ArticleCell proliferation2023
An artificial intelligence network-guided signature for predicting outcome and immunotherapy response in lung adenocarcinoma patients based on 26 machine learning algorithms.
Article in Cell proliferation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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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
59 citing papers in PubMed, 65 citations in OpenAlex.
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- Artificial Intelligence in Lung Cancer: From Early Detection to Personalized Therapy.Current oncology reports · 2026Review
- A new era of precision diagnosis and treatment for lung cancer: artificial intelligence-driven multimodal data integration and clinical applications.Cell death & disease · 2026Review
- Application of artificial intelligence in lung cancer diagnosis, therapy, and prognosis.BMC medical genomics · 2026Review
- Three-dimensional multimodal imaging for predicting early recurrence of hepatocellular carcinoma after surgical resection.Journal of advanced research · 2026Article
- Review
- Temporal dynamics in cancer immunotherapy: the interplay between circadian rhythms, tumor microenvironment, and immune checkpoint blockade.Journal of the National Cancer Center · 2026Review
- Integrative single-cell and machine-learning analysis identifies acBMC cancer · 2026Article
- Single-cell RNA sequencing analysis revealed a potential association between ELK3 expression and the progression of multiple myeloma.Frontiers in immunology · 2026Article
- Integrative analysis of scRNA-seq and bulk RNA-seq with machine learning develops a nucleotide metabolism-based prognostic model for ccRCC and reveals the function of IFI30.Frontiers in oncology · 2026Article
- Plying potency assays for immunotherapy of solid tumors.Frontiers in immunology · 2026Review
- Machine learning and bioinformatics identify and validate membrane protein biomarkers for type 2 diabetes mellitus.Frontiers in endocrinology · 2026Article
- The Current Research Landscape on Integrating Artificial Intelligence with Ultrasound Imaging for Cancer Diagnosis: A Dual-Database Bibliometric Study.Current medicinal chemistry · 2026Article
- Computational approaches to druggable site identification: Current status and future perspective.Acta pharmaceutica Sinica. B · 2026Review
- Systematic Pathway Screening via Integrated Machine Learning Identifies FOXO-Mediated Transcription Signature for Robust Immunotherapy Response Prediction in Non-Small Cell Lung Cancer.Human mutation · 2026Article
- Metabolic reprogramming signature predicts immunotherapy efficacy in lung adenocarcinoma: TargetingChinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2025Article
- A novel risk model incorporating 4 mitochondrial unfolded protein response-related genes to predict the prognosis, gene mutation landscape, and immunotherapy response in lung adenocarcinoma.European journal of medical research · 2025Article
- Integrative analysis of angiogenesis-related genes highlights prognostic indicators in colorectal cancer through single-cell sequencing and immune infiltration analysis.Discover oncology · 2025Article
- Review
Corrections and comments
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Authors and funding
17 authors at 6 institutions in 2 countries.
Funding
Abstract
The immune cells play an increasingly vital role in influencing the proliferation, progression, and metastasis of lung adenocarcinoma (LUAD) cells. However, the potential of immune cells' specific genes-based model remains largely unknown. In the current study, by analysing single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data, the tumour-infiltrating immune cell (TIIC) associated signature was developed based on a total of 26 machine learning (ML) algorithms. As a result, the TIIC signature score could predict survival outcomes of LUAD patients across five independent datasets. The TIIC signature score showed superior performance to 168 previously established signatures in LUAD. Moreover, the TIIC signature score developed by the immunofluorescence staining of the tissue array of LUAD patients showed a prognostic value. Our research revealed a solid connection between TIIC signature score and tumour immunity as well as metabolism. Additionally, it has been discovered that the TIIC signature score can forecast genomic change, chemotherapeutic drug susceptibility, and-most significantly-immunotherapeutic response. As a newly demonstrated biomarker, the TIIC signature score facilitated the selection of the LUAD population who would benefit from future clinical stratification.
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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.