ArticleClinical cancer research : an official journal of the American Association for Cancer Research2019
Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non-Small Cell Lung Cancer.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 152 papers, 2 of them syntheses that pooled it.
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Who cites it
152 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prognostic implications of tumor-infiltrating lymphocytes in non-small cell lung cancer: a systematic review and meta-analysis.Frontiers in immunology · 2024Pooled it
- Prognostic value of the common tumour-infiltrating lymphocyte subtypes for patients with non-small cell lung cancer: A meta-analysis.PloS one · 2020Pooled it
- Computationally Derived Spatial Immune Signature Identifies Trastuzumab Responders in HER2+ Breast Cancer: NSABP B-41 Clinical Trial Validation.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Trial
- ShadoNet: a cell detection and classification framework for Ki-67 pathology images.Bioinformatics (Oxford, England) · 2026Article
- Adaptive resistance in cancer immunotherapy.Cellular & molecular immunology · 2026Review
- Pan-cancer 8q24 amplification predicts primary immunotherapy resistance and therapeutic vulnerabilities.iScience · 2026Article
- Computational pathology features of immune architecture predict clinically relevant outcomes in small-cell lung cancer (SCLC).NPJ precision oncology · 2026Article
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- Integrating Genomics, Radiomics, and Pathomics in Oncology: A Scoping Review and a Framework for AI-Enabled Surgomics.Bioengineering (Basel, Switzerland) · 2026Review
- Artificial intelligence in digital pathology diagnosis and analysis: technologies, challenges, and future prospects.Military Medical Research · 2026Review
- A deep learning framework to iDentify prOgnostically releVant cancEr Regions (DOVER) within whole slide histopathology images.Cancer letters · 2026Article
- Reproducibility of digital pathology features extracted from deep learning and foundational AI models on sequential tissue slides.Scientific reports · 2025Article
- Review
- AI-informed computational pathology classifier predicts outcomes across treatment modalities in muscle-invasive urothelial carcinoma.Cancer letters · 2025Article
- Artificial Intelligence in Histopathological Analysis for Predicting Immunotherapy Response in Cutaneous Melanoma.International journal of molecular sciences · 2025Review
- Tumor-Infiltrating Lymphocytes Predict Extranodal Extension and Prognosis in Regionally Advanced Oral Cavity Cancer.Diagnostics (Basel, Switzerland) · 2025Article
- Collagen disorder architecture features are associated with clinical, molecular, genetic factors and survival outcomes in colon cancer.NPJ precision oncology · 2025Article
- Artificial intelligence-based digital pathology using H&E-stained whole slide images in immuno-oncology: from immune biomarker detection to immunotherapy response prediction.Journal for immunotherapy of cancer · 2025Review
- Spatial features of tumor-infiltrating lymphocytes in primary lesions of lung adenocarcinoma predict lymph node metastasis.Journal of translational medicine · 2025Article
92 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors.
Funding
Abstract
purposeThe presence of a high degree of tumor-infiltrating lymphocytes (TIL) has been proven to be associated with outcome in patients with non-small cell lung cancer (NSCLC). However, recent evidence indicates that tissue architecture is also prognostic of disease-specific survival and recurrence. We show a set of descriptors (spatial TIL, SpaTIL) that capture density, and spatial colocalization of TILs and tumor cells across digital images that can predict likelihood of recurrence in early-stage NSCLC. EXPERIMENTAL
designThe association between recurrence in early-stage NSCLC and SpaTIL features was explored on 301 patients across four different cohorts. Cohort D
resultsSpaTIL was associated with likelihood of recurrence in all test sets (log-rank
conclusionsA set of features related to density and spatial architecture of TILs was found to be associated with a likelihood of recurrence of early-stage NSCLC. This information could potentially be used for helping in treatment planning and management of early-stage NSCLC.
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