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

Co-Expression Network Analysis Identified Genes Associated with Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma

26 Nov 2019

Abstract excerpt

Objective: Cancer stem cells are self-renewal cells in tumors and can produce heterogeneous tumor cells, which play an important role in the development of lung squamous cell carcinoma (LSCC). In our research, we aimed to explore the expression of genes related to LSCC stem cells.Methods: We downloaded the RNAseq data, the pathological and prognostic profiles of LSCC cases from the public database TCGA. The mRNA...

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 Ferroptosis and cancer prognosis
Share to MicroRNA in disease regulation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 31770041
DOI: 10.1080/07357907.2019.1697281

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Co-Expression Network Analysis Identified Genes Associated with Cancer Stem Cell Characteristics in Lung Squamous Cell CarcinomaPMID 31770041Read ↗

mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell BiomarkersSemantic proximity Read ↗

Weighted Gene Coexpression Network Analysis of Features That Control Cancer Stem Cells Reveals Prognostic Biomarkers in Lung AdenocarcinomaSemantic proximity Read ↗

Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung AdenocarcinomaSemantic proximity Read ↗

Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell CarcinomaSemantic proximity Read ↗

Comprehensive analysis of transcriptome data stemness indices identifies key genes for controlling cancer stem cell characteristics in gastric cancerSemantic proximity Read ↗

scRNA-seq revealed high stemness epithelial malignant cell clusters and prognostic models of lung adenocarcinomaSemantic proximity Read ↗

Protein Co-expression Network-based Profiles Revealed from Laser-microdissected Cancerous Cells of Lung Squamous-Cell CarcinomasSemantic proximity Read ↗

Identifying key transcription factors and immune infiltration in non-small-cell lung cancer using weighted correlation network and Cox regression analysesSemantic proximity Read ↗

Bioinformatics role of the WGCNA analysis and co-expression network identifies of prognostic marker in lung cancerSemantic proximity Read ↗

Weighted Gene Co-expression Network Analysis Identifies a Cancer-Associated Fibroblast Signature for Predicting Prognosis and Therapeutic Responses in Lung Squamous Cell CarcinomaSemantic proximity Read ↗

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)Semantic proximity Read ↗

A cancer stemness-related eight-gene signature for predicting prognosis and malignant degree of lung adenocarcinomaSemantic proximity Read ↗

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