Integrative Analysis Identifies Cell-Type-Specific Genes Within Tumor Microenvironment as Prognostic Indicators in Hepatocellular Carcinoma

Abstract

BackgroundHepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, but effective early detection and prognostication methods are lacking. MethodsThe Cox regression model was built to stratify the HCC patients. The single-cell RNA sequencing data analysis and gene set enrichment analysis were employed to investigate the biological function of identified markers. PLCB1 gain- or loss-of-function experiments were performed, and obtained HCC samples were analyzed using quantitative real-time PCR and immunohistochemistry assay to validate the biological function of identified markers.ResultsIn this study, we developed a model using optimized markers for HCC recurrence prediction. Specifically, we screened out 8 genes through a series of data analyses, and built a multivariable Cox model based on their expression. The risk stratifications using the Eight-Gene Cox (EGC) model were closely associated with the recurrence-free survivals (RFS) in both training and three validation cohorts. We further demonstrated that this risk stratification could serve as an independent predictor in predicting HCC recurrence, and that the EGC model could outperform other models. Moreover, we also investigated the cell-type-specific expression patterns of the eight recurrence-related genes in tumor microenvironment using single-cell RNA sequencing data, and interpreted their functional roles from correlation and gene set enrichment analyses, in vitro and in vivo experiments. Particularly, PLCB1 and SLC22A7 were predominantly expressed in malignant cells, and they were predicted to promote angiogenesis and to help maintain normal metabolism in liver, respectively. In contrast, both FASLG and IL2RB were specifically expressed in T cells, and were highly correlated with T cell marker genes, suggesting that these two genes might assist in maintaining normal function of T cell-mediated immune response in tumor tissues.ConclusionIn conclusion, the EGC model and eight identified marker genes could not only facilitate the accurate prediction of HCC recurrence, but also improve our understanding of the mechanisms behind HCC recurrence.

Neuropilins as potential biomarkers in hepatocellular carcinoma: a systematic review of basic and clinical implications

“…Moreover, both NRPs are strongly associated with worse prognoses and different tumorassociated parameters in HCC patients. 15,16,[24][25][26][29][30][31][32][33]35 Similar findings were found with different solid tumors, where NRPs negatively correlated with prognosis and higher invasion and metastasis risk, 18,71,73-75 highlighting their potential role as diagnostic tools for HCC patient prognosis.…”

“…17,25 NRPs as prognostic biomarkers Consistent with previous evidence, numerous studies have evaluated the prognostic role of NRP1 and NRP2 in HCC patients. 15,16,[24][25][26][29][30][31][32][33] . NRP1 overexpression was significantly correlated with shorter overall (OS) 16,[24][25][26]29 and recurrence-free (RFS) 16,24 survival in patients, while NRP2 overexpression correlated with their lower OS and disease-free survival.…”

“…30 Moreover, NRP1 expression was correlated with RAD51 in hepatic stellate cells (HSCs), a valuable prognostic biomarker 34 , and with an increased recurrence rate. 32,33 Peritumoral NRP1 levels have also been evaluated in HCC human samples. Patients with higher peritumoral NRP1 expression had higher OS, higher time to recurrence, and lower early recurrence incidence.…”

Study of the role of neuropilin-1 in the development, prognosis and cellular response to lenvatinib in human hepatocellular carcinoma

“…Likewise, an increased expression of NRP1 has been strongly associated to worse prognosis of HCC patients, reporting shorter OS, PFS and recurrence-free survival (RFS) 78,84,[88][89][90][91] . Furthermore, not only survival, but also other tumor-associated parameters have been closely related to NRP1 78,79,84,92 .…”