Development of a Novel Autophagy-Related Prognostic Signature and Nomogram for Hepatocellular Carcinoma

Fang, Qiongxuan; Chen, Hongsong

doi:10.3389/fonc.2020.591356

Cited by 33 publications

(29 citation statements)

References 45 publications

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“…The AUCs of the seven AGs in predicting 1-, 2-, and 3-year OS were 0.655, 0.721, and 0.705, respectively ( Figure 3E ). Meanwhile, the AUCs of the current risk score in predicting 1-, 2-, and 3-year OS were higher than those of the risk score of Yan et al ( 2020 ), Fang and Chen ( 2020 ), Liang et al ( 2020 ), and Tang et al ( 2020 ) ( Supplementary Figure 4 ).…”

Section: Resultsmentioning

confidence: 90%

“…Compared with low-risk patients, high-risk patients typically present with more aggressive characteristics, advanced stages, and higher mortality (all p < 0.05). Furthermore, the risk score exhibited better predictive capability than the conventional TNM stage and published risk scores (Fang and Chen, 2020;Liang et al, 2020;Tang et al, 2020;Yan et al, 2020).…”

Section: Discussionmentioning

confidence: 88%

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Identification of Aging-Related Genes Associated With Clinical and Prognostic Features of Hepatocellular Carcinoma

et al. 2021

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Background: Aging is a well-studied concept, but no studies have comprehensively analyzed the association between aging-related genes (AGs) and hepatocellular carcinoma (HCC) prognosis.Methods: Gene candidates were selected from differentially expressed genes and prognostic genes in The Cancer Genome Atlas (TCGA) database. A gene risk score for overall survival prediction was established using the least absolute shrinkage and selection operator (LASSO) regression analysis, and this was validated using data from the International Cancer Genome Consortium (ICGC) database. Functional analysis was conducted using gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis, and immune microenvironment and tumor stemness analyses.Results: Initially, 72 AGs from the TCGA database were screened as differentially expressed between normal and tumor tissues and as genes associated with HCC prognosis. Then, seven AGs (POLA1, CDK1, SOCS2, HDAC1, MAPT, RAE1, and EEF1E1) were identified using the LASSO regression analysis. The seven AGs were used to develop a risk score in the training set, and the risk was validated to have a significant prognostic value in the ICGC set (p < 0.05). Patients with high risk scores had lower tumor differentiation, higher stage, and worse prognosis (all p < 0.05). Multivariate Cox regression analyses also confirmed that the risk score was an independent prognostic factor for HCC in both the TCGA and ICGC sets (all p < 0.05). Further analysis showed that a high risk score was correlated with the downregulation of metabolism and tumor immunity.Conclusion: The risk score predicts HCC prognosis and could thus be used as a biomarker not only for predicting HCC prognosis but also for deciding on treatment.

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Section: Resultsmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 88%

Identification of Aging-Related Genes Associated With Clinical and Prognostic Features of Hepatocellular Carcinoma

et al. 2021

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“…In general, the HIF is a key regulator of the cellular hypoxia response that plays crucial roles in tumor resistance to different treatment modalities and poor prognosis in HCC (Burroughs et al, 2013;Fallah and Rini, 2019). There are more than a hundred genes regulated by HIF in an induced or repressed method (Manalo et al, 2005), which primarily leads to a reprogramming of glucose metabolism and regulates epithelialmesenchymal transition (Denko, 2008;Taniguchi et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

“…Recently, Zhang et al ( 2020 ) also developed a prognostic model based on three hypoxia gene signatures and further constructed a nomogram predicting OS for HCC patients, and the AUCs of 1- and 3 year-OS were 0.672 and 0.684, respectively. In addition, the AUC values of nomogram integrating autophagy-related signature, cirrhosis, and tumor size in predicting 3-year OS of HCC were 0.638 (Fang and Chen, 2020 ). At the expense of the acquisition of the expression of more genes in tumor tissues, our nomogram had an excellent performance in predicting survival of HCC patients.…”

Section: Discussionmentioning

confidence: 99%

Novel Hypoxia-Related Gene Signature for Risk Stratification and Prognosis in Hepatocellular Carcinoma

Jin

2021

Front. Genet.

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Hepatocellular carcinoma (HCC) is the most common form of liver cancer with limited therapeutic options and low survival rate. The hypoxic microenvironment plays a vital role in progression, metabolism, and prognosis of malignancies. Therefore, this study aims to develop and validate a hypoxia gene signature for risk stratification and prognosis prediction of HCC patients. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used as a training cohort, and one Gene Expression Omnibus database (GSE14520) was served as an external validation cohort. Our results showed that eight hypoxia-related genes (HRGs) were identified by the least absolute shrinkage and selection operator analysis to develop the hypoxia gene signature and demarcated HCC patients into the high- and low-risk groups. In TCGA, ICGC, and GSE14520 datasets, patients in the high-risk group had worse overall survival outcomes than those in the low-risk group (all log-rank P < 0.001). Besides, the risk score derived from the hypoxia gene signature could serve as an independent prognostic factor for HCC patients in the three independent datasets. Finally, a nomogram including the gene signature and tumor-node-metastasis stage was constructed to serve clinical practice. In the present study, a novel hypoxia signature risk model could reflect individual risk classification and provide therapeutic targets for patients with HCC. The prognostic nomogram may help predict individualized survival.

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“…Late-stage cervical cancer is linked to poor prognosis, putting forth a need for a more effective method to predict disease earlier. Recently, a prognostic model constructed based on autophagy-related genes has attracted the attention of researchers; for example, in patients with colon cancer [ 18 ], head and neck squamous cell carcinoma [ 19 ], esophageal cancer [ 20 ], gastric cancer [ 21 ], glioma [ 22 ], hepatocellular carcinoma [ 23 ] and others, it has been proven that a prognostic model constructed by autophagy-related genes can predict the prognosis of tumor survival.…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of Autophagy-Related Gene Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer

Jiang

Wang

et al. 2021

Journal of Oncology

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Autophagy is a process of engulfing one’s own cytoplasmic proteins or organelles and coating them into vesicles, fusing with lysosomes to form autophagic lysosomes, and degrading the contents it encapsulates. Increasing studies have shown that autophagy disorders are closely related to the occurrence of tumors. However, the prognostic role of autophagy genes in cervical cancer is still unclear. In this study, we constructed risk signatures of autophagy-related genes (ARGs) to predict the prognosis of cervical cancer. The expression profiles and clinical information of autophagy gene sets were downloaded from TCGA and GSE52903 queues as training and validation sets. The normal cervical tissue expression profile data from the UCSC XENA website (obtained from GTEx) were used as a supplement to the TCGA normal cervical tissue. Univariate COX regression analysis of 17 different autophagy genes was performed with the consensus approach. Tumor samples from TCGA were divided into six subtypes, and the clinical traits of the six subtypes had different distributions. Further absolute shrinkage and selection operator (LASSO) and multivariable COX regression yielded an autophagy genetic risk model consisting of eight genes. In the training set, the survival rate of the high-risk group was lower than that of the low-risk group ( p < 0.0001). In the validation set, the AUC area of the receiver operating characteristic (ROC) curve was 0.772 for the training set and 0.889 for the verification set. We found that high and low risk scores were closely related to TNM stage ( p < 0.05). The nomogram shows that the risk score combined with other indicators, such as G, T, M, and N, better predicts 1-, 3-, and 5-year survival rates. Decline curve analysis (DCA) shows that the risk model combined with other indicators produces better clinical efficacy. Immune cells with an enrichment score of 28 showed statistically significant differences related to high and low risk. GSEA enrichment analysis showed the main enrichment being in KRAS activation, genes defining epithelial and mesenchymal transition (EMT), raised in response to the low oxygen level (hypoxia) gene and NF-kB in response to TNF. These pathways are closely related to the occurrence of tumors. Our constructed autophagy risk signature may be a prognostic tool for cervical cancer.

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Development of a Novel Autophagy-Related Prognostic Signature and Nomogram for Hepatocellular Carcinoma

Cited by 33 publications

References 45 publications

Identification of Aging-Related Genes Associated With Clinical and Prognostic Features of Hepatocellular Carcinoma

Identification of Aging-Related Genes Associated With Clinical and Prognostic Features of Hepatocellular Carcinoma

Novel Hypoxia-Related Gene Signature for Risk Stratification and Prognosis in Hepatocellular Carcinoma

Identification and Validation of Autophagy-Related Gene Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer

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