ArticleTranslational lung cancer research2025
Multi-omics and Mendelian randomization identify
Article in Translational lung cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Decoding the S1P-S1PR axis in cancer: Mechanisms, pathways and therapeutic horizons (Review).Biomedical reports · 2026Review
- Single-cell atlas reveals a pro-metastatic RELB+ neutrophil-myeloid subset underlying lymph node metastasis in EGFR-wildtype LUAD.Frontiers in cell and developmental biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lung adenocarcinoma (LUAD) sustains an immunosuppressive tumor microenvironment (TME) via stromal-immune interactions. Efferocytosis regulates immune suppression and tissue homeostasis, yet biomarkers stratifying its TME states are lacking in LUAD, hindering precision therapy. This study aimed to investigate efferocytosis-associated immune regulation with both causal and prognostic relevance in LUAD, and to identify key biomarkers with potential implications for tumor stratification and therapeutic guidance. Methods: Gene expression profiles from The Cancer Genome Atlas (TCGA) LUAD cohort and Genotype-Tissue Expression (GTEx) underwent differential expression analysis. Efferocytosis-related genes (ERGs) from GeneCards were intersected to identify LUAD-associated candidates. Mendelian randomization (MR) and colocalization evaluated causal ERG-LUAD relationships. Risk-related ERGs were systematically analyzed for expression, biological functions, prognosis, and immune interactions. Single-cell RNA sequencing (scRNA-seq) mapped cellular expression specificity of core ERGs. Machine learning prognostic models ( Results: Conclusions:
Indexed as
Identifiers
What OpenQuestion holds
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.