Evidence map›Paper›PMID 27721378›Full record

ArticleNature communications2016

Tissue-specific and convergent metabolic transformation of cancer correlates with metastatic potential and patient survival.

Edoardo Gaude, Christian Frezza

Abstract read
In one paragraph

Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 232 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
232citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

232 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Pan-cancer Distant Metastasis Prediction Based on Graph Neural Network.Interdisciplinary sciences, computational life sciences · 2026
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172 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

2 authors.

Edoardo GaudeMRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Box 197, Cambridge Biomedical Campus, Cambridge CB2 0XZ, UK.
Christian FrezzaMRC Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Box 197, Cambridge Biomedical Campus, Cambridge CB2 0XZ, UK.ORCID 0000-0002-3293-7397

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer cells undergo a multifaceted rewiring of cellular metabolism to support their biosynthetic needs. Although the major determinants of this metabolic transformation have been elucidated, their broad biological implications and clinical relevance are unclear. Here we systematically analyse the expression of metabolic genes across 20 different cancer types and investigate their impact on clinical outcome. We find that cancers undergo a tissue-specific metabolic rewiring, which converges towards a common metabolic landscape. Of note, downregulation of mitochondrial genes is associated with the worst clinical outcome across all cancer types and correlates with the expression of epithelial-to-mesenchymal transition gene signature, a feature of invasive and metastatic cancers. Consistently, suppression of mitochondrial genes is identified as a key metabolic signature of metastatic melanoma and renal cancer, and metastatic cell lines. This comprehensive analysis reveals unexpected facets of cancer metabolism, with important implications for cancer patients' stratification, prognosis and therapy.

Indexed as

Cell Line, TumorEpithelial-Mesenchymal TransitionGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNeoplasm MetastasisNeoplasmsOrgan SpecificityOxidative PhosphorylationSurvival AnalysisTreatment Outcome

Identifiers

PMID27721378
PMCPMC5062467

What OpenQuestion holds

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Registered trials

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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.