ArticleCancer control : journal of the Moffitt Cancer Center
Construction and Validation of a Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer.
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11 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Machine learning for lymph node metastasis prediction of in patients with gastric cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Article
- Combining biomarkers to construct a novel predictive model for predicting preoperative lymph node metastasis in early gastric cancer.Frontiers in oncology · 2025Article
- Analysis of lymph node metastasis and survival prognosis in early gastric cancer patients: A retrospective study.World journal of gastrointestinal surgery · 2024Article
- MS4A superfamily molecules in tumors, Alzheimer's and autoimmune diseases.Frontiers in immunology · 2024Review
- Mortality prediction and influencing factors for intensive care unit patients with acute tubular necrosis: random survival forest and cox regression analysis.Frontiers in pharmacology · 2024Article
- Risk factors of positive lymph node metastasis after radical gastrectomy for gastric cancer and construction of prediction models.American journal of cancer research · 2024Article
- A thirty-three gene-based signature predicts lymph node metastasis and prognosis in patients with gastric cancer.Heliyon · 2023Article
- Identification of critical prognosis signature associated with lymph node metastasis of stomach adenocarcinomas.World journal of surgical oncology · 2023Article
- Prognostic prediction by a novel integrative inflammatory and nutritional score based on least absolute shrinkage and selection operator in esophageal squamous cell carcinoma.Frontiers in nutrition · 2022Article
- Model based on preoperative clinical characteristics to predict lymph node metastasis in patients with gastric cancer.Frontiers in surgery · 2022Article
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8 authors at 1 institution in 1 country.
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Abstract
backgroundIncreasing evidence indicated that the tumor microenvironment (TME) plays a critical role in tumor progression. This study aimed to identify and evaluate mRNA signature involved in lymph node metastasis (LNM) in TME for gastric cancer (GC).
methodsGene expression and clinical data were downloaded from The Cancer Genome Atlas (TCGA). The ESTIMATE algorithm was used to evaluate the TME of GC. The heatmap and Venn plots were applied for visualizing and screening out intersect differentially expressed genes (DEGs) involved in LNM in TME. Functional enrichment analysis, gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network were also conducted. Furthermore, binary logistic regression analysis were employed to develop a 4-mRNAs signature for the LNM prediction. ROC curves were applied to validate the LNM predictive ability of the riskscore. Nomogram was constructed and calibration curve was plotted to verify the predictive power of nomogram.
resultsA total of 88 LNM related DEGs were identified. Functional enrichment analysis and GSEA implied that those genes were associated with some biological processes, such as ion transportation, lipid metabolism and thiolester hydrolase activity. After univariate and multivariate logistic regression analysis, 4 mRNAs (RASSF2, MS4A2, ANKRD33B and ADH1B) were eventually screened out to develop a predictive model. ROC curves manifested the good performance of the 4-mRNAs signature. The proportion of patients with LNM in high-risk group was significantly higher than that in low-risk group. The C-index of nomogram from training and test cohorts were 0.865 and 0.765, and the nomogram was well calibrated.
conclusionsIn general, we identified a 4-mRNAs signature that effectively predicted LNM in GC patients. Moreover, the 4-mRNAs signature and nomogram provide a guidance for the preoperative evaluation and postoperative treatment of GC patients.
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