Predicting of survival in metastatic melanoma patients under anti-PD-1 monotherapy using genomic mutation and copy number variation

Abstract Background Although PD-1 inhibitors have significantly reduced metastatic melanoma patients’ mortality, only a small proportion of these patients actually benefit. We aim to develop some parsimonious predictive models for identifying those patients’ survival outcome under anti-PD-1 treatment. Method Based on the genomic mutation and copy number variation data of metastatic melanoma patients in the Liu and Shoushtari cohorts, we developed and validated three different nomograms to identify their survival outcomes under anti-PD-1 monotherapy. Patients without anti-PD-1 monotherapy in the TCGA and MSK cohorts were employed as negative controls to assess the applicability of our models to anti-PD-1 monotherapy. All predictive models developed in this study are accessible and available for use at https://yyw0505.shinyapps.io/nomogram_app/ . Result The first nomogram, and also the one we most recommend, built on five genes including NID1 amplification, TYRP1 deletion, mutations of PIK3C2G, FLT1 and IKZF1, classified patients into the High-Risk and Low-Risk group, and patients in the High-Risk group exhibited shorter overall survival (OS) and progression-free survival (PFS). However, there was no difference of OS between the two groups in both the TCGA and MSK cohorts, indicated the first nomogram was a predictive model rather than prognostic model. Similar results were also observed in the second and third nomogram. Conclusion The parsimonious and robust predictive model could provide valuable assistance for clinical practice.

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Publication Details

Journal
Discover Oncology
Published
2026-05-18
DOI
https://doi.org/10.1007/s12672-026-05221-8
Primary Topic
Melanoma and MAPK Pathways
Type
article
Field-Weighted Citation Impact
0.00
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article

Predicting of survival in metastatic melanoma patients under anti-PD-1 monotherapy using genomic mutation and copy number variation

Ling Zhang, Xiaoyu Lu, Jiaojiao Yang, Yue Wang et al.
Discover Oncology
Melanoma and MAPK Pathways
article

Predicting of survival in metastatic melanoma patients under anti-PD-1 monotherapy using genomic mutation and copy number variation

Ling Zhang, Xiaoyu Lu, Jiaojiao Yang, Yue Wang, Shuibing Yang, Wei Tang, Jingjin Yang
article en

Abstract

Abstract Background Although PD-1 inhibitors have significantly reduced metastatic melanoma patients’ mortality, only a small proportion of these patients actually benefit. We aim to develop some parsimonious predictive models for identifying those patients’ survival outcome under anti-PD-1 treatment. Method Based on the genomic mutation and copy number variation data of metastatic melanoma patients in the Liu and Shoushtari cohorts, we developed and validated three different nomograms to identify their survival outcomes under anti-PD-1 monotherapy. Patients without anti-PD-1 monotherapy in the TCGA and MSK cohorts were employed as negative controls to assess the applicability of our models to anti-PD-1 monotherapy. All predictive models developed in this study are accessible and available for use at https://yyw0505.shinyapps.io/nomogram_app/ . Result The first nomogram, and also the one we most recommend, built on five genes including NID1 amplification, TYRP1 deletion, mutations of PIK3C2G, FLT1 and IKZF1, classified patients into the High-Risk and Low-Risk group, and patients in the High-Risk group exhibited shorter overall survival (OS) and progression-free survival (PFS). However, there was no difference of OS between the two groups in both the TCGA and MSK cohorts, indicated the first nomogram was a predictive model rather than prognostic model. Similar results were also observed in the second and third nomogram. Conclusion The parsimonious and robust predictive model could provide valuable assistance for clinical practice.

Discover Oncology
Huaihua University (CN), Jinshan Hospital of Fudan University (CN), Shanghai University of Medicine and Health Sciences (CN), University of South China (CN)
Good health and well-being
Openalex Percentile: Top 8%
Melanoma and MAPK Pathways
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