Evidence map›Paper›PMID 41766370›Full record

ArticleMolecular oncology2026

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer.

Brian Nelson, Lyanne Delgado-Coka, Natalia Marchenko, Luisa F Escobar-Hoyos, Kenneth R Shroyer, Alisa Yurovsky, Trey Ideker, Gábor Balázsi, Thomas MacCarthy, Scott Powers

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In one paragraph

Article in Molecular oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Brian NelsonDepartment of Applied Mathematics and Statistics, Stony Brook University, New York, NY, USA.
Lyanne Delgado-CokaDepartment of Pathology, Stony Brook University, New York, NY, USA.
Natalia MarchenkoDepartment of Pathology, Stony Brook University, New York, NY, USA.
Luisa F Escobar-HoyosDepartment of Pathology, Stony Brook University, New York, NY, USA.
Kenneth R ShroyerDepartment of Pathology, Stony Brook University, New York, NY, USA.ORCID 0000-0001-8090-0778
Alisa YurovskyDepartment of Biomedical Informatics, Stony Brook University, New York, NY, USA.
Trey IdekerDepartment of Medicine, University of California, San Diego, La Jolla, CA, USA.
Gábor BalázsiDepartment of Biomedical Engineering, Stony Brook University, New York, NY, USA.
Thomas MacCarthyDepartment of Applied Mathematics and Statistics, Stony Brook University, New York, NY, USA.
Scott PowersDepartment of Pathology, Stony Brook University, New York, NY, USA.ORCID 0000-0003-2769-1932

Funding

SBU Seed Grant
6 · The paper itself

Abstract

Transcriptional heterogeneity in pancreatic ductal adenocarcinoma (PDAC) arises not only from changes in gene expression but also from dynamic rewiring of gene-gene coordination. Using a divergent-edge framework applied to 77 155 malignant cells from 42 tumors, we identified four reproducible adaptive modules-integrated growth-energy (IGE), stress-adaptive transcription (SAT), IL-2-linked immune evasion (IL2), and multi-pathway collective invasion (MPC)-that cut across canonical PDAC states and reflect distinct regulatory programs. Integrating these modules with CRISPR-Cas9 dependency profiles and PRISM drug-response data revealed that adaptive behaviors collapse into two higher-order axes: a biosynthetic-metabolic IGE axis enriched for translational and DNA-repair dependencies, and a broader SAT-IL2-MPC stress-immune-invasion axis characterized by proteostasis, cytokine-linked, and cytoskeletal vulnerabilities. This architecture emerges only when divergent-edge modules are mapped into functional genomics space. Module activity also carried clinical relevance in PDAC. SAT-high tumors showed poorer survival, while MPC-high tumors exhibited a similar adverse trend; together, these modules defined a stress-immune-invasion poor-prognosis axis. In contrast, IGE activity showed no overall risk association, although an optimal-cut point-defined IGE-high subgroup displayed modestly improved survival.

Indexed as

Carcinoma, Pancreatic DuctalGene Expression Regulation, NeoplasticGene Regulatory NetworksPancreatic NeoplasmsHumanscell‐state plasticityfunctional genomicsgene regulatory networkspancreatic ductal adenocarcinomasingle‐cell transcriptomicstherapeutic vulnerabilities

Identifiers

PMID41766370
PMCPMC13352960

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.