Systematic profiling of invasion‐related gene signature predicts prognostic features of lung adenocarcinoma

Aim: To develop an oxidative phosphorylation (OXPHOS)-related gene signature of lung adenocarcinoma (LUAD). Materials & methods: We split The Cancer Genome Atlas LUAD cohort into a training set and a test set; we used the least absolute shrinkage and selection operator Cox method to structure the OXPHOS-related prognostic signature in the training set and verified in the test set and GSE30219 dataset. Meanwhile, the diagnostic model was constructed using the logistic Cox method. Results: The signature consisted of seven genes ( LDHA, CFTR, HSPD1, SNHG3, MAP1LC3C, COX6B2, and TWIST1). LUAD patients were divided into high- and low-risk groups, demonstrating good diagnostic and prognostic capabilities. Conclusion: We developed the first-ever OXPHOS-related signature with both prognostic predictive power and diagnostic efficacy.

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Development and validation of a hypoxia-related gene signature to predict overall survival in early-stage lung adenocarcinoma patients

Therapeutic Advances in Medical Oncology ◽

10.1177/1758835920937904 ◽

2020 ◽

Vol 12 ◽

pp. 175883592093790

Author(s):

Jing Sun ◽

Tianyu Zhao ◽

Di Zhao ◽

Xin Qi ◽

Xuanwen Bao ◽

...

Keyword(s):

Overall Survival ◽

Risk Factor ◽

Decision Tree ◽

Risk Stratification ◽

Lung Adenocarcinoma ◽

Early Stage ◽

Staging System ◽

Gene Signature ◽

Significant Heterogeneity ◽

Related Gene

Background: Patients with early-stage lung adenocarcinoma (LUAD) exhibit significant heterogeneity in overall survival. The current tumour-node-metastasis staging system is insufficient to provide precise prediction for prognosis. Methods: We quantified the levels of various hallmarks of cancer and identified hypoxia as the primary risk factor for overall survival in early-stage LUAD. Different bioinformatic and statistical methods were combined to construct a robust hypoxia-related gene signature for prognosis. Furthermore, a decision tree and a nomogram were constructed based on the gene signature and clinicopathological features to improve risk stratification and quantify risk assessment for individual patients. Results: The hypoxia-related gene signature discriminated high-risk patients at an early stage in our investigated cohorts. Survival analyses demonstrated that our gene signature served as an independent risk factor for overall survival. The decision tree identified risk subgroups powerfully, and the nomogram exhibited high accuracy. Conclusions: Our study might contribute to the optimization of risk stratification for survival and personalized management of early-stage LUAD.

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Identification of Inflammatory Response-Related Gene Signature Associated With Immune Status and Prognosis of Lung Adenocarcinoma

Frontiers in Bioengineering and Biotechnology ◽

10.3389/fbioe.2021.772206 ◽

2021 ◽

Vol 9 ◽

Author(s):

Weijie Zou ◽

Li Chen ◽

Wenwen Mao ◽

Su Hu ◽

Yuanqing Liu ◽

...

Keyword(s):

High Risk ◽

Inflammatory Response ◽

Lung Adenocarcinoma ◽

Immune Status ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Related Gene ◽

Gene Set Enrichment ◽

Cox Analysis

Background: Lung adenocarcinoma (LUAD) is an exceedingly diverse disease, making prognostication difficult. Inflammatory responses in the tumor or the tumor microenvironment can alter prognosis in the process of the ongoing cross-talk between the host and the tumor. Nonetheless, Inflammatory response-related genes’ prognostic significance in LUAD, on the other hand, has yet to be determined.Materials and Methods: The clinical data as well as the mRNA expression patterns of LUAD patients were obtained from a public dataset for this investigation. In the TCGA group, a multigene prognostic signature was built utilizing LASSO Cox analysis. Validation was executed on LUAD patients from the GEO cohort. The overall survival (OS) of low- and high-risk cohorts was compared utilizing the Kaplan-Meier analysis. The assessment of independent predictors of OS was carried out utilizing multivariate and univariate Cox analyses. The immune-associated pathway activity and immune cell infiltration score were computed utilizing single-sample gene set enrichment analysis. GO keywords and KEGG pathways were explored utilizing gene set enrichment analysis.Results: LASSO Cox regression analysis was employed to create an inflammatory response-related gene signature model. The high-risk cohort patients exhibited a considerably shorter OS as opposed to those in the low-risk cohort. The prognostic gene signature’s predictive ability was demonstrated using receiver operating characteristic curve analysis. The risk score was found to be an independent predictor of OS using multivariate Cox analysis. The functional analysis illustrated that the immune status and cancer-related pathways for the two-risk cohorts were clearly different. The tumor stage and kind of immune infiltrate were found to be substantially linked with the risk score. Furthermore, the cancer cells’ susceptibility to anti-tumor medication was substantially associated with the prognostic genes expression levels.Conclusion: In LUAD, a new signature made up of 8 inflammatory response-related genes may be utilized to forecast prognosis and influence immunological state. Inhibition of these genes could also be used as a treatment option.

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