ArticlePloS one2016
A Balanced Tissue Composition Reveals New Metabolic and Gene Expression Markers in Prostate Cancer.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 35 citations in OpenAlex.
- Spatial multi-omics identifies aggressive prostate cancer signatures highlighting pro-inflammatory chemokine activity in the tumor microenvironment.Nature communications · 2025Article
- Spatial integration of multi-omics data from serial sections using the novel Multi-Omics Imaging Integration Toolset.GigaScience · 2025Article
- The relationship between immune cells and prostate cancer, and the mediating role of metabolites: a Mendelian randomization study.Scientific reports · 2024Article
- Deciphering the Tumor Microenvironment in Prostate Cancer: A Focus on the Stromal Component.Cancers · 2024Review
- Transcending frontiers in prostate cancer: the role of oncometabolites on epigenetic regulation, CSCs, and tumor microenvironment to identify new therapeutic strategies.Cell communication and signaling : CCS · 2024Review
- A new tumorgraft panel to accelerate precision medicine in prostate cancer.Frontiers in oncology · 2023Article
- Genetics of enzymatic dysfunctions in metabolic disorders and cancer.Frontiers in oncology · 2023Review
- Succinate at the Crossroad of Metabolism and Angiogenesis: Roles of SDH, HIF1α and SUCNR1.Biomedicines · 2022Review
- Article
- Androgen-Dependent Prostate Cancer Cells Reprogram Their Metabolic Signature upon GLUT1 Upregulation by Manganese Superoxide Dismutase.Antioxidants (Basel, Switzerland) · 2022Article
- Review
- Article
- Spatial differentiation of metabolism in prostate cancer tissue by MALDI-TOF MSI.Cancer & metabolism · 2021Article
- Spatial modeling of prostate cancer metabolic gene expression reveals extensive heterogeneity and selective vulnerabilities.Scientific reports · 2020Article
- Cholesterol synthesis pathway genes in prostate cancer are transcriptionally downregulated when tissue confounding is minimized.BMC cancer · 2018Article
- Role of Polyamines in Immune Cell Functions.Medical sciences (Basel, Switzerland) · 2018Review
- Ex vivo metabolic fingerprinting identifies biomarkers predictive of prostate cancer recurrence following radical prostatectomy.British journal of cancer · 2017Article
- Article
- Presence of TMPRSS2-ERG is associated with alterations of the metabolic profile in human prostate cancer.Oncotarget · 2016Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular analysis of patient tissue samples is essential to characterize the in vivo variability in human cancers which are not accessible in cell-lines or animal models. This applies particularly to studies of tumor metabolism. The challenge is, however, the complex mixture of various tissue types within each sample, such as benign epithelium, stroma and cancer tissue, which can introduce systematic biases when cancers are compared to normal samples. In this study we apply a simple strategy to remove such biases using sample selections where the average content of stroma tissue is balanced between the sample groups. The strategy is applied to a prostate cancer patient cohort where data from MR spectroscopy and gene expression have been collected from and integrated on the exact same tissue samples. We reveal in vivo changes in cancer-relevant metabolic pathways which are otherwise hidden in the data due to tissue confounding. In particular, lowered levels of putrescine are connected to increased expression of SRM, reduced levels of citrate are attributed to upregulation of genes promoting fatty acid synthesis, and increased succinate levels coincide with reduced expression of SUCLA2 and SDHD. In addition, the strategy also highlights important metabolic differences between the stroma, epithelium and prostate cancer. These results show that important in vivo metabolic features of cancer can be revealed from patient data only if the heterogeneous tissue composition is properly accounted for in the analysis.
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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.