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

Screening, identification and validation of CCND1 and PECAM1/CD31 for predicting prognosis in renal cell carcinoma patients

18 Dec 2019

Abstract excerpt

. In summary, integrated bioinformatics analysis identified candidate DEGs and pathways in ccRCC that could improve our understanding of the causes and underlying molecular events of ccRCC. These candidate genes and pathways could be therapeutic targets for ccRCC.

Read the complete abstract on PubMed

Topics

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

Share to Ferroptosis and cancer prognosis
Share to Renal and related cancers
Share to Renal cell carcinoma treatment

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 31850854
DOI: 10.18632/aging.102540

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Screening, identification and validation of CCND1 and PECAM1/CD31 for predicting prognosis in renal cell carcinoma patientsPMID 31850854Read ↗

Systematic identification of key genes and pathways in clear cell renal cell carcinoma on bioinformatics analysisSemantic proximity Read ↗

Stage-Wise Gene Expression Profiling Reveals Potential Genes and the Pathways in Kidney CancerSemantic proximity Read ↗

Identification of Key Genes and Pathways in Renal Cell Carcinoma Through Expression Profiling DataSemantic proximity Read ↗

Identification of key genes CCL5, PLG, LOX and C3 in clear cell renal cell carcinoma through integrated bioinformatics analysisSemantic proximity Read ↗

Co-expression network analysis identified FCER1G in association with progression and prognosis in human clear cell renal cell carcinomaSemantic proximity Read ↗

Bioinformatics Analysis of C3 and CXCR4 act as Potential Prognostic Biomarkers in Clear Cell Renal Cell Carcinoma (ccRCC)Semantic proximity Read ↗

Clear Cell Renal Cell Carcinoma: A Comprehensive in silico Study in Searching for Therapeutic TargetsSemantic proximity Read ↗

Identification of the cuproptosis related prognostic gene signature and the associated regulation axis in clear cell renal cell carcinomaSemantic proximity Read ↗

Renal Cell Carcinoma: A Comprehensive in Silico Study in Searching for Therapeutic TargetsSemantic proximity Read ↗

Multi-staged gene expression profiling reveals potential genes and the critical pathways in kidney cancerSemantic proximity Read ↗

Identification of EGFR as a Novel Key Gene in Clear Cell Renal Cell Carcinoma (ccRCC) through Bioinformatics Analysis and Meta-AnalysisSemantic proximity Read ↗

The underlying molecular mechanism and potential drugs for treatment in papillary renal cell carcinoma: A study based on TCGA and Cmap datasetsSemantic proximity Read ↗

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