Some lncRNAs and cancer hallmark-related genes were specific and co-expressed in UCEC
In order to depict the roles of cancer hallmark in UCEC, we identified UCEC-specific lncRNAs and cancer hallmark-related genes by differential expression. 1880 (12.43%) UCEC-specific lncRNAs were identified between UCEC and control samples (Figure 2A). These UCEC-specific lncRNAs included 891 and 989 up- and down-regulated lncRNAs (Figure 2B). UCEC-specific genes were also identified for each cancer hallmark (Figure 2C). In all kinds of cancer hallmarks, there were more than 50% UCEC-specific genes. Specially, there was 70.57% UCEC-specific genes in cancer hallmark genome instability and mutation. The results indicated that these cancer hallmark-related genes maybe serve as essential roles in UCEC. We assumed that lncRNAs and cancer hallmark-related genes could function by cooperating in UCEC. Thus, some co-expressed lncRNAs and cancer hallmark-related genes pairs were identified in UCEC for each kind of cancer hallmark. Most PCCs of co-expressed lncRNAs and cancer hallmark-related genes pairs were concentrated between 0.3 and 0.5 (Figure 2D). There were 8631 co-expressed lncRNAs and cancer hallmark-related genes pairs which their PCCs were higher than 0.5 (Figure 2E). In each kind of cancer hallmark, the numbers of pairs, lncRNAs and genes were diverse (Figure 2F). For example, there were 2525, 365 and 384 pairs, genes and lncRNAs in cancer hallmark self sufficiency in growth signals. However, only there were 84, 47 and 12 pairs, genes and lncRNAs in cancer hallmark reprogramming energy metabolism. The results indicated that diverse cancer hallmarks play different roles in UCEC. All above results indicated that lncRNAs and cancer hallmark-related genes cooperative pairs were important in UCEC.
Some core modules were extracted from co-expressed lncRNAs and cancer hallmark-related genes networks in each cancer hallmark
For each cancer hallmark, co-expressed lncRNAs and cancer hallmark-related genes which their PCCs were higher than 0.5 were extracted for constructing co-expressed networks. In cancer hallmark evading apoptosis, lncRNAs and cancer hallmark-related genes co-expressed network was constructed (Figure 3A). This co-expressed network contained 380 nodes (234 UCEC-specific lncRNAs and 147 cancer hallmark-related genes) and 906 edges. We found that some cancer hallmark-related genes and lncRNAs such as SLC25A27, AC005288 and GD5-AS1 played core roles in this co-expressed network. Most of cancer hallmark-related genes and lncRNAs showed positive correlations in UCEC. In eight cancer hallmarks, there were diverse numbers of core modules were identified (Figure 3B). Cancer hallmarks insensitivity to antigrowth signals, self sufficiency in growth signals and tissue invasion and metastasis had most core modules. The numbers of cancer hallmark-related genes and lncRNAs were also different (Figure 3C). For example, there were more lncRNA in core module 1 in cancer hallmark insensitivity to antigrowth signals. These core modules maybe show specific functions. For example, a core module in cancer hallmark evading apoptosis contained three lncRNAs and three genes (Figure 3D). PSMB8, PSMB10, PSME2 and PSMB8-AS1 were all proteasome-related genes or lncRNAs. The proteasome is a multicatalytic proteinase complex which is characterized by its ability to cleave peptides. Specially, cancer hallmark-related gene PSMB8 and lncRNA PSMB8-AS1 showed strong positive correlation (P< 0.001, PCC=0.79). These genes and lncRNAs in this core module showed close interactions. Another core module also showed close interactions (Figure 3E). All the results explained these core modules in co-expressed networks could function and serve as specific biomarks in UCEC.
Specific cancer hallmark-related risk were evaluated for each UCEC patient based on core modules
We inferred that each UCEC patient maybe have diverse hallmark-related risk. Thus, we calculated risk scores for each UCEC patient based on core modules in each cancer hallmark. Only eight cancer hallmarks were extracted for calculating risk scores due to core modules. The density distribution of risk scores in all core modules of each cancer hallmark were similar (Figure 4A). Only a small number of UCEC patients showed higher risk scores. The differences of average risk scores for diverse top 20 core modules were also present (Figure 4B). These 20 core modules were significantly associated with more UCEC patients (Figure 4C). For example, there were 32.03% samples were significant in core module 1 in cancer hallmark insensitivity to antigrowth signals. This core module was a key module which had most related samples and also been explained in above results. We also discovered the percent of significant risk-related samples in 0%corresponding top ranked samples. 70% UCEC samples ranked before corresponding orders in most core modules (Figure 4D). These results indicated that UCEC patients showed differences of cancer hallmark-related risk scores.
UCEC groups with diverse cancer hallmark risk showed specific features
Each UCEC patient could be associated with diverse cancer hallmark follow above pipeline. The numbers of UCEC in each cancer hallmark were different (Figure 5A). For example, there were more than 350 UCEC samples were associated with cancer hallmark tissue invasion and metastasis. The cancer hallmark reprogramming energy metabolism was related to 300 UCEC samples. Specially, some UCEC patients were associated with multiple cancer hallmarks. 13.59% UCEC patients had some relationships with any kinds of cancer hallmarks (Figure 5B). 11.55% UCEC patients were only related to one kind of cancer hallmark. Thus, we could divide all the UCEC patients to diverse groups with different numbers of cancer hallmarks (Figure 5C). The three diverse groups contained non-, media- and multi-hallmarks. 70.76% samples belonged to media-hallmarks groups. The UCEC patients with more cancer hallmarks usually had better survival days (Figure 5D). In addition, we also divided all the UCEC patients to another three cancer hallmark-related risk groups based on hierarchical clustering (Figure 5E). We also discovered that these diverse cancer hallmark-related risk groups showed different prognosis (Figure 5F, G). Group 2 significantly had better survival than group 1 and 3 (P= 0.014 and 0.023). All the results suggested that diverse hallmark-related risk groups had respective features and prognosis.
Some key lncRNAs could participate in multiple kinds of cancer hallmarks and showed specific functions
In order to further depict the roles of lncRNAs in cancer hallmarks for UCEC, we extracted some key lncRNAs which participate in multiple kinds of cancer hallmarks. There were 11 lncRNAs were associated with more than three kinds of cancer hallmarks (Figure 6A). lncRNAs AL590764.1, ANKRD10-IT1, NORD and AP000766.1 could participated in four kinds of cancer hallmarks (Figure 6B). However, the classes of these four kinds of cancer hallmarks were diverse. We inferred that these lncRNAs may serve as essential roles in UCEC. Thus, we further performed functional analysis for these lncRNAs in each kind of cancer hallmark. The lncRNAs were enrichment in some essential functions for cancer development (Figure 6C). For example, lncRNAs associated with evading apoptosis were enrichment in some hormone-related pathways such as negative regulation of intracellular estrogen receptor signaling, negative regulation of intracellular steroid hormone receptor signaling and regulation of intracellular estrogen receptor signaling. The estrogen receptor status is reported to be an important marker of UCEC [18, 19]. In addition, we found most lncRNAs were associated with gap junction assembly pathway. Nishimura M et al. reported that gap junctional intercellular communication was suppressed via 5' CpG island methylation in promoter region of E-cadherin gene in UCEC cells . These results indicated that cancer hallmark-related lncRNAs could serve as essential roles in UCEC.