PDF(Pubmed)
Abstract：
Metastatic skin cutaneous melanoma (MSCM) is the most rapidly progressing/invasive skin-based malignancy, with median survival rates of about 12 months. It appears that metabolic disorders accelerate disease progression. However, correlations between metabolism-linked genes (MRGs) and prognosis in MSCM are unclear, and potential mechanisms explaining the correlation are unknown. The Cancer Genome Atlas (TCGA) was utilized as a training set to develop a genomic signature based on the differentially expressed MRGs (DE-MRGs) between primary skin cutaneous melanoma (PSCM) and MSCM. The Gene Expression Omnibus (GEO) was utilized as a validation set to verify the effectiveness of genomic signature. In addition, a nomogram was established to predict overall survival based on genomic signature and other clinic-based characteristics. Moreover, this study investigated the correlations between genomic signature and tumor micro-environment (TME). This study established a genomic signature consisting of 3 genes (CD38, DHRS3, and TYRP1) and classified MSCM patients into low and high-risk cohorts based on the median risk scores of MSCM cases. It was discovered that cases in the high-risk cohort had significantly lower survival than cases in the low-risk cohort across all sets. Furthermore, a nomogram containing this genomic signature and clinic-based parameters was developed and demonstrated high efficiency in predicting MSCM case survival times. Interestingly, Gene Set Variation Analysis results indicated that the genomic signature was involved in immune-related physiological processes. In addition, this study discovered that risk scoring was negatively correlated with immune-based cellular infiltrations in the TME and critical immune-based checkpoint expression profiles, indicating that favorable prognosis may be influenced in part by immunologically protective micro-environments. A novel 3-genomic signature was found to be reliable for predicting MSCM outcomes and may facilitate personalized immunotherapy.
摘要：
转移性皮肤皮肤黑色素瘤（MSCM）是进展最快/侵袭性皮肤恶性肿瘤，中位生存率约为12个月。似乎代谢紊乱加速了疾病进展。然而,代谢相关基因（MRGs）与MSCM预后的相关性尚不清楚，和解释相关性的潜在机制是未知的。癌症基因组图谱(TCGA)被用作训练集以开发基于原发性皮肤皮肤黑素瘤(PSCM)和MSCM之间的差异表达的MRG(DE-MRG)的基因组特征。利用基因表达综合(GEO)作为验证集以验证基因组签名的有效性。此外,我们建立了基于基因组特征和其他临床特征的列线图来预测总生存期.此外，这项研究调查了基因组特征与肿瘤微环境（TME）之间的相关性。这项研究建立了由3个基因（CD38，DHRS3和TYRP1）组成的基因组标签，并根据MSCM病例的中位风险评分将MSCM患者分为低风险和高风险队列。发现在所有集合中，高风险队列中的病例的生存率明显低于低风险队列中的病例。此外，建立了包含该基因组特征和基于临床的参数的列线图,并证明了在预测MSCM病例生存时间方面的高效率.有趣的是,基因集变异分析结果表明，基因组特征参与免疫相关的生理过程。此外,这项研究发现，风险评分与TME中基于免疫的细胞浸润和关键的基于免疫的检查点表达谱呈负相关，表明良好的预后可能部分受到免疫保护性微环境的影响。发现一种新的3基因组特征对于预测MSCM结果是可靠的，并且可以促进个性化免疫疗法。
