Abstract
Autophagy is involved in cancer initiation and progression but its role in uveal melanoma (UM) was rarely investigated. Herein, we built an autophagy-related gene (ARG) risk model of UM patients by univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression model and filtrated out nine prognostic ARGs in The Cancer Genome Atlas (TCGA) cohort. Survival and Receiver Operating Characteristic (ROC) Curve analysis in the TCGA and other four independent UM cohorts (GSE22138, GSE27831, GSE44295 and GSE84976) proved that the ARG-signature possessed robust and steady prognosis predictive ability. We calculated risk scores for patients included in our study and patients with higher risk scores showed worse clinical outcomes. We found the expressions of the nine ARGs were significantly associated with clinical and molecular features (including risk score) and overall survival (OS) of UM patients. Furthermore, we utilized univariate and multivariate Cox regression analyses to determine the independent prognostic ability of the ARG-signature. Functional enrichment analysis showed the ARG-signature was correlated with several immune-related processes and pathways like T-cell activation and T-cell receptor signaling pathway. Gene set enrichment analysis (GSEA) found tumor hallmarks including angiogenesis, IL6-JAK-STAT3-signaling, reactive oxygen species pathway and oxidative phosphorylation were enriched in high-risk UM patients. Finally, infiltrations of several immune cells and immune-related scores were found significantly associated with the ARG-signature. In conclusion, the ARG-signature might be a strong predictor for evaluating the prognosis and immune infiltration of UM patients.
Highlights
Uveal melanoma (UM) is a type of malignant intraocular cancer derived from melanocytes with high metastasis rate and poor prognosis [1]
Univariate Cox regression analysis showed that 133 of the 423 autophagy-related gene (ARG) were associated with the overall survival (OS) of UM patients in the The Cancer Genome Atlas (TCGA) cohort (P 1)
least absolute shrinkage and selection operator (Lasso) Cox regression model was subsequently applied to the 133 OS-related ARGs to establish a prognostic model for the UM patients in the TCGA cohort
Summary
Uveal melanoma (UM) is a type of malignant intraocular cancer derived from melanocytes with high metastasis rate and poor prognosis [1]. Fifty percent patients with UM were found with liver metastases within 10 years from first diagnosis, and the median survival time of patients with metastatic lesions is approx. These data indicated UM is an aggressive tumor with fetal malignancy. The methods of cancer biomedical diagnosis and targeted therapy have been developed rapidly in past decades, but the metastasis and death rate of UM did not decline [3]. With the rapid development of biomedical and bioinformatics technologies and methods, universal researches based on cancer expression profiles helped to search cancer diagnostic and therapeutic biomarkers, but similar studies in UM were rare. Identification of novel and effective prognostic and therapeutic biomarkers remains a priority for UM-tailored therapy
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