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

Comprehensive Analysis of a Nine-Gene Signature Related to Tumor Microenvironment in Lung Adenocarcinoma

1 Sept 2021

Abstract excerpt

Lung adenocarcinoma (LUAD) is the most common malignancy, leading to more than 1 million related deaths each year. Due to low long-term survival rates, the exploration of molecular mechanisms underlying LUAD progression and novel prognostic predictors is urgently needed to improve LUAD treatment. In our study, cancer-specific differentially expressed genes (DEGs) were identified using the robust rank aggregation...

Topics

Join the communities discussing this publication.

Cancer-related molecular mechanisms research
Ferroptosis and cancer prognosis
RNA modifications and cancer

Source

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Identifiers

PMID: 34540825
DOI: 10.3389/fcell.2021.700607

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 1 Sept 2026.

Community interpretation

Discuss the evidence

Ask a question, add context or challenge an interpretation. Community activity is separate from scientific evidence strength.

0

discussions

0

replies

Citations encouraged

Claims remain attributable.

No discussion yet

Be the first to add a careful, cited interpretation.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Comprehensive Analysis of a Nine-Gene Signature Related to Tumor Microenvironment in Lung AdenocarcinomaPMID 34540825Read ↗

Identification of a Four-Gene Signature Associated with the Prognosis Prediction of Lung Adenocarcinoma Based on Integrated Bioinformatics AnalysisSemantic proximity Read ↗

Identification of novel gene signature for lung adenocarcinoma by machine learning to predict immunotherapy and prognosisSemantic proximity Read ↗

Seven-gene biomarkers reveal prognostic and immune signatures in lung adenocarcinomaSemantic proximity Read ↗

Identification of a Novel Tumor Microenvironment–Associated Eight-Gene Signature for Prognosis Prediction in Lung AdenocarcinomaSemantic proximity Read ↗

Identification of pivotal genes with prognostic evaluation value in lung adenocarcinoma by bioinformatics analysisSemantic proximity Read ↗

Analysis of prognostic model based on immunotherapy related genes in lung adenocarcinomaSemantic proximity Read ↗

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

Development and Validation of a Seven‐Gene Signature for Predicting the Prognosis of Lung AdenocarcinomaSemantic proximity Read ↗

A Novel Inflammatory-Related Gene Signature Based Model for Risk Stratification and Prognosis Prediction in Lung AdenocarcinomaSemantic proximity Read ↗

Development and Validation of a 23-Gene Signature for Prognosis Prediction in Lung AdenocarcinomaSemantic proximity Read ↗

A risk model including eight tumor microenvironment-related genes for prediction of lung cancer prognosisSemantic proximity Read ↗

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

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