Chaudhuri, Aadel A.

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 < 0.001) and remained significant at mid-treatment (OS: HR 7.08; PFS: HR 12.06; both P < 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 < 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.

Summary Longitudinal plasma cell-free DNA profiling from the phase 3 Alliance A031201 trial revealed divergent resistance trajectories in metastatic castration-resistant prostate cancer. Rapid progressors harbored non–androgen receptor (AR) alterations suggesting intrinsic resistance, whereas delayed progressors showed progressive AR amplifications, structural rearrangements, and extrachromosomal DNA–associated evolution. These findings support biomarker-guided strategies targeting AR-dependent and AR-independent disease states. See related article by Valentín López et al., p. 2413

Abstract Introduction: Urine cell-free DNA (cfDNA) is a promising ultra-noninvasive analyte for genitourinary cancers (GU) cancers. In this study, we investigated urine cfDNA fragmentomic features and evaluated their ability to predict the tumor tissue of origin. Methods: A total of 204 GU cancer patients and 34 healthy adults were enrolled in this prospective study. Preoperative urine was collected from 89 bladder cancer (BC) patients (64% muscle-invasive) undergoing cystectomy, 65 renal cell carcinoma (RCC) patients undergoing nephrectomy and 50 metastatic prostate cancer (mPC) patients. Urine cfDNA was isolated and sequenced at 5x genome-wide coverage on a NovaSeq S4 flow cell. To identify malignant tissue of origin, we analyzed somatic copy number alterations (CNAs), genome-wide fragment length ratios, and 4-mer end motifs. CNAs and tumor fraction (TFx) were quantified using ichorCNA in 1-Mb windows, while chromosome arm-level fragment count z-scores and fragment length ratios were calculated in 5-Mb bins across the genome. Relative frequencies of all 256 possible 4-mer end motifs were calculated for each sample. Individual logistic regression models were developed based on each fragmentomic feature using leave-one-out cross validation (LOOCV). Outputs from these models were combined into multi-feature XGBoost models. Cohort-specific end-motif enrichments were identified using Kruskal-Wallis tests with FDR correction. Motifs were then hierarchically clustered based on their cohort-wise median frequencies to define groups of motifs with shared fragmentation patterns. Results: Across urine cfDNA in the GU cohort, BC showed the highest mean TFx at 10.0%, followed by mPC at 3.6% and RCC at 2.7%. A machine learning model based on 4-mer end motifs achieved a mean ROC AUC of 0.933 with classification accuracies of 63% for healthy, 87% for BC, 72% for mPC, and 83% for RCC. This model outperformed models based on ichorCNA (AUC = 0.767), chromosome arm fragment-count z-scores (AUC = 0.827), and fragment length ratios (AUC = 0.674). Combining end motifs with other fragmentomic features did not improve prediction accuracy. Multi-feature models incorporating end motifs with ichorCNA, chromosome arm-level z-scores, or fragment-length ratios yielded mean AUCs between 0.908-0.924, lower than the end-motif only model. Kruskal-Wallis tests identified 179 of 256 end motifs (79%) as significantly different across healthy, BC, mPC, and RCC. Hierarchical clustering of cohort-level median motifs revealed distinct end motif patterns: Motifs beginning with CT were enriched in RCC; AAAA was strongly enriched in BC; and motifs beginning with CA, AC, and AG were enriched in mPC. Conclusion: Urine cfDNA 4-mer end motifs capture GU cancer-specific biological patterns that enable accurate tissue-of-origin prediction, underscoring their promise as a diagnostic tool. Citation Format: Jessica Linford, Pradeep S. Chauhan, Irfan Alahi, Yohan Kim, Arpit Panda, Nathan Colon, Ryan Mueller, Faridi Qaium, Eric H. Kim, Melissa A. Reimers, Zachary L. Smith, Woodson W. Smelser, Fabrice Lucien-Matteoni, Aadel A. Chaudhuri. Urine cfDNA 4-mer end-motif signatures outperform other fragmentomic features for tissue-of-origin classification in genitourinary cancers [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 2590.

Abstract Background: Pediatric and AYA sarcomas are rare, biologically heterogeneous tumors with limited noninvasive biomarkers to guide diagnosis, personalized treatment, and disease monitoring. Standard-of-care evaluation relies on invasive biopsies that carry procedural risks and imaging modalities with limited sensitivity for detecting minimal residual disease and distinguishing tumor types. Cell-free DNA (cfDNA) methylation profiling offers a minimally invasive alternative capable of capturing tumor-derived epigenomic alterations and has consistently shown strong clinical utility in adult malignancies. However, genome-wide cfDNA methylation patterns across diverse pediatric and AYA sarcoma subtypes remain poorly defined. Methods: Plasma was collected from 93 pediatric and AYA patients (pediatric <18 years; AYA 15-39 years) representing 27 Ewing sarcoma, 17 rhabdomyosarcoma, 11 liposarcoma, 10 chordoma, 8 synovial sarcoma, 7 chondrosarcoma, 6 osteosarcoma, and 6 fibrosarcoma cases, plus 19 matched healthy donors. cfDNA was isolated from 1 mL plasma, quantified by Qubit, and assessed by Bioanalyzer. Libraries were prepared using the NEBNext EM-seq v2 workflow with PCR cycles scaled to cfDNA input amount. Genome-wide sequencing (15× target depth) was followed by alignment, deduplication, and methylation calling. MultiQC was used to assess depth, duplication rate, conversion efficiency, and CpG coverage. Global methylation summaries were computed, and methylKit was used to generate per-CpG and 1-kb tiling matrices and initiate differential methylation analyses. Results: Ewing sarcoma patients had significantly higher plasma cfDNA concentrations than age- and sex-matched healthy donors (24.4 vs 4.6 ng/mL, p < 0.0001), whereas cfDNA levels for other sarcoma subtypes overlapped with the healthy cohort. Low or undetectable cfDNA concentrations by Qubit were far more common among non-Ewing sarcoma samples (23 of 66) than Ewing sarcoma (1 of 27). All samples achieved sufficient CpG coverage for genome-wide methylation modeling. Global methylation summaries revealed no significant differences in mean β-values across sarcoma subtypes or versus healthy donors. An independent analysis of the Ewing subset identified 299 significant differentially methylated regions (DMRs), supporting the detectability of disease-specific methylation changes. Conclusions: These results demonstrate the feasibility of high-quality cfDNA methylome profiling across a large and diverse pediatric and AYA sarcoma cohort, including in plasma samples with cfDNA concentrations below the limit of detection. While global methylation levels appear broadly similar across subtypes, proof-of-concept DMR analysis in Ewing sarcoma suggests that subtype-specific epigenomic signatures could enable future noninvasive diagnostic tools for pediatric and AYA sarcomas. Citation Format: Lilli J. Greiner, Roman O. Kowalchuk, Jeff Szymanski, Pradeep S. Chauhan, Adam Amundson, Peter J. Schoettler, Wendy Allen-Rhoades, Stephanie F. Polites, Peter S. Rose, Kelly Bailey, Linda McAllister-Lucas, Anita Mahajan, Nadia Laack, Aadel Chaudhuri. Defining genome-wide cfDNA methylation landscapes in pediatric and adolescent and young adult (AYA) bone and soft-tissue sarcomas [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 7885.

Abstract Our team has demonstrated that lymphatic exudate collected via surgical drains (“lymph”) is a proximal biofluid rich in ctDNA and prognostic of recurrence in HPV-independent Head and Neck Cancer (HPV- HNSCC). Other analytes such as proteins, metabolites, and cells are also abundant in lymph. To understand the liquid tumor microenvironment (TME) immediately after tumor resection, we characterized lymph at 24 hrs in HNSCC. We performed a multi-omic survey, demonstrating that lymph is distinct from plasma and represents a largely unexplored source of biomarkers relevant to immune modulation and metastasis.Metabolomics and proteomics were run on lymph supernatant and plasma. Proteomic screening was performed via Olink and normalized to internal standards for quantitative analysis. Metabolomic samples were assayed via LC-MS and normalized. 16s libraries were sequenced utilizing Illumina and analyzed in QIIME. 16s sequencing on 6 patients indicated an array of bacterial genera present in post-surgical lymph with consistency across patients. The distribution consisted primarily of microbes native to the oral cavity, suggesting post-surgical lymph may reflect the native microbiome prior to surgery. Pathogenic blooms were observed in a subset of patients. Ongoing analysis will correlate microbiome data with both cancer and surgical outcomes.Metabolite profiling was performed on post-surgical lymph and matched plasma from 4 patients, including 3 who recurred within 1 year of surgery. The metabolite profile in lymph of all 4 patients was more diverse than plasma with higher metabolite abundance per mL. 13% of identified metabolites were >2-fold enriched in lymph. Lymph from recurred patients showed high levels of saturated and monounsaturated fatty acids, reported to be associated with metastasis. Post-surgical lymph has a unique and largely uncharted metabolome to mine for biomarkers associated with recurrence.Proteomes were compared between lymph and plasma from 44 HPV-HNSCC patients. This cohort consists of 25 recurred (REC) and 19 patients with no evidence of disease (NED) with >1 year of follow up. Lymph and plasma displayed highly non-overlapping protein repertoires. The mean absolute volcano score was 25.2, indicating a strong global difference between lymph and plasma. Lymph was significantly enriched in 91 proteins (p range 4.1e-47 to 0.037), many associated with inflammation. REC lymph was also enriched in inflammatory markers compared to NED, including IL-1a, TNF, and TSLP (p = 0.002, 0.015, 0.003, respectively), which have been implicated in cancer metastasis, invasion, and angiogenesis. Lymph hits were largely non-overlapping with plasma, indicating the opportunity for novel biomarker discovery in this fluid.Analysis of the microbiome, metabolome, and proteome of post-surgical lymph reveals a rich and differentiated tumor-adjacent biofluid to study biomarkers relevant to metastasis and the TME. Citation Format: Zachary Costliow, Seka Lazare, Zhuosheng Gu, Adam Harmon, Maciej Pacula, Megan Rivera, Aadel A. Chaudhuri, Jose P. Zevallos, Jessalyn Marie Ubellacker, Wendy Winckler. Multi-omicsinpostoperative lymphatic exudate in HPV-negative head and neck cancer [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 6137.

Abstract Background: Liquid biopsy approaches for cancer detection often rely on tissue-specific methylation or fragmentation features to infer tumor origin. However, a pan-aerodigestive cancer detection strategy is clinically valuable given shared risk exposures, field cancerization, and frequent diagnostic ambiguity among lung, esophageal, and head & neck cancers. We hypothesized that advanced-stage disease exhibits convergent chromatin remodeling, producing a dominant malignancy-associated fragmentomic signal that supersedes subtler tissue-of-origin patterns. Methods: Whole-genome EM-seq (∼15×) was performed on plasma cfDNA from 120 patients with stage III/IV aerodigestive cancers (lung, esophageal, head & neck; squamous and adenocarcinoma) and 60 age-matched controls. Four fragmentomic modalities were assessed: (1) genome-wide fragmentation in 5-Mb bins (DELFI-like), (2) NMF spectral components, (3) 4-mer end motifs, and (4) promoter-centric nucleosome scores (Griffin). All preprocessing occurred strictly within each training fold of a repeated stratified 10-fold CV (100 repeats) to prevent data leakage. No test-sample information was used in training. Hyperparameters were tuned only within training partitions. Random Forest classifiers were trained under this fully nested scheme. Results: The multimodal classifier robustly detected advanced aerodigestive malignancies with a mean AUROC 0.86 and AUPRC 0.94. However, modality dissection revealed a clear performance hierarchy: nucleosome positioning (Griffin) alone achieved AUROC 0.85 and AUPRC 0.93, nearly matching the full integrated model, whereas end motifs performed poorly (AUROC 0.61). Biological interpretation demonstrated prominent nucleosome depletion centered at promoters of proliferation-associated genes, indicating a convergent epigenetic state of promoter opening across late-stage aerodigestive malignancies. Conclusions: Advanced aerodigestive cancers exhibit a dominant, convergent chromatin remodeling signature detectable in plasma cfDNA, driven primarily by altered nucleosome positioning. In late-stage disease, this shared malignancy-associated fragmentomic signal outweighs tissue-of-origin-dependent patterns. These findings highlight the utility of nucleosome-based fragmentomics not merely for detection, but for resolving diagnostic ambiguity in patients with indeterminate masses and for monitoring total tumor burden in high-risk aerodigestive malignancies. Citation Format: Axel Misael Hidalgo, Ayesha Hashmi, Jeff Szymanski, Pradeep Chauhan, Lilli Greiner, Faridi Qaium, Daniel J. Ma, David M. Routman, Katie M. Van Abel, Aadel A. Chaudhuri.. Convergent chromatin remodeling enables pan-aerodigestive detection of advanced malignancies in plasma cfDNA [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 3862.

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: Combination immune checkpoint inhibitor (ICI) therapy represents a standard-of-care for patients with metastatic melanoma. However, >40% of patients do not respond to treatment and severe immune-related toxicity affects up to 60% of patients. Accordingly, we need more precise ways to select patients for combination ICIs. To address this, we developed LiquidTME, a liquid biopsy method based on Spatial EcoTyper (Cancer Res (2025) 85 (8_Supplement_1): 153) that leverages a deep learning approach to noninvasively assess the tumor microenvironment from cell-free DNA (cfDNA) methylation data. LiquidTME was previously trained to predict ICI response using 78 patients with advanced melanoma treated at Yale University. Here we performed a blinded validation of LiquidTME in coordination with clinicians at Washington University (WashU). Methods: The WashU cohort consisted of pre-ICI plasma from 34 patients with advanced melanoma, each treated with ipilimumab and nivolumab (n=27) or relatlimab and nivolumab (n=7). ICI response was classified as durable clinical benefit (DCB) or no durable benefit (NDB) by a board-certified oncologist. Tumor mutational burden (TMB) was determined for 27 patients using commercial CLIA assays and analyzed as nonsynonymous mutations (mt) per megabase (Mb), using the FDA-approved 10 mt/Mb cutpoint for TMB-high and -low groups. The WashU cohort was sent to a scientific team that was blinded to all clinical and TMB data. Cell-free DNA was extracted from 2 mL plasma per patient and subjected to enzymatic methyl-seq (EM-seq) at a median depth of 15x. LiquidTME was performed on the resulting profiles, yielding a binary response prediction and a continuous response score for each sample. Test results were locked down and returned. Both assays were compared by AUC and two-sided Wilcoxon rank-sum tests for response classification, and Kaplan-Meier analysis for progression-free survival (PFS). Results: Median follow-up time of the cohort was 21.6 months. LiquidTME performed on cycle 1 day 1 pre-ICI plasma significantly stratified PFS with a hazard ratio (HR) of 0.27 (P = 0.005), with LiquidTME(+) patients achieving a median PFS of 1.7 years longer than LiquidTME(-) patients. LiquidTME distinguished DCB from NDB with an AUC of 0.77 (P = 0.007). Similar performance was seen across distinct combination ICI regimens. In patients with TMB data, LiquidTME maintained whole-cohort performance with a PFS HR of 0.30 (P < 0.03; AUC = 0.77). In contrast, TMB high vs. low subsets failed to stratify PFS (HR = 0.49; P = 0.17) or response (AUC = 0.53; P = 0.8). Conclusion: LiquidTME identified durable responders to combination ICI from pretreatment plasma in this blinded validation cohort of melanoma patients. Given its favorable performance, LiquidTME shows promise as a clinical tool to guide personalized immunotherapy decision-making. Citation Format: Aadel A. Chaudhuri, David Y. Chen, Tucker Hansen, Mirna Jarosz, Vincent A. Miller, Aaron M. Newman. Blinded clinical validation of LiquidTME, a cell-free DNA assay for predicting response to immunotherapy by noninvasively profiling the tumor microenvironment [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 1040.

Abstract Introduction: Long intergenic noncoding RNAs (lincRNAs) and circular (circ) RNAs have been shown to play key roles in carcinogenesis and tumor progression. Urine represents a promising source of tumor-reflective signals shed directly from the urothelial microenvironment in bladder cancer (BC) patients. Here, we evaluate the urine cell-free (cf) RNA transcriptome in a cohort of 50 patients with localized BC. Methods: A total of 50 localized BC patients and 24 healthy adults were enrolled. Pre-operative urine (collected on the day of radical cystectomy) was processed to isolate cfRNA from urine supernatant. Libraries were prepared using an Illumina tagmentation-based RNA enrichment workflow and sequenced to 100M paired-end reads per sample on a NovaSeq X. FASTQ files were concatenated per sample and QC-checked with RNA-SeQC and Samtools. Reads were aligned to GRCh38/hg38 with STAR, and gene counts were generated using Feature Counts. Linear differential expression analysis (DEA) was performed with DESeq2. For discovery we used random halves of TCGA-BLCA and healthy urine cfRNA samples, alongside a second DEA with random halves of urine BC cfRNA vs. controls; overlapping upregulated genes were validated in the remaining samples. For circular (circ) RNAs, annotations from MiOncoCirc were used; junctions with ≥5 supporting reads were retained, and DEA was conducted with edgeR. Results: In this study, the median age was 68 years, and 80% (40/50) were male. Among the cohort, 66% (33/50) had muscle-invasive bladder cancer (MIBC), of whom 54% received neoadjuvant chemotherapy. Differential expression analysis of TCGA-BLCA tumors and BC urine cfRNA, identified 27 genes commonly upregulated, with 23 of the 27 shared genes strikingly being long intergenic noncoding RNAs (lincRNAs). These BC/urine-specific lincRNAs—including LINC00930, LINC01004, DLG5-AS1, APTR, PSORS1C3, and SERPINB9P1—have known roles in proliferation, EMT, metabolism, and immune signaling. Outside of lincRNAs, tumor-reflective coding transcripts in BC/urine were enriched for autophagy, driven by MAP1LC3B2.TCGA-BLCA survival analysis showed that LINC00930 and PSORS1C3 were associated with worse overall survival. Expanding beyond linear RNA sequences, analysis of urine circRNAs from BC patients revealed a strong cancer-specific dysregulation pattern, with 77 circRNAs significantly upregulated compared with healthy controls. Upregulated urine circRNAs arose from host genes involved in BC-relevant pathways, including invasion (DOCK1, ARHGAP5), autophagy/ER stress (VMP1, ERN1), and luminal differentiation (GRHL2, ESRP1). Conclusion: Cell-free RNA profiling reveals a distinct transcriptomic signature including differential lincRNA- and circRNA-driven autophagy, EMT, proliferation, metabolic, differentiation, and immune signaling programs in the urine of bladder cancer patients. Citation Format: Pradeep Chauhan, Li Lin, Irfan Alahi, Jessica Linford, Lilli J. Greiner, Ayesha Hashmi, Anushka Viswanathan, Nathan Colon, Faridi Qaium, Peter K. Harris, John Sheng, Jacob J. Orme, Eric H. Kim, Zachary L. Smith, Woodson Smelser, Christopher A. Maher, Aadel A. Chaudhuri. Urine cell-free RNA captures tumor-reflective long intergenic noncoding and circular RNA programs in bladder cancer [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 1133.