Department of Burn Surgery and Skin Regeneration, The First People's Hospital of Foshan, Foshan, China.
Nanjing University of Chinese Medicine, Nanjing, China.
J Cell Mol Med. 2021 Dec;25(23):10990-11001. doi: 10.1111/jcmm.17021. Epub 2021 Nov 10.
Skin cutaneous melanoma (SKCM) is one of the most destructive skin malignancies and has attracted worldwide attention. However, there is a lack of prognostic biomarkers, especially tumour microenvironment (TME)-based prognostic biomarkers. Therefore, there is an urgent need to investigate the TME in SKCM, as well as to identify efficient biomarkers for the diagnosis and treatment of SKCM patients. A comprehensive analysis was performed using SKCM samples from The Cancer Genome Atlas and normal samples from Genotype-Tissue Expression. TME scores were calculated using the ESTIMATE algorithm, and differential TME scores and differentially expressed prognostic genes were successively identified. We further identified more reliable prognostic genes via least absolute shrinkage and selection operator regression analysis and constructed a prognostic prediction model to predict overall survival. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy, and Cox regression analysis was applied to explore the relationship with clinicopathological characteristics. Finally, we identified a novel prognostic biomarker and conducted a functional enrichment analysis. After considering ESTIMATEScore and tumour purity as differential TME scores, we identified 34 differentially expressed prognostic genes. Using least absolute shrinkage and selection operator regression, we identified seven potential prognostic biomarkers (SLC13A5, RBM24, IGHV3OR16-15, PRSS35, SLC7A10, IGHV1-69D and IGHV2-26). Combined with receiver operating characteristic and regression analyses, we determined PRSS35 as a novel TME-based prognostic biomarker in SKCM, and functional analysis enriched immune-related cells, functions and signalling pathways. Our study indicated that PRSS35 could act as a potential prognostic biomarker in SKCM by investigating the TME, so as to provide new ideas and insights for the clinical diagnosis and treatment of SKCM.
皮肤黑色素瘤(SKCM)是最具破坏性的皮肤恶性肿瘤之一,引起了全球关注。然而,目前缺乏预后生物标志物,特别是基于肿瘤微环境(TME)的预后生物标志物。因此,迫切需要研究 SKCM 的 TME,并寻找用于 SKCM 患者诊断和治疗的有效生物标志物。使用来自癌症基因组图谱的 SKCM 样本和来自基因型组织表达的正常样本进行了全面分析。使用 ESTIMATE 算法计算 TME 评分,并相继鉴定了差异 TME 评分和差异表达的预后基因。我们通过最小绝对收缩和选择算子回归分析进一步确定了更可靠的预后基因,并构建了预后预测模型来预测总生存期。使用接收者操作特征分析评估诊断效能,并应用 Cox 回归分析探讨与临床病理特征的关系。最后,我们确定了一种新的预后生物标志物,并进行了功能富集分析。在考虑 ESTIMATEScore 和肿瘤纯度作为差异 TME 评分后,我们鉴定了 34 个差异表达的预后基因。使用最小绝对收缩和选择算子回归,我们鉴定了七个潜在的预后生物标志物(SLC13A5、RBM24、IGHV3OR16-15、PRSS35、SLC7A10、IGHV1-69D 和 IGHV2-26)。结合接收器操作特征和回归分析,我们确定 PRSS35 是 SKCM 中基于 TME 的新型预后生物标志物,功能分析富集了免疫相关细胞、功能和信号通路。我们的研究通过研究 TME 表明,PRSS35 可作为 SKCM 中的一种潜在预后生物标志物,为 SKCM 的临床诊断和治疗提供了新的思路和见解。