Immunoscore Classifier:A Gene Based Prognostic Tool In Early Non-Small Cell Lung Cancer.

e21030 Background: The clinical benefits of immunotherapy in patients with stage I non-small cell lung cancer (NSCLC) is still controversial. Immune status plays critical role in the development and progression of NSCLC, and is associated with the patient survival outcomes. The analysis of immune features is thus valuable for the determination of immunotherapy. However, one single immune feature cannot reflect the complex immune status, and its prognostic value is extremely limited. In this study, we aimed to construct an immunoscore classifier based on multiple immuno-genes to predict the prognosis of patients with early NSCLC. Methods: A total of 522 patients with stage I NSCLC were included in this study. All patients' follow-up records and gene expression data were completely preserved. A least absolute shrinkage and selection operator (LASSO) algorithm was used to screen immune-related genes, and a COX proportional hazard regression model was used to construct the immunoscore classifier based on multiple immune-genes. Besides, the net reclassification improvement (NRI) calculation and concordance index (C-index) were applied to quantify the improvement of usefulness added by the immunoscore classifier compared to TNM staging system. Results: The immunoscore classifier including CCL5, CD8A, CXCL9, HLA-DQA1, LAG3, STAT1, and CD276 was significantly correlated with OS (HR: 2.785 CI: 1.809-4.289 P < 0.001) in patients with stage I NSCLC. With the optimal cut-off value of 4.32, all patients can be divided into a low-risk immune group and a high-risk immune group. The 10-year survival rates of the two groups were 36.8% and 12.3%, respectively. Besides, the immunoscore classifier was superior to the traditional TNM staging system in terms of distinguishing ability (C-index improvement by 0.075) and net reclassification ability (NRI improvement by 11.29%), indicating that the immunoscore classifier plays an important role in improving prognostic value. Conclusions: Multiple immune-genes based immunoscore classifiers can effectively predict the prognosis of patients with stage I NSCLC, and is significantly superior to the traditional TNM staging system in terms of prediction effectiveness and accuracy. As a new assessment tool, the immunoscore classifier may be helpful for determining the immune status of patients with stage I NSCLC and screening patients suitable for subsequent immunotherapy.