The Affiliated Luohu Hospital of Shenzhen University, Department of Urological Surgery, Shenzhen University, Shenzhen, 518000, China.
Shenzhen Following Precision Medical Institute, Shenzhen Luohu Hospital Group, Shenzhen, 518000, China.
BMC Cancer. 2018 Mar 13;18(1):287. doi: 10.1186/s12885-018-4176-1.
Renal cell carcinoma (RCC) account for over 80% of renal malignancies. The most common type of RCC can be classified into three subtypes including clear cell, papillary and chromophobe. ccRCC (the Clear Cell Renal Cell Carcinoma) is the most frequent form and shows variations in genetics and behavior. To improve accuracy and personalized care and increase the cure rate of cancer, molecular typing for individuals is necessary.
We adopted the genome, transcriptome and methylation HMK450 data of ccRCC in The Cancer Genome Atlas Network in this research. Consensus Clustering algorithm was used to cluster the expression data and three subtypes were found. To further validate our results, we analyzed an independent data set and arrived at a consistent conclusion. Next, we characterized the subtype by unifying genomic and clinical dimensions of ccRCC molecular stratification. We also implemented GSEA between the malignant subtype and the other subtypes to explore latent pathway varieties and WGCNA to discover intratumoral gene interaction network. Moreover, the epigenetic state changes between subgroups on methylation data are discovered and Kaplan-Meier survival analysis was performed to delve the relation between specific genes and prognosis.
We found a subtype of poor prognosis in clear cell renal cell carcinoma, which is abnormally upregulated in focal adhesions and cytoskeleton related pathways, and the expression of core genes in the pathways are negatively correlated with patient outcomes.
Our work of classification schema could provide an applicable framework of molecular typing to ccRCC patients which has implications to influence treatment decisions, judge biological mechanisms involved in ccRCC tumor progression, and potential future drug discovery.
肾细胞癌（RCC）占肾脏恶性肿瘤的 80%以上。最常见的 RCC 可分为三种亚型，包括透明细胞、乳头状和嫌色细胞。ccRCC（透明细胞肾细胞癌）是最常见的形式，表现出遗传和行为的变化。为了提高准确性和个性化护理，提高癌症的治愈率，有必要对个体进行分子分型。
我们在本研究中采用了癌症基因组图谱网络中 ccRCC 的基因组、转录组和甲基化 HMK450 数据。采用共识聚类算法对表达数据进行聚类，发现了三种亚型。为了进一步验证我们的结果，我们分析了一个独立的数据集，并得出了一致的结论。接下来，我们通过统一 ccRCC 分子分层的基因组和临床维度来对亚型进行特征描述。我们还在恶性亚型和其他亚型之间实施了 GSEA，以探索潜在的途径变化，并进行 WGCNA 以发现肿瘤内基因相互作用网络。此外，还发现了亚组之间在甲基化数据上的表观遗传状态变化，并进行了 Kaplan-Meier 生存分析，以探讨特定基因与预后的关系。
我们在透明细胞肾细胞癌中发现了一种预后不良的亚型，该亚型在局灶性黏附与细胞骨架相关途径中异常上调，途径中的核心基因的表达与患者预后呈负相关。
我们的分类方案工作可为 ccRCC 患者提供一种可行的分子分型框架，这对影响治疗决策、判断 ccRCC 肿瘤进展中涉及的生物学机制以及潜在的未来药物发现具有重要意义。
