bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.03.07.642043

Identification and Implications for Tumor Heterogeneity of a DNA Methylation-Based Signature Classifying Pancreatic Ductal Adenocarcinoma Based on their Cellular Origin

Abstract

BackgroundPancreatic ductal adenocarcinoma (PDAC) arises from distinct cellular origins, yet the extent to which DNA methylation patterns from normal pancreatic cells are preserved in tumor cells remains unclear. Identifying cell-of-origin signatures may enhance PDAC classification and therapeutic stratification. ObjectiveTo determine whether DNA methylation signatures in normal acinar and ductal pancreatic cells are retained in PDAC cell lines and to develop a robust classifier for distinguishing tumor origins. DesignWe performed DNA methylation profiling using the Illumina Infinium Mouse MethylationEPIC array on normal acinar and ductal cells and their PDAC derivatives in genetically engineered mouse models (GEMMs). Differential methylation analysis, and hierarchical clustering were used to identify and validate a conserved cell-of-origin DNA methylation signature. A logistic regression model was developed for classification. ResultsWe identified 178 CpG sites that remain preserved during tumorigenesis and effectively distinguished acinar- and ductal-derived PDAC cell lines. This signature was validated across independent sample sets, primary tumors, and orthotopic allografts. It successfully classified cell lines of unknown origin, including PDAC samples from KPC mice, and revealed the impact of oncogenic mutations on tumor fate. A logistic regression model supported these findings, confirming the robustness of the classification approach. Furthermore, the cell of origin influenced key PDAC characteristics, including treatment response, highlighting its potential role in molecular subtyping and patient stratification. ConclusionA preserved DNA methylation signature during pancreatic carcinogenesis distinguishes PDAC origins and influences tumor behavior. These results highlight the potential of DNA methylation profiling for tumor classification and personalized treatment strategies. They also raise important questions about the relevance of KPC mice as a preclinical model and the mechanisms driving PDAC heterogeneity. What is already known on this topicO_LIHuman PDAC exhibits significant heterogeneity, with molecular subtyping (classical vs basal-like) providing some insights into tumor behavior and clinical outcomes. C_LIO_LIMouse acinar and ductal cells can give rise to PDAC, influencing tumor characteristics and survival outcomes. C_LIO_LIDNA methylation is a powerful tool for tracing cellular identity and distinguishing cancer subtypes based on epigenetic profiles. C_LI What this study addsO_LIA cell-of-origin methylation signature is preserved during mouse carcinogenesis and across diverse experimental settings, providing a reliable tool for tumor classification. C_LIO_LIA DNA methylation-based classification system reliably distinguishes between acinar- and ductal-origin PDAC, filling a critical gap in methods to trace tumor lineage. C_LIO_LIAcinar- and ductal-derived PDACs exhibit distinct methylation patterns that correlate with differences in tumor behavior, such as chemoresistance, highlighting the biological relevance of cellular origin in PDAC. C_LIO_LIThe study provides new insights into how cell-of-origin influences PDAC heterogeneity and could lead to more precise therapeutic strategies tailored to the tumors lineage. C_LI How this study might affect research, practice or policyO_LIThis study provides a new, reliable method for classifying PDAC based on its cellular origin, which could significantly improve tumor classification in both preclinical and clinical settings, aiding in more accurate diagnoses and prognostic predictions. C_LIO_LIThe identification of distinct methylation patterns linked to tumor behavior offers valuable insights for developing personalized treatment strategies, as therapies could be tailored based on the tumors cellular origin and associated molecular characteristics. C_LIO_LIThe preservation of cell-of-origin methylation signature suggests the potential for developing a universal biomarker for PDAC classification, which could guide future clinical trials, therapeutic targeting, and patient stratification in PDAC care. C_LI

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zoi, I., Rajput, M., Holguin-Horcajo, A., Haidar, M., Brusa, D., Chu, K., Xie, J., Shields, M., Morgadinho Ferreira, S., Stanger, B., Attardi, L. D., Kopp, J., Stemmler, M. P., Nicolle, R., Rovira, M., Jacquemin, P.. 2025-03-11. Identification and Implications for Tumor Heterogeneity of a DNA Methylation-Based Signature Classifying Pancreatic Ductal Adenocarcinoma Based on their Cellular Origin. https://doi.org/10.1101/2025.03.07.642043

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

BAF complexes cooperate with lineage-restricted transcription factors to establish cell-state-specific regulatory programs

BRG1/BRM-associated factor (BAF) complexes are essential regulators of chromatin organization and cell identity. Genes encoding BAF subunits are among the most frequently mutated in human cancer. Yet, how disruption of a single subunit gives rise to distinct tumor states remains poorly understood. Atypical teratoid rhabdoid tumors (ATRTs) provide a compelling model, as they are uniformly driven by bi-allelic loss of the BAF subunit SMARCB1, yet segregate into distinct molecular subtypes. Using integrated multi-omics profiling of patient-derived ATRT organoids and primary tumor tissues, we show that transcriptional and chromatin accessibility changes upon SMARCB1 reconstitution are directed by subtype- and lineage-specific transcription factor (TF) repertoires. Genome-wide binding and transcriptomic analyses reveal that SMARCB1 reconstitution enables the lineage-specific TF RFX4 to engage regulatory elements and activate neuronal differentiation programs, partially reprogramming ATRT-MYC toward an ATRT-SHH-like identity. Together, these findings demonstrate that SMARCB1 loss disrupts TF-dependent chromatin priming, revealing that the lineage-specific regulatory output of BAF complexes is constrained by the underlying TF repertoire.

cancer biology↗

Curvature-based schedule ordering is preserved in homogeneous and heterogeneous tumors

During treatment, dosing protocols with identical total dose may favor one schedule over another depending on how exposure is distributed over time. In homogeneous cell populations, Jensen's inequality has been shown to predict whether continuous or intermittent high-dose followed by low-dose is favored, based on the curvature of the concentration-effect function. Scheduling ordering can be performed based on curvature only: concave functions favor continuous dosing while convex functions favor intermittent dosing schedules with a high time-variance. However, tumors exhibit heterogeneous drug sensitivities, and treatment preferentially eliminates drug-sensitive cells, progressively shifting the surviving population toward greater drug resistance. Whether this treatment-induced selection can reverse curvature-based schedule ordering remains unclear. We develop a mathematical framework in which phenotypes share a common concentration-effect function but differ by fixed, nonnegative sensitivity scales. We prove that the ordering of equal-mean schedules is administrated solely by the scalar cumulative treatment effect, that is, by the curvature of the effect function alone. Consequently, baseline heterogeneity and treatment-induced selection can alter the magnitude of treatment response and the composition of surviving cells, but cannot reverse the ordering of equal-mean schedules predicted by the curvature of the single-cell concentration-effect function. This preservation holds across different temporal dosing profiles and repeated treatment cycles. Our work uncovers a general principle that curvature-based schedule ordering is preserved in heterogeneous tumors despite treatment-induced selection toward resistance.

cancer biology↗

Enhanced antitumour activity of combined PD-1 blockade and HER2-targeted therapy is associated with reduced epithelial-mesenchymal transition and extracellular matrix-remodelling signatures in gastric cancer

Background The combination of PD-1 blockade, HER2-targeted therapy and chemotherapy improves outcomes in HER2-positive advanced gastric and gastro-oesophageal junction adenocarcinoma. However, chemotherapy can independently alter the tumour microenvironment, making the biological effects of PD-1 and HER2 targeting difficult to distinguish. We therefore investigated how PD-1 and HER2 blockade, alone and in combination, affect tumour growth and associated transcriptional programmes. Methods Immunodeficient NOG mice received human PBMCs by tail-vein injection. Three days later, NCI-N87 gastric cancer cells were implanted subcutaneously. Mice were randomised to vehicle, pembrolizumab, trastuzumab, or combination treatment. Tumour growth was assessed, and bulk RNA sequencing was used to identify treatment-associated changes in gene expression, pathway enrichment, and tumour, stromal, and immune cell-associated signatures. Results Combined treatment produced greater tumour growth control than either monotherapy. Trastuzumab-treated tumours showed enrichment of immune activation, epithelial-mesenchymal transition (EMT), and TGF{beta}-associated signatures, whereas pembrolizumab alone produced a limited transcriptional effect. Combination treatment was associated with reduced proliferation, EMT, and stromal-remodelling signatures, alongside increased cytotoxic immune-associated signatures. Expression of extracellular matrix-associated genes, including VCAN, SPARC, POSTN, collagen genes, and FAP, was lower in combination-treated tumours. Complement-related transcriptional pathways were also enriched. Conclusions In this chemotherapy-free model, combined PD-1 blockade and HER2-targeted therapy was associated with greater tumour growth control, enrichment of cytotoxic immune-associated transcriptional signatures, and reduced EMT and extracellular matrix remodelling signatures. These findings provide hypotheses for further mechanistic validation.

cancer biology↗