A Mitophagy-Related Gene Signature for Subtype Identification and Prognosis Prediction of Hepatocellular Carcinoma

Abstract

Globally, hepatocellular carcinoma (HCC) is the sixth most common cancer. In this study, the correlation between mitophagy and HCC prognosis was evaluated using data from The Cancer Genome Atlas (TCGA). Clinical and transcriptomic data of HCC patients were downloaded from TCGA dataset, and mitophagy-related gene (MRG) datasets were obtained from the Molecular Signature Database. Then, a consensus clustering analysis was performed to classify the patients into two clusters. Furthermore, tumor prognosis, clinicopathological features, functional analysis, immune infiltration, immune checkpoint (IC)-related gene expression level, tumor stem cells, ferroptosis status, and N6-methyladenosine analysis were compared between the two clusters. Finally, a mitophagy-related signature was developed. Two clusters (C1 and C2) were identified using the consensus clustering analysis based on the MRG signature. Patients with the C1 subtype exhibited upregulated pathways with better liver function, downregulated cancer-related pathways, lower cancer stem cell scores, lower Tumor Immune Dysfunction and Exclusion scores (TIDE), different ferroptosis status, and better prognosis compared with the patients with the C2 subtype. The C2 subtype was characterized by the increased grade of HCC, as well as the increased number of immune-related pathways and m6A-related genes. Higher immune scores were also observed for the C2 subtype. A signature containing four MRGs (PGAM5, SQSTM1, ATG9A, and GABARAPL1) which can accurately predict the prognosis of HCC patients was then identified. This four-gene signature exhibited a predictive effect in five other cancer types, namely glioma, uveal melanoma, acute myeloid leukemia, adrenocortical carcinoma, and mesothelioma. The mitophagy-associated subtypes of HCC were closely related to the immune microenvironment, immune checkpoint-related gene expression, cancer stem cells, ferroptosis status, m6A, prognosis, and HCC progression. The established MRG signature could predict prognosis in patients with HCC.

Comprehensive analysis of diverse programmed cell death patterns in the prognosis, tumor microenvironment and drug sensitivity in hepatocellular carcinoma

“…Most of these genes, except for DEDD and IL33, had also been included in different prognostic models of LIHC in previous studies. [35][36][37][38][39][40][41][42][43] The protein DEDD (death effector domain-containing protein) has been implicated in numerous physiological processes, including apoptosis. [44] Recent studies have suggested that DEDD could potentially serve as a valuable prognostic marker and therapeutic target for the treatment of cancer metastasis.…”

Integrated multi-omics analysis and machine learning based on O_linked_glycosylation genes refine molecular subtypes and prognosis for hepatocellular carcinoma

“…To date, research commonly focuses on speci c biological pathways, such as immunity, m6A methylation, and ferroptosis, to stratify HCC populations or construct prognostic survival models for patients (45)(46)(47). However, most of these studies were biased towards a single-omics and employed singular analysis methods such as ConsensusClustering, NMF clustering, or LASSO-Cox, which signi cantly limited the scope and adversely affected the accuracy of the nal outcomes.…”

Integrative analyses of a mitophagy-related gene signature for predicting prognosis in patients with uveal melanoma

“…Later, TCGA samples were classified into two subtypes using hierarchical clustering analysis based on the expression of mitophagy-related genes, and 16 DEGs were discovered in separate subtypes. A recent paper revealed that mitophagy-related biomarkers ( PGAM5, SQSTM1, ATG9A , and GABARAPL1 ) were survival-related genes of UM patients, which could be used to predict the survival of these patients ( Liu et al, 2022 ). Our results also showed the high expression of PGAM5 and SQSTM1 in the high immune-level and high-risk groups.…”

“…Although definitive functional changes and molecular mechanisms of mitophagy have not been completely elucidated, the expression levels of some mitophagy-related genes could serve as biomarkers for the diagnosis, prognosis, or therapy of some cancers ( Wang et al, 2021 ; Wang et al, 2022 ). A recent paper revealed that mitophagy is closely related to the clinical prognosis of patients with UM, and indicated that mitophagy-related biomarkers ( PGAM5, SQSTM1, ATG9A , and GABARAPL1 ) are survival-related genes of UM patients ( Liu et al, 2022 ). However, the mitophagy-related genes that cause pathogenesis, as well as their importance in the diagnosis, prognosis, and therapeutic interventions of UM, remain unclear.…”