ArticleCancer & metabolism2021
Robust metabolic transcriptional components in 34,494 patient-derived cancer-related samples and cell lines.
Article in Cancer & metabolism, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Advances in the understanding and therapeutic manipulation of cancer immune responsiveness: a Society for Immunotherapy of Cancer (SITC) review.Journal for immunotherapy of cancer · 2025Review
- Multivariate analysis of metabolic state vulnerabilities across diverse cancer contexts reveals synthetically lethal associations.Cell reports · 2024Article
- Multivariate analysis of metabolic state vulnerabilities across diverse cancer contexts reveals synthetically lethal associations.bioRxiv : the preprint server for biology · 2024Article
- Propionate reinforces epithelial identity and reduces aggressiveness of lung carcinoma.EMBO molecular medicine · 2023Article
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7 authors.
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Abstract
backgroundPatient-derived bulk expression profiles of cancers can provide insight into the transcriptional changes that underlie reprogrammed metabolism in cancer. These profiles represent the average expression pattern of all heterogeneous tumor and non-tumor cells present in biopsies of tumor lesions. Hence, subtle transcriptional footprints of metabolic processes can be concealed by other biological processes and experimental artifacts. However, consensus independent component analyses (c-ICA) can capture statistically independent transcriptional footprints of both subtle and more pronounced metabolic processes.
methodsWe performed c-ICA with 34,494 bulk expression profiles of patient-derived tumor biopsies, non-cancer tissues, and cell lines. Gene set enrichment analysis with 608 gene sets that describe metabolic processes was performed to identify the transcriptional components enriched for metabolic processes (mTCs). The activity of these mTCs was determined in all samples to create a metabolic transcriptional landscape.
resultsA set of 555 mTCs was identified of which many were robust across different datasets, platforms, and patient-derived tissues and cell lines. We demonstrate how the metabolic transcriptional landscape defined by the activity of these mTCs in samples can be used to explore the associations between the metabolic transcriptome and drug sensitivities, patient outcomes, and the composition of the immune tumor microenvironment.
conclusionsTo facilitate the use of our transcriptional metabolic landscape, we have provided access to all data via a web portal ( www.themetaboliclandscapeofcancer.com ). We believe this resource will contribute to the formulation of new hypotheses on how to metabolically engage the tumor or its (immune) microenvironment.
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