ArticleOncoimmunology2021
Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT.
Article in Oncoimmunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.
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Who cites it
38 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.
- Utilizing Deep Machine Learning for Prognostication of Oral Squamous Cell Carcinoma-A Systematic Review.Frontiers in oral health · 2021Pooled it
- Exploring peripheral immune mechanisms and potential therapeutic drugs for Alzheimer's disease.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Glioma biomarker analysis and drug targeting prediction based on ferroptosis-related genes.Medicine · 2026Article
- Integrative Multiomics and Single-Cell Profiling Identify TNFRSF1AComputational and structural biotechnology journal · 2026Article
- IER3 Promotes Malignant Progression of Colorectal Cancer Through the NF-International journal of genomics · 2026Article
- Mitophagy-related molecular signatures in ulcerative colitis revealed by machine learning and molecular dynamics.Frontiers in genetics · 2026Article
- IFI44 Orchestrates an IL-10-Driven M2 Macrophage Program in Breast Cancer: An Immune Prognostic Signature.Breast cancer (Dove Medical Press) · 2026Article
- Lactate-related biomarkers in severe acute pancreatitis: insights from machine learning, molecular dynamics, and experimental validation.Journal of biological engineering · 2025Article
- MS4A1 regulates M1-polarized tumor-associated macrophage infiltration, angiogenesis, and cancer progression through the HIPPO pathway in lung adenocarcinoma.Cancer immunology, immunotherapy : CII · 2025Article
- Identification of key biomarkers and immune microenvironment features in gliomas based on single-cell analysis combined with bioinformatics.Discover oncology · 2025Article
- Bladder cancer biomarker analysis and drugtarget prediction based on pyroptosis-related genes.Discover oncology · 2025Article
- Identification of ferroptosis-related genes and potential drugs in osteoarthritis.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Article
- Exploring the molecular mechanisms of subarachnoid hemorrhage and potential therapeutic targets: insights from bioinformatics and drug prediction.Scientific reports · 2025Article
- Exploring the mechanisms of PANoptosis in osteoarthritis and the therapeutic potential of andrographolide through bioinformatics and single-cell analysis.Biology direct · 2025Article
- Deep structured learning with vision intelligence for oral carcinoma lesion segmentation and classification using medical imaging.Scientific reports · 2025Article
- Artificial Intelligence in Oral Cancer: A Comprehensive Scoping Review of Diagnostic and Prognostic Applications.Diagnostics (Basel, Switzerland) · 2025Review
- Comprehensive assessment of cellular senescence in intestinal immunity and biologic therapy response in ulcerative colitis.Scientific reports · 2024Article
- SCC-NET: segmentation of clinical cancer image for head and neck squamous cell carcinoma.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Comprehensive evaluation of disulfidptosis in intestinal immunity and biologic therapy response in Ulcerative Colitis.Heliyon · 2024Article
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Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs). Here, a clustering method was performed using CIBERSORT profiles of ORCA data that were filtered from the publicly accessible data of patients with head and neck cancer in The Cancer Genome Atlas (TCGA) using hierarchical clustering where patients were regrouped into binary risk groups based on the clustering-measuring scores and survival patterns associated with individual groups. Based on this analysis, clinically reasonable differences were identified in 16 out of 22 TIL fractions between groups. A deep neural network classifier was trained using the TIL fraction patterns. This internally validated classifier was used on another individual ORCA dataset from the International Cancer Genome Consortium data portal, and patient survival patterns were precisely predicted. Seven common differentially expressed genes between the two risk groups were obtained. This new approach confirms the importance of TILs in the TME and provides a direction for the use of a novel deep-learning approach for cancer prognosis.
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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.