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| Content Provider | frontiers |
|---|---|
| Author | Yang, Yuan Shi, Li Zhang, Jun Zheng, Ya Wu, Guozhi Sun, Jie Liu, Min Chen, Zhaofeng Wang, Yuping Ji, Rui Guo, Qinghong Zhou, Yongning |
| Abstract | Background: The different matrisomal pattern is shared across carcinomas. However, little is known about whether there exists unique tumor matrisome that modulates GC progression and immune regulation. Methods: We conducted a genome-wide analysis based on matrisomal-related lncRNAs (MRLs) in 375 patients with GC from the Cancer Genome Atlas (TCGA) database. Patients were split into the training set and validation set at the radio of 1:1 using R package cart. Pearson correlation analysis (PCA) was performed to identify lncRNAs corelated with matrisome based on differential expression genes. Subsequently, we performed univariate Cox regression analyses and lasso Cox analysis on these lncRNAs to construct risk model. Considering the primary effect of GRASLND on the GC prognosis, we chose it for further validated it in the experimental setting. Results: We identified a 15-MRLs signature to predict overall survival and immune cell infiltration of patients with GC. The AUC values to predict 5-year outcome in three sets were 0.89, 0.65, and 0.78, respectively. Further analyses suggested that the high-risk group showed more obvious immune cell infiltration, and demonstrated an immunologically “cold” profile. In vitro, knockdown of GRASLND could inhibit the invasion capability of GC cells, and downregulate the protein expression of crucial matrisomal-related gene MMP9. Conclusions: The 15-MRLs gene signature might serve as a relatively good predictive tool to manage patients with GC. |
| ISSN | 2234943X |
| DOI | 10.3389/fonc.2022.926404 |
| Volume Number | 12 |
| Journal | Frontiers in Oncology |
| Language | English |
| Publisher Date | 2022-06-24 |
| Access Restriction | Open |
| Subject Keyword | Matrisomal pattern1 Immune regulation4 Overall survival (OS)3 Gastric cancer2 Risk model5 |
| Content Type | Text |
| Resource Type | Article |
| Subject | Cancer Research Oncology |
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