2480 lncRNAs were up-regulated and 707 were down-regulated in GC
A total of 50455 genes were detected to be expressed in GC tissues from the downloaded TCGA database, in which 14,464 were lncRNAs (fold change of cut-off value ≥2 and p <0.05). Particularly, 2480 up-regulated lncRNAs and 707 lncRNAs were obtained (Fig 1A).
48 prognostic lncRNAs in GC
Survival R package was utilized for screening prognostic lncRNAs of DFS and OS of GC. Firstly, GC patients were divided to two groups based on the median expression of alternative lncRNAs. Prognosis curve was drawn using the K-M method. LncRNAs with log-rank p value <0.05 were output. Finally, there were 234 lncRNAs screened out to be the prognostic factors for OS, of which 48 lncRNAs were prognostic factors for DFS (data were not all showed, Fig 1B, 1C, 1D and 1E).
ENSG00000224363 was an independent unfavorable prognostic factor for DFS and OS of GC
The univariate Cox analyses of DFS and OS were conducted in the 48 screened lncRNAs, respectively. Eleven lncRNAs were associated with OS and 16 were associated with DFS (Table 1). Only 4 lncRNAs were both associated with DFS and OS of GC, which were subjected to the multivariate Cox analyses of DFS, in which 2 were associated with DFS of GC (Table 2-5). At last, these 2 lncRNAs were enrolled in multivariate Cox analyses of OS and only lncRNA ENSG00000224363 was obtained, which was an independent prognostic risk factor for DFS and OS of GC (Table 6- 7). Chi-square test showed that ENSG00000224363 was associated with lymph node metastasis of GC (Table 8). However, ENSG00000224363 was not correlated to age, tumor grade, TNM staging and other indicators of GC patients.
ENSG00000224363 could predict DFS and OS of GC
To analyze the prognostic potential of ENSG00000224363 in GC, we divided GC patients in the TCGA database into 14 groups according to tumor stage, grade, tumor remnant, depth of tumor local infiltration, lymph node metastasis, gender and age. Correlation between ENSG00000224363 expression with DFS and OS in each group was calculated, respectively. Among them, ENSG00000224363 was a risk factor for DFS in the female group (Fig 2A), male group (Fig 2B), low-grade group (Fig 2C), high-grade group (Fig 2D), early-stage group (Fig 2E), advanced-stage group (Fig 2F), no distant metastasis group (Fig 2G), no lymph node metastasis group (Fig 2H), lymph node metastasis group (Fig 2I), no tumor residual group (Fig 2J), local tumor deep infiltration group (Fig 2K) and older group (Fig 2L). In addition, ENSG00000224363 expression was a risk factor for OS in the female group (Fig 3A), male group (Fig 3B), older group (Fig 3C), no distant metastasis group (Fig 3D), high-grade group (Fig 3E), lymph node metastasis group (Fig 3F), no tumor residual group (Fig 3G), local tumor deep infiltration group (Fig 3H) and advanced-stage group (Fig 3I).
ENSG00000224363 mainly regulated cell cycle, apoptosis and autophagy of GC
Subsequently, potential biological signaling that ENSG00000224363 enriched in was analyzed by KEGG and GO analyses using GSEA software. KEGG results showed that ENSG00000224363 mainly regulated cell apoptosis (Fig 4A), cell cycle (Fig 4B), DNA replication (Fig 4C), and Wnt (Fig 4G), P53 (Fig 4F), mTOR (Fig 4E) and ErbB pathways (Fig 4D). GO analysis results showed that ENSG00000224363 mainly regulated cell apoptosis pathway (Fig 4H-J), cell cycle (Fig 4K) and autophagy (Fig 4L) in GC.
Correlation between ENSG00000224363 and genes involved in GC progression
Correlation between the whole genome and ENSG00000224363 was analyzed using Cor R package. It is found that cyclin dependent kinase 3 (CDK3) (Fig 5A), CDK15 (Fig 5B), cyclin dependent kinase-like 3 (CDKL3) (Fig 5C) and CDKL4 (Fig 5D) were positively correlated with ENSG00000224363 expression. However, cyclin dependent kinase inhibitor 1A (CDKN1A) (Fig 5E) and CDKN3 (Fig 5F) were negatively correlated with ENSG00000224363 expression. In addition, ENSG00000224363 was positively correlated with cell apoptosis inhibitor molecules [Caspase12 (Fig 5G) and Caspase14 (Fig 5H)], invasiveness and metastasis molecules [matrix metalloproteinase-21 (MMP-21) (Fig 5L) and MMP26 (Fig 5M)], and key factors of ErbB (Fig 5I), mitogen-activated protein kinase (MAPK) (Fig 5J and 5K) and Wnt (Fig 5N-P). pathways.