ArticleCancers2023
Unique Metabolic Contexts Sensitize Cancer Cells and Discriminate between Glycolytic Tumor Types.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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
4 citing papers in PubMed, 7 citations in OpenAlex.
- Construction and validation of an oxidative phosphorylation-related gene signature in lung squamous cell carcinoma patients.Lung cancer management · 2025Article
- Blockage of Autophagy for Cancer Therapy: A Comprehensive Review.International journal of molecular sciences · 2024Review
- Metabolic Oscillations and Glycolytic Phenotypes of Cancer Cells.International journal of molecular sciences · 2023Article
- Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes.Frontiers in endocrinology · 2023Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Cancer cells utilize variable metabolic programs in order to maintain homeostasis in response to environmental challenges. To interrogate cancer cell reliance on glycolytic programs under different nutrient availabilities, we analyzed a gene panel containing all glycolytic genes as well as pathways associated with glycolysis. Using this gene panel, we analyzed the impact of an siRNA library on cellular viability in cells containing only glucose or only pyruvate as the major bioenergetic nutrient source. From these panels, we aimed to identify genes that elicited conserved and glycolysis-dependent changes in cellular bioenergetics across glycolysis-promoting and OXPHOS-promoting conditions. To further characterize gene sets within this panel and identify similarities and differences amongst glycolytic tumor RNA-seq profiles across a pan-cancer cohort, we then used unsupervised statistical classification of RNA-seq profiles for glycolytic cancers and non-glycolytic cancer types. Here, Kidney renal clear cell carcinoma (KIRC); Head and Neck squamous cell carcinoma (HNSC); and Lung squamous cell carcinoma (LUSC) defined the glycolytic cancer group, while Prostate adenocarcinoma (PRAD), Thyroid carcinoma (THCA), and Thymoma (THYM) defined the non-glycolytic cancer group. These groups were defined based on glycolysis scoring from previous studies, where KIRC, HNSC, and LUSC had the highest glycolysis scores, meanwhile, PRAD, THCA, and THYM had the lowest. Collectively, these results aimed to identify multi-omic profiles across cancer types with demonstrated variably glycolytic rates. Our analyses provide further support for strategies aiming to classify tumors by metabolic phenotypes in order to therapeutically target tumor-specific vulnerabilities.
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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.