4.6 Article

Establishment of a new prognostic risk model of GNG7 pathway-related molecules in clear cell renal cell carcinoma based on immunomodulators

Journal

BMC CANCER
Volume 23, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12885-023-11265-8

Keywords

Immune infiltration; GNG7; Clear cell renal cell carcinoma; Prognosis

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This study explores the biological role of GNG7 in clear cell renal cell carcinoma (CCRCC), finding that high GNG7 expression predicts better prognosis for patients. A prognostic model involving 7 immune genes was established to predict the survival probabilities of CCRCC patients. The results provide valuable insights for individualized treatment decisions for CCRCC patients.
Clear cell renal cell carcinoma (CCRCC) is a common tumor of the urological system for which surgery is the preferred treatment, but there is a lack of therapeutic options after surgery. This study aims to explore the biological role of GNG7 on CCRCC from a genetic perspective. Differences in mRNA expression and patient survival of GNG7 in patients with CCRCC and healthy patients were analyzed using the TCGA database. It was observed that GNG7 gene expression was downregulated in CCRCC tissue compared with healthy tissue, and high GNG7 predicted better prognosis for patients, and GNG7 also showed strong variability in clinical and TMN staging. The immune relevance of GNG7 and related genes was explored using renal cancer data from CCLE and TISIDB database. It was verified that the risk score constructed by 7 GNG7-related regulators might be used as an independent prognostic risk factor for CCRCC. A CCRCC prognostic model that involved 7 immune genes was further established to predict the survival probabilities of patients. At last, the GEO database and immunochemical tissue staining were used to validate GNG7 expression in CCRCC. Our study proposed a novel panel of genes to predict CCRCC OS based on GNG7-related immune genes, which may help to accurately predict the prognosis of CCRCC patients and make better clinical decisions for individual treatment.

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