Functional variants of autophagy-related genes are associated with the development of hepatocellular carcinoma

Shen, Mingyang; Lin, Lin

doi:10.1016/j.lfs.2019.116675

Cited by 27 publications

(29 citation statements)

References 35 publications

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“…The ATG family tends to regulate the production of autophagic vesicles [22], while ATG10, a member of the ATG family, is also closely associated with tumorigenesis and development, e.g., high expression of ATG10 in colorectal cancer is associated with lymphovascular in ltration and lymph node metastasis, leading to tumor migration and invasion [23]. In addition, overexpression of ATG10 in cancers such as nasopharyngeal, hepatocellular, and gastric cancers has been associated with poor patient prognosis [24][25][26]. Past studies have found that overexpression of SIRT1 is associated with ES metastasis and poor prognosis, while the SIRT1 / 2 inhibitor Tenovin-6 kills ES cells in vitro [27].…”

Section: Discussionmentioning

confidence: 99%

Prognostic Implications of Autophagy-Related Gene Signatures in Ewing’s Sarcoma

Zhou¹,

Wu²,

Liu³

et al. 2021

Preprint

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Backgrand：Ewing's sarcoma (ES) is a highly aggressive malignant bone tumor with a high incidence among children and adolescents. While autophagy often plays an important role in tumor development species, we developed an autophagy-related prognostic signature based on the GEO dataset.Methods: Using the GEO database with the online website Human Autophagy Database(HADb), we screened for autophagy-related differential genes and we performed enrichment analysis and PPI analysis for autophagy-related differential genes, and then, constructed our autophagy-related prognostic gene signature by univariate Cox regression, lasso regression, and multivariate Cox regression .Results: We screened a total of 72 autophagy-related differential genes, and a total of 8 autophagy-related prognostic genes were screened by machine learning algorithms. ROC curves and survival curves also showed good predictive power of the 8 gene signatures. In addition, univariate and multivariate cox regression also showed that the 8 gene signatures were independent prognostic factors. And the results of GSEA enrichment analysis also revealed the correlation between autophagy and metabolic pathways.Conlusion：In summary, we developed an autophagy-related mRNA signature consisting of 8 mRNAs that effectively classified ES patients into low- and high-risk groups. The application of the signature in clinical treatment needs further observation to validate the validity of our findings.

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Section: Discussionmentioning

confidence: 99%

Prognostic Implications of Autophagy-Related Gene Signatures in Ewing’s Sarcoma

Zhou¹,

Wu²,

Liu³

et al. 2021

Preprint

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“…As previously mentioned, by bioinformatics analyses for the high-throughput sequencing data of the whole ARGs, several essential ARGs could be screened out and make up a novel prognostic model, which might better guide the prognosis of patients (7)(8)(9). Previous studies have also testified that some individual ARGs were related to the prognosis of LIHC patients (15)(16)(17). Thus, we have reasons to believe that, with the similar bioinformatics analysis for the global ARGs, we could construct an autophagy-related prognostic index model which may better help clinicians to monitor the prognosis of LIHC patients.…”

Section: Discussionmentioning

confidence: 99%

“…In recent years, a large number of studies have shown that autophagy could play dual roles (inhibition or promotion) in the generation and progression of LIHC by regulating immunity, oxidative stress, cell homeostasis and so on (13,14). It have been testified that some ARGs, proteins and pathways had a certain relationship with LIHC, and guided the diagnosis and prognosis of LIHC patients (15)(16)(17). Specially, Shanshan Wang et al found that AFP may be able to inhibit autophagy to promote the proliferation, migration and invasion of LIHC via activating PI3K/AKT/mTOR signaling (18).…”

Section: Introductionmentioning

confidence: 99%

A novel prognostic index model constructed with five autophagy-related genes may be a potential prognostic biomarker and therapeutic target in liver hepatocellular carcinoma

Zhu¹,

Wang²,

Liu³

et al. 2020

Preprint

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Background Early diagnosis and effective treatment of liver hepatocellular carcinoma (LIHC) are keys to improving the prognosis of patients. Increasing evidences clarify that autophagy-related genes (ARGs) make great differences to the generation and progression of LIHC, and may serve as prognostic biomarkers for LIHC. Methods We randomly divided the LIHC patients in The Cancer Genome Atlas (TCGA) into the training and testing group. Next, use the training group to perform univariate Cox, LASSO and multivariate Cox analysis to construct our prognostic index (PI) model for LIHC; use the testing group and the whole TCGA set to make internal validations; use the International Cancer Genome Consortium to make external validations; and use the whole TCGA, GSE14520 and Oncomine to exam the expression patterns of the five ARGs. Then, we performed the ROC curve as well as univariate and multivariate analysis to evaluate the independent prognostic prediction power of the PI model, and made nomograms to estimate 1,3,5-year survival rate of LIHC patients. Besides, we conducted functional enrichment analyses of differentially expressed ARGs with GO, KEGG and GSEA, and made drug sensitivity analysis for the PI model via the GDSC database. Results A novel PI model which was composed of five key ARGs ( ATG9A , EIF2S1 , GRID1 , SAR1A and SQSTM1 ) succeeded to be constructed. All the internal and external validations testified that the PI model could well distinguish high-risk patients from low-risk ones, with AUC values > 0.60. Further comparison analysis showed that the PI model was no less than some common prognostic factors. People can estimate the 1,3,5-year survival rate of individual LIHC patient with the nomograms. Additionally, we obtained 62 differentially expressed ARGs and studied the potential mechanisms or pathways. Furthermore, we also found some potential targeted drugs associated to the five ARGs for LIHC patients. Conclusions The novel five-ARGs PI model has great potential to serve as a diagnostic or prognostic biomarker and therapeutic target in LIHC, which may guide future clinical applications to some extent and improve the outcome of LIHC patients.

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“…A Chinese comparative study comprising around 1000 HCC cases vs. 1000 healthy controls showed that in an allelic model, ATG variants ATG5 rs17067724, ATG10 rs1864183, ATG10 rs10514231, ATG12 rs26537, and ATG16L1 rs4663402 were significantly associated with the risk of HCC, in which the ATG10 10514231 was the strongest factor. Bioinformatics analysis of TCGA database showed that mRNA expression of the ATG5, ATG10, ATG12, and ATG16L1 genes in HCC tissues was higher than that in normal tissues [111].…”

Section: Autophagymentioning

confidence: 97%

Sorafenib Resistance in Hepatocellular Carcinoma: The Relevance of Genetic Heterogeneity

Cabral

Tiribelli

Sukowati

2020

Cancers

118

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Despite advances in biomedicine, the incidence and the mortality of hepatocellular carcinoma (HCC) remain high. The majority of HCC cases are diagnosed in later stages leading to the less than optimal outcome of the treatments. Molecular targeted therapy with sorafenib, a dual-target inhibitor targeting the serine-threonine kinase Raf and the tyrosine kinases VEGFR/PDGFR, is at present the main treatment for advanced-stage HCC, either in a single or combinatory regimen. However, it was observed in a large number of patients that its effectiveness is hampered by drug resistance. HCC is highly heterogeneous, within the tumor and among individuals, and this influences disease progression, classification, prognosis, and naturally cellular susceptibility to drug resistance. This review aims to provide an insight on how HCC heterogeneity influences the different primary mechanisms of chemoresistance against sorafenib including reduced drug intake, enhanced drug efflux, intracellular drug metabolism, alteration of molecular targets, activation/inactivation of signaling pathways, changes in the DNA repair machinery, and negative balance between apoptosis and survival of the cancer cells. The diverse variants, mutations, and polymorphisms in molecules and their association with drug response can be a helpful tool in treatment decision making. Accordingly, the existence of heterogeneous biomarkers in the tumor must be considered to strengthen multi-target strategies in patient-tailored treatment.

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Functional variants of autophagy-related genes are associated with the development of hepatocellular carcinoma

Cited by 27 publications

References 35 publications

Prognostic Implications of Autophagy-Related Gene Signatures in Ewing’s Sarcoma

Prognostic Implications of Autophagy-Related Gene Signatures in Ewing’s Sarcoma

A novel prognostic index model constructed with five autophagy-related genes may be a potential prognostic biomarker and therapeutic target in liver hepatocellular carcinoma

Sorafenib Resistance in Hepatocellular Carcinoma: The Relevance of Genetic Heterogeneity

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