Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Prediction of Lymph Node Metastasis in Patients with Bladder Cancer Using Whole Transcriptome Gene Expression Signatures

30 Apr 2016

Abstract excerpt

PURPOSE: Clinical staging in patients with muscle invasive bladder cancer misses up to 25% of lymph node metastasis. These patients are at high risk for disease recurrence and improved clinical staging is critical to guide management. MATERIALS AND METHODS: Whole transcriptome expression profiles were generated in 199 patients who underwent radical cystectomy and extended pelvic lymph node dissection. The cohort...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Bladder and Urothelial Cancer Treatments
Share to Cancer-related molecular mechanisms research
Share to Ferroptosis and cancer prognosis

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Source

Identifiers

PMID: 27105761
DOI: 10.1016/j.juro.2016.04.061

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 10 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Prediction of Lymph Node Metastasis in Patients with Bladder Cancer Using Whole Transcriptome Gene Expression SignaturesPMID 27105761Read ↗

Novel Gene expression-based Risk Stratification tool predicts recurrence in Non-muscle invasive Bladder cancerSemantic proximity Read ↗

Long non-coding RNAs to predict postoperative recurrence in muscle-invasive bladder cancer and to develop a new molecular classification systemSemantic proximity Read ↗

Novel Gene expression-based Risk Stratification tool predicts recurrence in Non-muscle invasive Bladder cancerSemantic proximity Read ↗

Novel Biomarkers for Lymph Node Metastasis and Prognosis of Bladder Cancer by Bioinformatics AnalysisSemantic proximity Read ↗

Evaluation of gene expression-based predictors of lymph node metastasis in bladder cancerSemantic proximity Read ↗

Integrating transcriptomics, single-cell omics, and deep learning-based histopathological features to identify OLFML3 as in bladder cancerSemantic proximity Read ↗

Development of a Multiplex Quantitative PCR Signature to Predict Progression in Non–Muscle-Invasive Bladder CancerSemantic proximity Read ↗

Prediction of Stage, Grade, and Survival in Bladder Cancer Using Genome-wide Expression Data: A Validation StudySemantic proximity Read ↗

Development and Validation of a Prognostic Nomogram Model for Recurrence of Non-Muscle Invasive Bladder CancerSemantic proximity Read ↗

Predictive value of progression-related gene classifier in primary non-muscle invasive bladder cancerSemantic proximity Read ↗

Loss of GAS5 tumour suppressor lncRNA: an independent molecular cancer biomarker for short-term relapse and progression in bladder cancer patientsSemantic proximity Read ↗

Use of Artificial Intelligence and Machine Learning Algorithms with Gene Expression Profiling to Predict Recurrent Nonmuscle Invasive Urothelial Carcinoma of the BladderSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.