Available online 29 October 2023

This study investigates the link between SARS-CoV-2-associated long non-coding RNAs (lncRNAs) and lung adenocarcinoma (LUAD). LUAD is a prevalent and aggressive lung cancer type. The study aims to identify prognostic lncRNAs and construct a predictive model while shedding light on potential therapeutic targets during the COVID-19 era.

Eight SARS-CoV-2-associated lncRNAs with significant prognostic value in LUAD were identified, forming a robust prognostic risk model. The model exhibited strong predictive performance, with high area under the ROC curve (AUC) values at one, three, and five years. Furthermore, the risk score was an independent prognostic factor, correlating with cancer stage. Notably, differences in immune function, drug sensitivity, and immune checkpoint expression were observed between high- and low-risk groups.

This study unveils eight SARS-CoV-2-associated lncRNAs as valuable prognostic markers in LUAD, yielding a reliable prognostic risk model. Additionally, the model's ability to predict patient outcomes and its correlation with cancer stage underscores its clinical utility. The observed variances in immune function, drug sensitivity, and immune checkpoint expression suggest potential avenues for personalized LUAD treatment strategies. Clinicians can utilize the prognostic risk model to predict LUAD patient outcomes, informing treatment decisions. The insights into immune function, drug sensitivity, and immune checkpoints offer opportunities for tailored therapies, potentially enhancing patient outcomes. This study underscores the importance of considering the interplay between SARS-CoV-2-associated factors and cancer biology, especially in the context of the COVID-19 pandemic.

Clinical prognosis

COVID-19

Drug sensitivity

Immune function

lncRNA

Lung adenocarcinoma

Lung cancer

Molecular biomarkers

Prognostic risk model

SARS-CoV-2

Therapeutic targets

The datasets generated and/or analyzed during the current study are available in the [https://portal.gdc.cancer.gov/].

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