ArticleHeliyon2022
Comprehensive analysis of chemokines family and related regulatory ceRNA network in lung adenocarcinoma.
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Identification of EGR2 and TGFB1 as Potential Immunoregulatory Biomarkers for Allergic Rhinitis: An Exploratory Bioinformatics and Pilot Validation Study.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Bioinformatics analysis of macrophage-associated genes reveals prognostic signatures and immune landscape in gastric cancer.Discover oncology · 2025Article
- BHCox: Bayesian heredity-constrained Cox proportional hazards models for detecting gene-environment interactions.BMC bioinformatics · 2025Article
- Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung adenocarcinoma (LUAD) is one of the world's commonest malignancies with a high fatality rate. Chemokines not only regulate immune response but also participate in tumor development and metastasis and yet the mechanism of chemokines in LUAD remains unclear. In this study, transcriptional expression profiles, mutation data, and copy number variation data were downloaded from The Cancer Genome Atlas (TCGA). Risk gene protein expression was assessed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (HPA). Gene Expression Omnibus (GEO) data was used to validate the prognostic model. We summarized the genetic mutation variation landscape of chemokines. The risk prognosis model was developed based on differentially expressed chemokines, and patients in the high-risk score (RS) group had lower survival rates. Gene Set Enrichment Analysis (GSEA) revealed that high-RS patients were associated with metabolic transformation pathways, while low-RS patients were associated with immune-related pathways. Compared with the high-RS group, the low-RS group had higher immune/stromal/estimate scores calculated by the ESTIMATE package. The proportion of immune cells obtained using the CIBERSORT package was significantly different between the two groups. Most of the immune checkpoints were highly expressed in low-RS samples. Finally, we discovered that the lncRNA MIR17HG/AC009299.3/miR-21-5p/CCL20 regulatory network might be crucial in the pathogenesis of LUAD. In conclusion, we developed a risk signature and chemokine-related competing endogenous RNA (ceRNA) network.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.