Results 21 to 30 of about 73,736 (149)
Using mass cytometry, we analyzed serial blood samples from patients with relapsed epithelial ovarian cancer (EOC) treated with oleclumab–durvalumab combination immunotherapy in the NSGO‐OV‐UMB1/ENGOT‐OV30 trial. Our analysis identified potential predictive, monitoring, and response biomarkers detectable through liquid biopsy. These findings facilitate
Luka Tandaric+11 more
wiley +1 more source
Epithelial–mesenchymal transition (EMT) and tumor‐infiltrating lymphocytes (TILs) are associated with early breast cancer response to neoadjuvant chemotherapy (NAC). This study evaluated EMT and TIL shifts, with immunofluorescence and RNA sequencing, at diagnosis and in residual tumors as potential biomarkers associated with treatment response.
Françoise Derouane+16 more
wiley +1 more source
CircCCNB1 expression is down‐regulated in nasopharyngeal carcinoma (NPC); thus, less NF90 protein is bound to circCCNB1 and more binds to pri‐miRNAs, blocking their (pri‐miRNAs) binding to DGCR8 and inhibiting the processing and generation of miR‐15b‐5p/miR‐7‐1‐3p. Furthermore, decreased miR‐15b‐5p/miR‐7‐1‐3p promotes the expression of the target genes
Chunmei Fan+6 more
wiley +1 more source
Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value
The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song+13 more
wiley +1 more source
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes+20 more
wiley +1 more source
Abstract Purpose Training deep learning dose prediction models for the latest cutting‐edge radiotherapy techniques, such as AI‐based nodal radiotherapy (AINRT) and Daily Adaptive AI‐based nodal radiotherapy (DA‐AINRT), is challenging due to limited data.
Hui‐Ju Wang+5 more
wiley +1 more source
Abstract Purpose To compare plan quality among photon volumetric modulated arc therapy (VMAT) and intensity‐modulated proton therapy (IMPT) with robustness using three different proton beam delivery systems with various spot size (σ) ranges: cyclotron‐generated proton beams (CPBs) (σ: 2.7–7.0 mm), linear accelerator proton beams (LPBs) (σ: 2.9–5.5 mm),
Tara Gray+9 more
wiley +1 more source
Abstract Purpose This study evaluates the technical feasibility of adapting a surface monitoring system, designed for conventional four‐dimensional computed tomography (4DCT), to an intelligent, breathing‐adapted 4DCT and examines its potential to expand the currently limited range of supported surrogate systems.
Niklas Lackner+4 more
wiley +1 more source
Abstract Background This study aims to develop a novel predictive model for determining human papillomavirus (HPV) presence in oropharyngeal cancer using computed tomography (CT). Current image‐based HPV prediction methods are hindered by high computational demands or suboptimal performance.
Junhua Chen+3 more
wiley +1 more source
Abstract Introduction The use of radioactive materials in the United States has been tightly regulated by the Nuclear Regulatory Commission and other entities for many decades. In 2015, however, the Joint Commission began to require hospital‐based nuclear medicine departments to conduct shielding designs and evaluations for radioactive material areas ...
Michael Oumano+12 more
wiley +1 more source