98%
921
2 minutes
20
The vital copy number variation (CNV) plays a crucial role in clear cell renal cell carcinoma (ccRCC). MPDZ inhibit cell polarity associate with osmotic pressure response and cancer-related biological processes. In order to clarify the role of the CNV of in the progression of ccRCC, we analyzed the CNV and expression of and prognosis in ccRCC patients from The Cancer Genome Atlas data portal. Notably, we found that the deletion of was the common CNV, which was present in 28.65% of ccRCC patients. With the development of tumors, the percentage of deletion increased significantly (19.38% in stage I; 20.00% in stage II; 40.94% in stage III; and 45.00% in stage IV). The deletion of significantly increased ccRCC risk (P=0.0025). Low expression associated with its deletion was significantly associated with adverse outcomes in ccRCC patients (P=0.0342). Furthermore, immunohistochemical analysis by tissue microarray showed that MPDZ was expressed at lower levels in tumor tissues compared with adjacent tissues (P<0.01). Kaplan-Meier survival curves showed that ccRCC patients with low MPDZ expression had significantly shorter survival than those with high MPDZ expression (P=0.002). These results indicated that low MPDZ expression associated with CNV is a potential biomarker for the prognosis of ccRCC patients.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5667992 | PMC |
http://dx.doi.org/10.18632/oncotarget.20220 | DOI Listing |
Cancer Med
September 2025
Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia.
Background: Patients with clear cell renal cell carcinoma (ccRCC) often undergo organ resection, with treatment strategies based on recurrence risk. Current metastatic potential assessments rely on the WHO/ISUP grading system, which is subject to interobserver variability.
Methods: We developed an artificial intelligence (AI) model to classify cells according to contemporary grading rules and evaluated the prognostic significance of tumor cell profiles, particularly focusing on cells with prominent nucleoli.
Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer and is associated with poor prognosis in advanced stages. This study aims to develop a prognostic model for patients with ccRCC based on a lysosome-related gene signature.
Methods: The clinical and transcriptomic data of Kidney Renal Clear Cell Carcinoma (KIRC) patients were downloaded from TCGA, cBioportal and GEO databases, and lysosome-related gene sets were acquired in the previous study.
Front Immunol
September 2025
Department of Urology, Graduate School of Medicine, Juntendo University, Tokyo, Japan.
Background: Immune checkpoint inhibitors (ICIs) are a cornerstone of systemic therapy for clear cell renal cell carcinoma (ccRCC), yet response rates remain variable and predictive biomarkers are lacking. This study aimed to determine whether baseline levels of myeloid-derived suppressor cells (MDSCs), especially monocytic (M-MDSC) and polymorphonuclear (PMN-MDSC) subtypes, could predict ICI response in ccRCC patients.
Methods: In this prospective cohort study, 20 ccRCC patients receiving ICI-based therapy for at least 3 months were enrolled.
Oncol Lett
November 2025
Service of Immunology, University Hospital 'José Eleuterio González', Autonomous University of Nuevo León, Monterrey, Nuevo León 64460, Mexico.
Clear cell renal cell carcinoma (ccRCC) is a neoplastic disease associated with poor prognosis. Localized disease is successfully treated with nephrectomy; however, advanced disease often requires the combined use of immunotherapy and targeted therapy. To the best of our knowledge, there is no validated method to predict immunotherapy response and there is a lack of knowledge regarding the expression kinetics of exhaustion receptors in the early stages of ccRCC.
View Article and Find Full Text PDFOncol Lett
November 2025
Department of Radiology, Zibo Central Hospital, Zibo, Shandong 255020, P.R. China.
Clear cell renal cell carcinoma (ccRCC) is a malignant tumor, originating from the renal epithelium, and accounts for ~85% of RCC cases. The present study aimed to validate the efficacy of an MRI deep learning (DL) model to preoperatively predict the pathological grading of ccRCC. Therefore, a DL algorithm was constructed and trained using diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) sequence images.
View Article and Find Full Text PDF