Background: Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system with a high incidence that seriously threatens patients' lives and health. However, with the rise and application of new treatments, such as immunotherapy, there are still some restrictions in the treatment and diagnosis of HCC, and the therapeutic effects on patients are not ideal.
Methods: Two single-cell RNA sequencing (scRNA-seq) datasets from HCC patients, encompassing 25,189 cells, were analyzed in the study. We utilized non-negative matrix factorization (NMF) clustering to identify mitophagy patterns in HCC TME cells, including cancer-associated fibroblasts (CAFs), T cells, B cells, and tumor-associated macrophages (TAMs). Cell-to-cell communication was analyzed using the CellChat package, and pseudotime trajectory analysis was performed using the Monocle package. Gene regulatory networks were investigated with the SCENIC package, and survival analyses were conducted with mitophagy-related signatures.
Results: HCC samples analysis identified 22 clusters, including 7 principal cell types. Complex cell communications were observed among these cell types. Mitophagy-related CAFs, TAMs, CD8+ T cells, and B cells were identified. These subtypes had different biological states, cell-cell communications, and metabolic pathways. Mitophagy levels were elevated in tumor samples. Changes in mitophagy-related genes within specific cell subtypes were associated with different overall survival rates. However, mitophagy did not seem to affect the effectiveness of immunotherapy.
Conclusion: This study provides evidence that mitophagy within the HCC TME modulates intercellular communication, influencing tumor progression and patient prognosis. Targeting mitophagy may offer a promising approach to improve the long-term prognosis of HCC patients.
Keywords: bioinformatics; hepatocellular carcinoma; mitophagy; prognosis; tumor microenvironment.
Copyright © 2025 Li, Chen, Yao, Peng, Liu, Tang and Feng.