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Updated: Aug 17, 2025
The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Development of a polyamine gene expression score for predicting prognosis and treatment response in clear cell renal
Mei Chen1, Zhenyu Nie1, Denggao Huang1
1Central Laboratory, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, China.
Backgrounds:
Polyamine metabolism (PM) is closely related to the tumor microenvironment (TME) and is involved in antitumor immunity. Clear cell renal cell carcinoma (ccRCC) not only has high immunogenicity but also has significant metabolic changes. However, the role of PM in the immune microenvironment of ccRCC remains unclear. This study aimed to reveal the prognostic value of PM-related genes (PMRGs) expression in ccRCC and their correlation with the TME.
Methods:
The expression levels PMRGs in different cells were characterized with single-cell sequencing analysis. The PMRG expression pattern of 777 ccRCC patients was evaluated based on PMRGs. Unsupervised clustering analysis was used in identifying PMRG expression subtypes, and Lasso regression analysis was used in developing polyamine gene expression score (PGES), which was validated in external and internal data sets. The predictive value of PGES for immunotherapy was validated in the IMvigor210 cohort. Multiple algorithms were used in analyzing the correlation between PGES and immune cells. The sensitivity of PGES to chemotherapeutic drugs was analyzed with the "pRRophetic" package. We validated the genes that develop PGES in tissue samples. Finally, weighted gene co-expression network analysis was used in identifying the key PMRGs closely related to ccRCC, and cell function experiments were carried out.
Results:
PMRGs were abundantly expressed on tumor cells, and PMRG expression was active in CD8+ T cells and fibroblasts. We identified three PMRG expression subtypes. Cancer and immune related pathways were active in PMRG expression cluster A, which had better prognosis. PGES exhibited excellent predictive value. The high-PGES group was characterized by high immune cell infiltration, high expression of T cell depletion markers, high tumor mutation burden and tumor immune dysfunction and exclusion, was insensitive to immunotherapy but sensitive to sunitinib, temsirolimus, and rapamycin, and had poor prognosis. Spermidine synthetase (SRM) has been identified as a key gene and is highly expressed in ccRCC at RNA and protein levels. SRM knockdown can inhibit ccRCC cell proliferation, migration, and invasion.
Conclusions:
We revealed the biological characteristics of PMRG expression subtypes and developed PGES to accurately predict the prognosis of patients and response to immunotherapy.
