A Novel Prognostic Model Based on Seven Necroptosis-Related miRNAs for Predicting the Overall Survival of Patients with Lung Adenocarcinoma

Author:

Hong Xiaohua1ORCID,Wang Guangyao2,Pei Kai1,Mo Chunmei3,Rong Zhen3ORCID,Xu Guanglan2ORCID

Affiliation:

1. Graduate School, Guangxi University of Chinese Medicine, Nanning 530000, China

2. Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530000, China

3. Department of Oncology, Bao’an Authentic TCM Therapy Hospital, Shenzhen 518038, China

Abstract

Lung adenocarcinoma (LUAD) remains one of the leading causes of cancer-related deaths worldwide. This study is aimed at constructing a risk scoring model based on necroptosis-related miRNAs to predict prognosis of LUAD. Expression profile of miRNA in LUAD was downloaded from The Cancer Genome Atlas (TCGA) database. We screened the differentially expressed necroptosis-related miRNAs between LUAD patients and normal samples, thus constructed a seven miRNA-based risk stratification on the basis of the TGCA cohort. This risk stratification was prove to be effective in predicting the overall survival (OS) of patients with LUAD. Furthermore, we constructed a nomogram model based on the combination of risk characteristics and clinicopathological features, which was also prove to be accurate and efficient in predicting OS of LUAD patients. Functional enrichment analyses on the targeted genes of these miRNAs with prognostic value were carried out. Results indicated that these targeted genes were closely related to the development and metastasis of tumors. In summary, our research has developed a prognostic model based on the expression of miRNAs related to necroptosis. This model might be used to predict the prognosis of LUAD accurately, which might be helpful in improving treatment efficacy of LUAD.

Funder

Innovation Project of Guangxi Graduate Education

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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