Abstract
Cutaneous melanoma is the most life-threatening skin malignant tumor due to its increasing metastasis and mortality rate. The abnormal competitive endogenous RNA network promotes the development of tumors and becomes biomarkers for the prognosis of various tumors. At the same time, the tumor immune microenvironment (TIME) is of great significance for tumor outcome and prognosis. From the perspective of TIME and ceRNA network, this study aims to explain the prognostic factors of cutaneous melanoma systematically and find novel and powerful biomarkers for target therapies. We obtained the transcriptome data of cutaneous melanoma from The Cancer Genome Atlas (TCGA) database, 3 survival-related mRNAs co-expression modules and 2 survival-related lncRNAs co-expression modules were identified through weighted gene co-expression network analysis (WCGNA), and 144 prognostic miRNAs were screened out by univariate Cox proportional hazard regression. Cox regression model and Kaplan-Meier survival analysis were employed to identify 4 hub prognostic mRNAs, and the prognostic ceRNA network consisting of 7 lncRNAs, 1 miRNA and 4 mRNAs was established. After analyzing the composition and proportion of total immune cells in cutaneous melanoma microenvironment through CIBERSORT algorithm, it is found through correlation analysis that lncRNA-TUG1 in the ceRNA network was closely related to the TIME. In this study, we first established cutaneous melanoma’s TIME-related ceRNA network by WGCNA. Cutaneous melanoma prognostic markers have been identified from multiple levels, which has important guiding significance for clinical diagnosis, treatment, and further scientific research on cutaneous melanoma.
Highlights
Cutaneous melanoma is the most malignant skin tumor originating from melanocytes with abnormal proliferation and differentiation, and is the leading cause of skin cancer-related deaths [1]
In order to explore the role of tumor immune microenvironment (TIME) related Competitive endogenous RNA (ceRNA) network in melanoma, Weighted gene co-expression network analysis (WGCNA) method was used in this study to screen the hub mRNA and long non-coding RNA (lncRNA) modules that were significantly related to clinical prognosis from the melanoma transcriptome data of The Cancer Genome Atlas (TCGA) database
This study found that there was a positive correlation between lnc-TUG1 in melanoma and NK cells resting, suggesting that lncTUG1 highly expressed in melanoma may mediate the inactivation of immune surveillance and immune clearance
Summary
Cutaneous melanoma is the most malignant skin tumor originating from melanocytes with abnormal proliferation and differentiation, and is the leading cause of skin cancer-related deaths [1]. Melanoma has a higher cure rate after complete resection, and the mortality rate of stage III/IV patients is as high as 70%, and the 5-year survival rate is less than 16% [4]. In recent years, targeted therapy and immunotherapy for melanoma have made certain breakthroughs, while low response rates and severe adverse reactions have limited its long-term effects [5, 6]. Seeking in-depth understanding of the pathogenesis and malignant transformation mechanism of melanoma, exploring more biological targets, and making accurate prediction of the prognosis, will bring new hope for overcoming melanoma’s recurrence and resistance, and improving the survival rate of patients. To clarify the complex tumor-immune regulation in the progression and drug resistance of melanoma, and to find new immunetherapy targets is the only way to to discover new treatment for advancedstage, recurrent and metastatic melanoma
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
