C Chen1, H Chi, L Min, Z Junhua. 1. Department of Urology, Shanghai Tenth People's Hospital, Tongji University, Shanghai, 200072, China.
Abstract
PURPOSE: Clear-cell renal cell carcinoma (ccRCC) is characterized by genetic abnormalities, while the role of Guanine Nucleotide-Binding Protein Beta 1 (GNB1) in ccRCC has not been studied. We thus aimed to evaluate the expression and prognostic value of GNB1 in ccRCC. METHODS: A two-stage study (exploration and validation) was conducted using in silico and immunohistochemical (IHC) scoring of ccRCC samples from our institute, to evaluate the association between GNB1 expression and clinicopathological parameters of ccRCC patients. Pathway analyses were performed for genes coexpressed with GNB1 using the KOBAS platform to profile the function of GNB1 and IHC validation. RESULTS: In the exploration stage, data from TCGA ccRCC dataset were reproduced, which contained 537 patients with ccRCC and found that downregulation of GNB1 was significantly associated with worse prognosis. IHC staining from the Human Protein Atlas showed significantly downregulation of GNB1 in ccRCC tissue compared with normal kidney. Pathway analysis showed significantly altered vascular endothelial growth factor (VEGF) signaling pathways among which expressions of 3 genes (WASF2, NRP1, and HIP1) were significantly associated with GNB1 expression, respectively. In the validation stage, included were 80 ccRCC samples and GNB1 expression was scored using IHC positivity. GNB1 expression was negatively associated with tumor stage, lymph node invasion, metastasis, older age, and increased tumor grade. Female gender and receiving neoadjuvant therapy were also associated with decreased GNB1 expression. The expressions of WASF2, NRP1 and HIP1 were also studied and found that they were significantly associated with GNB1. CONCLUSION: GNB1 was downregulated in ccRCC. Decreased GNB1 expression was associated with worsened disease characteristics and prognosis. GNB1 was related with VEGF signaling in ccRCC, implying a therapeutic potential of this factor.
PURPOSE:Clear-cell renal cell carcinoma (ccRCC) is characterized by genetic abnormalities, while the role of Guanine Nucleotide-Binding Protein Beta 1 (GNB1) in ccRCC has not been studied. We thus aimed to evaluate the expression and prognostic value of GNB1 in ccRCC. METHODS: A two-stage study (exploration and validation) was conducted using in silico and immunohistochemical (IHC) scoring of ccRCC samples from our institute, to evaluate the association between GNB1 expression and clinicopathological parameters of ccRCC patients. Pathway analyses were performed for genes coexpressed with GNB1 using the KOBAS platform to profile the function of GNB1 and IHC validation. RESULTS: In the exploration stage, data from TCGA ccRCC dataset were reproduced, which contained 537 patients with ccRCC and found that downregulation of GNB1 was significantly associated with worse prognosis. IHC staining from the Human Protein Atlas showed significantly downregulation of GNB1 in ccRCC tissue compared with normal kidney. Pathway analysis showed significantly altered vascular endothelial growth factor (VEGF) signaling pathways among which expressions of 3 genes (WASF2, NRP1, and HIP1) were significantly associated with GNB1 expression, respectively. In the validation stage, included were 80 ccRCC samples and GNB1 expression was scored using IHC positivity. GNB1 expression was negatively associated with tumor stage, lymph node invasion, metastasis, older age, and increased tumor grade. Female gender and receiving neoadjuvant therapy were also associated with decreased GNB1 expression. The expressions of WASF2, NRP1 and HIP1 were also studied and found that they were significantly associated with GNB1. CONCLUSION:GNB1 was downregulated in ccRCC. Decreased GNB1 expression was associated with worsened disease characteristics and prognosis. GNB1 was related with VEGF signaling in ccRCC, implying a therapeutic potential of this factor.
Authors: Elisabetta Manduchi; Weixuan Fu; Joseph D Romano; Stefano Ruberto; Jason H Moore Journal: BMC Bioinformatics Date: 2020-10-01 Impact factor: 3.169