The Identification of Key Gene Expression Signature and Biological Pathways in Metastatic Renal Cell Carcinoma

Label-free quantitative proteomics reveals the mechanisms of Aurora kinase B in renal cell carcinoma

Background

Renal cell carcinoma is the most common form of kidney cancer which is a global threat to human health, needing to explore effective therapeutic targets and treatment methods. Aurora kinase B acts as an important carcinogenic role in various kinds of tumors, while its mechanism in renal cell carcinoma is indistinct. Herein we explore the underlying mechanism of Aurora kinase B in renal cell carcinoma.

Methods and results

Label-free quantitative proteomics analysis was employed to analyze the differentially expressed proteins in 786-O cells which were treated with si-Aurora kinase B or si-ctrl. In the current study, 169 differentially expressed proteins were identified. The top 10 upregulated proteins were MX2, IFI44L, ISG20, DDX58, F3, IFI44, ECE1, PRIC285, NIT1, and IFIT2. The top 10 downregulated proteins were FKBP9, FSTL1, DDAH1, TGFB2, HMGN3, COIL, FAM65A, PTPN14, ARFGAP2, and EIF2C2. GO enrichment analysis showed that these differentially expressed proteins participated in biological processes, including defense response to virus, response to virus, and type I interferon signaling pathway. These differentially expressed proteins participated in cellular components, including focal adhesion, cell-substrate adherens junction, cell-substrate junction, and endoplasmic reticulum lumen. These differentially expressed proteins participated in molecule functions, including guanyl nucleotide binding, nucleotidase activity, double-stranded RNA binding, 2'-5'-oligoadenylate synthetase activity, and virus receptor activity. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the significantly changed proteins including OAS3, OAS2, JAK1, TAP1, and RAC1 were involved in Epstein-Barr virus infection.

Conclusions

Taken together, our results demonstrate the possible mechanisms that Aurora kinase B may participate in renal cell carcinoma. These findings may provide insights into tumorigenesis and a theoretical basis for developing potential therapies of renal cell carcinoma.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

Development and Validation of a Prognostic Gene Signature in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC), one of the most common urologic cancer types, has a relatively good prognosis. However, clinical diagnoses are mostly done during the medium or late stages, when mortality and recurrence rates are quite high. Therefore, it is important to perform real-time information tracking and dynamic prognosis analysis for these patients. We downloaded the RNA-seq data and corresponding clinical information of ccRCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 3,238 differentially expressed genes were identified between normal and ccRCC tissues. Through a series of Weighted Gene Co-expression Network, overall survival, immunohistochemical and the least absolute shrinkage selection operator (LASSO) analyses, seven prognosis-associated genes (AURKB, FOXM1, PTTG1, TOP2A, TACC3, CCNA2, and MELK) were screened. Their risk score signature was then constructed. Survival analysis showed that high-risk scores exhibited significantly worse overall survival outcomes than low-risk patients. Accuracy of this prognostic signature was confirmed by the receiver operating characteristic curve and was further validated using another cohort. Gene set enrichment analysis showed that some cancer-associated phenotypes were significantly prevalent in the high-risk group. Overall, these findings prove that this risk model can potentially improve individualized diagnostic and therapeutic strategies.

The circular RNAs differential expression profiles in the metastasis of salivary adenoid cystic carcinoma cells

In order to reveal circular RNAs (circRNAs) differential expression profiles and investigate the function and mechanism of circRNAs in the metastasis of salivary adenoid cystic carcinoma (SACC), microarray was used to detect differentially expressed circRNAs in SACC-83 and SACC-lung metastasis (LM) cell lines. Up-regulated circRNAs were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to further predict their function. Expression of candidate circRNA and microRNA (miRNA) was determined using quantitative real-time polymerase chain reaction (qRT-PCR). Constructed circRNA-miRNA-mRNA co-expression network was based on TargetScan, miRanda databases. Wound healing and transwell assays were completed to examine the effects of hsa_circRNA_001982 and miR-181a-5p on cell migration and invasion. qRT-PCR confirmed hsa_circRNA_092556, hsa_circRNA_101379, and hsa_circRNA_001982 up-regulation in SACC-LM. miR-181a-5p was down-regulated in SACC-LM and correlated with up-regulated hsa_circRNA_001982. Wound healing and transwell assays indicated that silencing hsa_circRNA_001982 inhibited the migration and invasion of the SACC-LM cells. Furthermore, over-expression of hsa_circRNA_001982 promoted the migration and invasion of SACC-83 cells. Interestingly, up-regulation or down-regulation of miR-181a-5p led to the opposite result in wound healing and transwell assays. Overall, differential expression circRNA profiles in SACC-83 and SACC-LM cells may reveal potential targets and a novel mechanism of circRNAs in the metastasis of SACC. Moreover, the interaction of hsa_circRNA_001982/miR-181a-5p is closely related to the metastasis of SACC cells.

HI-511 overcomes melanoma drug resistance via targeting AURKB and BRAF V600E

Rationale: Melanoma is an aggressive tumor of the skin and drug resistance is still a major problem in melanoma therapy. Novel targets and effective agents to overcome drug resistant melanoma are urgently needed in clinical therapy.

Methods: Gene Expression Omnibus (GEO) database analysis, pathway enrichment analysis, and survival rate analysis were utilized to identify a candidate target. An anchorage-independent cell growth assay, flow cytometry, Western blot, and a xenograft mouse model were used to study the function of Aurora kinase B (AURKB) in both drug-sensitive and drug-resistant melanoma. Next, HI-511, a novel dual-target inhibitor targeting both AURKB and BRAF V600E, was designed and examined by an in vitro kinase assay. Methods as indicated above in addition to a BRAF V600E/PTEN-loss melanoma mouse model were used to demonstrate the effect of HI-511 on melanoma development in vitro and in vivo.

Results: AURKB is highly expressed in melanoma and especially in vemurafenib-resistant melanoma and the expression was correlated with patient survival rate. Knocking down AURKB inhibited cell growth and induced apoptosis in melanoma, which was associated with the BRAF/MEK/ERKs and PI3-K/AKT signaling pathways. Importantly, we found that HI-511, a novel dual-target inhibitor against AURKB and BRAF V600E, suppresses both vemurafenib-sensitive and vemurafenib-resistant melanoma growth in vitro and in vivo by inducing apoptosis and mediating the inhibition of the BRAF/MEK/ERKs and PI3K/AKT signaling pathways.

Conclusion: AURKB is a potential target for melanoma treatment. HI-511, a novel dual-target inhibitor against both AURKB and BRAF V600E, could achieve durable suppression of melanoma growth, even drug-resistant melanoma growth.