Regulatory T-cells-related signature for identifying a prognostic subtype of hepatocellular carcinoma with an exhausted tumor microenvironment

Abstract

Regulatory T-Cells (Tregs) are important in the progression of hepatocellular cancer (HCC). The goal of this work was to look into Tregs-related genes and develop a Tregs-related prognostic model. We used the weighted gene coexpression network analysis (WGCNA) to look for Tregs-related genes in the TCGA, ICGC, and GSE14520 cohorts and then used the non-negative matrix factorization (NMF) algorithm to find Tregs-related subpopulations. The LASSO-Cox regression approach was used to determine Tregs-related genes, which were then condensed into a risk score. A total of 153 overlapping genes among the three cohorts were considered Tregs-related genes. Based on these genes, two Tregs-associated clusters that varied in both prognostic and biological characteristics were identified. When compared with Cluster 1, Cluster 2 was a TME-exhausted HCC subpopulation with substantial immune cell infiltration but a poor prognosis. Five Tregs-related genes including HMOX1, MMP9, CTSC, SDC3, and TNFRSF11B were finally used to construct a prognostic model, which could accurately predict the prognosis of HCC patients in the three datasets. Patients in the high-risk scores group with bad survival outcomes were replete with immune/inflammatory responses, but exhausted T cells and elevated PD-1 and PD-L1 expression. The results of qRT-PCR and immunohistochemical staining (IHC) analysis in clinical tissue samples confirmed the above findings. Moreover, the signature also accurately predicted anti-PD-L1 antibody responses in the IMvigor210 dataset. Finally, HMOX1, MMP9, and TNFRSF11B were expressed differently in Hep3B and Huh7 cells after being treated with a PD1/PD-L1 inhibitor. In conclusion, our study uncovered a Tregs-related prognostic model that could identify TMEexhausted subpopulations and revealed that PD1/PD-L1 inhibitors could alter the expression levels of HMOX1, MMP9, and TNFRSF11B in Hep3B and Huh7 cells, which might help us better understand Tregs infiltration and develop personalized immunotherapy treatments for HCC patients.

Predictive Value of a Diagnostic Five-Gene Biomarker for Pediatric Sepsis

“…After total RNA was extracted from PBMCs, mRNA levels of diagnostic markers were detected by qRT-PCR and normalized using β-ACTIN. 11 The primer sequences are shown in Table 2 .…”

Combined analysis of bulk and single-cell RNA sequencing reveals novel natural killer cell-related prognostic biomarkers for predicting immunotherapeutic response in hepatocellular carcinoma

“…Following the tissue wax blocks’ serial sectioning, sample sections were gathered and stored for subsequent use in a 4°C freezer. We next used TUBA1B (Abcam, ab108629) and CD56 (Abcam, ab75813) antibodies in IHC experiments on formalin-fixed de-paraffinized slices and captured pictures using microscopy as previously reported ( 19 ).…”

Prognostic Lysosome-Related Biomarkers for Predicting Drug Candidates in Hepatocellular Carcinoma: An Insilco Analysis

“…We then utilized qRT-PCR to determine the expression of genes in the signature, as previously done. 26 Sequences of primers were shown in Table S2 . The sections were heated in citrate buffer for antigen retrieval after quenching endogenous peroxidase with 2% hydrogen peroxide and blocking with 5% bovine serum albumin (BSA, A602449, Sangon Biotech, China).…”