A twelve-gene signature for survival prediction in malignant melanoma patients
| Autor: | Ninghong Song, Lebin Song, Qijie Zhang, Yan-Yan Xiu, Lin Chen, Xiaoyuan Hou, Yan Lu |
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| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Neuroblastoma RAS viral oncogene homolog Oncology medicine.medical_specialty business.industry Melanoma Viral Oncogene General Medicine Disease Gene signature medicine.disease 03 medical and health sciences 030104 developmental biology 0302 clinical medicine 030220 oncology & carcinogenesis Internal medicine Cohort Gene expression medicine Original Article business Gene |
| Zdroj: | Ann Transl Med |
| ISSN: | 2305-5847 2305-5839 |
| DOI: | 10.21037/atm.2020.02.132 |
| Popis: | Background Melanoma is defined as a highly mutational heterogeneous disease containing numerous alternations of the molecule. However, due to the phenotypically and genetically heterogeneity of malignant melanoma, conventional clinical characteristics remain restricted or limited in the ability to accurately predict individual outcomes and survival. This study aimed to establish an accurate gene expression signature to predict melanoma prognosis. Methods In this study, we established an RNA sequencing-based 12-gene signature data of melanoma patients obtained from 2 independent databases: the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. We evaluated the quality of each gene to predict survival conditions in each database by employing univariate and multivariate regression models. A prognostic risk score based on a prognostic signature was determined. This prognostic gene signature further classified patients into low-risk and high-risk groups. Results Based on a prognostic signature, a prognostic risk score was determined. This prognostic gene signature further divided the patients into low-risk and high-risk groups. In the chemotherapy and radiotherapy groups of the TCGA cohort and V-raf murine sarcoma viral oncogene homolog B1 (BRAF) expression group in the GEO cohort, patients in the low-risk group had a longer survival duration compared to patients in the high-risk group. Nevertheless, the immunotherapy group in the TCGA database and neuroblastoma RAS viral oncogene homolog (NRAS) expression group in the GEO database had no significant differences in statistics. Moreover, this gene signature was associated with patient prognosis regardless of whether the Breslow depth was greater than or less than 3.75 mm. Stratified gene set enrichment analysis (GSEA) revealed that certain immune-related pathways, such as the T-cell signaling pathway, chemokine signaling pathway, and primary immunodeficiency, were significantly enriched in the low-risk group of both TCGA and GEO cohorts. This information implied the immune-related properties of the 12-gene signature. Conclusions Our study emphasizes the significance of the gene expression signature in that it may be an indispensable prognostic predictor in melanoma and has great potential for application in personalized treatment. |
| Databáze: | OpenAIRE |
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