ArticleNature communications2019
An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
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Who cites it
66 citing papers in PubMed.
- Spatial and Single-Cell Multi-Omics Analyses of T-Cell Subsets and Interactions in Melanoma Lymph Node Metastasis.Experimental dermatology · 2026Review
- Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study.The Lancet. Oncology · 2026Article
- An Open Source Automated Tumor Infiltrating Lymphocytes Algorithm for Prognosis in Primary Small Bowel Adenocarcinoma Using Routine Hematoxylin and Eosin Stained Sections.Cancer medicine · 2026Article
- Targeting TPX2-dependent lineage plasticity by CDK4/6 inhibition reverses therapy resistance in neuroendocrine bladder carcinoma.Cell reports. Medicine · 2026Article
- Automated quantification of tumor-infiltrating lymphocytes by machine learning reveals prognostic and immunogenomic features in lung cancer.Scientific reports · 2026Article
- Targeting MDSCs in cancer: emerging immunotherapeutic and metabolic strategies.Frontiers in immunology · 2026Review
- Artificial Intelligence-Detected Tumor-Infiltrating Lymphocytes and Outcomes in Anti-PD-1-Based Treated Melanoma.JAMA oncology · 2025Article
- Pathomic immune biomarkers define recurrence risk in early-stage melanoma.The oncologist · 2025Article
- Multi-omics analysis of zinc finger protein 683 as a prognostic biomarker for immune infiltration in clear cell renal cell carcinoma.BMC cancer · 2025Article
- Pathologist-Read vs AI-Driven Assessment of Tumor-Infiltrating Lymphocytes in Melanoma.JAMA network open · 2025Article
- Higher density of compact B cell clusters in invasive front may contribute to better prognosis in pancreatic ductal adenocarcinoma.Discover oncology · 2025Article
- Automated deep learning-based assessment of tumour-infiltrating lymphocyte density determines prognosis in colorectal cancer.Journal of translational medicine · 2025Article
- Machine learning-based spatial characterization of tumor-immune microenvironment in the EORTC 10994/BIG 1-00 early breast cancer trial.NPJ breast cancer · 2025Article
- Deep-learning enabled combined measurement of tumour cell density and tumour infiltrating lymphocyte density as a prognostic biomarker in colorectal cancer.BJC reports · 2025Article
- A novel dataset for nuclei and tissue segmentation in melanoma with baseline nuclei segmentation and tissue segmentation benchmarks.GigaScience · 2025Article
- Article
- Ecto-NOX Disulfide-Thiol Exchanger 2 (ENOX2/tNOX) Is a Potential Prognostic Marker in Primary Malignant Melanoma and May Serve as a Therapeutic Target.International journal of molecular sciences · 2024Article
- Ten challenges and opportunities in computational immuno-oncology.Journal for immunotherapy of cancer · 2024Review
- Prognostic value of tumor-infiltrating lymphocytes and PD-L1 expression in esophageal squamous cell carcinoma.Cancer medicine · 2024Article
- Tricaprylin-based drug crystalline suspension for intramuscular long-acting delivery of entecavir with alleviated local inflammation.Bioengineering & translational medicine · 2024Article
6 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors.
Funding
Abstract
Assessment of tumor infiltrating lymphocytes (TILs) as a prognostic variable in melanoma has not seen broad adoption due to lack of standardization. Automation could represent a solution. Here, using open source software, we build an algorithm for image-based automated assessment of TILs on hematoxylin-eosin stained sections in melanoma. Using a retrospective collection of 641 melanoma patients comprising four independent cohorts; one training set (N = 227) and three validation cohorts (N = 137, N = 201, N = 76) from 2 institutions, we show that the automated TIL scoring algorithm separates patients into favorable and poor prognosis cohorts, where higher TILs scores were associated with favorable prognosis. In multivariable analyses, automated TIL scores show an independent association with disease-specific overall survival. Therefore, the open source, automated TIL scoring is an independent prognostic marker in melanoma. With further study, we believe that this algorithm could be useful to define a subset of patients that could potentially be spared immunotherapy.
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