Renal cell Carcinoma (RCC) is one of the top ten most common malignant tumors in both males and females worldwide, accounting for 4.2% of all new cancer cases. Clear cell carcinoma of the kidney (Ccrcc) is the most common histological subtype, originating from the proximal Renal epithelial tubules and being the cause of most cancer-related deaths.
It is difficult to detect early, resulting in approximately 30% of ccRCC patients already experiencing distant metastasis at diagnosis. In recent years, the clinical application of targeted therapy and immunotherapy has improved the overall survival level of patients to a certain extent. However, most patients inevitably progress to the stage of metastatic renal cell carcinoma due to individual differences in treatment response and drug resistance, with a 5-year survival rate of less than 10%. Therefore, elucidating the molecular drivers of ccRCC progression and metastasis, as well as developing effective methods for treating advanced RCC, is crucial.
The treatment of advanced renal clear cell carcinoma (CcRCC) remains a significant challenge in clinical practice. Building more reliable prognostic models and further elucidating the key molecular mechanisms of tumor progression are urgently needed for in-depth research.
This study used CiberSort to estimate the proportion of 22 tumor-infiltrating immune cell types in the TCGAKIRC cohort. Weighted Gene co-expression network analysis, minimum absolute contraction, and selection operator regression analysis were used to establish the risk prediction model. The expression pattern and clinical significance of TRAF2 were determined by bioinformatics analysis, real-time fluorescence quantitative polymerase chain reaction, Western Blot, immunohistochemistry, and other methods. The function and mechanism of the TRAF2/M2 macrophage/autophagy cell axis were studied by GSEA analysis, Transmission electron microscopy, 2D/3D colony formation experiment, Cell migration and invasion experiment, and tubule formation experiment.
This study constructs a new prognostic prediction model based on M2 macrophage-related genes, which is considered an accurate, independent, and specific prognostic risk model for renal cancer patients. A reliable nomogram was constructed to predict the overall survival time of chronic renal cell carcinoma patients at 1, 3, and 5 years. As one of the constituent genes of the risk model, TRAF2 is upregulated in renal cell carcinoma and is associated with poor clinical prognosis.
The researchers found that TRAF2 promotes the malignant progression of renal cell carcinoma by regulating Macrophage polarization, migration, and angiogenesis. Mechanically, researchers have found that TRAF2 promotes the polarization of M2 macrophages, and this chemotaxis is achieved through an autophagy-dependent pathway. The results of in situ tumor growth experiments show that TRAF2 plays a crucial role as a promoter of ccRCC growth and metastasis.
In summary, the prognosis prediction model constructed by researchers can accurately and stably predict the prognosis of patients, and is expected to promote the evaluation of therapeutic efficacy and improvement of comprehensive treatment levels in renal cell carcinoma patients. In addition, the results of this study indicate that the TRAF2/M2 macrophage/autophagy axis plays a crucial regulatory role in the malignant progression of renal cell carcinoma, suggesting that TRAF2 is a potential new target for the treatment of advanced renal cell carcinoma.
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Reference
Yawei Xu et al. TRAF2 promotes M2-polarized tumor-associated macrophage infiltration, angiogenesis and cancer progression by inhibiting autophagy in clear cell renal cell carcinoma. J Exp Clin Cancer Res. 2023 Jul 6;42(1):159. doi: 10.1186/s13046-023-02742-w.
