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Transcriptional regulation of hypoxic cancer cell metabolism and artificial intelligence

Luana Schito1, Sergio Rey-Keim1

  • 1School of Medicine, University College Dublin, Belfield, Dublin 4, D04 C7X2, Ireland; UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, D04 C7X2, Ireland.

Trends in Cancer
|October 31, 2024
PubMed

Insights

Hypoxic tumor microenvironments rely on oxygen-sensing transcription factors (O2R-TFs) to adapt cancer cell metabolism. Emerging artificial intelligence (AI) tools can help study these O2R-TF relationships.

Area of Science:

  • Molecular Biology
  • Cancer Research
  • Bioinformatics

Background:

  • Gene expression in hypoxic tumors is controlled by oxygen-responsive transcription factors (O2R-TFs).
  • These O2R-TFs regulate cancer cell oxygen consumption based on availability.
  • Understanding these mechanisms is crucial for cancer therapy.

Purpose of the Study:

  • To review key O2R-TFs involved in cancer.
  • To explore the application of artificial intelligence (AI) in studying O2R-TF interactions.
  • To understand cancer cell metabolic adaptation to hypoxia.

Main Methods:

  • Literature review of O2R-TFs.
  • Discussion of AI-based approaches for analyzing O2R-TF relationships.
  • Focus on cancer cell metabolic adaptations.

Main Results:

  • Identified key O2R-TFs regulating metabolic demand in hypoxia.
  • Highlighted the potential of AI in dissecting complex O2R-TF networks.
  • Provided insights into cancer cell adaptation strategies.

Conclusions:

  • O2R-TFs are central to cancer cell survival under hypoxia.
  • AI offers novel avenues for investigating O2R-TF functions.
  • Further research integrating AI can advance cancer treatment strategies.
Keywords:
HIFMYCdeep learninghypoxiamachine learningmetabolism

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