The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma

Abstract

Background: Mitophagy has been found to play a significant part in the cancer process in a growing number of studies in recent years. However, there is still a lack of study on mitophagy-related genes’ (MRGs) prognostic potential and clinical significance in hepatocellular carcinoma (HCC).Methods: We employed bioinformatics and statistical knowledge to examine the transcriptome data of HCC patients in the TCGA and GEO databases, with the goal of constructing a multigene predictive model. Then, we separated the patients into high- and low-risk groups based on the score. The model’s dependability was determined using principal components analysis (PCA), survival analysis, independent prognostic analysis, and receiver operating characteristic (ROC) analysis. Following that, we examined the clinical correlations, pharmacological treatment sensitivity, immune checkpoint expression, and immunological correlations between patients in high and low risk groups. Finally, we evaluated the variations in gene expression between high- and low-risk groups and further analyzed the network core genes using protein-protein interaction network analysis.Results: Prognostic models were built using eight genes (OPTN, ATG12, CSNK2A2, MFN1, PGAM5, SQSTM1, TOMM22, TOMM5). During validation, the prognostic model demonstrated high reliability, indicating that it could accurately predict the prognosis of HCC patients. Additionally, we discovered that typical HCC treatment medicines had varying impacts on patients classified as high or low risk, and that individuals classified as high risk are more likely to fail immunotherapy. Additionally, the high-risk group expressed more immunological checkpoints. The immunological status of patients in different risk categories varies as well, and patients with a high-risk score have a diminished ability to fight cancer. Finally, PPI analysis identified ten related genes with potential for research.Conclusion: Our prognostic model had good and reliable predictive ability, as well as clinical diagnosis and treatment guiding significance. Eight prognostic MRGs and ten network core genes merited further investigation.

Machine Learning-Based Identification of B4GALNT1 as a Key Player in Hepatocellular Carcinoma: A Comprehensive Bioinformatics and Structural Analysis

“…DGE (Differential gene expression) analysis was performed on the whole dataset, and 36 PC genes were identified to be differentially expressed from ML identified genes (Figure 3(F)) . After that using lasso penalized coz regression analysis theses 55 PC genes were reduced to 13 genes SEMA3F [51], B4GALNT1 [7], COLEC10 [52], CEP131 [53], APLN [54], GBA [55], SCAMP3 [56], TOMM40L [57], PYGO2 [58] and PLVAP [59] has been reported in literature while CAPN11, SPTY2D1OS and C14orf180 is not so far has been studied in LIHC. Additionally, these 13 genes from survival analysis predicted to be prognostic genes for OS of LIHC cases.…”

Identification of ULK1 as a novel mitophagy-related gene in diabetic nephropathy

“…For instance, Zhuo et al constructed a signature of MRGs as a new prognostic model to predict the survival of pancreatic cancer patients (37). Another recent study analyzed the prognostic value and clinical significance of MRGs in hepatocellular carcinoma (38). However, the bioinformatic analysis of MRGs in DN, to our knowledge, has not yet been explored until now.…”

Six mitophagy-related hub genes as peripheral blood biomarkers of Alzheimer’s disease and their immune cell infiltration correlation

“…Mitophagy as a selective degradation process, is critical to keeping mitochondria healthy, producing ATP, and maintaining neuronal activity and survival by removing impaired mitochondria. MRGs have been previously reported as prognostic or diagnostic markers for various tumors, including pancreatic cancer ( Zhuo et al, 2022 ), breast cancer ( Zhao et al, 2022 ), and liver cancer ( Chen et al, 2021 ; Xu et al, 2022 ), whereas only a limited number of studies have examined the usefulness of them as AD biomarkers. Pakpian et al (2020) recently reported that alterations in mitochondrial dynamic-related genes in the peripheral blood may be useful for diagnosing AD.…”