The transcriptional and post-transcriptional levels of ORCs in LUAD
The flow diagram of this systemic analysis is shown in Fig. 1.
At first, we confirmed these ORC complex transcriptional level in 20 cancer types compared to according normal tissue samples based on oncomine database (Fig. 2). Total unique analysis among ORC1, ORC2, ORC3, ORC4, ORC5 and ORC6 were 432, 437, 430, 400, 401 and 369, respectively. These ORCs were both increased in most cancer types, especially in bladder cancer, cervical cancer, colorectal cancer, lung cancer, sarcoma. Moreover, ORC1 mRNA level was enhanced in 17 datasets and reduced in 2 datasets. The transcriptional level of ORC2 was markedly increased in 5 datasets and decreased in 2 datasets. For ORC3, 11 datasets showed upregulated, but 5 datasets showed downregulated. High levels of ORC4 was observed in 2 datasets, and low levels of ORC4 was also observed in 2 datasets. The ORC5 mRNA level was increased in 11 datasets but decreased in 4 datasets. At last but not least, ORC6 was significantly increased in 36 datasets, but decreased in 3 datasets.
Subsequently, we confirmed the transcriptional level of ORC complex in LUAD patients based on UALCAN database. The results indicated that both ORC mRNA levels were significantly enhanced in LUAD patients compared to normal lung tissue samples (Fig. 3A). The survival analysis data among these ORC complexes was also showed that the mRNA levels of ORC1 and ORC6 was significantly and negatively correlated with prognosis in LUAD patients. However, the mRNA levels of other ORCs were not correlated the LUAD patient’s prognosis (Fig. 3B).
Then, we extracted the post-transcriptional level among ORCs in LUAD patients based on HPA database. The results showed that the IHC staining intensity of ORCs were obviously and significantly increased in LUAD tissue samples compared to normal lung tissue samples (Fig. 4A). The survival analysis data based on ORCs protein expression showed that ORC1, ORC5 and ORC6 were negatively and significantly correlated with prognosis in LUAD patients. But the ORC2, ORC3 and ORC4 was not significantly correlated with LUAD patient’s prognosis (Fig. 4B).
Prognostic Values Of Orc Complex In Luad Patients
From the above analysis, we found that the prognostic values of these ORCs were obviously different in each other based on the transcriptional and post-transcriptional levels. To further validate the prognostic value of these ORCs, we conducted survival analyses of the ORCs used by KM-plot database and GEO database. The meta-survival analyses showed that ORC1, ORC2, ORC5 and ORC6 had a prognostic value (Fig. 5A). KM-plot database analysis showing overall survival probability of ORC1, ORC3 and ORC6 were significant (Fig. 5B). Taken together, the prognostic values of ORC1 and ORC6 is more significant compared to other ORCs in LUAD patients.
The underlying mechanism of the ORC complex regulation based on bioinformatic analysis
In DNA level, we explored the alteration level in ORC complex based on cBioProtal database. The lung cancer dataset was showed that the DNA alteration percentages of ORC complex were 1.9% (ORC1), 1.7% (ORC2), 1.5% (ORC3), 1.2% (ORC4), 2.2% (ORC5), and 1.4% (ORC6), respectively (Fig. 6A-B). Then, we further confirmed the survival rate between ORC complex alteration group and no alteration group (Fig. 6C), which indicated that the DNA alteration was not correlated with the prognosis outcome in LUAD patients. Moreover, we also investigated the DNA methylation level of ORCs in LUAD based on TCGA database. The result indicated that the methylated level was significantly decreased in the CpG promoter of ORC1 and ORC2, but significantly increased in the CpG promoter of ORC4 for LUAD tissue samples compared to normal lung tissue samples (Table 1 & Fig. 7A). However, the Heat map with hierarchical clustering of CpG methylation among ORCs has no significance (Fig. 7B), which indicated that methylation profiles cannot be used to distinguish normal samples from cancers. These results indicated that these ORCs were regulated by DNA methylation rather than DNA alteration in DNA level.
In mRNA level, we extracted the profiles of miRNA interacted ORC complex based on GSCALite database. The results showed that ORC1 and ORC2 could be regulated by multiple miRNAs, including hsa-miR-3132, hsa-miR-125b-5p, hsa-miR-7-5p, hsa-miR-200a-3p, hsa-miR-375, hsa-miR-330-5p, hsa-miR-539-5p, hsa-miR-125a-5p, hsa-miR-141-3p, hsa-miR-143-3p, hsa-miR-183-5p, hsa-miR-636, hsa-miR-24-3p, hsa-miR-1224-3p, hsa-miR-149-5p, hsa-miR-2110, hsa-miR-4254, hsa-miR-1254, hsa-miR-124-3p, hsa-miR-671-5p, hsa-miR-150-5p for ORC1 ,and hsa-miR-122-5p, hsa-miR-3154, hsa-miR-15b-5p, hsa-miR-491-3p, hsa-miR-486-5p for ORC2 (Fig. 7C). There results indicated that ORC1 and ORC2 might be regulated by many miRNAs in mRNA level, resulting in dysregulation of ORC complex.
In protein level, we investigated the protein secondary structure data in ORCs based on PDB database (Fig. 8). ORC1 has three classic domains, such as BAH, AAA, and Cdc6_C. ORC1 also had several chemical modification types (phosphirylation, acetylation, ubiquitination and methylation). ORC2 has ORC2 domain, and two chemical modification types (phosphirylation and acetylation). ORC3 has AAA_16 domain and four chemical modification types (phosphirylation, acetylation, ubiquitination and glutathionylation). ORC4 has two domains, such as AAA_16 and ORC4_C domain, and may regulated by phosphirylation, acetylation, ubiquitination and methylation. ORC5, modified by phosphirylation, acetylation and ubiquitination, has AAA_16 and ORC5_C domain. ORC6 has a ORC6 domain, and can be regulated by phosphirylation, acetylation, ubiquitination, methylation and sumoylation. Taken together, these results indicated that the activity of these ORCs could be mediated by multiple chemical modification types.
Functional enrichment and pathway analyses for ORC complex in LUAD
Subsequently, the structural models of six ORC subunits were also constructed by PDB database (Fig. 9A), which indicated that these ORCs were able to bind each other. We also excavated the expression data of ORCs in LUAD patients to analysis the correlations among these ORC complex (Fig. 9B). This result indicated a positively and significantly correlation between these ORC1/2/3/4/5/6 and other ORCs, especially in ORC1-ORC6 (R = 0.66) and ORC2-ORC4 (R = 0.54). Next, the protein-protein interaction networks of ORC complex were constructed by GeneMANIA, including ORC1, ORC2, ORC3, ORC4, ORC5, ORC6, LRWD1, DBF4, HMGA1, HIST1H3I, CDC6, MCM5, MCM4, CDC45, MCM7, CDC7, MCM2, MCM3, MCM6, MCM10, TERF2, HIST4H4, MCM8, CBX5, CDT1 and CCNE2 (Fig. 9C). Then, we used these genes generated by GeneMANIA tools to further analyze the GO functional enrichment and KEGG pathway analyses by Metascape database. Pathway and process enrichment analysis indicated that these genes had an important effect on activation of the pre-replicative complex, regulation of nuclear cell cycle DNA replication, regulation of chromosome organization, PID E2F pathway, cellular senescence, PID ATR pathway, and 22q11.2 copy number variation syndrome (Fig. 9D). The top-level Gene Ontology biological processes showed that these genes were enriched in multiple biological progression, such as metabolic process, cellular process, response to stimulus, cell component organization or biogenesis, regulation of biological process, positive regulation of biological process, negative regulation of biological process, localization, and biological regulation (Fig. 9E). Then, we also constructed networks for pathway and process enrichment analysis (Fig. 9F) and protein-protein interaction enrichment analysis (Fig. 9G), which showed the interaction among these GO enrichments and KEGG pathway analysis.
The Correlation Between Orc Complex Expression And Immune Infiltration
Owing to the significant role of tumor-infiltrating immune in carcinogenesis and its impact on prognosis, we also confirmed the immune infiltration of ORC complex in LUAD based on the GEPIA database. Our result indicated that the expression of ORC1, ORC2, ORC3, ORC4, ORC5 and ORC6 had a different level in the seven-common tumor-infiltrating immune cells, such as B cells, CD4 T cells, CD8 T cells, NK cells, macrophages, endothelials, and cancer associated fibroblasts (Fig. 10A). Furthermore, we found ORC1 had a correlation with purity (p = 2.16e-03, cor = 0.138), B cell (p = 1.31e-06, cor=-0.218), CD8+ T cell (p = 7.87e-01, cor=-0.218), CD4+ T cell (p = 2.99e-04, cor=-0.164), Macrophage (p = 1.69e-01, cor=-0.063), Neutrophil (p = 3.16e-03, cor=-0.134), and Dendritic cell (p = 3.72e-08, cor=-0.246). ORC2 expression was associated with purity (p = 7.43e-02, cor = 0.08), B cell (p = 1.07e-01, cor=-0.073), CD8+ T cell (p = 4.45e-07, cor = 0.226), CD4+ T cell (p = 5.77e-01, cor = 0.025), Macrophage (p = 2.24e-01, cor = 0.055), Neutrophil (p = 9.39e-05, cor = 0.177), and Dendritic cell (p = 7.30e-01, cor = 0.016). The expression of ORC3 was correlated with purity (p = 4.96e-01, cor=-0.031), B cell (p = 1.15e-01, cor = 0.072), CD8+ T cell (p = 5.29e-03, cor = 0.126), CD4+ T cell (p = 2.83e-02, cor=-0.1), Macrophage (p = 2.51e-02, cor = 0.102), Neutrophil (p = 2.19e-02, cor = 0.104), and Dendritic cell (p = 8.06e-05, cor = 0.178). The ORC4 mRNA level was correlated with purity (p = 7.4e-03, cor = 0.12), B cell (p = 8.24e-02, cor=-0.079), CD8+ T cell (p = 1.86e-04, cor = 0.169), CD4+ T cell (p = 7.59e-03, cor=-0.121), Macrophage (p = 4.54e-02, cor = 0.091), Neutrophil (p = 8.74e-04, cor = 0.151), and Dendritic cell (p = 6.15e-01, cor = 0.023). ORC5 was correlated with purity (p = 7.4e-01, cor = 0.015), B cell (p = 2e-04, cor=-0.168), CD8+ T cell (p = 4.48e-03, cor = 0.129), CD4+ T cell (p = 1.70e-04, cor=-0.17), Macrophage (p = 7.48e-01, cor=-0.015), Neutrophil (p = 2.84e-03, cor = 0.136), and Dendritic cell (p = 6.33e-01, cor = 0.022). ORC6 was also correlated with purity (p = 7.08e-01, cor = 0.017), B cell (p = 3.41e-04, cor=-0.162), CD8+ T cell (p = 6.35e-01, cor=-0.022), CD4+ T cell (p = 6.80e-03, cor=-0.123), Macrophage (p = 3.25e-03, cor=-0.133), Neutrophil (p = 4.01e-01, cor = 0.038), and Dendritic cell (p = 2.60e-02, cor=-0.101) (Fig. 10B). Therefore, these ORCs were closely associated with immune infiltration.
Verification Of The Drug Sensitivity Of Hub Orc Proteins
Finally, we analyzed the drug sensitivity of hub ORC proteins. Our results indicated that ORC1 (SLC25A15) and ORC2 (SLC25A2) was closely associated with chemotherapy resistance based on the GSCALite database (Supplementary Figures S1 and S2). Hence, these results indicated that ORC1 and ORC2 could be potential therapeutic target for LUAD patients.