GRAMD1A Is a Biomarker of Kidney Renal Clear Cell Carcinoma and Is Associated with Immune Infiltration in the Tumour Microenvironment

Identification of Renal Transplantation Rejection Biomarkers in Blood Using the Systems Biology Approach

Background

Renal transplantation plays an essential role in the quality of life of patients with end-stage renal disease. At least 12% of the renal patients receiving transplantations show graft rejection. One of the methods used to diagnose renal transplantation rejection is renal allograft biopsy. This procedure is associated with some risks such as bleeding and arteriovenous fistula formation. In this study, we applied a bioinformatics approach to identify serum markers for graft rejection in patients receiving a renal transplantation.

Methods

Transcriptomic data were first retrieved from the blood of renal transplantation rejection patients using the GEO database. The data were then used to construct the protein-protein interaction and gene regulatory networks using Cytoscape software. Next, network analysis was performed to identify hub-bottlenecks, and key blood markers involved in renal graft rejection. Lastly, the gene ontology and functional pathways related to hub-bottlenecks were detected using PANTHER and DAVID servers.

Results

In PPIN and GRN, SYNCRIP, SQSTM1, GRAMD1A, FAM104A, ND2, TPGS2, ZNF652, RORA, and MALAT1 were the identified critical genes. In GRN, miR-155, miR17, miR146b, miR-200 family, and GATA2 were the factors that regulated critical genes. The MAPK, neurotrophin, and TNF signaling pathways, IL-17, and human cytomegalovirus infection, human papillomavirus infection, and shigellosis were identified as significant pathways involved in graft rejection.

Concusion

The above-mentioned genes can be used as diagnostic and therapeutic serum markers of transplantation rejection in renal patients. The newly predicted biomarkers and pathways require further studies.

Elevated NDC1 expression predicts poor prognosis and correlates with immunity in hepatocellular carcinoma

Background

NDC1 was identified to be a tumor-promoting factor in non-small cell lung cancer and cervical cancer. However, no report had clarified the relationship between NDC1 and hepatocellular carcinoma (HCC). In this paper, we explored the expression and potential functions of NDC1 in HCC for the first time through the rational application of bioinformatics and relevant basic experiments.

Methods

NDC1-related expression profiles and clinical data of HCC patients were collected from The Cancer Genome Atlas (TCGA) database, which were verified via quantitative real-time polymerase chain reaction (qRT-PCR), immunohistochemistry and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Univariate and multivariate Cox regression analyses were used to identify NDC1 as an independent factor for HCC prognosis, and NDC1-related signaling pathways were determined by gene set enrichment analysis (GSEA). Furthermore, we deeply probed the potential links of NDC1 to immunity and immune response. Finally, the bioeffects and underlying mechanisms of ectopic NDC1 overexpression and depletion were determined in HepG2 cells by immunoblotting, flow cytometry, Cell-Counting-Kit-8 (CCK-8), and EDU (5-Ethynyl-2'-deoxyuridine).

Results

Up-regulated expression of NDC1 was detected by means of the TCGA database, which was consistent with the results obtained from further qRT-PCR, immunohistochemistry and the CPTAC database. Kaplan-Meier (K-M) survival analysis revealed a worse prognosis in HCC patients with high NDC1 expression. Besides, NDC1 was certified to be closely linked to tumor histologic grade, clinical stage and T stage. Moreover, univariate and multivariate Cox regression analyses defined NDC1 as an independent element for HCC prognosis. NDC1-related signaling pathways, utilizing GSEA analysis, were subsequently found out. What's more, NDC1 expression was detected to be enormously associated with microsatellite instability (MSI), immune cell infiltration, immune checkpoint molecules and immune cell pathways. As for immunotherapy, we discovered that different risk groups tended to have different immune checkpoint inhibitor responses, which indicated crucial implication value of NDC1 for HCC immunotherapy. More interestingly, we observed that the overexpression of NDC1 could promote the migration and invasion of HCC cells.

Conclusions

Our article demonstrated that NDC1 might serve as a valuable predictor in the prognosis and immunotherapy of HCC. NDC1 played an oncogenic role in HCC.