Routh, J. | bioRxiv Science

bioRxiv2026

Detection of Pancreatic Cancer Using a Methylation-Specific PCR-Based Multi-Cancer Early Detection Test

ContextPancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy often diagnosed at advanced stages due to the lack of early clinical symptoms. DNA methylation alterations arise early in PDAC tumorigenesis and may serve as promising biomarkers for blood-based cancer detection. ObjectiveTo evaluate the performance of EPISEEK, a laboratory-developed blood-based multi-cancer early detection (MCED) assay, for detecting PDAC across disease stages. DesignA retrospective cohort study included 97 patients with stage I-IV PDAC and 201 asymptomatic healthy controls. Sensitivity, specificity, area under the curve (AUC), and stage-specific performance were assessed. EPISEEK-MCED performance was also compared with CA 19-9 alone and in combination with CA 19-9. ResultsEPISEEK-MCED classified 65 of 97 PDAC cases as positive, corresponding to an observed sensitivity of 70.1% (95% CI, 60.3% - 78.3%) at 99.5% specificity. The assay demonstrated strong discrimination between PDAC cases and healthy controls, with an AUC of 0.916 (95% CI, 0.88 - 0.952). Sensitivity increased with advancing stage while remaining substantial in early-stage disease, measuring 53.6% for stage I and 65.1% for stage II PDAC, 100% for stage III and 94.7% for stage IV. Across stages, EPISEEK-MCED outperformed CA 19-9 alone, particularly in early-stage disease. Combined analysis of EPISEEK-MCED and CA 19-9 further improved detection performance, achieving sensitivity of 57.1% and 81.4% for stage I and II, respectively. ConclusionsEPISEEK-MCED demonstrated high specificity and sensitivity for PDAC detection across disease stages, including early-stage disease. Combining EPISEEK-MCED with CA19-9 further improved performance, supporting its clinical utility for PDAC detection.

molecular biology↗

bioRxiv2025

A live tumor fragment platform to assess immunotherapy response in core needle biopsies while addressing challenges of tumor heterogeneity

BackgroundImmune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, providing durable and even curative responses. However, most patients do not respond and current biomarkers (eg, programmed death ligand (PD-L1), mismatch repair deficiency (dMMR)/high microsatellite instability (MSI) and tumor mutational burden) lack predictive accuracy. Ex vivo profiling of patient-derived tumor fragments shows promise as a predictive biomarker but relies on substantial surgical tissue to mitigate intra-specimen heterogeneity. Innovations are needed that address these challenges, particularly where limited tissue is available in core needle biopsies (CNBs). MethodsLive tumor fragments (LTFs) were generated from 59 human tumor resections and 31 CNBs from patients enrolled in observational clinical trials (ClinicalTrials.gov identifiers: NCT05478538, NCT05520099, NCT06349642) to assess cytokine induction following ICI treatment. LTFs were encapsulated in hydrogel and cultured ex vivo for up to 72 hours. A sequential treatment strategy that applies control and treatment within the same well was used with response to ICI or CD3/CD28 assessed using a multiplex secretome assay. Viability was assessed using established metabolic assays and dynamic optical coherence microscopy. ResultsLTFs maintained viability and retained T cells responsive to stimulation throughout ex vivo culture. Multiplex immunofluorescence and immunohistochemistry showed key components of the tumor microenvironment, including relative proportions of CD4+ and CD8+ immune cell populations, were preserved. Specimens positive for PD-L1 or dMMR/MSI-high were enriched for cytokine upregulation, including T-cell response cytokines IFN{gamma} and CXCL10, after PD-1 treatment. To demonstrate clinical applicability of the sequential treatment strategy, CNBs from patients with lung, gastrointestinal or kidney cancer were profiled and differential cytokine induction in response to ICI treatment was observed. ConclusionsThe novel ex vivo platform presented is capable of detecting T-cell response to ICI treatment by using a sequential treatment strategy. This approach addresses challenges associated with cross-well heterogeneity in tissue composition and requires half as much tissue as a cross-well comparison, mitigating tissue limitations typically associated with non-surgical biopsies. Importantly, the platform is compatible with established functional assays as well as non-destructive spatial imaging, enabling researchers to characterize response to ICI longitudinally. Ongoing trials will enable clinicians to assess platform performance in predicting response to immunotherapy.

cancer biology↗