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Kidney renal clear cell carcinoma (KIRC) is a cancer that is closely associated with epigenetic alterations, and histone modifiers (HMs) are closely related to epigenetic regulation. Therefore, this study aimed to comprehensively explore the function and prognostic value of HMs-based signature in KIRC. HMs were first obtained from top journal. Then, the mRNA expression profiles and clinical information in KIRC samples were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. Cox regression analysis and least absolute shrinkage and selection operator (Lasso) analysis were implemented to find prognosis-related HMs and construct a risk model related to the prognosis in KIRC. Kaplan-Meier analysis was used to determine prognostic differences between high- and low-risk groups. Immune infiltration and drug sensitivity analysis were also performed between high- and low-risk groups. Eventually, 8 HMs were successfully identified for the construction of a risk model in KIRC. The results of the correlation analysis between risk signature and the prognosis showed HMs-based signature has good prognostic value in KIRC. Results of immune analysis of risk models showed there were significant differences in the level of immune cell infiltration and expression of immune checkpoints between high- and low-risk groups. The results of the drug sensitivity analysis showed that the high-risk group was more sensitive to several chemotherapeutic agents such as Sunitinib, Tipifarnib, Nilotinib and Bosutinib than the low-risk group. In conclusion, we successfully constructed HMs-based prognostic signature that can predict the prognosis of KIRC.
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http://dx.doi.org/10.18632/aging.205944 | DOI Listing |
J Cyst Fibros
September 2025
Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Oregon Health and Science University, Portland, OR, USA.
Recent improvements in cell-free DNA technology have enabled non-invasive prenatal testing (NIPT) to screen for fetal single-gene autosomal recessive conditions from maternal blood as early as the first trimester. This technique can determine the fetal risk for cystic fibrosis (CF) with a single blood sample from a pregnant person without the need for a partner sample, which is required for traditional carrier screening. A retrospective review of 100,106 consecutive general-risk pregnant patients who underwent CF carrier screening was completed.
View Article and Find Full Text PDFJ Dent
September 2025
Department of Endodontics, Recep Tayyip Erdogan University, Turkey. Electronic address:
Objectives: To assess patterns across 21 countries in dentists' thresholds for initiating operative treatment of active non-cavitated carious lesions and to evaluate the influence of caries risk, clinician characteristics, and geographic variation on decision-making in accordance with current guidelines.
Methods: A cross-sectional, vignette-style web-based survey was conducted between June and October 2023 across 21 countries. A standardized questionnaire, comprising theoretical radiographic scenarios of occlusal and approximal active non-cavitated carious lesions at four progressive stages (E1,E2,EDJ,D1), was distributed to general dentists and specialists.
Int J Obstet Anesth
September 2025
Westmead Hospital Department of Anaesthesia and Perioperative Medicine, Westmead, Australia.
Background: Maternal cardiovascular disease (CVD) is a leading cause of maternal mortality. Data on anaesthetic management in patients with CVD is limited.
Methods: This ten-year retrospective cohort study of 508 pregnancies in women with CVD, stratified by modified World Health Organization (mWHO) risk category, compared lowrisk (mWHO I-II) (n = 323) and high-risk (mWHO II to III-IV) (n = 185) groups to a control obstetric population (n = 55,153).
Gastric Cancer
September 2025
Department of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Background: Immune checkpoint inhibitors (ICIs) play a pivotal role in the treatment of advanced gastric cancer (GC). However, the biomarkers used to predict ICI efficacy are limited due to their reliance on single or static tumor characteristics. This study aims to develop a machine learning (ML) model that incorporates dynamic changes in clinlabomics data to optimize the predictive accuracy of ICI efficacy.
View Article and Find Full Text PDFAcad Radiol
September 2025
Department of Urology, the Second Affiliated Hospital of Kunming Medical University, Kunming, China (H.S., Q.W., S.F., H.W.). Electronic address:
Rationale And Objectives: This study systematically evaluates the diagnostic performance of artificial intelligence (AI)-driven and conventional radiomics models in detecting muscle-invasive bladder cancer (MIBC) through meta-analytical approaches. Furthermore, it investigates their potential synergistic value with the Vesical Imaging-Reporting and Data System (VI-RADS) and assesses clinical translation prospects.
Methods: This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.