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

Transcriptomic heterogeneity of driver gene mutations reveals novel mutual exclusivity and improves exploration of functional associations.

Cancer medicine - 1 Jul 2021

Lan Yujia, Liu Wei, Zhang Wanmei, Hu Jing, Zhu Xiaojing, Wan Linyun, A Suru, Ping Yanyan, Xiao Yun

Abstract excerpt

BACKGROUND: Lung adenocarcinoma (LUAD), as the most common subtype of lung cancer, is the leading cause of cancer deaths in the world. The accumulation of driver gene mutations enables cancer cells to gradually acquire growth advantage. Therefore, it is important to understand the functions and interactions of driver gene mutations in cancer progression. METHODS: We obtained gene mutation data and gene expression...

Read the complete abstract on PubMed

Topics

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

Share to Adenocarcinoma of Lung
Share to Databases, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Disease Progression

Share to Gene Expression Profiling

Share to Genetic Heterogeneity

Share to Lung Neoplasms

Share to Mutation

Share to Transcriptome

Source

Open in PubMed Open full text

Identifiers

PMID: 34076361
DOI: 10.1002/cam4.4039
PMCID: PMC8290236

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Transcriptomic heterogeneity of driver gene mutations reveals novel mutual exclusivity and improves exploration of functional associations.PMID 34076361Read ↗

Co-occurrence and mutual exclusivity: what cross-cancer mutation patterns can tell us.Semantic proximity Read ↗

The Discovery of Mutated Driver Pathways in Cancer: Models and Algorithms.Semantic proximity Read ↗

WeSME: uncovering mutual exclusivity of cancer drivers and beyond.Semantic proximity Read ↗

Circuits of cancer drivers revealed by convergent misregulation of transcription factor targets across tumor types.Semantic proximity Read ↗

Analysis of pathway mutation profiles highlights collaboration between cancer-associated superpathways.Semantic proximity Read ↗

Advancing cancer driver gene identification through an integrative network and pathway approach.Semantic proximity Read ↗

Single-Cell Transcriptomic, hdWGCNA, and Machine Learning reveal the Role of DYNLL1 in Lung Adenocarcinoma within Epithelial CellsSemantic proximity Read ↗

Lung Adenocarcinoma Just Desserts: An Expanding Pie of Activating Oncogenes or a Layer Cake of Integrated AlterationsSemantic proximity Read ↗

Detection of driver pathways using mutated gene network in cancer.Semantic proximity Read ↗

Lung adenocarcinomas without driver genes converge to common adaptive strategies through diverse genetic, epigenetic, and niche construction evolutionary pathways.Semantic proximity Read ↗

Identifying Cancer Specific Driver Modules Using a Network-Based Method.Semantic proximity Read ↗

Molecular Heterogeneity Analysis and Prognostic Stratification of Driver-Gene mutated NSCLC Based on Concurrent Alteration ProfilesSemantic proximity Read ↗

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