Expression profile and GSEA analysis of UBR1 in human cancer
Pan-cancer analysis was conducted using TCGA in conjunction with the GTEx database to determine UBR1 expression levels in normal and tumor tissues owing to the limited number of normal tissue samples in TCGA. In the pan-cancer analysis, UBR1 was found to be expressed in various categories of cancer, including breast invasive carcinoma (BRCA), cervical ductal adenocarcinoma (CESC), cholangiocarcinoma (CHOL), colonic adenocarcinoma (COAD), lymphoma-like tumors diffuse large B-cell lymphoma (DLBC), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), renal clear cell carcinoma (KIRC), renal-like cell carcinoma (KIRP), acute myeloid leukemia (LAML), low-grade glioma (LGG), hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), ovarian plasmacytoid cystic adenocarcinoma (OV), pancreatic adenocarcinoma (PAAD), prostate adenocarcinoma (PRAD), rectal adenocarcinoma (READ), cutaneous melanoma (SKCM), gastric (STAD), testicular germ cell tumor (TGCT), thyroid cancer (THCA), thymoma (THYM), endometrial cancer (UCEC), and uterine carcinosarcoma (UCS) (P < 0.0001). In addition, UBR1 was raised in adrenocortical carcinoma (ACC), bladder uroepithelial carcinoma (BLCA), and kidney-sparing carcinoma (KICH) (P < 0.05). In total, 28 cancers showed an elevated expression of this protein (Fig. 1A). Subsequently, we conducted pan-cancer GSEA to identify the potential pathways influenced by UBR1. The results indicated that the UBR1 protein is associated with various signaling pathways in pan-cancer. Additionally, it was enriched in gastric adenocarcinoma (STAD) and related to the NF-κB signaling pathway, mTOR signaling pathway, oxidative phosphorylation, mitosis, and DNA damage checkpoints (Fig. 1B). These findings suggest that UBR1 is upregulated in most cancers, including STAD, and is associated with multiple signaling pathways and functions.
UBR1 is upregulated in GC
The association between UBR1 and GC development remains poorly understood. UBR1 expression in GC was analyzed using TCGA and GTEX databases (Fig. 2A) as well as GSE54129, GSE66229, and GSE118916 datasets from the GEO database to validate the findings (Fig. 2B-D). UBR1 expression levels were found to be drastically higher in GC tissues than in normal tissues in both TCGA and GEO datasets, which is consistent with the results from the GEPIA database. Additionally, analysis of tissue microarrays from the HPA database using immunohistochemistry (IHC) showed that UBR1 levels in STAD tissues were significantly higher than those in normal gastric tissues (Fig. 2E). The experimental findings align with the bioinformatics analysis, indicating a significant increase in UBR1 expression in GC tissues relative to paired gastric cancer with paraneoplastic tissues, as determined by IHC (Fig. 2F). The mRNA expression of UBR1 was measured in 21 paired carcinoma and paraneoplastic tissue samples. UBR1 mRNA levels were significantly elevated in GC tissues (p < 0.001) (Fig. 2G). Furthermore, we analyzed the expression of UBR1 in gastric cancer cell lines. qPCR assay of the mRNA and protein levels of UBR1 in GES1, MGC803, MKN45, AGS, and HGC27 gastric cancer cells (Fig. 2H-I) confirmed significant overexpression in gastric cancer cell lines compared to human gastric mucosal cells (GES1). Next, potential pathways associated with UBR1 in AGS cells were predicted using the HPA database. Z-SCORE normalization was used to demonstrate that UBR1 may be linked to various pathways in AGS cells, including NF-κB, JAK-STAT, PI3K, TNFα, and hypoxia (Fig. 2J). Finally, the potential of UBR1 as a diagnostic biomarker for GC was evaluated using ROC curve analysis. ROC curve analysis based on TCGA database revealed that UBR1 has potential as a diagnostic biomarker for patients. The area under the curve (AUC) for UBR1 was 0.752 (Fig. 2K). Therefore, it could conceivably be hypothesized that UBR1 is overexpressed in GC tissues and cell lines compared to that in normal gastric mucosal tissues at the biochemical, transcriptional, and translational levels.
High UBR1 expression is associated with poor prognosis in GC patients
We assessed the prognostic significance of UBR1 expression in patients with GC by analyzing TCGA and GEO data. The KM curves indicated a significant negative correlation between UBR1 expression and OS, PFI, and DSS in patients (Fig. 3A-C). Similarly, high UBR1 expression in GEO datasets (GSE15459, GSE51105, and GSE62254) was positively correlated with poor prognosis of GC patients (Fig. 3D-F). Gender was correlated with UBR1 expression, and higher expression of UBR1 was associated with lower survival rates in women (Fig. 3G). Patients with GC who had higher expression of UBR1 showed lower OS rates after surgery (Fig. 3H) and poorer response to chemotherapy. The data reported here suggest that UBR1 expression is connected with OS and involved in GC progression.
UBR1 genetic alterations in cancer types
We investigated the genetic modifications of UBR1 in human malignancies because of its anomalous expression in cancer. The frequency of UBR1 alterations was predicted using cBioPortal database analysis. UBR1 exhibited frequent genetic alterations in GC, including amplifications, profound deletions, and mutations, with a prevalence of 07.163% in three cases (Fig. 4A). The 4D structure of UBR1 protein was acquired from the HPA database (Fig. 4B). We predicted the site of UBR1 mutations, the mutated amino acids, their association with post-translational modifications, and the frequency of somatic mutations (Fig. 4C).
UBR1 expression is associated with GC progression
This study evaluated the involvement of UBR1 in GC by examining the correlation between UBR1 expression and clinical parameters (including age, gender, tumor grade, residual tumor grade, anti-reflux treatment, and tumor TNM stage). The analysis was conducted using data from the GEO dataset GSE84437 and TCGA database. UBR1 was upregulated in patients with stage T3 and T4 GC compared to those with stage T2 GC, as evidenced by data from the GEO database (Fig. 5A). UBR1 was upregulated in patients with stage N1 and N2 GC compared with that in patients with stage N0 GC (Fig. 5B). UBR1 expression was significantly elevated in GC patients aged ≥ 65 years compared to that in GC patients aged < 65 years (Fig. 5C).
Male GC patients exhibited significantly higher expression of UBR1 than females (Fig. 5D). In contrast to the GEO database, TCGA database revealed an increase in UBR1 expression in T4 stage GC patients (Fig. 5E) and a higher UBR1 expression in stage III GC patients than in stage II breast cancer patients (Fig. 5F). In addition, UBR1 exhibited significant upregulation in the tumor sarcoid residual (R2) compared to complete tumor resection (R0) (Fig. 5G). UBR1 expression was increased in patients with GC who did not receive anti-reflux treatment (Fig. 5H). Fan and column plots were used to illustrate the variation in high and low UBR1 expression distributions among the clinical prognostic stages (Fig. 5I and J). These data suggested that various clinical factors may influence UBR1 expression and its role in GC progression. Elevated UBR1 levels may serve as an unfavorable prognostic factor for patients with GC. The patient's baseline information table for UBR1 in the TCGA database can be found in Additional file 1: Table S1.
Biological functions of UBR1
Multiple analyses were completed to identify the biological functions of UBR1. TCGA database was used to identify differential genes in UBR1 in GC, leading to the detection of numerous differentially expressed genes, as depicted in the volcano map (Fig. 6A). Next, a heat map was generated based on the differential expression of UBR1 (Fig. 6B). Subsequently, KEGG and GO analyses were conducted separately for upregulated and downregulated genes (Fig. 6C). KEGG analysis revealed the enrichment of downregulated genes in Parkinson's disease, SLE, oxidative phosphorylation, ribosome metabolism, and olfactory transmission. The upregulated genes were enriched in small cell lung cancer, phospholipid acyl signaling, cancer pathways, ECM receptor interactions, and adhesion. We conducted a search for differentially expressed genes enriched in miRNA target genes (MIR). We analyzed a vast collection of computational genes defined by cancer-specific microarray data. In GO analysis, downregulated genes were mainly enriched in structural components of ribosomes, keratinization, ribosomal subunits, olfactory sensory perception, and olfactory receptor activity. The upregulated genes were mainly enriched in various cellular functions, such as cell adhesion via plasma membrane adhesion molecules, regulation of cellular molecules, cell attachment components, homogeneous cell adhesion via plasma membrane adhesion powder brains, synaptic organization, and other cytological functions. Next, we searched for gene sets that represent disrupted cellular pathways in cancer, specifically focusing on downregulated gene sets, such as P53, MYC, SRC. Next, we used the GEO database to enrich the upregulated and downregulated gene sets associated with CD4 + and CD8 + immune cells for cellular states and immune system perturbations. Finally, we used single-cell sequencing of human tissues to identify cell-type markers and enriched gene sets for these clusters. Overall, our findings suggested that the differential gene sets for UBR1 are enriched in cancer pathways, P53 association, immune cells, and multiple metabolic pathways.
Analysis of the correlation between UBR1 expression and immunity
We examined the correlation between UBR1 expression and immune infiltration levels (Fig. 7A, C) using the TIMER and EPIC algorithms to evaluate the immune cell infiltration of UBR1 in certain malignancies. We then compared the immune, stromal, and ESTIMATE scores between the high and low UBR1 expression groups. The results indicated significant differences in the immune and ESTIMATE scores (p > 0.001) (Fig. 7B). The TIMER algorithm disclosed a significant positive correlation between UBR1 expression and CD4 + T-cell infiltration in STAD (P < 0.05). This association was observed using the EPIC algorithm, which linked multiple UBR1 expressions. High UBR1 expression in the EPIC algorithm was positively correlated with UVM, UCS, UCEC, THYM, THCA, TGCT, SKCM, PAAD, OV, MESO, LUAD, LIHC, LGG, LAML, KIRP, KIRC, HNSC, GBM, ESCA, COAD, CESC, BRCA, BLCA, and ACC, which was also validated in the TIME algorithm. The results suggested a correlation between UBR1 expression and immune infiltration levels, highlighting the potential significance of CD4 + T cells as a target.
UBR1 interacts with PDL1 in GC
Regarding the correlation between UBR1 and immune checkpoint genes, this study made a further investigation by generating a heatmap. The results showed a statistically significant correlation (p < 0.05) between UBR1 and immune checkpoint-related genes, including PDL1, CTLA4, TNFRS, ICOS, CD80, PDCD1LG2, TIGIT, CD86, IDO2, CD40, CD244, HAVCR2, BTLA, CD28, CD40LG, CD200R1, TNFSF4, CD200, and NRP1 (p < 0.05) (Fig. 8A). The immune checkpoint-related genes were ranked based on correlation size and presented in a correlation lollipop graph. The top five genes in the correlation ranking were CD80, PDCD1LG2, CD28, PDL1, and HAVCR2 (Fig. 8B). The correlation between UBR1 and PDL1 in STAD was confirmed using the TCGA database. UBR1 displayed a significant positive correlation with PDL1 (R = 0.314, p < 0.001) (Fig. 8C). In the immunotherapy analysis, the UBR1 low-expression group had higher immune scores in patients who were negative for both PD1 and CTLA4. The low-expression group was also significantly more responsive to immunotherapy (p < 0.01) (Fig. 8D). The UBR1 low-expression group exhibited higher immune scores in CTLA4-positive patients compared to that in the UBR1 high-expression group, suggesting that the former was more responsive to anti-CTLA4 treatment in the CTLA4 low-expression group (p < 0.01) (Fig. 8F). Immunotherapy in PD1- and CTLA4-positive patients showed no statistically significant difference between high and low UBR1 expression (Fig. 8E, G). Next, Immunoprecipitation assays were conducted in AGS cells to verify the direct interaction between UBR1 and PDL1. The results indicated that the UBR1 and PDL1 proteins exhibited binding affinity (Fig. 8H). Finally, null and knockdown cis-transformed cell lines were constructed using AGS and MGC803 cells, respectively. The mRNA expression was verified using qPCR. The efficacy of si-1 and si-2 knockdown was higher than that of si-3, leading to the subsequent utilization of the si-1 and si-2 sequences (Fig. 8I). The expression of PDL1 was verified at both protein and mRNA levels following UBR1 knockdown. A decrease in both UBR1 protein and mRNA expression levels was observed (Fig. 8J, K). In summary, UBR1 is associated with immunotherapy and directly affects PDL1.
UBR1 knockdown inhibits proliferation, invasion, and apoptosis of GC cells in vitro
High gene expression is often connected with poor prognosis. To elucidate the function of UBR1 in GC, we used three siRNAs for cis-translational knockdown in AGS and MGC803 cells. Prior to the experiment, we evaluated the efficiency of knockdown using Western blotting and qPCR analysis. The effect of UBR1 silencing on the proliferative capacity of GC cells was evaluated by knockdown of UBR1 in AGS and MGC803 cells. Cell growth significantly decreased at 24, 48, and 72 h (p < 0.001), as regulated by the Cell Counting Kit-8 (CCK8) assay (Fig. 9A, B). UBR1 knockdown in both the cell lines resulted in a noteworthy reduction in colony formation (Fig. 9C). UBR1 knockdown resulted in a significant decrease in the invasive ability of AGS and MGC803 cells (p < 0.001) in Transwell invasion assays using Matrigel gel (Fig. 9D, E, F). In the wound healing assay, UBR1 knockdown reduced migratory capacity (p < 0.001) (Fig. 9H, I, J) and induced apoptosis in both cell types (p < 0.01) (Fig. 9G, K). In previous analyses, GESA and HPA predicted that UBR1 may be enriched in the NF-κB pathway, which was validated through knockdown experiments in AGS and MGC803 cells. Knockdown of UBR1 resulted in a significant reduction in phosphorylated NF-κB P65 expression, as indicated by Western blotting. Additionally, UBR1 expression affected various cellular processes, including cell growth, colony formation, invasion, migration, and apoptosis, and was enriched in the NF-κB P65 pathway in GC cell lines.