ArticleAging2019
Robust immunoscore model to predict the response to anti-PD1 therapy in melanoma.
Article in Aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Immunoscore and beyond: evolution and clinical integration of immune contexture-based biomarkers across solid tumours.Frontiers in immunology · 2026Review
- Nomograms for predicting prognosis in postoperative lip squamous cell carcinoma patients.Discover oncology · 2025Article
- Targeted demethylation and activation ofProceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- A Comprehensive Benchmark of Transcriptomic Biomarkers for Immune Checkpoint Blockades.Cancers · 2023Article
- Immunoscore Signatures in Surgical Specimens and Tumor-Infiltrating Lymphocytes in Pretreatment Biopsy Predict Treatment Efficacy and Survival in Esophageal Cancer.Annals of surgery · 2023Article
- Integration of transcriptomics data into agent-based models of solid tumor metastasis.Computational and structural biotechnology journal · 2023Article
- Article
- Downregulated Expression of RIPOR3 Correlated with Immune Infiltrates Predicts Poor Prognosis in Oral Tongue Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2022Article
- Article
- The Ratio of GrzBCancers · 2021Article
- Role of the Neutrophil in the Pathogenesis of Advanced Cancer and Impaired Responsiveness to Therapy.Molecules (Basel, Switzerland) · 2020Review
- Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling.Frontiers in oncology · 2020Article
- Identification of an Immune-Related Prognostic Signature Associated With Immune Infiltration in Melanoma.Frontiers in genetics · 2020Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to construct immune-related predictors to identify responders to anti-PD1 therapy of melanoma through CIBERSORT algorithm. Using the least absolute shrinkage and selection operator (LASSO) logistic regression, we constructed an immunoscore consisting of 8 immune subsets to predict the anti-PD1 response. This score achieved an overall accuracy of AUC = 0.77, 0.80 and 0.73 in the training cohort, validation cohort and on-anti-PD1 cohort, respectively. Patients with high immunoscores had significantly higher objective response rates (ORRs) than did those with low immunoscores (ORR: 53.8% vs 17.7%, P < 0.001 for entire pre-anti-PD1 cohort; 42.1% vs 15.1%, P = 0.022 for on-anti-PD1 cohort; 66.7% vs 16.7%, P = 0.038 for neoadjuvant anti-PD1 cohort). Prolonged survival trends were observed in high-immunoscore group (1-year PFS: 42.4% vs 14.3%, P = 0.059; 3-year OS: 41.5% vs 31.6%, P = 0.057). Furthermore, we found that high-immunoscore group exhibited higher fractions of tumor-infiltrating lymphocytes and an increased IFN-γ response. Analysis of the results of the GSEA indicated a significant enrichment of antitumor immunity pathways in the high-immunoscore group. Therefore, this study indicated that we constructed a robust immunoscore model to predict the anti-PD1 response of metastatic melanoma and the neoadjuvant anti-PD1 response of resectable melanoma.
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