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

Genome‐scale analysis to identify prognostic markers and predict the survival of lung adenocarcinoma

13 Aug 2018

Abstract excerpt

Lung cancer is one of the most malignant cancers worldwide, and lung adenocarcinoma (LAC) remains the most common histologic subtype. However, the functional significance of RNA expression-based prognosis prediction in LAC is still unclear and needs to be further studied. By utilizing the Cox multivariate regression, we established a risk score staging system to predict the outcome of patients with LAC and...

Read the complete abstract on PubMed

Topics

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

Share to Cancer-related molecular mechanisms research
Share to Lung Cancer Treatments and Mutations
Share to RNA modifications and cancer

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 30105759
DOI: 10.1002/jcb.27144

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

Genome‐scale analysis to identify prognostic markers and predict the survival of lung adenocarcinomaPMID 30105759Read ↗

A 5-mRNA-Based Prognostic Signature of Survival in Lung AdenocarcinomaSemantic proximity Read ↗

Analysis of genomic and transcriptomic variations as prognostic signature for lung adenocarcinomaSemantic proximity Read ↗

Genome-Wide Analysis of Lung Adenocarcinoma Identifies Novel Prognostic Factors and a Prognostic ScoreSemantic proximity Read ↗

Twenty-gene-based prognostic model predicts lung adenocarcinoma survivalSemantic proximity Read ↗

Systematical identifications of prognostic meaningful lung adenocarcinoma subtypes and the underlying mutational and expressional characters.Semantic proximity Read ↗

The identification of key biomarkers in patients with lung adenocarcinoma based on bioinformaticsSemantic proximity Read ↗

Identification of significant genes as prognostic markers and potential tumor suppressors in lung adenocarcinoma via bioinformatical analysisSemantic proximity Read ↗

A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)Semantic proximity Read ↗

A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards modelSemantic proximity Read ↗

The establishment of a prognostic model based on bioinformatic analysis of DNA damage repair genes in lung adenocarcinomaSemantic proximity Read ↗

Identification key genes, key miRNAs and key transcription factors of lung adenocarcinomaSemantic proximity Read ↗

Establishment of a Gene Signature to Predict Prognosis for Patients with Lung AdenocarcinomaSemantic proximity Read ↗

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