly, heterogeneity was not limited to contralateral or anatomically distant lesions, challenging the assumption that spatial proximity implies clonal relatedness. Further, this study shows that relying solely on density or radiographic features of a nodule is an incomplete discriminator between separate primary lung cancers and intrapulmonary metastasis. Our findings support the need for an integrated diagnostic paradigm in which sampling of multiple lesions is used to inform clonality, refine staging, and guide precision therapy.

7569 Background: MAIA and CEPHEUS trials demonstrated that daratumumab (Dara) with standard of care (SOC) VRd or Rd significantly improved clinical outcomes versus SOC in TIE NDMM. Here we describe efficacy and safety in TIE pts from both trials by age and baseline (BL) frailty using the latest data cuts. Methods: Pts were randomized 1:1 to DRd (n=368) or Rd (n=369) in MAIA and 1:1 to DVRd (n=144) or VRd (n=145) in CEPHEUS. Progression-free survival (PFS), complete response or better (≥CR), overall MRD negativity (neg) at 10 -5 with ≥CR, sustained MRD neg with ≥CR (confirmed MRD neg ≥12 ± 1 months [mo] apart without MRD positivity in between), and safety were assessed by age (<70, 70–<75, or ≥75 years [y]) and BL frailty (assessed by IFM simplified frailty score: 0–1, non-frail; ≥2, frail). Results: Median follow-up was 64.5 mo in MAIA and 76.0 mo in CEPHEUS. In MAIA, 155 (21%) pts were <70 y, 261 (35%) 70–<75 y, and 321 (44%) ≥75 y; 341 (46%) pts were frail, 88.0 % of whom were ≥70 y. In CEPHEUS TIE pts, 70 (24%) pts were <70 y, 133 (46%) 70–<75 y, and 86 (30%) ≥75 y; 83 (29%) pts were frail, 86% of whom were ≥70 y. DRd or DVRd improved PFS, MRD neg rates, sustained MRD neg rates, and ≥CR rates vs Rd or VRd arms across age and frailty subgroups in both trials (Table). Safety was consistent with established individual drug profiles, and adverse event rates were generally comparable across treatment arms and subgroups within both trials. Additional data on patient-specific factors relevant to these subgroups will be presented. Conclusions: Dara-based regimens improved efficacy outcomes across subgroups in MAIA and CEPHEUS trials, reinforcing Dara-based regimens as SOC in TIE NDMM regardless of age or frailty. These data offer clinically relevant insights to help guide treatment selection for TIE pts. Clinical trial information: NCT03652064 ; NCT02252172 . PFS, hazard ratio (95% CI) ≥CR rate, % MRD neg with ≥CR (10 -5 ) rate, % Sustained MRD neg with ≥CR (10 -5 ) rate, % Age/ Frailty status MAIA* CEPHEUS** MAIA* CEPHEUS ** MAIA* CEPHEUS** MAIA* CEPHEUS ** <70 y 0.35 (0.21–0.56) 0.60 (0.31–1.18) 56.4 vs 31.2 85.7 vs 68.6 35.9 vs 11.7 74.3 vs 42.9 25.6 vs 3.9 62.9 vs 28.6 70–<75 y 0.64 (0.45–0.89) 0.60 (0.37–0.99) 56.2 vs 31.3 77.9 vs 69.2 36.2 vs 12.2 55.9 vs 47.7 20.8 vs 5.3 45.6 vs 38.5 ≥75 y 0.59 (0.44–0.79) 0.46 (0.22–0.94) 44.4 vs 28.6 80.5 vs 44.4 26.9 vs 9.9 58.5 vs 26.7 13.8 vs 3.1 43.9 vs 15.6 Frail 0.64 (0.48–0.85) 0.62 (0.32–1.18) 44.8 vs 33.1 72.9 vs 54.3 25.6 vs 13.0 56.3 vs 34.3 15.7 vs 4.1 39.6 vs 17.1 Non-frail 0.48 (0.36–0.64) 0.51 (0.34–0.78) 56.6 vs 27.5 84.4 vs 63.6 37.8 vs 9.5 63.5 vs 41.8 21.4 vs 4.0 54.2 vs 32.7 *MAIA: DRd vs Rd; **CEPHEUS: DVRd vs VRd.