Machine learning-based integration develops a neutrophil-derived signature for improving outcomes in hepatocellular carcinoma - Gong, Qiming; Chen, Xiaodan; Liu, Fahui; Cao, Yuhua (Frontiers in Immunology, 2023)
The heterogeneity of tumor immune microenvironments plays a significant role in drug resistance, recurrence, and poor prognosis among patients with hepatocellular carcinoma (HCC). Recent large-scale single-cell studies have revealed the critical clinical significance of neutrophils and their crucial role in the immune microenvironment of HCC. However, there is still a gap in exploring the stratification of patients with HCC based on the heterogeneity of neutrophils. Therefore, it is crucial to identify a convenient and efficient approach to describing the "neutrophil characteristics" of patients with HCC to guide clinical decision-making. This study describes the tumor microenvironment in patients with HCC. Neutrophils are emphasized as a critical component of this environment.Using bulk-sequencing data and single-cell sequencing data, we successfully stratified two cohorts of patients with HCC into subtypes that exhibit significant differences in prognosis, clinical pathological characteristics, inflammation-related pathways, levels of immune infiltration, and expression levels of immune genes. These findings indicate that patients with different subtypes based on neutrophil feature gene stratification exhibit high heterogeneity. Following further screening, we construct a risk model of 10 essential genes called the “neutrophil-derived signature” (NDS) using machine learning-integrated analysis of 101 prediction models. The NDS of patients is expressed as a “RiskScore,” which demonstrates significantly higher accuracy than traditional clinical variables and is associated with higher malignancy degrees in patients with higher scores. Furthermore, RiskScore is an independent prognostic factor for overall survival and demonstrates solid predictive value for the prognosis of patients with HCC. Additionally, our study reveals that RiskScore is associated with the efficacy of immune therapy and commonly used chemotherapy drugs, indicating the potential for further clinical applications of RiskScore. Our study also identifies and analyzes the feasibility of the critical gene RTN3 in NDS as a molecular marker for HCC and its biological function and role in tumor cell lines. In summary, these findings suggest that developing potential drugs targeting these neutrophil cell marker genes can help assess the risk and clinical treatment of HCC. NDS represents a powerful and promising tool to improve the clinical outcomes of individual patients with HCC.