Improved Prediction of Prognosis and Therapy Response for Lung Adenocarcinoma After Identification of DNA-directed RNA Polymerase-associated LncRNAs

Overview

Journal J Cancer Res Clin Oncol

Specialty Oncology

Date 2023 Jul 15

PMID 37453971

Authors

Jiaao Yu

Liqiang Lan

Caixin Liu

Xiao Zhu

Affiliations

Soon will be listed here.

Abstract

Background: DNA-directed RNA polymerase (DDRP) related genes and long non-coding RNAs (lncRNAs) play an important role in the development of lung adenocarcinoma (LUAD), the leading cause of cancer-related death worldwide. Therefore, we aimed to construct a DDRP-associated lncRNA model to predict the prognosis of LUAD and to evaluate its sensitivity to immunotherapy and chemotherapy.

Methods: To construct a predictive signature, we used univariate and multivariate Cox regression analyses, as well as the least absolute shrinkage and selection operator regression analysis. The prognostic model was verified by applying the ROC curve analysis, Kaplan-Meier analysis, GO/KEGG analysis, and a predictive nomogram. Eventually, immunotherapy and drug susceptibility were examined and stemness indices were analyzed.

Results: 24 DDRP-associated lncRNAs were found as independent prognosis factors, which may be further developed as potential therapeutic vaccines for LUAD. The area under the ROC curve and the conformance index showed that the constructed model can predict the prognosis of LUAD patients. The predicted incidences of overall survival showed perfect conformance. And there were significant changes in immunological markers between the two risk subgroups in the model. Finally, an analysis of 50% maximum inhibitory concentration between the two risk subgroups showed that the high-risk subgroup was more sensitive to certain chemotherapy drugs.

Conclusion: We constructed a model that accurately predicts the outcomes of LUAD based on 24 DDRP-related lncRNAs and provided promising treatment options for the future.

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