Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer characterized by metabolic reprogramming. Glutamine metabolism is pivotal in metabolic reprogramming, contributing to the significant heterogeneity observed in ccRCC. Consequently, developing prognostic markers associated with glutamine metabolism could enhance personalized treatment strategies for ccRCC patients. This study obtained RNA sequencing and clinical data from 763 ccRCC cases sourced from multiple databases. Consensus clustering of 74 glutamine metabolism related genes (GMRGs)- profiles stratified the patients into three clusters, each of which exhibited distinct prognosis, tumor microenvironment, and biological characteristics. Then, six genes (SMTNL2, MIOX, TMEM27, SLC16A12, HRH2, and SAA1) were identified by machine-learning algorithms to develop a predictive signature related to glutamine metabolism, termed as GMRScore. The GMRScore showed significant differences in clinical prognosis, expression profile of immune checkpoints, abundance of immune cells, and immunotherapy response of ccRCC patients. Besides, the nomogram incorporating the GMRScore and clinical features showed strong predictive performance in prognosis of ccRCC patients. ALDH18A1, one of the GRMGs, exhibited elevated expression level in ccRCC and was related to markedly poorer prognosis in the integrated cohort, validated by proteomic profiling of 232 ccRCC samples from Fudan University Shanghai Cancer Center (FUSCC). Conducting western blotting, CCK-8, transwell, and flow cytometry assays, we found the knockdown of ALDH18A1 in ccRCC significantly promoted apoptosis and inhibited proliferation, invasion, and epithelial-mesenchymal transition (EMT) in two human ccRCC cell lines (786-O and 769-P). In conclusion, we developed a glutamine metabolism-related prognostic signature in ccRCC, which is tightly linked to the tumor immune microenvironment and immunotherapy response, potentially facilitating precision therapy for ccRCC patients. Additionally, this study revealed the key role of ALDH18A1 in promoting ccRCC progression for the first time.

PYCARD is a protein engaged in inflammation, pyroptosis, and apoptosis. However, the function of PYCARD in human cancers remains unclear. The objective of our study was to explore PYCARD expression and prognostic value in human cancers. Public databases were used to assess PYCARD expression and prognostic value. The TISIDB database was used to explore the associations between PYCARD expression and different immune subtypes. The correlations between PYCARD expression and ICP genes, MMR genes, MSI, and TMB were also investigated. The immunotherapy response was assessed using the TIDE database. Single-cell RNA databases evaluated the PYCARD expression of immune cells. External datasets and immunohistochemical staining were conducted to validate PYCARD expression and prognostic value. The results showed that PYCARD expression varied in several cancers and was associated with prognosis, immune-related genes, published biomarkers, and immunotherapy response. Of note, PYCARD expression was upregulated in renal cancers with high diagnostic ability. Upregulation of PYCARD was correlated with worse prognosis in KIRC and external validation cohorts. In conclusion, PYCARD demonstrated strong correlations with prognosis, immune response, and disease progression in pan-cancer analysis. In ccRCC, PYCARD might serve as a biomarker for diagnosis and therapeutic target-boosting immunotherapy response.

Renal angiomyolipoma (AML) encompasses benign variants (lipomatous [L-AML], myomatous [M-AML]) and epithelioid AML (eAML), a potentially malignant subtype associated with aggressive behavior. While TSC1/TSC2 mutations are frequent, the molecular drivers underlying eAML pathogenesis remain unclear. Whole-exome sequencing (WES) was performed on 35 AML samples (15 eAML, 10 L-AML, 10 M-AML) with matched germline controls. Driver genes were identified using OncodriveCLUST and MutSigCV. Validation was conducted on 71 FFPE samples integrating expression profiling and survival analysis. The finding suggested that TSC2 emerged as the most frequently mutated pathogenic gene in AML, exhibiting a mutation rate of 69 %. TSC2, POLDIP2, NEFH, and MUC2 emerged as potential driver genes across AML subtypes, whereas RHPN2, ASXL1, TOP3B, and USP35 showed subtype-specific mutations. Notably, distinct cytogenetic aberrations were observed among AML variants, including deletions at 3p26.3, 5p13.1, 6p22.1, and 11p11.11. Clonal evolution analysis suggested that l-AML and eAML, as well as M-AML and eAML, may originate from a common ancestral clone, retaining early mutations and acquiring additional alterations post-divergence. Low TSC2/POLDIP2 and high NEFH/MUC2 expression correlated with favorable survival in eAML patients. Importantly, lower TSC2/POLDIP2 expression also predicted superior response rates to Everolimus therapy. In conclusion, our study comprehensively delineates genomic distinctions and evolutionary trajectories among renal AML subtypes, establishing TSC2, POLDIP2, NEFH, and MUC2 as prognostic biomarkers and therapeutic predictors, facilitating precision medicine in eAML management.