ArticleNature communications2026
Metabolic characterization of the tumor microenvironment orchestrates therapeutic strategies and clinical outcomes in pancreatic cancer.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Metabolic reprogramming and immunosuppressive tumor microenvironment (TME) are hallmark features driving pancreatic ductal adenocarcinoma (PDAC) progression. Despite the therapeutic potential of targeting immunometabolism, effective strategies remain scarce in clinical practice, likely due to cell-specific metabolic heterogeneity within PDAC TME. Here, we show integration of three algorithms to estimate metabolic fluxomes and pathways using scRNA-seq data, generating a comprehensive cell type-specific metabolic atlas. Leveraging 460 PDAC samples, we establish a TME-metabolism subtyping system, classifying PDAC into three subtypes (TMS1-3) with distinct immune-metabolic profiles and clinical outcomes. TMS1, characterized by low immune infiltrates, is susceptible to ferroptosis inducers. TMS2, enriched in macrophages, responds to chemoimmunotherapy with inhibition of glutamine synthetase. TMS3, characterized by matrix remodeling, responds to glycolysis inhibitors and albumin-paclitaxel. Finally, we develop a computational classifier for subtype discrimination. Together, this study delineates the metabolic heterogeneity of the PDAC TME and proposes a classification system that suggests promising therapeutic targets.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.