Zhou Sitong, Han Yuanyuan, Li Jiehua, Pi Xiaobing, Lyu Jin, Xiang Shijian, Zhou Xinzhu, Chen Xiaodong, Wang Zhengguang, Yang Ronghua
Department of Dermatology, The First People's Hospital of Foshan, Foshan, China.
Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Yunnan Key Laboratory of Vaccine Research and Development on Severe Infectious Diseases, Kunming, China.
Front Oncol. 2021 Oct 13;11:745384. doi: 10.3389/fonc.2021.745384. eCollection 2021.
Skin cutaneous melanoma (SKCM) is the most aggressive and fatal type of skin cancer. Its highly heterogeneous features make personalized treatments difficult, so there is an urgent need to identify markers for early diagnosis and therapy. Detailed profiles are useful for assessing malignancy potential and treatment in various cancers. In this study, we constructed a co-expression module using expression data for cutaneous melanoma. A weighted gene co-expression network analysis was used to discover a co-expression gene module for the pathogenesis of this disease, followed by a comprehensive bioinformatics analysis of selected hub genes. A connectivity map (CMap) was used to predict drugs for the treatment of SKCM based on hub genes, and immunohistochemical (IHC) staining was performed to validate the protein levels. After discovering a co-expression gene module for the pathogenesis of this disease, we combined GWAS validation and DEG analysis to identify 10 hub genes in the most relevant module. Survival curves indicated that eight hub genes were significantly and negatively associated with overall survival. A total of eight hub genes were positively correlated with SKCM tumor purity, and 10 hub genes were negatively correlated with the infiltration level of CD4+ T cells and B cells. Methylation levels of seven hub genes in stage 2 SKCM were significantly lower than those in stage 3. We also analyzed the isomer expression levels of 10 hub genes to explore the therapeutic target value of 10 hub genes in terms of alternative splicing (AS). All 10 hub genes had mutations in skin tissue. Furthermore, CMap analysis identified cefamandole, ursolic acid, podophyllotoxin, and Gly-His-Lys as four targeted therapy drugs that may be effective treatments for SKCM. Finally, IHC staining results showed that all 10 molecules were highly expressed in melanoma specimens compared to normal samples. These findings provide new insights into SKCM pathogenesis based on multi-omics profiles of key prognostic biomarkers and drug targets. GPR143 and SLC45A2 may serve as drug targets for immunotherapy and prognostic biomarkers for SKCM. This study identified four drugs with significant potential in treating SKCM patients.
皮肤黑色素瘤(SKCM)是最具侵袭性和致命性的皮肤癌类型。其高度异质性的特征使得个性化治疗变得困难,因此迫切需要鉴定用于早期诊断和治疗的标志物。详细的特征分析对于评估各种癌症的恶性潜能和治疗方法很有用。在本研究中,我们利用皮肤黑色素瘤的表达数据构建了一个共表达模块。使用加权基因共表达网络分析来发现该疾病发病机制的共表达基因模块,随后对选定的枢纽基因进行全面的生物信息学分析。基于枢纽基因,使用连通性图谱(CMap)预测治疗SKCM的药物,并进行免疫组织化学(IHC)染色以验证蛋白水平。在发现该疾病发病机制的共表达基因模块后,我们结合全基因组关联研究(GWAS)验证和差异表达基因(DEG)分析,在最相关的模块中鉴定出10个枢纽基因。生存曲线表明,8个枢纽基因与总生存期显著负相关。总共8个枢纽基因与SKCM肿瘤纯度呈正相关,10个枢纽基因与CD4 + T细胞和B细胞的浸润水平呈负相关。2期SKCM中7个枢纽基因的甲基化水平显著低于3期。我们还分析了10个枢纽基因的异构体表达水平,以探索10个枢纽基因在可变剪接(AS)方面的治疗靶点价值。所有10个枢纽基因在皮肤组织中均有突变。此外,CMap分析确定头孢孟多、熊果酸、鬼臼毒素和甘氨酰 - 组氨酰 - 赖氨酸为四种靶向治疗药物,可能对SKCM有效。最后,IHC染色结果表明,与正常样本相比,所有10种分子在黑色素瘤标本中均高表达。这些发现基于关键预后生物标志物和药物靶点的多组学特征,为SKCM发病机制提供了新的见解。GPR143和SLC45A2可能作为SKCM免疫治疗的药物靶点和预后生物标志物。本研究鉴定出四种在治疗SKCM患者方面具有显著潜力的药物。