Molecular profiling of prostate cancer.

Curr Urol Rep

Cancer Prevention Studies Branch, National Cancer Institute/National Institutes of Health, 6116 Executive Blvd., Suite 705, Rockville, MD 20852, USA.

Published: February 2004

The ability to distinguish between aggressive and nonaggressive tumors has not changed despite vast improvements in the detection of prostate cancer (PCA). To improve predictive accuracy, additional PCA-specific biomarkers must be identified and it is the emerging microarray technology and gene expression profiling that appear to be capable of achieving this goal. Through comparisons of a number of published microarray studies of PCA, several potential biomarkers appear on the horizon, including the serine protease Hepsin, a-methylacyl CoA racemase, and the human homologue of the Drosophila protein Enhancer of Zeste. Although these markers will move toward validation by eventual protein expression studies, another aspect of microarray expression, global signature expression patterns through multidimensional scaling, appears to be promising in distinguishing between aggressive and nonaggressive forms of PCA or in distinguishing PCA from benign prostatic hyperplasia or normal prostate tissue.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11934-004-0011-0DOI Listing

Publication Analysis

Top Keywords

prostate cancer
8
aggressive nonaggressive
8
molecular profiling
4
profiling prostate
4
cancer ability
4
ability distinguish
4
distinguish aggressive
4
nonaggressive tumors
4
tumors changed
4
changed despite
4

Similar Publications

Background: Cancers of the bladder, kidney, and prostate are the 3 major genitourinary cancers that significantly contribute to the global burden of disease (GBD) and continue to show increasing rates of morbidity and mortality worldwide. In mainland China, understanding the cancer burden on patients and their families is crucial; however, public awareness and concerns about these cancers, particularly from the patient's perspective, remain predominantly focused on financial costs. A more comprehensive exploration of their needs and concerns has yet to be fully addressed.

View Article and Find Full Text PDF

Dynamic contrast-enhanced ultrasound (DCEUS) is an imaging modality for assessing microvascular perfusion and dispersion kinetics. However, the presence of speckle noise may hamper the quantitative analysis of the contrast kinetics. Common speckle denoising techniques based on low-rank approximations typically model the speckle noise as white Gaussian noise (WGN) after the log transformation and apply matrix-based algorithms.

View Article and Find Full Text PDF

Our study aimed to examine the predictive relevance of the Systemic Immune-Inflammation Index (SII) in patients with metastatic castration-resistant prostate cancer (mCRPC). A total of 113 mCRPC patients were assessed. In this descriptive study, SII was calculated using the formula (neutrophil count × platelet count)/lymphocyte count.

View Article and Find Full Text PDF

Stable and discriminating OCT-derived radiomics features for predicting anti-VEGF treatment response in diabetic macular edema.

Med Phys

March 2025

The Tony and Leona Campane Center for Excellence in Image-Guided Surgery and Advanced Imaging Research, Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio, USA.

Background: Radiomics-based characterization of fluid and retinal tissue compartments of spectral-domain optical coherence tomography (SD-OCT) scans has shown promise to predict anti-VEGF therapy treatment response in diabetic macular edema (DME). Radiomics features are sensitive to different image acquisition parameters of OCT scanners such as axial resolution, A-scan rate, and voxel size; consequently, the predictive capability of the radiomics features might be impacted by inter-site and inter-scanner variations.

Purpose: The main objective of this study was (1) to develop a more generalized classifier by identifying the OCT-derived texture-based radiomics features that are both stable (across multiple scanners) as well as discriminative of therapeutic response in DME and (2) to identify the relative stability of individual radiomic features that are associated with specific spatial compartments (e/g.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!