ArticleBiomolecules2020
Uncovering Prognosis-Related Genes and Pathways by Multi-Omics Analysis in Lung Cancer.
Article in Biomolecules, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review.Journal of medical systems · 2024Pooled it
- Identification of Clinically Relevant Genes Using Machine Learning Techniques.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Identification of potential molecular targets for thyroid cancer using multiple-omics analysis and machine learning.Annals of medicine and surgery (2012) · 2025Article
- Synthesis and Biological Evaluation of Herceptin-Conjugated Liposomes Loaded with Lipocalin-2 siRNA for the Treatment of Inflammatory Breast Cancer.Pharmaceuticals (Basel, Switzerland) · 2025Article
- A comprehensive review of cancer survival prediction using multi-omics integration and clinical variables.Briefings in bioinformatics · 2025Review
- Establishment of a machine learning model for predicting splenic hilar lymph node metastasis.NPJ digital medicine · 2025Article
- Current status and future direction of cancer research using artificial intelligence for clinical application.Cancer science · 2025Review
- Analysis of Inertial Measurement Unit Data for an AI-Based Physical Function Assessment System Using In-Clinic-like Movements.Bioengineering (Basel, Switzerland) · 2024Article
- Introduction of AI Technology for Objective Physical Function Assessment.Bioengineering (Basel, Switzerland) · 2024Review
- A machine learning and deep learning-based integrated multi-omics technique for leukemia prediction.Heliyon · 2024Article
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- Proteomic associations with forced expiratory volume: a Mendelian randomisation study.Respiratory research · 2024Article
- Identification of tumor heterogeneity associated with KRAS/TP53 co-mutation status in lung adenocarcinoma based on single-cell RNA sequencing.American journal of cancer research · 2024Article
- What is circulating factor disease and how is it currently explained?Pediatric nephrology (Berlin, Germany) · 2023Review
- Autoencoder-based multimodal prediction of non-small cell lung cancer survival.Scientific reports · 2023Article
- Integration of IDPC Clustering Analysis and Interpretable Machine Learning for Survival Risk Prediction of Patients with ESCC.Interdisciplinary sciences, computational life sciences · 2023Article
- Analysis of super-enhancer using machine learning and its application to medical biology.Briefings in bioinformatics · 2023Review
- Article
- Aberrant Expression and Prognostic Potential of IL-37 in Human Lung Adenocarcinoma.Biomedicines · 2022Article
- Introducing AI to the molecular tumor board: one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information.Experimental hematology & oncology · 2022Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Lung cancer is one of the leading causes of death worldwide. Therefore, understanding the factors linked to patient survival is essential. Recently, multi-omics analysis has emerged, allowing for patient groups to be classified according to prognosis and at a more individual level, to support the use of precision medicine. Here, we combined RNA expression and miRNA expression with clinical information, to conduct a multi-omics analysis, using publicly available datasets (the cancer genome atlas (TCGA) focusing on lung adenocarcinoma (LUAD)). We were able to successfully subclass patients according to survival. The classifiers we developed, using inferred labels obtained from patient subtypes showed that a support vector machine (SVM), gave the best classification results, with an accuracy of 0.82 with the test dataset. Using these subtypes, we ranked genes based on RNA expression levels. The top 25 genes were investigated, to elucidate the mechanisms that underlie patient prognosis. Bioinformatics analyses showed that the expression levels of six out of 25 genes (
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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.