Department of Obstetrics and Gynecology, The Second Affiliated Hospital of University of South China, Hengyang, Hunan 421001, P.R. China.
Department of Histology and Embryology, Clinical Anatomy and Reproductive Medicine Application Institute, University of South China, Hengyang, Hunan 421001, P.R. China.
Biosci Rep. 2020 Sep 30;40(9). doi: 10.1042/BSR20201937.
Tumour metabolism has become a novel factor targeted by personalised cancer drugs. This research evaluated the prognostic significance of metabolism-related genes (MRGs) in ovarian serous cystadenocarcinoma (OSC).
MRGs in 379 women surviving OSC were obtained using The Cancer Genome Atlas (TCGA) database. Then, several biomedical computational algorithms were employed to identify eight hub prognostic MRGs that were significantly relevant to OSC survival. These eight genes have important clinical significance and prognostic value in OSC. Subsequently, a prognostic index was constructed. Drug sensitivity analysis was used to screen the key genes in eight MRGs. Immunohistochemistry (IHC) staining confirmed the expression levels of key genes and their correlations with clinical parameters and prognosis for patients.
A total of 701 differentially expressed MRGs were confirmed in women with OSC by the TCGA database. The random walking with restart (RWR) algorithm and the univariate Cox and lasso regression analyses indicated a prognostic signature based on eight MRGs (i.e., ENPP1, FH, CYP2E1, HPGDS, ADCY9, NDUFA5, ADH1B and PYGB), which performed moderately well in prognostic predictions. Drug sensitivity analysis indicated that PYGB played a key role in the progression of OSC. Also, IHC staining confirmed that PYGB has a close correlation with clinical parameters and poor prognosis in OSC.
The results of the present study may help to establish a foundation for future research attempting to predict the prognosis of OSC patients and to characterise OSC metabolism.
肿瘤代谢已成为个性化癌症药物的一个新靶点。本研究评估了代谢相关基因（MRGs）在卵巢浆液性囊腺癌（OSC）中的预后意义。
使用癌症基因组图谱（TCGA）数据库获取 379 名生存的 OSC 女性的 MRGs。然后，采用几种生物医学计算算法，鉴定出与 OSC 生存显著相关的 8 个关键预后 MRGs。这 8 个基因在 OSC 中具有重要的临床意义和预后价值。随后构建了预后指数。药物敏感性分析用于筛选 8 个 MRGs 中的关键基因。免疫组织化学（IHC）染色证实了关键基因的表达水平及其与患者临床参数和预后的相关性。
TCGA 数据库证实 OSC 女性存在 701 个差异表达的 MRGs。随机游走重启（RWR）算法和单因素 Cox 和套索回归分析表明，基于 8 个 MRGs（即 ENPP1、FH、CYP2E1、HPGDS、ADCY9、NDUFA5、ADH1B 和 PYGB）构建的预后特征具有中等的预后预测能力。药物敏感性分析表明，PYGB 在 OSC 的进展中起关键作用。此外，IHC 染色证实，PYGB 与 OSC 的临床参数和不良预后密切相关。
本研究结果可能有助于为未来试图预测 OSC 患者预后和表征 OSC 代谢的研究奠定基础。
