Deciphering the tumour microenvironment of clear cell renal cell carcinoma: Prognostic insights from programmed death genes using machine learning

Journal of Cellular and Molecular Medicine, Год журнала: 2024, Номер 28(13)

Опубликована: Июль 1, 2024

Abstract Clear cell renal carcinoma (ccRCC), a prevalent kidney cancer form characterised by its invasiveness and heterogeneity, presents challenges in late‐stage prognosis treatment outcomes. Programmed death mechanisms, crucial eliminating cells, offer substantial insights into malignant tumour diagnosis, prognosis. This study aims to provide model based on 15 types of Cell Death‐Related Genes (PCDRGs) for evaluating immune microenvironment ccRCC patients. patients from the TCGA arrayexpress cohorts were grouped PCDRGs. A combination using Lasso SuperPC was constructed identify prognostic gene features. The cohort validated model, confirming robustness. Immune analysis, facilitated PCDRGs, employed various methods, including CIBERSORT. Drug sensitivity analysis guided clinical decisions. Single‐cell data enabled scoring, subsequent pseudo‐temporal cell–cell communication analyses. PCDRGs signature established TCGA‐KIRC data. External validation underscored model's superiority over traditional Furthermore, our single‐cell unveiled roles PCDRG‐based subgroups ccRCC, both progression intercellular communication. Finally, we performed CCK‐8 assay other experiments investigate csf2 . In conclusion, these findings reveal that inhibit growth, infiltration movement cells associated with clear carcinoma. introduces benefiting while shedding light pivotal role programmed genes shaping

Язык: Английский

Identification of a Combined Immune- and Metabolism- Related Prognostic Signature for Clear Cell Renal Cell Carcinoma

Research Square (Research Square), Год журнала: 2023, Номер unknown

Опубликована: Июль 14, 2023

Abstract A typically observed form of malignancy within the urological system is clear cell renal carcinoma (ccRCC) which major histological subtype (RCC) that develops from proximal convoluted tubules. Despite ongoing efforts to develop effective treatments for ccRCC, it remains a significant challenge in field oncology, and further studies are required fully understand this complex disease. Tumor biology has recently shown increasing interest immune evasion metabolic reprogramming, crucial tumor initiation progression. this, an all-inclusive analysis genes linked combined metabolism immunity ccRCC not yet available. This study establishes prognostic signature relates microenvironment (TME) by utilizing nine immune- metabolism-related (IMRGs). The findings revealed IMRGs-based excelled over previously published signatures relied solely on either or predict outcomes, thus underscoring its robustness reliability. Furthermore, predictive tool nomogram was developed, both IMRGs range clinical parameters. differences infiltration, checkpoint expression, immunophenoscore (IPS) between high- low-risk groups classified our model were significantly notable. It can be concluded holds immense potential accurately predicting risks, evaluating efficacy immunotherapy, facilitating personalized treatment regimens patients with ccRCC.

Язык: Английский