A Nomogram Combining Two Novel Biomarkers for Predicting Lung Adenocarcinoma in Ground-Glass Nodule Patients

Objective: Combination of CT imaging and RNA sequencing techniques was used to explore the potential biomarkers specific to lung adenocarcinoma within pulmonary ground-glass nodules. Method: The imaging and pathological data of patients with pulmonary ground-glass nodules who underwent chest CT scanning were confirmed through surgical procedures. Based on the pathological results, the patients were categorized into a benign nodule group and a malignant nodule group. Subsequently, RNA sequencing was conducted to analyze gene expression information in the pulmonary ground-glass nodules of these 16 patients. Results: CT signs demonstrated statistical significance in both benign and malignant nodules. A total of 2080 upregulated genes and 1240 downregulated genes were identified through RNA sequencing in malignant nodules compared to benign nodules. CST1 exhibited increased expression among the upregulated genes in lung adenocarcinoma tissues compared to lung tissues. Among the downregulated genes, only GIMAP1-GIMAP5 showed decreased expression in lung adenocarcinoma tissues. Finally, we validated the clinical significance of CST1 and GIMAP1-GIMAP5 in patients with lung adenocarcinoma, particularly highlighting a strong correlation between GIMAP1-GIMAP5 expression levels and prognosis for patients. A visual nomogram predictive model for pulmonary ground-glass nodules was constructed (area under the receiver operating characteristic curve (AUC) > 0.8). Conclusion: We constructed a nomogram combining CST1 and GIMAP1-GIMAP5 expression for predicting lung adenocarcinoma in ground-glass nodules in the context of COVID-19. This nomogram addresses the unique diagnostic challenges posed by COVID-19, where overlapping pulmonary imaging findings between viral pneumonia and early lung cancer necessitate robust molecular-aided discrimination.