Single‐cell transcriptomic analysis in clear cell renal cell carcinoma: Deciphering the role of APP within the tumour microenvironment

• Published in: Journal of cellular and molecular medicine 2024-03, Vol.28 (6), p.e18186-n/a
• Main Authors: Guan, Bo, Li, Ming, Cui, Di, Shen, Chen, Hao, Zongyao, Li, Xiaowei
• Format: Article
• Language: English
• Subjects: Alzheimer's disease; Amyloid beta-Protein Precursor; Amyloid precursor protein; amyloid precursor protein (APP); Biomarkers; Cancer therapies; Carcinoma; Carcinoma, Renal Cell - genetics; Cell adhesion & migration; Chemotherapy; clear cell renal cell carcinoma (ccRCC); Clear cell-type renal cell carcinoma; Communication; Gene expression; Gene Expression Profiling; Hospitals; Humans; Kidney cancer; Kidney Neoplasms - genetics; Macrophages; Medical prognosis; Metastasis; Original; Pathogenesis; Patients; Prognosis; Survival analysis; Therapeutic targets; Transcriptomics; Tumor microenvironment; Tumor Microenvironment - genetics; Tumors; tumour microenvironment (TME); tumour‐associated macrophages (TAMs); Urology
• ISSN: 1582-1838; 1582-4934; 1582-4934
• DOI: 10.1111/jcmm.18186

Clear cell renal cell carcinoma (ccRCC) represents a significant challenge in oncology, primarily due to its resistance to conventional therapies. Understanding the tumour microenvironment (TME) is crucial for developing new treatment strategies. This study focuses on the role of amyloid precursor protein (APP) in tumour‐associated macrophages (TAMs) within the ccRCC TME, exploring its potential as a prognostic biomarker. Basing TAM‐related genes, the prognostic model was important to constructed. Employing advanced single‐cell transcriptomic analysis, this research dissects the TME of ccRCC at an unprecedented cellular resolution. By isolating and examining the gene expression profiles of individual cells, particularly focusing on TAMs, the study investigates the expression levels of APP and their association with the clinical outcomes of ccRCC patients. The analysis reveals a significant correlation between the expression of APP in TAMs and patient prognosis in ccRCC. Patients with higher APP expression in TAMs showed differing clinical outcomes compared to those with lower expression. This finding suggests that APP could serve as a novel prognostic biomarker for ccRCC, providing insights into the disease progression and potential therapeutic targets. This study underscores the importance of single‐cell transcriptomics in understanding the complex dynamics of the TME in ccRCC. The correlation between APP expression in TAMs and patient prognosis highlights APP as a potential prognostic biomarker. However, further research is needed to validate these findings and explore the regulatory mechanisms and therapeutic implications of APP in ccRCC.