Evidence map›Paper›PMID 26216984›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2015

Metabolite profiling stratifies pancreatic ductal adenocarcinomas into subtypes with distinct sensitivities to metabolic inhibitors.

Anneleen Daemen, David Peterson, Nisebita Sahu, Ron McCord, Xiangnan Du, Bonnie Liu, Katarzyna Kowanetz, Rebecca Hong, John Moffat, Min Gao and 12 more

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 246 papers.

0numbers the graph read from it
0cells of the map it votes in
246citing papers in PubMed
9.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

246 citing papers in PubMed, 412 citations in OpenAlex.

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  18. Metabolomics and Biomarker Discovery.Advances in experimental medicine and biology · 2026
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186 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors at 1 institution.

Anneleen DaemenBioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080;
David PetersonDiscovery Oncology, Genentech, South San Francisco, CA 94080;
Nisebita SahuDiscovery Oncology, Genentech, South San Francisco, CA 94080;
Ron McCordDiscovery Oncology, Genentech, South San Francisco, CA 94080;
Xiangnan DuTranslational Oncology, Genentech, South San Francisco, CA 94080;
Bonnie LiuTranslational Oncology, Genentech, South San Francisco, CA 94080;
Katarzyna KowanetzDiscovery Oncology, Genentech, South San Francisco, CA 94080;
Rebecca HongTranslational Oncology, Genentech, South San Francisco, CA 94080;
John MoffatBiochemical Pharmacology, Genentech, South San Francisco, CA 94080.
Min GaoTranslational Oncology, Genentech, South San Francisco, CA 94080;
Aaron BoudreauDiscovery Oncology, Genentech, South San Francisco, CA 94080;
Rana MroueDiscovery Oncology, Genentech, South San Francisco, CA 94080;
Laura CorsonTranslational Oncology, Genentech, South San Francisco, CA 94080;
Thomas O'BrienTranslational Oncology, Genentech, South San Francisco, CA 94080;
Jing QingTranslational Oncology, Genentech, South San Francisco, CA 94080;
Deepak SampathTranslational Oncology, Genentech, South San Francisco, CA 94080;
Mark MerchantTranslational Oncology, Genentech, South San Francisco, CA 94080;
Robert YauchDiscovery Oncology, Genentech, South San Francisco, CA 94080;
Gerard ManningBioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080;
Jeffrey SettlemanDiscovery Oncology, Genentech, South San Francisco, CA 94080;
Georgia HatzivassiliouTranslational Oncology, Genentech, South San Francisco, CA 94080;
Marie EvangelistaDiscovery Oncology, Genentech, South San Francisco, CA 94080; evangelista.marie@gene.com.
Genentech

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although targeting cancer metabolism is a promising therapeutic strategy, clinical success will depend on an accurate diagnostic identification of tumor subtypes with specific metabolic requirements. Through broad metabolite profiling, we successfully identified three highly distinct metabolic subtypes in pancreatic ductal adenocarcinoma (PDAC). One subtype was defined by reduced proliferative capacity, whereas the other two subtypes (glycolytic and lipogenic) showed distinct metabolite levels associated with glycolysis, lipogenesis, and redox pathways, confirmed at the transcriptional level. The glycolytic and lipogenic subtypes showed striking differences in glucose and glutamine utilization, as well as mitochondrial function, and corresponded to differences in cell sensitivity to inhibitors of glycolysis, glutamine metabolism, lipid synthesis, and redox balance. In PDAC clinical samples, the lipogenic subtype associated with the epithelial (classical) subtype, whereas the glycolytic subtype strongly associated with the mesenchymal (QM-PDA) subtype, suggesting functional relevance in disease progression. Pharmacogenomic screening of an additional ∼ 200 non-PDAC cell lines validated the association between mesenchymal status and metabolic drug response in other tumor indications. Our findings highlight the utility of broad metabolite profiling to predict sensitivity of tumors to a variety of metabolic inhibitors.

Indexed as

MetabolomeMetabolomicsAdenocarcinomaBiomarkers, TumorCarcinoma, Pancreatic DuctalCell ProliferationGlucoseGlutamineGlycolysisHumansInhibitory Concentration 50LipogenesisMesodermReproducibility of ResultsTranscription, GeneticBiomarkers, TumorGlucoseGlutaminebiomarkers for metabolic inhibitorsglycolysislipid synthesismetabolic subtypes in PDACmetabolite profiling

Identifiers

PMID26216984
PMCPMC4538616
OpenAlexW1940824108

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.