Journal of Immunology Research (Jan 2023)

Development and Validation of an Immunotherapy-Related Prognostic Signature Based on Lymph Node Ratio for Gastric Cancer

  • Jianxin Li,
  • Ting Han,
  • Xin Wang,
  • Yinchun Wang,
  • Xuan Chen,
  • Wangsheng Chen,
  • Qingqiang Yang

DOI
https://doi.org/10.1155/2023/6562422
Journal volume & issue
Vol. 2023

Abstract

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Background. The long-term prognosis of gastric cancer (GC) remains poor due to postoperative recurrence and metastasis. The increasing evidence show that the lymph node ratio (LNR) serves as an independent prognostic factor in patients with GC. In this study, we aimed to develop a prognostic signature for GC based on LNR. Methods. Survival analysis was conducted by comparing low- and high-LNR groups according to the optimal cutoff value of LNR, which was identified by receiver operating characteristic (ROC) curve analysis. Then, we identified the differentially expressed genes (DEGs) related to LNR in the training cohort of GC. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression were performed to construct the risk score signature. We then evaluated the risk score signature from the viewpoints of survival, clinic-pathological characteristics, tumor microenvironment (TME), tumor mutation burden (TMB), and immunotherapeutic and chemotherapeutic efficacy. Results. High LNR was significantly correlated with poorer prognosis and was an independent predictor of recurrence in patients with GC. Then, an eleven-gene signature that could predict the prognosis of GC patients was developed based on LNR-related DEGs in the training cohort, and the results were further confirmed in external independent cohort. In addition, the high-risk group showed aggressive clinicopathological characteristics, specific TME status, low TMB, and low immunotherapeutic sensitivity. Conclusions. The present study constructed an eleven-gene prognostic signature based on LNR to predict the prognosis of patients with GC and facilitate the development of individualized treatment strategy.