Purpose: Improved early diagnosis and determination of aggressiveness of prostate cancer (PC) is important to select suitable treatment options and to decrease over-treatment. The conventional marker is total prostate specific antigen (PSA) levels in blood, but lacks specificity and ability to accurately discriminate indolent from aggressive disease.
Experimental Design: In this study, we sought to identify a serum biomarker signature associated with metastatic PC. We measured 157 analytes in 363 serum samples from healthy subjects, patients with non-metastatic PC and patients with metastatic PC, using a recombinant antibody microarray.
Results: A signature consisting of 69 proteins differentiating metastatic PC patients from healthy controls was identified.
Conclusions And Clinical Relevance: The clinical value of this biomarker signature requires validation in larger independent patient cohorts before providing a new prospect for detection of metastatic PC.
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http://dx.doi.org/10.1002/prca.202000025 | DOI Listing |
ACS Nano
January 2025
Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, People's Republic of China.
Identifying effective biomarkers has long been a persistent need for early diagnosis and targeted therapy of disease. While mass spectrometry-based label-free proteomics with trace cell has been demonstrated, deep proteomics with ultratrace human biofluid remains challenging due to low protein concentration, extremely limited patient sample volume, and substantial protein contact losses during preprocessing. Herein, we proposed and validated lanthanide metal-organic framework flowers (MOF-flowers), as effective materials, to trap and enrich protein in biofluid jointly through cation-π interaction and O-Ln coordination.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Department of Gastrointestinal Surgery, Yantai Yuhuangding Hospital, Qingdao University, No. 20 Yuhuangding East Road, Zhifu District, Yantai, 264001, China.
Background: Gastric cancer (GC) remains a significant health burden, calling for the discovery of novel biomarkers. Golgi apparatus, a crucial cellular organelle involved in tumorigenesis, remains underexplored in GC research. A comprehensive understanding of its role and associated mechanisms is urgently needed.
View Article and Find Full Text PDFFuture Oncol
January 2025
Department of Oncology, Daping Hospital, Army Medical University, Chongqing, China.
Esophageal squamous cell carcinoma (ESCC) is a severe malignant tumor of the digestive system that poses a significant threat to human health. Despite its significance, the complex molecular mechanism regulating the occurrence and development of ESCC remain elusive. The apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3 (APOBEC3) members constitute a pivotal subfamily of the APOBEC family that possess cytidine deaminase activity.
View Article and Find Full Text PDFMol Oncol
January 2025
Urologic Oncology Research Group, Cancer Research Program, Research Institute of the McGill University Health Center, Montreal, Canada.
Patient stratification remains a challenge for optimal treatment of prostate cancer (PCa). This clinical heterogeneity implies intra-tumoural heterogeneity, with different prostate epithelial cell subtypes not all targeted by current treatments. We reported that such cell subtypes are traceable in liquid biopsies through representative transcripts.
View Article and Find Full Text PDFFront Mol Biosci
January 2025
Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Background: Emerging evidence underscores the comorbidity mechanisms among autoimmune diseases (AIDs), with innovative technologies such as single-cell RNA sequencing (scRNA-seq) significantly advancing the explorations in this field. This study aimed to investigate the shared genes among three AIDs-Multiple Sclerosis (MS), Systemic Lupus Erythematosus (SLE), and Rheumatoid Arthritis (RA) using bioinformatics databases, and to identify potential biomarkers for early diagnosis.
Methods: We retrieved transcriptomic data of MS, SLE, and RA patients from public databases.
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