ArticleThe oncologist2024
Automated Quantitative CD8+ Tumor-Infiltrating Lymphocytes and Tumor Mutation Burden as Independent Biomarkers in Melanoma Patients Receiving Front-Line Anti-PD-1 Immunotherapy.
Article in The oncologist, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 10 citations in OpenAlex.
- Enhancing Translation of H&E to IHC with Robust Tumor-Infiltrating Lymphocytes Quantification Using Deep Generative Models: A Feasibility Study.Journal of imaging informatics in medicine · 2026Article
- Commentary on: "The Effects of Sun Exposure and Pigmentation Phenotype on Prognosis in Metastatic Melanoma".Acta dermato-venereologica · 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
- The Effects of Sun Exposure and Pigmentation Phenotype on Prognosis in Metastatic Melanoma.Acta dermato-venereologica · 2026Article
- Advanced Mucosal Melanoma Therapies: Current Status and Future Directions.Current treatment options in oncology · 2026Review
- Decoding the tumor immune landscape: emerging TIL subsets as prognostic biomarkers and therapeutic targets.Naunyn-Schmiedeberg's archives of pharmacology · 2026Review
- Targeting Telomerase in Cancer: Vaccine-Based Strategies, Clinical Evidence, and Synergy with Immunotherapy.Diseases (Basel, Switzerland) · 2026Review
- Predicting anti-PD-1 immune checkpoint blockade response in melanoma patients with spatially aware machine learning models.NPJ precision oncology · 2026Article
- Sucralose Consumption Ablates Cancer Immunotherapy Response through Microbiome Disruption.Cancer discovery · 2025Article
- Article
- Prognostic Biomarkers in Evolving Melanoma Immunotherapy.American journal of clinical dermatology · 2025Review
- Spatial proteomics of the tumor microenvironment in melanoma: current insights and future directions.Frontiers in immunology · 2025Review
- Cold and hot tumors: from molecular mechanisms to targeted therapy.Signal transduction and targeted therapy · 2024Review
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundCD8+ tumor-infiltrating lymphocyte (TIL) predicts response to anti-PD-(L)1 therapy. However, there remains no standardized method to assess CD8+ TIL in melanoma, and developing a specific, cost-effective, reproducible, and clinically actionable biomarker to anti-PD-(L)1 remains elusive. We report on the development of automatic CD8+ TIL density quantification via whole slide image (WSI) analysis in advanced melanoma patients treated with front-line anti-PD-1 blockade, and correlation immunotherapy response.
methodsSeventy-eight patients treated with PD-1 inhibitors in the front-line setting between January 2015 and May 2023 at the University of Pittsburgh Cancer Institute were included. CD8+ TIL density was quantified using an image analysis algorithm on digitized WSI. Targeted next-generation sequencing (NGS) was performed to determine tumor mutation burden (TMB) in a subset of 62 patients. ROC curves were used to determine biomarker cutoffs and response to therapy. Correlation between CD8+ TIL density and TMB cutoffs and response to therapy was studied.
resultsHigher CD8+ TIL density was significantly associated with improved response to front-line anti-PD-1 across all time points measured. CD8+ TIL density ≥222.9 cells/mm2 reliably segregated responders and non-responders to front-line anti-PD-1 therapy regardless of when response was measured. In a multivariate analysis, patients with CD8+ TIL density exceeding cutoff had significantly improved PFS with a trend toward improved OS. Similarly, increasing TMB was associated with improved response to anti-PD-1, and a cutoff of 14.70 Mut/Mb was associated with improved odds of response. The correlation between TMB and CD8+ TIL density was low, suggesting that each represented independent predictive biomarkers of response.
conclusionsAn automatic digital analysis algorithm provides a standardized method to quantify CD8+ TIL density, which predicts response to front-line anti-PD-1 therapy. CD8+ TIL density and TMB are independent predictors of response to anti-PD-1 blockade.
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