4.8 Article

The Clinical Prediction Value of the Ubiquitination Model Reflecting the Immune Traits in LUAD

Journal

FRONTIERS IN IMMUNOLOGY
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2022.846402

Keywords

ubiquitination; prognostic model; immune infiltration; genome mutation; drug response

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This study revealed the important impact of the ubiquitin-proteasome system on lung adenocarcinoma. Through bioinformatics and statistical analysis, a reliable prognostic risk model based on ubiquitination was constructed. The model stratification reflected the immune and mutation characteristics of patients with lung adenocarcinoma. Furthermore, targeting ubiquitin and proteasome could be a beneficial prospective treatment for this type of cancer.
BackgroundIncreasing evidence shows that the ubiquitin-proteasome system has a crucial impact on lung adenocarcinoma. However, reliable prognostic signatures based on ubiquitination and immune traits have not yet been established. MethodsBioinformatics was performed to analyze the characteristic of ubiquitination in lung adenocarcinoma. Principal component analysis was employed to identify the difference between lung adenocarcinoma and adjacent tissue. The ubiquitin prognostic risk model was constructed by multivariate Cox regression and least absolute shrinkage and selection operator regression based on the public database The Cancer Genome Atlas, with evaluation of the time-dependent receiver operating characteristic curve. A variety of algorithms was used to analyze the immune traits of model stratification. Meanwhile, the drug response sensitivity for subgroups was predicted by the pRRophetic package based on the database of the Cancer Genome Project. ResultsThe expression of ubiquitin genes was different in the tumor and in the adjacent tissue. The ubiquitin model was superior to the clinical indexes, and four validation datasets verified the prognostic effect. Additionally, the stratification of the model reflected distinct immune landscapes and mutation traits. The low-risk group was infiltrating plenty of immune cells and highly expressed major histocompatibility complex and immune genes, which illustrated that these patients could benefit from immune treatment. The high-risk group showed higher mutation and tumor mutation burden. Integrating the tumor mutation burden and the immune score revealed the patient's discrepancy between survival and drug response. Finally, we discovered that the drug targeting ubiquitin and proteasome would be a beneficial prospective treatment for lung adenocarcinoma. ConclusionThe ubiquitin trait could reflect the prognosis of lung adenocarcinoma, and it might shed light on the development of novel ubiquitin biomarkers and targeted therapy for lung adenocarcinoma.

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