ArticleJournal of translational medicine2025
Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Multi-Omics and Machine Learning Identify Immune-Linked Gene Signatures for LUAD Stratification.Genes · 2026Article
- A nucleolar stress gene signature enables quantitative scoring across multi-omics contexts.Communications biology · 2026Article
- Bulk and single-cell transcriptomics reveal prognostic signatures of phosphoinositide metabolism in lung adenocarcinoma.Scientific reports · 2026Article
- KIF23 in disease pathogenesis and its therapeutic and diagnostic potential.Discover oncology · 2026Review
- Multi-omics integration identifies ribosome biogenesis-active macrophage subpopulation and its key gene GNL2 in driving liver hepatocellular carcinoma progression and mechanisms.Cancer cell international · 2026Article
- Characterization of telomere-related gene subtypes in lung adenocarcinoma and their implications for prognosis and treatment.Discover oncology · 2026Article
- LUADnet: a deep learning model for prediction of clinical outcomes in lung adenocarcinoma based on gene expression signatures.Translational lung cancer research · 2026Article
- Construction and validation of a palmitoylation-related prognostic model for lung adenocarcinoma based on integrated bioinformatics and machine learning.Translational cancer research · 2026Article
- Deciphering immune heterogeneity in lung adenocarcinoma via machine learning-based Differential Phenotype Immune Score: TPX2 as a key biomarker for immunotherapy resistance.Frontiers in immunology · 2026Article
- Spatial omics for profiling the dynamic tumor microenvironment.Clinical & translational immunology · 2026Review
- PTGER4 Governs Immune Evasion and Therapy Resistance in Kidney Cancer via Ribosome Biogenesis Dysregulation.Journal of cellular and molecular medicine · 2025Article
- Establishing a glycolysis-linked multigene prognostic signature in lung adenocarcinoma: a multicenter integrative approach.Journal of thoracic disease · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundLung adenocarcinoma (LUAD) presents a considerable danger to human health and has evolved into a major public health concern. Ribosome biogenesis (RiboSis) is a critical process for synthesizing ribosomes, closely associated with cancer initiation, progression, and treatment resistance, potentially serving as a target for future cancer therapies.
methodsUtilizing single-cell RNA sequencing (scRNA-seq) technology, a single-cell atlas of LUAD was delineated, focusing on the analysis of T cell subpopulations. Cells were scored based on the expression patterns of 331 genes associated with RiboSis across different cell types, and monocle2 was employed to analyze the developmental trajectory of CD4
resultsUsing single-cell analysis, two distinct T cell subtypes were identified: CD8
conclusionThis study delves into the relationship between RiboSis and LUAD cell subpopulations, identifying a potent prognostic biomarker for LUAD. This biomarker aids in assessing immunotherapy efficacy in LUAD patients, ultimately enhancing their prognosis and guiding clinical decision-making.
Indexed as
Identifiers
What Socratic 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 Socratic graph.