ArticleEBioMedicine2023
Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases.
Article in EBioMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed, 45 citations in OpenAlex.
- Article
- Interleukin-1β Gene (Current oncology (Toronto, Ont.) · 2026Article
- The tumoural landscape of lymphocytes and immune pathways in immunotherapy-treated melanoma patients.Genes and immunity · 2026Article
- Clinical utility of preoperative lymphocyte-albumin-neutrophil ratio for prognostication in patients with oral cancer undergoing surgery.Journal of the Chinese Medical Association : JCMA · 2026Article
- Predicting Response to Immune Checkpoint Inhibitors in Melanoma: Emerging Approaches in Digital Pathology, Spatial Profiling and Machine Learning.International journal of molecular sciences · 2026Review
- A Multitask Deep Learning Approach for Tumor Segmentation and Morphological Quantification in Acral Melanoma Whole-Slide Images.Journal of imaging informatics in medicine · 2026Article
- From Slide to Insight: The Emerging Alliance of Digital Pathology and AI in Melanoma Diagnostics.Cancers · 2025Review
- Artificial Intelligence in Histopathological Analysis for Predicting Immunotherapy Response in Cutaneous Melanoma.International journal of molecular sciences · 2025Review
- Systemic Immune-Inflammation Index as a Predictor of Progression in Melanoma: A Retrospective Cohort Study.Cureus · 2025Article
- Current Trends and Future Directions of Digital Pathology and Artificial Intelligence in Dermatopathology: A Scientometric-Based Review.Diagnostics (Basel, Switzerland) · 2025Review
- Pathologist-Read vs AI-Driven Assessment of Tumor-Infiltrating Lymphocytes in Melanoma.JAMA network open · 2025Article
- Machine learning to detect melanoma exploiting nuclei morphology and Spatial organization.Scientific reports · 2025Article
- Optimizing Immunotherapy: The Synergy of Immune Checkpoint Inhibitors with Artificial Intelligence in Melanoma Treatment.Biomolecules · 2025Review
- A novel dataset for nuclei and tissue segmentation in melanoma with baseline nuclei segmentation and tissue segmentation benchmarks.GigaScience · 2025Article
- 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
- Role of tumor-infiltrating lymphocytes in melanoma prognosis and treatment strategies: A systematic review and meta-analysis.Heliyon · 2024Article
- Tumor-infiltrating lymphocytes as a prognostic and predictive factor for Melanoma.Expert review of molecular diagnostics · 2024Review
- Nomograms based on the lymphocyte-albumin-neutrophil ratio (LANR) for predicting the prognosis of nasopharyngeal carcinoma patients after definitive radiotherapy.Scientific reports · 2024Article
- The global trends and distribution in tumor-infiltrating lymphocytes over the past 49 years: bibliometric and visualized analysis.Frontiers in immunology · 2024Article
- A novel semi-quantitative scoring method for CD8+ tumor-infiltrating lymphocytes based on infiltration sites in gastric cancer.American journal of cancer research · 2024Article
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Authors and funding
20 authors at 7 institutions in 3 countries.
Funding
Abstract
backgroundRecent advances in digital pathology have enabled accurate and standardised enumeration of tumour-infiltrating lymphocytes (TILs). Here, we aim to evaluate TILs as a percentage electronic TIL score (eTILs) and investigate its prognostic and predictive relevance in cutaneous melanoma.
methodsWe included stage I to IV cutaneous melanoma patients and used hematoxylin-eosin-stained slides for TIL analysis. We assessed eTILs as a continuous and categorical variable using the published cut-off of 16.6% and applied Cox regression models to evaluate associations of eTILs with relapse-free, distant metastasis-free, and overall survival. We compared eTILs of the primaries with matched metastasis. Moreover, we assessed the predictive relevance of eTILs in therapy-naïve metastases according to the first-line therapy.
findingsWe analysed 321 primary cutaneous melanomas and 191 metastatic samples. In simple Cox regression, tumour thickness (p < 0.0001), presence of ulceration (p = 0.0001) and eTILs ≤16.6% (p = 0.0012) were found to be significant unfavourable prognostic factors for RFS. In multiple Cox regression, eTILs ≤16.6% (p = 0.0161) remained significant and downgraded the current staging. Lower eTILs in the primary tissue was associated with unfavourable relapse-free (p = 0.0014) and distant metastasis-free survival (p = 0.0056). In multiple Cox regression adjusted for tumour thickness and ulceration, eTILs as continuous remained significant (p = 0.019). When comparing TILs in primary tissue and corresponding metastasis of the same patient, eTILs in metastases was lower than in primary melanomas (p < 0.0001). In therapy-naïve metastases, an eTILs >12.2% was associated with longer progression-free survival (p = 0.037) and melanoma-specific survival (p = 0.0038) in patients treated with anti-PD-1-based immunotherapy. In multiple Cox regression, lactate dehydrogenase (p < 0.0001) and eTILs ≤12.2% (p = 0.0130) were significantly associated with unfavourable melanoma-specific survival.
interpretationAssessment of TILs is prognostic in primary melanoma samples, and the eTILs complements staging. In therapy-naïve metastases, eTILs ≤12.2% is predictive of unfavourable survival outcomes in patients receiving anti-PD-1-based therapy.
fundingSee a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.
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