Dataset Information

Expression of AKT1 Related with Clinicopathological Parameters in Clear Cell Renal Cell Carcinoma.

ABSTRACT: Pathways such as VEGF, EGF and mTOR are known to be one of the major mechanisms of tumorigenesis including kidney cancer. To identify potential signaling pathway proteins, we performed differential/correlation analyses of mTOR-associated genes from three public datasets. AKT1 protein, one of the PI3K/AKT/mTOR pathways, turned out to be the potential by showing a consistent discrepancy between ccRCC-associated conditions as well as strong correlation with other mTOR-associated genes across the datasets. Then, we analyzed how AKT1 alteration affects clear cell renal cell carcinoma. The pathology of 58 kidney cancer patients was constructed to analyze the relationship between the expression level of AKT1 through immunohistochemical staining and their clinicopathological data. Gender, age and TNM stage did not show significant results. AKT1 is a known oncogene. However, in this study, high expression of AKT1 showed a slight correlation with lower WHO/ISUP grade, longer recurrence-free and progression-free survival rates.

SUBMITTER: Choi T

PROVIDER: S-EPMC9600081 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Expression of AKT1 Related with Clinicopathological Parameters in Clear Cell Renal Cell Carcinoma.

Choi Taesoo T Yoo Koo Han KH Kim Man S MS

Current issues in molecular biology 20221015 10

Pathways such as VEGF, EGF and mTOR are known to be one of the major mechanisms of tumorigenesis including kidney cancer. To identify potential signaling pathway proteins, we performed differential/correlation analyses of mTOR-associated genes from three public datasets. AKT1 protein, one of the PI3K/AKT/mTOR pathways, turned out to be the potential by showing a consistent discrepancy between ccRCC-associated conditions as well as strong correlation with other mTOR-associated genes across the da ...[more]

PMID: 36286049

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Project description:ObjectivesThis study aimed to assess the cellular localization and expression levels of hypoxia-inducible factor (HIF) -α proteins (specifically HIF-1α, HIF-2α, and HIF-3α) that play a role in the hypoxia pathway and to determine their correlation with clinicopathological parameters and patient survival in renal cell carcinoma (RCC).Materials and methodsTissue microarray (TMA) with cores from 150 clear cell RCCs and 31 non-ccRCC samples. HIF-1α, HIF-2α, and HIF-3α antibodies were used for immunohistochemistry (IHC) of TMA to evaluate the cellular localization and expression levels of HIF-α proteins, specifically in relation to the hypoxia pathway.ResultsThe expression levels of the HIF-α proteins were higher in the nucleus than in the cytoplasm. Furthermore, the nuclear expression levels of all HIF-α proteins were significantly higher in clear cell RCC (ccRCC) than in non-ccRCC. Cytoplasmic HIF-3α expression was also higher in ccRCC than in non-ccRCC, whereas cytoplasmic HIF-1α and HIF-2α expression levels were similar between the different RCC types. In ccRCC, nuclear HIF-1α expression levels correlated with both nuclear HIF-2α and HIF-3α levels, whereas cytoplasmic HIF-3α expression levels were associated with HIF-1α only.In non-ccRCC, there was a positive correlation observed between nuclear HIF-1α and HIF-3α expression, but no correlation was found with HIF-2α. In patients with ccRCC, the nuclear expressions of HIF-1α and HIF-3α was significantly associated with cancer-specific survival (CSS) in univariate analysis. This association was no longer evident in multivariate analysis. Notably, there was no correlation observed between nuclear HIF-2α expression and CSS in these patients. In contrast, cytoplasmic expression levels showed no association with CSS.ConclusionThe expression levels of the three primary HIF-α proteins were found to be higher in the nucleus than in the cytoplasm. Furthermore, the results indicated that HIF-3α and HIF-1α expression levels were significant univariate factors associated with CSS in patients with clear cell RCC. These results highlight the critical role that HIF-3α and HIF-1α play in the hypoxia pathway.

Project description:Objective: To construct a prognostic evaluation model for clear cell renal cell carcinoma (ccRCC) patients using bioinformatics method and to screen potential drugs for ccRCC. Methods: ccRCC RNA sequencing data, clinical data, and protein expression data were downloaded from the TCGA database. Univariate Cox and Lasso regression analyses were performed on the combined data to screen out the proteins related to the prognosis, and they were included in a multivariate Cox proportional hazard model. The patients were divided into high and low-risk groups for a survival difference analysis. The predictive power of the model was evaluated on the basis of overall survival, progression-free survival, independent prognostic, clinically relevant receiver operating characteristic (ROC) curve, C-index, principal component, and clinical data statistics analyses. GSEA enrichment and immune function correlation analyses were performed. The samples were divided into different subtypes based on the expression of the risk proteins, and survival analysis of the subtypes was performed. The risk-related protein and RNA sequencing data were analyzed to screen out sensitive drugs with significant differences between the high and low-risk groups. Results: A total of 469 ccRCC-related proteins were screened, of which 13 proteins with independent prognostic significance were screened by univariate Cox, Lasso, and multivariate Cox regression analyses to construct the prognostic model. The sensitivity and accuracy of the model in predicting the survival of patients with ccRCC were high (1 year: 0.811, 3 years: 0.783, 5 years: 0.777). The 13 proteins were closely related to immunity, and the model proteins were different between kidney and tumor tissues according to the HPA database. The samples were divided into three subtypes, and there were obvious clinical characteristics of the three subtypes in the grade and T, N and M stages. According to the IC50 values, CGP-60474, vinorelbine, doxorubicin, etoposide, FTI-277, JQ12, OSU-03012, pyrimethamine, and other drugs were more sensitive in the high-risk group. Conclusions: A prognostic model of protein expression in ccRCC was successfully constructed, which had good predictive ability for the prognosis of ccRCC patients. The ccRCC-related proteins in the model can be used as targets for studying the pathogenesis and targeted therapy.

Dataset Information

Expression of AKT1 Related with Clinicopathological Parameters in Clear Cell Renal Cell Carcinoma.

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Expression of AKT1 Related with Clinicopathological Parameters in Clear Cell Renal Cell Carcinoma.

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