Integrative analysis of genomic and transcriptomic data informs precancer progression in the pancreas
Noller, K.; Lai, J.; Lesperance, D.; Adkins, R. S.; Elhossiny, A.; Guerrero, P. A.; Rajapakshe, K. I.; Maitra, A.; Giglio, M.; Mahurkar, A.; White, O.; Pasca di Magliano, M.; Ochs, M. F.; Kagohara, L. T.; Wood, L. D.; Karchin, R.; Fertig, E. J.
Show abstract
Pancreatic ductal adenocarcinoma (PDAC) arises from heterogeneous precursor lesions, including intraductal papillary mucinous neoplasms (IPMNs), but the features distinguishing indolent from progressive lesions remain unclear. We performed an integrative analysis of transcriptomic, genomic, and microenvironmental profiles of IPMNs to define multi-omic phenotypes. Using transfer learning, we projected IPMN-derived transcriptional programs onto spatial transcriptomic datasets from IPMNs and pancreatic intraepithelial neoplasias (PanINs). We identified two major phenotypes: one associated with cancer-associated fibroblasts and epithelial-to-mesenchymal transition, shared across IPMN, PanIN, and PDAC; and a second, glycolysis-enriched phenotype with a unique somatic mutation profile specific to IPMN. Spatial mapping further revealed grade-specific enrichment of transcriptional programs and distinct interactions with stromal and immune subtypes, underscoring the role of the precancer microenvironment in progression. These findings establish multi-omic phenotypes that unify genetic, transcriptional, and microenvironmental heterogeneity, providing a framework for distinguishing progressive from indolent precancers and a web-based public atlas for future exploration of these data and transcriptional phenotypes.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Single-Cell RNA Sequencing Reveals the Effects of Chemotherapy on Human Pancreatic Adenocarcinoma and its Tumor Microenvironment 97%
- Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy 96%
- Application of high-throughput, high-depth, targeted single-nucleus DNA sequencing in pancreatic cancer 96%
Similar papers in this journal
Similar papers in this journal
- DNA methylation memory of pancreatic acinar-ductal metaplasia transition state altering Kras-downstream PI3K and Rho GTPase signaling in the absence of Kras mutation 95%
- Evaluating the transcriptional fidelity of cancer models 95%
- SiRCle (Signature Regulatory Clustering) model integration reveals mechanisms of phenotype regulation in renal cancer 95%
Similar papers in this journal
- Identifying a gene signature of metastatic potential by linking pre-metastatic state to ultimate metastatic fate 95%
- Evolution of chromosome arm aberrations in breast cancer through genetic network rewiring 95%
- ECM-free patient-derived organoids preserve diverse prostate cancer lineages and uncover in vitro-enriched cell types 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.