PubMed Health⌕ Search

PubMed · 11114594

Radical prostatectomy: options and issues.

Abstract

Radical prostatectomy is an effective treatment for patients with clinically localized prostate cancer and is associated with a very low level of mortality. However, many men with untreated clinically localized prostate cancer do not die from the disease and, following radical prostatectomy, some patients will suffer from a loss of potency and/or incontinence. A major challenge faced by the clinician is to identify the individual patient who will benefit from radical prostatectomy. In this review, we discuss the natural history of clinically localized prostate cancer and the factors likely to affect the treatment decision for an individual patient. Recent studies by other investigators and ourselves have revealed that the T1/T2 tumour is heterogeneous with respect to pathological stage and outcome, and that the quantity of Gleason grade 4/5 tumour is a significant prognostic factor predicting lymph node progression and capsular penetration. Classification and Regression Trees (CART) analysis including such preoperative parameters can be used to predict the probability of an individual patient having a pT2 tumour and, therefore, whether he could have a nerve-sparing radical prostatectomy - a procedure which offers better outcomes in terms of potency and continence.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

H Huland. 2001. Radical prostatectomy: options and issues.. https://doi.org/10.1159/000052543

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗