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Identification of HCC Subtypes With Different Prognosis and Metabolic Patterns Based on Mitophagy.

ABSTRACT: Background: Mitophagy is correlated with tumor initiation and development of malignancy. However, HCC heterogeneity with reference to mitophagy has yet not been systematically explored. Materials and Methods: Mitophagy-related, glycolysis-related, and cholesterol biosynthesis-related gene sets were obtained from the Reactome database. Mitophagy-related and metabolism-related subtypes were identified using the ConsensusClusterPlus algorithm. Univariate Cox regression was analysis was performed to identify prognosis-related mitophagy regulators. Principal component analysis (PCA) was used to create composite measures of the prognosis-related mitophagy regulators (mitophagyscore). Individuals with a mitophagyscore higher or lower than the median value were classified in high- or low-risk groups. Kaplan-Meier survival and ROC curve analyses were utilized to evaluate the prognostic value of the mitophagyscore. The nomogram and calibration curves were plotted using the"rms" R package. The package "limma" was used for differential gene expression analysis. Differentially expressed genes (DEGs) between high- and low-risk groups were used as queries in the CMap database. R package "pRRophetic" and Genomics of Drug Sensitivity in Cancer (GDSC) database were used to determine the sensitivity of 21 previously reported anti-HCC drugs. Results: Three distinct HCC subtypes with different mitophagic accumulation (low, high, and intermediate mitophagy subtypes) were identified. High mitophagy subtype had the worst outcome and highest glycolysis level. The lowest degree of hypoxia and highest cholesterol biosynthesis was observed in the low mitophagy subtype; oncogenic dedifferentiation level in the intermediate mitophagy subtype was the lowest. Mitophagyscore could serve as a novel prognostic indicator for HCC.High-risk patients had a poorer prognosis (log-rank test, p < 0.001). The area under the ROC curve for mitophagyscore in 1-year survival was 0.77 in the TCGA cohort and 0.75 in the ICGC cohort. Nine candidate small molecules which were potential drugs for HCC treatment were identified from the CMap database. A decline in the sensitivity towards 21 anti-HCC drugs was observed in low-risk patients by GDSC database. We also identified a novel key gene, SPP1, which was highly associated with different mitophagic subtypes. Conclusion: Based on bioinformatic analyses, we systematically examined the HCC heterogeneity with reference to mitophagy and observed three distinct HCC subtypes having different prognoses and metabolic patterns.

SUBMITTER: Wang Y

PROVIDER: S-EPMC8716756 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundGastric cancer (GC) is a digestive system cancer with a high mortality rate globally. Previous experiences and studies have provided clinicians with ample evidence to diagnose and treat patients with reasonable therapeutic options. However, there remains a need for sensitive biomarkers that can provide clues for early diagnosis and prognosis assessment.ResultsWe found 610 independent prognosis-related 5'-cytosine-phosphate-guanine-3' (CpG) sites (P < 0.05) among 21,121 sites in the training samples. We divided the GC samples into seven clusters based on the selected 610 sites. Cluster 6 had relatively higher methylation levels and high survival rates than the other six clusters. A prognostic risk model was constructed using the significantly altered CpG sites in cluster 6 (P < 0.05). This model could distinguish high-risk GC patients from low-risk groups efficiently with the area under the receiver operating characteristic curve of 0.92. Risk assessment showed that the high-risk patients had poorer prognosis than the low-risk patients. The methylation levels of the selected sites in the established model decreased as the risk scores increased. This model had been validated in testing group and its effectiveness was confirmed. Corresponding genes of the independent prognosis-associated CpGs were identified, they were enriched in several pathways such as pathways in cancer and gastric cancer. Among all of the genes, the transcript level of transforming growth factor β2 (TGFβ2) was changed in different tumor stages, T categories, grades, and patients' survival states, and up-regulated in patients with GC compared with the normal. It was included in the pathways as pathways in cancer, hepatocellular carcinoma or gastric cancer. The methylation site located on the promoter of TGFβ2 was cg11976166.ConclusionsThis is the first study to separate GC into different molecular subtypes based on the CpG sites using a large number of samples. We constructed an effective prognosis risk model that can identify high-risk GC patients. The key CpGs sites or their corresponding genes such as TGFβ2 identified in this research can provide new clues that will enable gastroenterologists to make diagnosis or personalized prognosis assessments and better understand this disease.

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Identification of HCC Subtypes With Different Prognosis and Metabolic Patterns Based on Mitophagy.

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