Abstract
BackgroundLung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of various biomarkers to predict survival for LUAD patients. In our study, we attempted to identify a new prognostic model by developing a new algorithm to calculate the allele frequency deviation (AFD), which in turn may assist in the early diagnosis and prediction of clinical outcomes in LUAD.MethodFirst, a new algorithm was developed to calculate AFD using the whole-exome sequencing (WES) dataset. Then, AFD was measured for 102 patients, and the predictive power of AFD was assessed using Kaplan–Meier analysis, receiver operating characteristic (ROC) curves, and area under the curve (AUC). Finally, multivariable cox regression analyses were conducted to evaluate the independence of AFD as an independent prognostic tool.ResultThe Kaplan–Meier analysis showed that AFD effectively segregated patients with LUAD into high-AFD-value and low-AFD-value risk groups (hazard ratio HR = 1.125, 95% confidence interval CI 1.001–1.26, p = 0.04) in the training group. Moreover, the overall survival (OS) of patients who belong to the high-AFD-value group was significantly shorter than that of patients who belong to the low-AFD-value group with 42.8% higher risk and 10% lower risk of death for both groups respectively (HR for death = 1.10; 95% CI 1.01–1.2, p = 0.03) in the training group. Similar results were obtained in the validation group (HR = 4.62, 95% CI 1.22–17.4, p = 0.02) with 41.6%, and 5.5% risk of death for patients who belong to the high and low-AFD-value groups respectively. Univariate and multivariable cox regression analyses demonstrated that AFD is an independent prognostic model for patients with LUAD. The AUC for 5-year survival were 0.712 and 0.86 in the training and validation groups, respectively.ConclusionAFD was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions.
Highlights
Lung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate
allele frequency deviation (AFD) was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions
The result showed no correlation between AFD and tumor mutation burden (TMB), with a p-value of 0.6 and correlation coefficient = −0.077 (Fig. 3B)
Summary
Lung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Al‐Dherasi et al Cancer Cell Int (2021) 21:451 histopathologically classified into two main subtypes: lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) [3], where the latter is the most common type, with a survival rate of approximately 15% within 5 years [4, 5]. Patients with NSCLC receive different treatments, whether early-stage surgical treatment or other potential curative treatments for different stages, the prognosis of patients with NSCLC in the early stages remains poor, with a relapse rate of approximately 40% in patients within 5 years [6] and a survival rate of 50–60% [7, 8] These information indicate the existence of some individual cases of high-risk among patients who are in the early stages of the disease. Patients need to be diagnosed in the early stages, and a reliable prognostic biomarker or prognostic factors to identify high-risk individuals are urgent and considerably important for NSCLC
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