Ferroptosis-Associated Classifier and Indicator for Prognostic Prediction in Cutaneous Melanoma.

Hao Zeng,Xiaoying Ye,Chunlei Wan,Cong You,Longying Deng,Jiangyi Wang,Tao Yang,Leran Zhao,Jimei Wang

doi:10.1155/2021/3658196

Abstract

Ferroptosis plays a critical role in different types of cancers, but the prognostic impact of ferroptosis in cutaneous melanoma remains lacking. Therefore, ferroptosis-related genes (FRGs) were firstly obtained from the FerrDb database and the differentially expressed FRGs were identified by the “limma” algorithm. Next, the prognostic differentially expressed FRGs were screened out by univariate Cox regression, which were subsequently used to cluster melanomas into two subtypes (clusters A and B). Besides, the Boruta algorithm and principal component analysis (PCA) were performed to build a 15-FRGs indicator, which can robustly predict patients' overall survival (OS) and be considered as an independent prognostic factor in melanoma. The melanoma patients were further divided into high- and low-FRGs score groups. The high score group have a good prognosis, with higher T cell immune infiltrating and lower mutation frequencies in NRAS, KRAS, and NF1. Finally, we discovered that many immune processes and several chemotherapy drugs were closely associated with FRGs score. Thus, our study provides a novel ferroptosis-associated classifier and indicator to predict the prognosis of melanoma. Besides, we identified several potential chemotherapy drugs to induce ferroptosis and could supply additional effective treatments.

Highlights

Melanoma is a highly lethal cutaneous tumor which originates from the malignant transformation of melanocytes
A total of 870 samples were merged into a large cohort from the meta-cohort (TCGASKCM, GSE15605, GSE3189, and GSE46517), which consisted of 579 melanoma samples and 291 normal skin samples. e ComBat algorithm was performed to reduce the batch effect generated from the different platforms, and the PAC plot showed that the clusters based on the removal batch effect placed more together than before removal (Figure 1(a))
To explore the signaling pathways enrichment for different ferroptosis-related genes (FRGs) score phenotypes in melanoma, Gene Set Enrichment Analysis (GSEA) was performed between low- and high-FRGs score groups. e cancer hallmark database (h.all.v7.0.symbols) and KEGG database (c2.cp.kegg.v7.0.symbols) were applied in GSEA to investigate the signaling pathways correlated with different subgroups of melanoma. e adjusted P < 0.05 were used to sort the significant pathways enriched in each phenotype

Summary

Introduction

Melanoma is a highly lethal cutaneous tumor which originates from the malignant transformation of melanocytes. Due to the absence of early symptoms, melanomas are frequently diagnosed at an advanced stage and only 10% of patients have 5-year survival [1, 2]. The traditional system for melanoma treatment and prognostic prediction, such as Clark level, tumor stage, and histological type, is growingly becoming difficult to illustrate the diversity of clinical outcomes [3]. Molecular features such as gene transcription, translation, and many posttranslational modifications lead to heterogeneity of cutaneous melanoma [4]. Many significant studies have demonstrated that ferroptosis is a participant in a large number of pathological processes, especially in the proliferation and growth of cancer cells [6, 7]. e activation of ferroptosis suppressed the development of many chemotherapy-resistant cancers, which indicated that ferroptosis may be a promising therapeutic

Methods

Results

Conclusion