PeerJ (Jan 2023)

A novel fatty acid metabolism-related gene prognostic signature and candidate drugs for patients with hepatocellular carcinoma

  • Jingze Yang,
  • Xin Yang,
  • Jinlu Guo,
  • Shi Liu

DOI
https://doi.org/10.7717/peerj.14622
Journal volume & issue
Vol. 11
p. e14622

Abstract

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Hepatocellular carcinoma (HCC) is one of the deadliest cancers. Fatty acid metabolism (FAM) is associated with the development and treatment of HCC. This study aimed to build a FAM-related gene model to assess the prognosis of HCC and provide guidance for individual treatment. RNA-sequencing data of patients with HCC from The Cancer Genome Atlas and Gene Expression Omnibus database (GSE14520) were extracted as the training and validation sets, respectively. A FAM-related gene predictive signature was built, and the performance of prognostic model was assessed. The immune infiltration and drug sensitivity were also evaluated. Quantitative real-time polymerase chain reaction and western blot were performed to evaluate the levels of the model genes. A 12-gene FAM-related risk signature was constructed; patients with a higher risk score had poorer prognosis than those with a lower risk score. Risk score was shown as an independent risk factor for overall survival of HCC, and the signature was further confirmed as an effective and accurate model. A nomogram was constructed, and it exhibited the good performance in the prognostic prediction. In addition, the immune cell infiltration and sensitivity to chemotherapy drugs were correlated with different risk levels. Finally, quantitative real-time polymerase chain reaction and western blot proved the changes of above genes. Differential expression of FAM-related genes can be used to predict response to immunotherapy and chemotherapy, and improve the clinical prognosis evaluation of patients with HCC, which provides new clues for further experimental exploration and verification on FAM-related genes in HCC.

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