4.6 Article

Predictive value of hypoxia, metabolism and immune factors for prognosis in hepatocellular carcinoma: a retrospective analysis and multicenter validation study

Journal

JOURNAL OF CANCER
Volume 11, Issue 14, Pages 4145-4156

Publisher

IVYSPRING INT PUBL
DOI: 10.7150/jca.41983

Keywords

hepatocellular carcinoma; tumor microenvironment; prognosis; multi-omics data

Categories

Funding

  1. Fund of National Natural Science Foundation of China [NSFC81860319]
  2. Guangxi Science and Technology Program [GuikeAB17195020]

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The tumor microenvironment (TME), as a potent and pervasive factor of tumorigenesis and tumor progression, has a profound impact on the clinical outcomes of hepatocellular carcinoma (HCC). A systematic analysis of TME factors in HCC is still lacking and urgently needed. In this retrospective analysis and multicenter validation study, a total of 987 HCC patients with RNA-seq or microarray data and the corresponding clinical information from five cohorts were included. A TME risk score was developed based on five factors (hypoxia, nucleotide, TCA cycle, T helper cells and activated CD8 T cells). We also identified various types of clinical parameters and molecular features associated with the TME risk score. The TME risk factor network depicts close associations among the factors. Our TME risk score could be a practical and reliable predictor that can stratify patients according to distinct clinical outcomes and was validated by integrating five HCC patient cohorts (HR= 2.27, 95% CI: 1.79-2.86, P<0.001). Pan-cancer analysis also suggested that the prognostic signature was an effective prognostic indicator in 9,122 patients across 30 types of cancer. Correlation analysis revealed that the TME risk score was significantly associated with tumor progression-related clinical factors and molecular factors. TME factors are perturbations in HCC patients, and these alterations are vital determinants of both clinical outcomes and biological characteristics. The TME risk score we proposed is valuable for deciphering the molecular characteristics of the TME in HCC and is an effective prognostic predictor for HCC prognosis evaluation.

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