A four-DNA methylation signature as a novel prognostic biomarker for survival of patients with gastric cancer

Li, Chunmei; Zheng, Ya; Pu, Ke; Zhao, Da; Wang, Yuping; Guan, Qun; Zhou, Yongning

doi:10.1186/s12935-020-1156-8

Cited by 17 publications

(14 citation statements)

References 51 publications

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“…A risk score model based on four genes ( GRID2 , ATG4D , GABARAPL2 , and CXCR4 ) was identified as a potential prognostic biomarker for OS of GC (AUC, 0.671; Qiu et al, 2020 ). Another study suggested a high prognostic accuracy of a four-DNA methylation signature in GC patients (AUC, 0.724; Li et al, 2020 ). A seven-miRNA biomarker panel (miR-10b, miR-223, miR-30a-5p, miR-126, miR-21, miR-338, and let-7a) was established for OS prediction and validated using an independent dataset ( Li et al, 2010 ).…”

Section: Discussionmentioning

confidence: 99%

A Novel Six-Gene-Based Prognostic Model Predicts Survival and Clinical Risk Score for Gastric Cancer

et al. 2021

Front. Genet.

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Background: Autophagy plays a vital role in cancer initiation, malignant progression, and resistance to treatment. However, autophagy-related genes (ARGs) have rarely been analyzed in gastric cancer (GC). The purpose of this study was to analyze ARGs in GC using bioinformatic analysis and to identify new biomarkers for predicting the overall survival (OS) of patients with GC.Methods: The gene expression profiles and clinical data of patients with GC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, and ARGs were obtained from two other datasets (the Human Autophagy Database and Molecular Signatures Database). Lasso, univariate, and multivariate Cox regression analyses were performed to identify the OS-related ARGs. Finally, a six-ARG model was identified as a prognostic indicator using the risk-score model, and survival and prognostic performance were analyzed based on the Kaplan-Meier test and ROC curve. Estimate calculations were used to assess the immune status of this model, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed for investigating the functions and terms associated with the model-related genes in GC.Results: The six ARGs, DYNLL1, PGK2, HPR, PLOD2, PHYHIP, and CXCR4, were identified using Lasso and Cox regression analyses. Survival analysis revealed that the OS of GC patients in the high-risk group was significantly lower than that of the low-risk group (p < 0.05). The ROC curves revealed that the risk score model exhibited better prognostic performance with respect to OS. Multivariate Cox regression analysis indicated that the model was an independent predictor of OS and was not affected by most of the clinical traits (p < 0.05). The model-related genes were associated with immune suppression and several biological process terms, such as extracellular structure organization and matrix organization. Moreover, the genes were associated with the P13K-Akt signaling pathway, focal adhesion, and MAPK signaling pathway.Conclusions: This study presents potential prognostic biomarkers for GC patients that would aid in determining the best patient-specific course of treatment.

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Section: Discussionmentioning

confidence: 99%

A Novel Six-Gene-Based Prognostic Model Predicts Survival and Clinical Risk Score for Gastric Cancer

et al. 2021

Front. Genet.

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“…In contrast, epigenetic changes such as DNA methylation are reliable and specific cancer biomarkers that can be detected by PCR in blood and other body fluids samples easily obtained through noninvasive approach 13 . In particular, evidence from several studies indicated that the combinations of several DNA methylation markers achieved higher sensitivity and specificity for cancer prognosis compared with individual DNA methylation marker 14 – 16 . Therefore, in this study, we aimed to develop DNA methylation signature significantly associated with CRC prognosis with univariate and multivariate Cox proportional hazards regression analysis and the ROC analysis based on the genome-wide DNA methylation analysis.…”

Section: Discussionmentioning

confidence: 99%

The Development of Three-DNA Methylation Signature as a Novel Prognostic Biomarker in Patients with Colorectal Cancer

Gong

Ye²,

Liu

et al. 2020

BioMed Research International

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Aims. The prognosis of colorectal cancer (CRC) remains poor. This study aimed to develop and validate DNA methylation-based signature model to predict overall survival of CRC patients. Methods. The methylation array data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) database. These patients were divided into training and validation datasets. A risk score model was established based on Kaplan-Meier and multivariate Cox regression analysis of training cohort and tested in validation cohort. Results. Among total 14,626 DNA methylation candidate markers, we found that a three-DNA methylation signature (NR1H2, SCRIB, and UACA) was significantly associated with overall survival of CRC patients. Subgroup analysis indicated that this signature could predict overall survival of CRC patients regardless of age and gender. Conclusions. We established a prognostic model consisted of 3-DNA methylation sites, which could be used as potential biomarker to evaluate the prognosis of CRC patients.

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“…Thus, there is an increasing interest about GC epigenetic events, aiming to better understand GC physiopathology and, more importantly, to find relevant targets for translational medicine. In this context, recent investigations proposed new classifications of GCs based on different epigenetic profiles rather than on somatic alterations subtyping, identifying gene methylation panels able to predict the prognosis of patients and the risk of GC metastasis [ 36 , 37 , 38 ]. In this section, we discuss the main histone and DNA epigenetic modifications characterizing GC, while the role of non-coding RNAs and their potential therapeutic interest in gastrointestinal cancers have been recently reviewed elsewhere [ 39 ].…”

Section: Epigenetics Of Gcmentioning

confidence: 99%

Epigenetic Mechanisms in Gastric Cancer: Potential New Therapeutic Opportunities

Canale

Casadei-Gardini

Ulivi

et al. 2020

IJMS

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Gastric cancer (GC) is one of the deadliest malignancies worldwide. Complex disease heterogeneity, late diagnosis, and suboptimal therapies result in the poor prognosis of patients. Besides genetic alterations and environmental factors, it has been demonstrated that alterations of the epigenetic machinery guide cancer onset and progression, representing a hallmark of gastric malignancies. Moreover, epigenetic mechanisms undergo an intricate crosstalk, and distinct epigenomic profiles can be shaped under different microenvironmental contexts. In this scenario, targeting epigenetic mechanisms could be an interesting therapeutic strategy to overcome gastric cancer heterogeneity, and the efforts conducted to date are delivering promising results. In this review, we summarize the key epigenetic events involved in gastric cancer development. We conclude with a discussion of new promising epigenetic strategies for gastric cancer treatment.

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A four-DNA methylation signature as a novel prognostic biomarker for survival of patients with gastric cancer

Cited by 17 publications

References 51 publications

A Novel Six-Gene-Based Prognostic Model Predicts Survival and Clinical Risk Score for Gastric Cancer

A Novel Six-Gene-Based Prognostic Model Predicts Survival and Clinical Risk Score for Gastric Cancer

The Development of Three-DNA Methylation Signature as a Novel Prognostic Biomarker in Patients with Colorectal Cancer

Epigenetic Mechanisms in Gastric Cancer: Potential New Therapeutic Opportunities

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