International Journal of General Medicine (Nov 2023)

The Characteristics of Transcription Factors Regulating T Cell Exhaustion Were Analyzed to Predict the Prognosis and Therapeutic Effect in Patients with HCC

  • Li J,
  • Zhou K,
  • Wu M,
  • Zhang R,
  • Jin X,
  • Qiao H,
  • Li J,
  • Cao X,
  • Zhang S,
  • Dong G

Journal volume & issue
Vol. Volume 16
pp. 5597 – 5619

Abstract

Read online

Jingbo Li,1,* Kun Zhou,2,3,* Meng Wu,3,* Rongzheng Zhang,3 Xi Jin,3 Han Qiao,3 Jiaqi Li,3 Xinyang Cao,3 Shuyun Zhang,3 Guanglu Dong4 1Department of Anesthesiology Research Institute, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 2Department of Clinical Laboratory, Beidahuang Industry Group General Hospital, Harbin, People’s Republic of China; 3Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 4Department of Tumor Radiotherapy, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China*These authors contributed equally to this workCorrespondence: Guanglu Dong, Department of Tumor Radiotherapy, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China, Tel +1 380 450 3001, Email [email protected] Shuyun Zhang, Scientific Research Center, the Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China, Tel +1 321 450 1198, Email [email protected]: Hepatocellular carcinoma (HCC) ranks as the third leading cause of cancer-related deaths, posing a significant threat to people in diverse regions. T-cell exhaustion (Tex) can hinder the efficacy of immunotherapy in patients with HCC, and the transcription factors that regulate Tex in HCC have not yet been fully elucidated.Patients and Methods: We used the single sample gene set enrichment analysis (ssGSEA) method to define the transcription factor pathway that regulates Tex and employed LASSO regression analysis to establish Tex related genes (TEXRS). To predict differences in immunotherapy efficacy between the two groups, we used the immunophenotype score and submap algorithm. RT-qPCR was used to detect the expression levels of the model genes in 21 pairs of HCC tissues. Finally, we assessed the cell communication strength and identified ligand receptors using the “CellChat” R package.Results: Nine Tex transcription factors were identified as regulators of the HCC immune microenvironment, with Tex scores affecting patient survival. Patients with a high Tex Risk Score (TEXRS) had significantly worse overall survival compared to patients with low TEXRS. After adjusting for confounding factors, TEXRS remained an independent prognostic factor. Importantly, TEXRS performed well in multiple independent external validation cohorts. Various algorithms have shown that patients in the low-TEXRS group might benefit more from immunotherapy. Finally, RT-qPCR analysis of 21 HCC samples showed that C7, CD5L, and SDS were significantly downregulated in HCC tissues, consistent with the bioinformatics analysis results.Conclusion: TEXRS proved to be a valuable predictor of immunotherapy and transcatheter arterial chemoembolization efficacy in patients with HCC. This holds promise for enhancing the prognosis and treatment outcomes of patients with HCC.Keywords: T-cell exhaustion, transcription factors, single-cell RNA sequencing, immune microenvironment, immunotherapy

Keywords