cg04448376, cg24387542, cg08548498, and cg14621323 as a Novel Signature to Predict Prognosis in Kidney Renal Papillary Cell Carcinoma

Joint Authors

Zhang, Ying-Ying
Wang, Ying-Lei

Source

BioMed Research International

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-17

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Medicine

Abstract EN

Introduction.

DNA methylation plays a vital role in prognosis prediction of cancers.

In this study, we aimed to identify novel DNA methylation site biomarkers and create an efficient methylated site model for predicting survival in kidney renal papillary cell carcinoma (KIRP).

Methods.

DNA methylation and gene expression profile data were downloaded from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database.

Differential methylated genes (DMGs) and differential expression genes (DEGs) were identified and then searched for the hub genes.

Cox proportional hazards regression was applied to identify DNA methylated site biomarkers from the hub genes.

Kaplan–Meier survival and ROC analyses were used to validate the effective prognostic ability of the methylation gene site biomarker.

The biomarker sites were validated in the GEO cohorts.

The GO and KEGG annotation was done to explore the biological function of DNA methylated site signature.

Results.

Nine DMGs with opposite expression patterns containing 47 methylated sites were identified.

Finally, four methylated sites were identified using the hazard regression model (cg04448376, cg24387542, cg08548498, and cg14621323) located in UTY, LGALS9B, SLPI, and PFN3, respectively.

These sites classified patients into high- and low-risk groups in the training cohort.

The 5-year survival rates for patients with low-risk and high-risk scores were 97.5% and 75.9% (P<0.001).

The prognostic accuracy and signature methylation sites were validated in the test (TCGA, n=87) and GEO cohorts (n=14).

Multivariate regression analysis showed that the signature was an independent prediction prognostic factor for KIRP.

Based on this analysis, we developed methylated site signature nomogram that predicts an individual’s risk of survival.

Functional analysis suggested that these signature genes are involved in the biological processes of protein binding.

Conclusions.

Our study demonstrated that the methylated gene site signature might be a powerful prognostic tool for evaluating survival rate and guiding tailored therapy for KIRP patients.

American Psychological Association (APA)

Wang, Ying-Lei& Zhang, Ying-Ying. 2020. cg04448376, cg24387542, cg08548498, and cg14621323 as a Novel Signature to Predict Prognosis in Kidney Renal Papillary Cell Carcinoma. BioMed Research International،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1134268

Modern Language Association (MLA)

Wang, Ying-Lei& Zhang, Ying-Ying. cg04448376, cg24387542, cg08548498, and cg14621323 as a Novel Signature to Predict Prognosis in Kidney Renal Papillary Cell Carcinoma. BioMed Research International No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1134268

American Medical Association (AMA)

Wang, Ying-Lei& Zhang, Ying-Ying. cg04448376, cg24387542, cg08548498, and cg14621323 as a Novel Signature to Predict Prognosis in Kidney Renal Papillary Cell Carcinoma. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1134268

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1134268