4.6 Article

Identification and Validation of Immune-Related Gene Signature for Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma

Journal

FRONTIERS IN MOLECULAR BIOSCIENCES
Volume 8, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fmolb.2021.679031

Keywords

lung adenocarcinoma; immune-related genes; lymph node metastasis; immune cell infiltration; immune and stromal scores; immune checkpoint genes; risk score; prognosis

Funding

  1. National Natural Science Foundation of China [81772619, 82002551]
  2. Clinical Trial Project of Tianjin Medical University [2017kylc006]
  3. Bethune Charitable Foundation-Excelsior Surgical Fund [HZB-20190528-18]
  4. Science and Technology Project of Tianjin Municipal Health Commission [RC20119]

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This study identified immune-related genes associated with lymph node metastasis in lung adenocarcinoma and established a reliable risk score model for predicting lymph node metastasis in patients. The risk score was also correlated with immune cell infiltration and checkpoint gene expression, suggesting potential biomarkers for lung adenocarcinoma patients.
Lung cancer is a serious malignancy, and lung adenocarcinoma (LUAD) is the most common pathological subtype. Immune-related factors play an important role in lymph node metastasis. In this study, we obtained gene expression profile data for LUAD and normal tissues from the TCGA database and analyzed their immune-related genes (IRGs), and observed that 459 IRGs were differentially expressed. Further analysis of the correlation between differentially expressed IRGs and lymph node metastasis revealed 18 lymph node metastasis-associated IRGs. In addition, we analyzed the mutations status, function and pathway enrichment of these IRGs, and regulatory networks established through TF genes. We then identified eight IRGs (IKBKB, LTBR, MIF, PPARD, PPIA, PSME3, S100A6, SEMA4B) as the best predictors by LASSO Logistic analysis and used these IRGs to construct a model to predict lymph node metastasis in patients with LUAD (AUC 0.75; 95% CI: 0.7064-0.7978), and survival analysis showed that the risk score independently affected patient survival. We validated the predictive effect of risk scores on lymph node metastasis and survival using the GEO database as a validation cohort and the results showed good agreement. In addition, the risk score was highly correlated with infiltration of immune cells (mast cells activated, macrophages M2, macrophages M0 and B cells naive), immune and stromal scores, and immune checkpoint genes (LTBR, CD40LG, EDA2R, and TNFRSF19). We identified key IRGs associated with lymph node metastasis in LUAD and constructed a reliable risk score model, which may provide valuable biomarkers for LUAD patients and further reveal the mechanism of its occurrence.

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